CN116298722A - Aluminum electrolysis cell short-circuit port insulation on-line monitoring method and system based on partial discharge signals - Google Patents
Aluminum electrolysis cell short-circuit port insulation on-line monitoring method and system based on partial discharge signals Download PDFInfo
- Publication number
- CN116298722A CN116298722A CN202310151229.4A CN202310151229A CN116298722A CN 116298722 A CN116298722 A CN 116298722A CN 202310151229 A CN202310151229 A CN 202310151229A CN 116298722 A CN116298722 A CN 116298722A
- Authority
- CN
- China
- Prior art keywords
- circuit port
- short
- discharge
- insulation
- voltage
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000009413 insulation Methods 0.000 title claims abstract description 142
- 238000000034 method Methods 0.000 title claims abstract description 72
- 229910052782 aluminium Inorganic materials 0.000 title claims abstract description 70
- XAGFODPZIPBFFR-UHFFFAOYSA-N aluminium Chemical compound [Al] XAGFODPZIPBFFR-UHFFFAOYSA-N 0.000 title claims abstract description 70
- 238000005868 electrolysis reaction Methods 0.000 title claims abstract description 61
- 238000012544 monitoring process Methods 0.000 title claims abstract description 38
- 230000015556 catabolic process Effects 0.000 claims description 130
- 238000006731 degradation reaction Methods 0.000 claims description 117
- 230000006866 deterioration Effects 0.000 claims description 22
- 238000009826 distribution Methods 0.000 claims description 19
- 230000000694 effects Effects 0.000 claims description 19
- 230000008569 process Effects 0.000 claims description 16
- 230000007547 defect Effects 0.000 claims description 15
- 238000004590 computer program Methods 0.000 claims description 13
- 239000011159 matrix material Substances 0.000 claims description 9
- 238000007500 overflow downdraw method Methods 0.000 claims description 9
- 238000013506 data mapping Methods 0.000 claims description 8
- 238000003860 storage Methods 0.000 claims description 8
- 238000001228 spectrum Methods 0.000 claims description 5
- 238000001914 filtration Methods 0.000 claims description 3
- 230000009191 jumping Effects 0.000 claims description 3
- 238000001514 detection method Methods 0.000 abstract description 11
- 239000000428 dust Substances 0.000 description 19
- 238000003745 diagnosis Methods 0.000 description 14
- 238000009825 accumulation Methods 0.000 description 11
- 238000005422 blasting Methods 0.000 description 11
- 230000009471 action Effects 0.000 description 7
- 238000010586 diagram Methods 0.000 description 7
- 229910052751 metal Inorganic materials 0.000 description 6
- 239000002184 metal Substances 0.000 description 6
- 238000004422 calculation algorithm Methods 0.000 description 5
- 230000006870 function Effects 0.000 description 5
- 230000004927 fusion Effects 0.000 description 5
- 238000013507 mapping Methods 0.000 description 5
- 238000012545 processing Methods 0.000 description 5
- 101100083446 Danio rerio plekhh1 gene Proteins 0.000 description 4
- 230000032683 aging Effects 0.000 description 4
- 238000004458 analytical method Methods 0.000 description 4
- 238000012360 testing method Methods 0.000 description 4
- 238000002474 experimental method Methods 0.000 description 3
- 230000006872 improvement Effects 0.000 description 3
- 238000011160 research Methods 0.000 description 3
- 101100129500 Caenorhabditis elegans max-2 gene Proteins 0.000 description 2
- 241001391944 Commicarpus scandens Species 0.000 description 2
- 238000012937 correction Methods 0.000 description 2
- 230000005684 electric field Effects 0.000 description 2
- 230000001788 irregular Effects 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 230000000750 progressive effect Effects 0.000 description 2
- 238000005070 sampling Methods 0.000 description 2
- 241000283073 Equus caballus Species 0.000 description 1
- 230000002159 abnormal effect Effects 0.000 description 1
- 230000006978 adaptation Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 230000002950 deficient Effects 0.000 description 1
- 238000002405 diagnostic procedure Methods 0.000 description 1
- 238000012631 diagnostic technique Methods 0.000 description 1
- 238000007599 discharging Methods 0.000 description 1
- 238000005315 distribution function Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000004880 explosion Methods 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 238000009421 internal insulation Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 239000002923 metal particle Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000001681 protective effect Effects 0.000 description 1
- 230000003252 repetitive effect Effects 0.000 description 1
- 238000012827 research and development Methods 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 230000005236 sound signal Effects 0.000 description 1
- 238000003786 synthesis reaction Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/12—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing
- G01R31/1209—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing using acoustic measurements
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R19/00—Arrangements for measuring currents or voltages or for indicating presence or sign thereof
- G01R19/165—Indicating that current or voltage is either above or below a predetermined value or within or outside a predetermined range of values
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R19/00—Arrangements for measuring currents or voltages or for indicating presence or sign thereof
- G01R19/165—Indicating that current or voltage is either above or below a predetermined value or within or outside a predetermined range of values
- G01R19/16566—Circuits and arrangements for comparing voltage or current with one or several thresholds and for indicating the result not covered by subgroups G01R19/16504, G01R19/16528, G01R19/16533
- G01R19/16585—Circuits and arrangements for comparing voltage or current with one or several thresholds and for indicating the result not covered by subgroups G01R19/16504, G01R19/16528, G01R19/16533 for individual pulses, ripple or noise and other applications where timing or duration is of importance
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R19/00—Arrangements for measuring currents or voltages or for indicating presence or sign thereof
- G01R19/165—Indicating that current or voltage is either above or below a predetermined value or within or outside a predetermined range of values
- G01R19/16566—Circuits and arrangements for comparing voltage or current with one or several thresholds and for indicating the result not covered by subgroups G01R19/16504, G01R19/16528, G01R19/16533
- G01R19/1659—Circuits and arrangements for comparing voltage or current with one or several thresholds and for indicating the result not covered by subgroups G01R19/16504, G01R19/16528, G01R19/16533 to indicate that the value is within or outside a predetermined range of values (window)
- G01R19/16595—Circuits and arrangements for comparing voltage or current with one or several thresholds and for indicating the result not covered by subgroups G01R19/16504, G01R19/16528, G01R19/16533 to indicate that the value is within or outside a predetermined range of values (window) with multi level indication
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/12—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing
- G01R31/1227—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing of components, parts or materials
- G01R31/1245—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing of components, parts or materials of line insulators or spacers, e.g. ceramic overhead line cap insulators; of insulators in HV bushings
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/12—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing
- G01R31/14—Circuits therefor, e.g. for generating test voltages, sensing circuits
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Chemical & Material Sciences (AREA)
- Engineering & Computer Science (AREA)
- Ceramic Engineering (AREA)
- Acoustics & Sound (AREA)
- Testing Relating To Insulation (AREA)
Abstract
The invention discloses an on-line monitoring method and a system for insulation of an aluminum electrolysis cell short circuit port based on a partial discharge signal, wherein the method comprises the steps of monitoring the short circuit port voltage and an ultrasonic signal of the aluminum electrolysis cell, if the short circuit port voltage exceeds a set value or the ultrasonic signal is detected, performing fault classification based on the partial discharge signal in the short circuit port voltage to determine the insulation state of the short circuit port, and performing fault classification based on the voiceprint characteristic of the ultrasonic signal to determine the insulation state of the short circuit port; and fusing the two determined short-circuit port insulating states to obtain a final short-circuit port insulating state. The invention carries out fault classification based on the partial discharge signal in the short circuit port voltage to determine the insulation state of the short circuit port, can accurately realize the detection of the insulation state of the short circuit port, and can ensure the reliability and the accuracy of the insulation state detection of the short circuit port by fusing the insulation state of the short circuit port with the insulation state of the short circuit port by carrying out fault classification based on the voiceprint characteristics of the ultrasonic signal.
Description
Technical Field
The invention relates to the technical field of electrolytic aluminum, in particular to an on-line monitoring method and system for insulation of an aluminum electrolysis cell short circuit port based on partial discharge signals.
Background
The aluminum electrolysis cell is an important device for producing electrolytic aluminum, and the production efficiency and quality of the aluminum are affected by the internal insulation of the aluminum electrolysis cell, wherein the insulation of the short circuit port of the aluminum electrolysis cell is one of the main insulation of the aluminum electrolysis cell. The short circuit port insulation of the electrolytic tank mainly comprises an air gap, a bus guard board, an insulation board and an insulation sleeve. The electrolytic cell is additionally provided with an insulating plate when electrified, so that the upright bus bar is separated from the short-circuit bus bar, and current flows into the cathode bus bar after acting from the anode to the electrolytic cell; the cathode short-circuit bus of the production-stopping electrolytic tank is directly connected with the anode bus (the power-off plate is removed) and separated from the whole power supply loop. In the event of a short circuit port fault, the "blow out" fault is particularly pronounced. The intrinsic causes of the "blasting" failure at the short circuit port are deterioration of the short circuit port insulation, including aging of insulation plates, concentrated defects, and accumulation of metal chips and dust in gaps. The external factors of the blasting failure at the short circuit port are abnormal voltage rise at the short circuit port, including electrolytic tank effect voltage rise, voltage rise formed by the breaking of the electrolytic tank series conductive loop, and the like, wherein the blasting failure caused by the breaking has serious consequences. Therefore, a diagnostic technique for studying the insulation condition of the short-circuit junction is of great importance to ensure safe operation of the electrolytic cell series. At present, in industry, no mature method exists for diagnosing and early warning the insulation of the short circuit port of the electrolytic tank, and most enterprises prevent the insulation fault of the short circuit port by improving the insulation level of the short circuit port, replacing the insulation at fixed time, and the like.
Disclosure of Invention
The invention aims to solve the technical problems: aiming at the problems in the prior art, the invention provides an on-line monitoring method and system for the insulation of the short circuit port of the aluminum electrolysis cell based on the partial discharge signals.
In order to solve the technical problems, the invention adopts the following technical scheme:
an aluminum electrolysis cell short-circuit port insulation on-line monitoring method based on partial discharge signals comprises the following steps:
s101, monitoring the voltage of a short circuit port of the aluminum electrolysis cell and an ultrasonic signal, and jumping to the next step if the voltage of the short circuit port exceeds a set value or the ultrasonic signal is detected:
s102, performing fault classification based on partial discharge signals in the short circuit port voltage to determine the insulation state of the short circuit port, and performing fault classification based on voiceprint features of ultrasonic signals to determine the insulation state of the short circuit port;
s103, fusing the two determined short-circuit port insulating states to obtain a final short-circuit port insulating state, wherein the short-circuit port insulating state is one of a plurality of insulating state grade states which are distributed continuously.
Optionally, performing fault classification based on the partial discharge signal in the short-circuit voltage in step S102 includes:
s201, separating pulse signals from waveform signals of short-circuit port voltages with specified duration;
s202, extracting characteristic quantity of a pulse signal;
s203, determining the insulation state of the short-circuit opening by using a specified fault classification method according to the characteristic quantity of the pulse signal.
Optionally, before separating the pulse signal from the collected waveform signal of the short-circuit voltage with the specified duration in step S201, filtering the waveform signal of the short-circuit voltage by adopting a band-pass filter to suppress the field interference signal, where the center frequency of the band-pass filter is 300kHz and the bandwidth is 100kHz.
Optionally, the feature quantity of the pulse signal extracted in step S202 includes:
s301, respectively extracting an initial discharge voltage U, an apparent discharge quantity Q and a discharge pulse number N of pulse signals, wherein the initial discharge voltage U is a short-circuit port voltage when a first discharge pulse appears, the apparent discharge quantity Q is a discharge quantity obtained by calibration of a voltage sensor of a discharge pulse amplitude and the short-circuit port voltage, and the discharge pulse number N is the number of discharge pulses per second in a specified duration;
s302, the initial discharge voltage U, the apparent discharge quantity Q and the discharge pulse number N of the pulse signal are normalized to be within the value range [0,1] to obtain the degradation degree U of the initial discharge voltage, the degradation degree Q of the apparent discharge quantity and the degradation degree N of the discharge pulse number as the characteristic quantity of the pulse signal.
Optionally, determining the insulation state of the short-circuit junction in step S103 by using the specified fault classification method includes:
s401, respectively representing the insulating state grade states of the continuous distributions as the relative degradation degrees of the continuous distributions in the value ranges [0,1], and determining the data mapping relation between the insulating state grade states and the relative degradation degrees;
s402, determining a decision matrix which is constructed by comparing the degradation degree u of the initial discharge voltage, the degradation degree q of the apparent discharge quantity and the degradation degree n of the discharge pulse number according to a scale method for judging the importance degree of insulation degradation effect of the short-circuit mouth of the aluminum electrolysis cell, and respectively determining the weights of the degradation degree u of the initial discharge voltage, the degradation degree q of the apparent discharge quantity and the degradation degree n of the discharge pulse number by adopting an improved analytic hierarchy process based on the decision matrix;
s403, calculating the relative degradation degree of the short-circuit port of the aluminum electrolysis cell according to the following formula:
S＝w n ·n+w q ·q+w u ·u，
in the above description, S represents the relative degradation degree of the short-circuit port of the aluminum electrolysis cell, and w n The weight of the degradation degree n of the number of discharge pulses, n is the degradation degree of the number of discharge pulses, w q The weight of the degradation degree q of the apparent discharge amount, q is the degradation degree of the apparent discharge amount, w u The weight of the degradation degree u of the initial discharge voltage is that u is the degradation degree of the initial discharge voltage;
s404, obtaining the insulation state grade state corresponding to the relative degradation degree based on the relative degradation degree of the short circuit port of the aluminum electrolysis cell, the insulation state grade state and the data mapping relation between the relative degradation degrees.
Optionally, performing fault classification based on voiceprint features of the ultrasonic signal in step S102 includes:
s501, extracting voiceprint features of an ultrasonic signal, wherein the voiceprint features comprise frequency spectrums, amplitude values, mel Frequency Cepstrum Coefficients (MFCC) and gamma cepstrum coefficients (GFCC) of the ultrasonic signal;
s502, comparing the voiceprint characteristics of the ultrasonic signals with a preset characteristic library of the insulating defect discharge voiceprint of the short circuit port of the aluminum electrolysis cell to determine the insulating state of the short circuit port, wherein the characteristic library of the insulating defect discharge voiceprint of the short circuit port of the aluminum electrolysis cell comprises voiceprint characteristic values or value ranges under different insulating states of the short circuit port.
Alternatively, the plurality of sequentially distributed insulation state level states in step S103 include four states of good, slight deterioration, moderate deterioration, and severe deterioration.
Optionally, the fusing in step S103 to obtain the final insulating state of the short-circuit port includes: and taking the two short-circuit port insulating states as sub evidence bodies of a data fusion method based on the D-S evidence theory, and obtaining the final short-circuit port insulating state by utilizing the data fusion method based on the D-S evidence theory.
In addition, the invention also provides an aluminum electrolysis cell short-circuit opening insulation on-line monitoring system based on the partial discharge signal, which comprises a microprocessor and a memory which are connected with each other, wherein the microprocessor is programmed or configured to execute the aluminum electrolysis cell short-circuit opening insulation on-line monitoring method based on the partial discharge signal.
In addition, the invention also provides a computer readable storage medium, wherein the computer readable storage medium is stored with a computer program, and the computer program is used for being programmed or configured by a microprocessor to execute the aluminum electrolysis cell short-circuit port insulation on-line monitoring method based on the partial discharge signal.
Compared with the prior art, the invention has the following advantages: monitoring the voltage of a short circuit port of an aluminum electrolysis cell and an ultrasonic signal, if the voltage of the short circuit port exceeds a set value or the ultrasonic signal is detected, performing fault classification based on a partial discharge signal in the voltage of the short circuit port to determine the insulation state of the short circuit port, and performing fault classification based on the voiceprint characteristic of the ultrasonic signal to determine the insulation state of the short circuit port; and fusing the two determined short-circuit port insulating states to obtain a final short-circuit port insulating state. The invention carries out fault classification based on the partial discharge signal in the short circuit port voltage to determine the insulation state of the short circuit port, can accurately realize the detection of the insulation state of the short circuit port, and can ensure the reliability and the accuracy of the insulation state detection of the short circuit port by fusing the insulation state of the short circuit port with the insulation state of the short circuit port by carrying out fault classification based on the voiceprint characteristics of the ultrasonic signal.
Drawings
Fig. 1 shows a short-circuit discharge pulse waveform detected in an embodiment of the present invention.
Fig. 2 is a schematic diagram of a basic flow of a method according to an embodiment of the present invention.
FIG. 3 is a detailed flow chart of the method according to the embodiment of the invention.
Fig. 4 shows a waveform of a detection pulse of a short-circuit port simulated discharge test sensor according to an embodiment of the present invention.
Detailed Description
The research shows that when the electrolytic tank generates anode effect, the voltage of the electrolytic tank, namely the voltage of a short-circuit port is rapidly increased to about 50V; if the insulation of the short circuit port is deteriorated, the metal dust entering and the deterioration of the insulation board are mainly aged. The metal dust is accumulated on the surface of the bus bar to form a tip electrode, and the voltage is not high, but the local field is strong, so that partial discharge is generated. If the insulating board burns and ages, when the voltage rises, especially when the direct current loop is broken, the voltage of a short circuit port may rise to the working voltage, the discharge further develops, the insulating board opening and the insulating screw rod generate surface flashover, and the short circuit port is broken down in an insulating way, so that a blasting fault is generated. And the insulation fault of the short-circuit port of the aluminum electrolysis cell has the following rules: (1) Partial discharge (partial discharge) must occur before the blasting failure. In the early stage of insulation degradation, dust accumulation is small, a short-circuit port gap forms local field intensity at the burr tip under the action of effect voltage to generate partial discharge, but the voltage is not too high, the partial discharge is weaker, and the gap cannot break down. Even if the 'open circuit' happens, the discharge does not reach the critical value, and the gap of the short circuit port is not broken down. Partial discharge of the gap under the effect voltage is a phenomenon which inevitably occurs in the process of insulation degradation, and the initial stage of gap breakdown is partial discharge. Theory and experiment show that: the gap breakdown process is as follows: partial discharge is generated first, brush-shaped discharge is formed as the applied voltage rises and corona discharge extends, and finally if the voltage exceeds a certain threshold value, surface flashover occurs. When the dust accumulation on the surface of the electrode is slight, the accumulation point is raised to be thin and pointed, and when the voltage is increased, the electric field intensity at the point reaches the ionization degree of the gas to generate partial discharge, but the partial discharge is weak, and the pulse amplitude is small; positive space charges generated by ionization at the tip end homogenize the electric field, so that the gap is not easy to break down. When dust on the surface of the electrode is accumulated more, the two electrodes are almost bridged, the field intensity is stronger under the same voltage, and partial discharge generated at the tip is easier to develop to a gap and is easy to break down. (2) And detecting partial discharge of the short circuit port to realize blasting early warning. In general, insulation board high temperature burn aging, gap dust accumulation, etc. are a progressive process. Breakdown is only possible under the effect of the voltage effect if the insulation deteriorates and interstitial metal dust accumulates to some extent. Therefore, the insulation defect is detected before the insulation degradation critical state of the short-circuit port, and the occurrence of the blasting fault can be completely prevented. (3) discharge pulse rule of the short circuit port. According to the analysis of the breakdown mechanism of the gap of the short circuit port, the gap of the short circuit port is simulated by a tip-plate electrode structure, the gap is discharged under the action of direct current voltage, the short circuit port detects the discharge pulse of the circuit voltage and current waveform, and the pulse current waveform characteristics of the breakdown process are as follows: (1) when the voltage is low, even if gas is ionized, the discharge current is extremely small and the waveform is irregular; (2) when the voltage rises to a certain value, a more remarkable repetitive pulse current waveform with regularity appears, as shown in fig. 1, wherein t is time, and i is pulse current; (3) the voltage continues to rise, the current pulse amplitude is unchanged, but the frequency is increased, the pulse waveforms are dense, even the front and back overlap, and the average current is continuously increased; (4) the voltage is increased again, the discharge is further developed, brush-shaped discharge appears when breakdown is near, and irregular strong current pulse appears again; (5) eventually breakdown occurs. If the insulating state of the short circuit port is divided into: good, generally defective (operational), severe (critical breakdown) four states. Wherein: the insulation board is good in insulation, and dust accumulation in the gap is avoided; dust is accumulated in the gaps generally, but partial discharge is not generated under the action of effect voltage, and the insulating plate is well insulated; the defect is that dust in the gap is accumulated to a certain degree, partial discharge is generated under the action of higher effect voltage, and insulation of the insulating plate is slightly deteriorated; the defect that dust is seriously accumulated in gaps, partial discharge is developed to a critical flashover state under the action of effect voltage, and insulation of an insulating plate is seriously deteriorated is overcome. In order to prevent the explosion fault of the short circuit port, the insulation fault is detected before the critical breakdown of the insulation defect is not reached, so that the insulation state of the short circuit port can be judged according to the current waveform or the voltage waveform in the short circuit port monitoring loop. Therefore, the principle of the method for on-line monitoring of the short circuit port insulation of the aluminum electrolysis cell based on the partial discharge signals is that the short circuit port insulation state is determined based on the fault classification of the partial discharge signals in the short circuit port voltage, whether partial discharge occurs in the process of increasing the short circuit port voltage when the electrolytic cell is in effect or not, the voltage magnitude and the current pulse characteristics when the partial discharge occurs can be utilized to determine the insulation degradation state, and when obvious discharge pulses occur in the short circuit port voltage detection circuit and the pulse waveform deformation is dense, the insulation state is determined to be a defect state, and the insulation state is detected before critical breakdown. Protective measures such as replacing insulating plates, removing dust in the gap of the short circuit port, eliminating burrs, etc. are taken before the insulation is deteriorated to a critical degree. Further, it is further contemplated that partial discharge of the short-circuit port gap may generate an electrical pulse signal in the short-circuit port voltage measurement loop while simultaneously transmitting voiceprint signals (including audible sound and ultrasonic waves), ultrasonic signals detectable on the insulating sleeve, and very high frequency signals. Therefore, fault classification is carried out on the voiceprint characteristics based on ultrasonic signals to determine the insulation state of the short-circuit port, and the two determined insulation states of the short-circuit port are fused to obtain the final insulation state of the short-circuit port so as to improve the effectiveness and reliability of on-line monitoring of the insulation of the short-circuit port of the aluminum electrolysis cell.
As shown in fig. 2, the method for on-line monitoring insulation of the short circuit port of the aluminum electrolysis cell based on the partial discharge signal in the embodiment comprises the following steps:
s101, monitoring the voltage of a short circuit port of the aluminum electrolysis cell and an ultrasonic signal, and jumping to the next step if the voltage of the short circuit port exceeds a set value or the ultrasonic signal is detected:
s102, performing fault classification based on partial discharge signals in the short circuit port voltage to determine the insulation state of the short circuit port, and performing fault classification based on voiceprint features of ultrasonic signals to determine the insulation state of the short circuit port;
s103, fusing the two determined short-circuit port insulating states to obtain a final short-circuit port insulating state, wherein the short-circuit port insulating state is one of a plurality of insulating state grade states which are distributed continuously.
In step S101, if the short-circuit voltage exceeds 8V, it is determined that the electrolytic cell has an anode effect, and the monitoring system is activated to detect the collected voltage signal, analyze the voltage waveform, and determine whether a "discharge pulse" is generated.
Referring to fig. 3, the fault classification based on the partial discharge signal in the short-circuit voltage in step S102 of the present embodiment includes:
s201, separating pulse signals from waveform signals of short-circuit port voltages with specified duration;
s202, extracting characteristic quantity of a pulse signal;
s203, determining the insulation state of the short-circuit opening by using a specified fault classification method according to the characteristic quantity of the pulse signal.
It should be noted that the specified duration in step S201 may be specified according to actual needs, for example, as an alternative implementation, the specified duration in this embodiment specifically refers to 1 second.
In this embodiment, before separating the pulse signal from the collected waveform signal of the short-circuit voltage with the specified duration in step S201, filtering the waveform signal of the short-circuit voltage with a band-pass filter to suppress the field interference signal, where the center frequency of the band-pass filter is 500kHz and the bandwidth is 200kHz.
In this embodiment, the feature values of the pulse signal extracted in step S202 include:
s301, respectively extracting an initial discharge voltage U, an apparent discharge quantity Q and a discharge pulse number N of pulse signals, wherein the initial discharge voltage U is a short-circuit port voltage when a first discharge pulse appears, the apparent discharge quantity Q is a discharge quantity obtained by calibration of a voltage sensor of a discharge pulse amplitude and the short-circuit port voltage, and the discharge pulse number N is the number of discharge pulses per second in a specified duration;
s302, the initial discharge voltage U, the apparent discharge quantity Q and the discharge pulse number N of the pulse signal are normalized to be within the value range [0,1] to obtain the degradation degree U of the initial discharge voltage, the degradation degree Q of the apparent discharge quantity and the degradation degree N of the discharge pulse number as the characteristic quantity of the pulse signal. In the present embodiment, for the number of discharge pulses N: n=0, which indicates that the short circuit port has no partial discharge and has good insulation; n is more than or equal to 10, and represents the serious deterioration of the insulation of the short-circuit port and is the insulation deterioration warning value of the short-circuit port; for apparent discharge Q: q=0, which means that the short circuit port has no partial discharge and has good insulation; q is more than or equal to 50PC, and represents the serious deterioration of the insulation of the short circuit port, and is the insulation deterioration warning value of the short circuit port; for the initial discharge voltage U: when the anode effect of the aluminum electrolysis cell occurs, the voltage of the short circuit port is increased, and if the voltage is increased to 60V and partial discharge does not exist, the short circuit port is considered to have good insulation state; if the short-circuit port voltage is slightly increased, partial discharge occurs, the short-circuit port insulation is seriously deteriorated, and U=20V is taken as a short-circuit port insulation deterioration warning value. Therefore, the functional expression for normalizing the initial discharge voltage U of the pulse signal in this embodiment is:
in the above formula, U represents the initial discharge voltage.
The functional expression for normalizing the apparent discharge Q is:
the functional expression for normalizing the number of discharge pulses N is:
on the basis, the insulation state of the short-circuit mouth can be determined by using a specified fault classification method by using three characteristic indexes of the degradation degree u of the initial discharge voltage, the degradation degree q of the apparent discharge quantity and the degradation degree n of the discharge pulse number.
In this embodiment, determining the insulation state of the short-circuit junction using the specified fault classification method in step S103 includes:
s401, respectively representing the insulating state grade states of the continuous distributions as the relative degradation degrees of the continuous distributions in the value ranges [0,1], and determining the data mapping relation between the insulating state grade states and the relative degradation degrees;
s402, determining a decision matrix which is constructed by comparing the degradation degree u of the initial discharge voltage, the degradation degree q of the apparent discharge quantity and the degradation degree n of the discharge pulse number according to a scale method for judging the importance degree of insulation degradation effect of the short-circuit mouth of the aluminum electrolysis cell, and respectively determining the weights of the degradation degree u of the initial discharge voltage, the degradation degree q of the apparent discharge quantity and the degradation degree n of the discharge pulse number by adopting an improved analytic hierarchy process based on the decision matrix;
s403, calculating the relative degradation degree of the short-circuit port of the aluminum electrolysis cell according to the following formula:
S＝w n ·n+w q ·q+w u ·u，
in the above description, S represents the relative degradation degree of the short-circuit port of the aluminum electrolysis cell, and w n The weight of the degradation degree n of the number of discharge pulses, n is the degradation degree of the number of discharge pulses, w q The weight of the degradation degree q of the apparent discharge amount, q is the degradation degree of the apparent discharge amount, w u The weight of the degradation degree u of the initial discharge voltage is that u is the degradation degree of the initial discharge voltage;
s404, obtaining the insulation state grade state corresponding to the relative degradation degree based on the relative degradation degree of the short circuit port of the aluminum electrolysis cell, the insulation state grade state and the data mapping relation between the relative degradation degrees.
As an alternative embodiment, the plurality of continuously distributed insulation state grade states in step S103 in this embodiment include four states of good, slight degradation, moderate degradation and severe degradation, and the data mapping relationship between the insulation state grade states and the relative degradation degree determined in step S401 in this embodiment is specifically shown in table 1.
Table 1: and a data mapping relation table between the insulating state grade state and the relative degradation degree.
| Status level | Degree of relative deterioration | Insulation state grade state |
| H1 | 0-0.1 | Good quality |
| H2 | 0.1-0.3 | Slightly deteriorated |
| H3 | 0.3-0.7 | Moderate deterioration |
| H4 | 0.7-1.0 | Severe deterioration |
In step S402 of the present embodiment, a decision matrix a is specifically determined, which is constructed by comparing three experts in a scale method according to three indexes of the degradation degree u of the initial discharge voltage, the degradation degree q of the apparent discharge amount and the degradation degree n of the discharge pulse number, to determine the importance degree of insulation degradation effect of the short circuit port of the aluminum electrolysis cell 1 、A 2 、A 3 Wherein the scale is fixedThe meaning is as follows:
| scale a ij | Meaning of the following description |
| 1 | Index i is as important as index j |
| 3 | Index i is slightly more important than |
| 5 | Index i is more important than index j |
| 7 | Index i is important compared with index j |
| 2,4,6 | Intermediate values of 1-3,3-5,5-7 |
| a ji | Taking 1/a as the importance degree of index j relative to index i ij |
Finally, a decision matrix A is obtained 1 、A 2 、A 3 The following are provided:
on the basis, the degradation degree u of the initial discharge voltage, the degradation degree q of the apparent discharge quantity and the degradation degree n of the discharge pulse number can be respectively determined by adopting an improved analytic hierarchy process based on a decision matrix, and it is to be noted that the improved analytic hierarchy process is an existing index weight analysis method, and in the embodiment, only the application of the improved analytic hierarchy process is involved, and the improvement of the improved analytic hierarchy process is not involved, and the specific implementation can be seen in: litt, research on oil paper insulation aging diagnosis method of transformer [ D ]]University of North China, university of electric power, 2019. Finally, the weight of the degradation degree u of the initial discharge voltage, the degradation degree q of the apparent discharge amount, and the degradation degree n of the discharge pulse number obtained in this example is w= (W n ,w q ,w u ) = (0.5337,0.2331,0.2331). Therefore, in step S403, the relative degradation degree of the aluminum electrolysis cell short-circuit port may be calculated according to the following formula:
S＝0.5337·n+0.2331·q+0.2331·u，
in the above description, S represents the relative degradation degree of the short-circuit port of the aluminum electrolysis cell, and w n The weight of the degradation degree n of the number of discharge pulses, n is the degradation degree of the number of discharge pulses, w q The weight of the degradation degree q of the apparent discharge amount, q is the degradation degree of the apparent discharge amount, w u The degradation degree u of the initial discharge voltage is given by the weight of the degradation degree u of the initial discharge voltage. For example, the initial discharge voltage u=40, the apparent discharge quantity q=10, and the discharge pulse number n=4 of the pulse signal extracted in this embodiment are normalized to obtain the degradation degree u=0.4 of the initial discharge voltage, the degradation degree q=0.2 of the apparent discharge quantity, and the degradation degree n=0.4 of the discharge pulse number, and the relative degradation degree of the final aluminum electrolysis cell short-circuit mouth is:
S＝0.5337×0.4+0.2331×0.2+0.2331×0.4＝0.3533
referring to table 1, the insulation state grade state is a moderate degradation H3.
When the insulation of the short circuit opening of the electrolytic cell is deteriorated to a certain extent, partial discharge can occur under the action of the anode effect voltage of the electrolytic cell, and not only electric pulse but also audible sound and ultrasonic signals can be generated. In consideration of the field environment and the detection means, the method is to additionally install an ultrasonic sensor on an anode bus of the short-circuit port, detect ultrasonic signals generated by discharge of the short-circuit port, analyze and classify voiceprint signals, and qualitatively judge the state of insulation of the short-circuit port. Partial discharge must occur before the blasting failure: analysis shows that dust accumulation is small in the early stage of insulation degradation, a short-circuit port gap forms local field intensity at the burr tip under the action of effect voltage to generate partial discharge, but the partial discharge is weaker, if the voltage is not increased any more, the gap cannot break down. Detecting the partial discharge of the short circuit port to realize 'blasting' early warning: gap dust accumulation and insulation degradation are a progressive process. Only if the insulation deteriorates to some extent will breakdown under the effect of the voltage. Therefore, the critical state of insulation breakdown of the short circuit port is studied, the insulation defect is detected and early-warned before the critical state, and the occurrence of blasting faults can be completely prevented. The short circuit port discharges the characteristic of the electroacoustic line signal: and establishing a short-circuit port insulation simulation device, testing and researching voiceprint signal characteristics of a short-circuit port gap in the process from discharging to breakdown, determining voiceprint characteristic quantity representing the insulation state of the short-circuit port, and constructing a voiceprint characteristic library in four states of good, slight degradation, moderate degradation and serious degradation, thereby providing a basis for the diagnosis of the insulation state of the actual short-circuit port. Diagnosis of insulation state of short-circuit port: and measuring the discharge electric ripple signal of the short circuit port, extracting the voiceprint characteristics, and diagnosing the insulating state of the short circuit port based on the discharge electric ripple characteristic library of the short circuit port.
In this embodiment, performing fault classification based on the voiceprint features of the ultrasonic signal in step S102 includes:
s501, extracting voiceprint features of an ultrasonic signal, wherein the voiceprint features comprise frequency spectrums, amplitude values, mel Frequency Cepstrum Coefficients (MFCC) and gamma cepstrum coefficients (GFCC) of the ultrasonic signal;
s502, comparing the voiceprint characteristics of the ultrasonic signals with a preset characteristic library of the insulating defect discharge voiceprint of the short circuit port of the aluminum electrolysis cell to determine the insulating state of the short circuit port, wherein the characteristic library of the insulating defect discharge voiceprint of the short circuit port of the aluminum electrolysis cell comprises voiceprint characteristic values or value ranges under different insulating states of the short circuit port. In this embodiment, the comparison of the voiceprint characteristics of the ultrasonic signal with the preset voiceprint characteristic library of the insulation defect of the short-circuit port of the aluminum electrolysis cell to determine the insulation state of the short-circuit port is realized by adopting a gray correlation algorithm, but in this embodiment, only the application of the gray correlation algorithm is involved, the improvement of the gray correlation algorithm is not involved, and the specific realization can be seen in: wu Weihui, zhou Yuanyuan, zhou Li improved gray correlation algorithm for transformer fault diagnosis, programming for science and technology 2009,24 (03): 45-48+53.
The effectiveness of fault classification based on voiceprint features of ultrasonic signals is represented by: (1) partial discharge ultrasonic signal sensor: from the insulating structure of the short circuit port and the propagation characteristics of discharge ultrasonic waves, the propagation attenuation of the ultrasonic waves in the metal is very small. Therefore, if partial discharge occurs at the short-circuit port, an ultrasonic sensor is arranged on the anode upright post bus bar, the couplant is coated at the contact point, ultrasonic signals generated by the discharge can be effectively monitored, and the effectiveness of the ultrasonic sensor is proved by tests and the partial discharge ultrasonic detection of electrical equipment. (2) Voiceprint signal characteristics generated by partial discharge: the short-circuit mouth discharge mainly comprises: the spike discharge formed by the accumulation of metal dust is along the surface of the insulated screw. Therefore, a needle-plate model and a column-plate model are constructed, the discharge phenomenon of the short circuit in the insulation four states is simulated, ultrasonic signals and audio signals in the discharge process are collected, characteristic quantities such as frequency spectrums, amplitude values, frequency cepstrum coefficients MFCC and GFCC are analyzed and extracted, and a typical insulation defect discharge ripple characteristic library of the short circuit is constructed. (3) The partial discharge voiceprint detection is applied to the online monitoring of the partial discharge of the transformer, and lays a foundation for the research and development of the method. The voiceprint diagnosis result can be deeply fused with the electric pulse diagnosis result, the insulation condition of the short-circuit port can be accurately judged, and early warning is given. The method can completely realize the insulation degradation monitoring of the short circuit port and prevent the occurrence of blasting faults.
The final insulating state of the short-circuit port obtained by fusion in step S103 may be obtained by using a desired method including a weighting method, a voting method, etc. as required. However, in consideration of the priority of the accuracy of the fusion results obtained by the weighting method, the voting method, and the like, as a preferred embodiment, the fusion in step S103 of this embodiment to obtain the final short-circuit-port insulating state includes: and taking the two short-circuit port insulating states as sub evidence bodies of a data fusion method based on the D-S evidence theory, and obtaining the final short-circuit port insulating state by utilizing the data fusion method based on the D-S evidence theory.
The embodiment relates to application of the data fusion method based on the D-S evidence theory only, and does not relate to improvement of the data fusion method based on the D-S evidence theory, and specific implementation can be seen in: litt, research on oil paper insulation aging diagnosis method of transformer [ D ]]University of North China, university of electric power, 2019. As described above, the plurality of continuously distributed insulation state level states in step S103 of the present embodiment include four states of good, slight degradation, moderate degradation, and severe degradation, which can be expressed as: Θ= { H 1 ,H 2 ,H 3 ,H 4 And, where Θ is the recognition framework of the D-S evidence theory. H denotes a subset of the recognition frames Θ, i.e
All possible hypotheses in Θ form a set, with power set 2 Θ Representing, if there is a mapping: m is 2 Θ —[0,1]And satisfies:
m(Φ)＝0，
m (H) is more than or equal to 0 and
that is, the mapping result m (Φ) of the empty set is 0, the mapping result m (H) of any subset H is 0 or more, and the sum of the mapping results m (H) of all subsets H is 1. In the D-S evidence theory, the mapping result m (H) of the subset H is called as the basic probability distribution of the subset H of the recognition framework Θ, and the support degree of the sub-evidence body to the subset H is represented. Each sub evidence body is a partial discharge pulse method diagnosis result and a partial discharge ultrasonic method diagnosis result, and the membership degree of the sub evidence body to different insulation degradation grades represents trust allocation of the evidence body to the state grade in the identification framework. The data fusion method based on the D-S evidence theory aims at comprehensively processing the multi-source evidence to obtain final basic probability distribution and credibility functions. The rule of composition of the two child evidence bodies is determined as follows:
K＝∑ A∩B＝Φ m 1 (A)m 2 (B)，
where K represents a collision factor between evidence, and the larger the K value, the larger the collision between evidence. m is m 1 (A) And m 2 (B) Representing the basic probability distributions of A and B, respectively, and A and B are power set 2 Θ And the medium element phi is an empty set.
The rule of composition of the multiple pieces of evidence may be determined as follows:
wherein m is 1 (A 1 )～m n (A n ) Representing the basic probability distribution of n sub evidence bodies respectively, and A 1 ～A n Is a power set 2 Θ And the medium element phi is an empty set.
Based on the above steps, the basic probability distribution m (H) of each insulation state level state H can be finally calculated. In order to avoid errors in fusion results caused by collisions between evidence, an open framework composition rule is employed. The relative importance degree of different evidences is different, and a confidence coefficient alpha is introduced k To represent the confidence level of evidence, alpha k The larger the value, the higher the evidence credibility. Will be alpha k For correcting the basic trust distribution before evidence synthesis, the corrected basic probability distribution is determined by the following formula:
m k (H)＝α k m k (H)′，
in the above, m k (H) And m k (H) ' basic probability distribution after correction and before correction respectively, and there are:
α k ＝α K γ k ，
γ k ＝ω k /ω max ，
in the above, alpha K Taking 0.9 in the embodiment as the priority credibility; omega k Weight, ω, of the kth insulation state class state max Is the maximum value of the weights of all the insulating state level states. On this basis, it is assumed that, of the corrected basic probability distributions corresponding to the respective subsets in the recognition frame Θ, the maximum basic probability distribution corresponding to the two diagnostic methods is m (H max1 ) And m (H) max2 ) In this embodiment, the maximum basic probability distribution function rule is adopted to judge the diagnosis target, which requires: (1) diagnostic grade determination result m (H) max1 ) Should be greater than the base probability distribution value m (Θ); (2) diagnostic grade determination result m (H) max1 ) And the difference from the other basic probability distribution values of any level (m (H max1 )-m(H max2 ) Not less than the set threshold epsilon 0 Threshold epsilon 0 The value can be taken according to actual needs, for example, the embodiment is specifically set to be 0.001; (3) the basic probability distribution value m (Θ) of uncertainty is smaller than a set threshold epsilon 1 Threshold epsilon 1 The value can be set to 0.05 according to practical needs, for example, in this embodiment.
The above requirements can be expressed as:
wherein:
in the above equation, N is the number of subsets in the identification framework Θ. And selecting the maximum basic allocation probability under the comprehensive evidence as a final judgment result by utilizing a decision rule, namely a final judgment rule of the event to be solved.
In order to verify the method of the embodiment, a short-circuit port module experimental device is built in the embodiment, two aluminum plates are used as electrodes, an insulating screw is inserted into the middle of each aluminum plate after the middle of each aluminum plate is perforated and fixed, so that insulating bolts of a short-circuit port are simulated, a proper amount of metal particle dust is scattered into a gap between the two aluminum plates, the dust accumulation phenomenon of the insulating screw on site is simulated, and power lines of two poles of a direct-current voltage source are respectively connected with the two aluminum plates. (2) And the sensor signal acquisition line and the oscilloscope signal line are respectively connected to the two aluminum plates and used for monitoring voltage waveforms at two sides of the short circuit port. (3) And gradually increasing the voltages at two ends of the short-circuit port to generate a discharge phenomenon, recording pulse waveforms acquired by the oscilloscope and the sensor, and recording voiceprint spectrograms acquired by the oscilloscope and voiceprint results detected by the short-circuit port integrated signal sensor. The short-circuit test results are shown in fig. 4 by oscilloscope sampling and sensor sampling. When the discharge phenomenon occurs at the short circuit port, a discharge pulse signal is obviously generated in the voltage waveform, but the gap is not broken down. The experiment proves the correctness and feasibility of the short-circuit junction insulation fault diagnosis method based on partial discharge pulse detection. Experimental results show that when the short circuit port generates a discharge site, a discharge pulse signal is obviously generated in the voltage waveform, but the gap is not broken down; meanwhile, the comprehensive signal sensor of the short-circuit port also judges that the short-circuit port is detected to have a voiceprint signal when the short-circuit port discharges. The experiment proves the correctness and feasibility of the insulation fault diagnosis method based on the partial discharge voiceprint detection short-circuit junction. In addition, the embodiment also utilizes Matlab platform to develop corresponding calculation software to realize the insulation on-line monitoring method of the aluminum electrolysis cell short circuit port based on the partial discharge signal. The partial discharge monitoring result of a certain 350kA electrolytic tank short circuit port is represented as S by the characteristic quantity of partial discharge pulse (apparent discharge quantity q, pulse frequency n, initial discharge voltage Us) 1 = [ good, slight deterioration, moderate deterioration, severe deterioration ]]＝[0.6935,0.3065,0,0]The judgment result is normal and good; and adopts partial discharge voiceprint diagnosis method to obtain the spectrum, amplitude and mel frequency cepstrum coefficients MFCC and gammaThe equine cepstrum coefficient GFCC is taken as a characteristic quantity, and the diagnosis result is S 2 = [ good, slight deterioration, moderate deterioration, severe deterioration ]]＝[0.2349,0.7492,0.0159,0]. The result obtained by adopting the fusion algorithm is S= [ good, slight degradation, moderate degradation and serious degradation]＝[0.1243,0.8204,0.0121,0.0431]The insulation state of the insulating board is slightly degraded by comprehensive analysis, and the insulating board is matched with dust accumulation at the short-circuit port found by on-site inspection and scratch on the insulating board.
In addition, the embodiment also provides an aluminum electrolysis cell short-circuit opening insulation on-line monitoring system based on the partial discharge signal, which comprises a microprocessor and a memory which are connected with each other, wherein the microprocessor is programmed or configured to execute the aluminum electrolysis cell short-circuit opening insulation on-line monitoring method based on the partial discharge signal. In addition, the embodiment also provides a computer readable storage medium, wherein a computer program is stored in the computer readable storage medium, and the computer program is used for being programmed or configured by a microprocessor to execute the aluminum electrolysis cell short-circuit port insulation on-line monitoring method based on the partial discharge signals.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-readable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein. The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks. These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks. These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above examples, and all technical solutions belonging to the concept of the present invention belong to the protection scope of the present invention. It should be noted that modifications and adaptations to the present invention may occur to one skilled in the art without departing from the principles of the present invention and are intended to be within the scope of the present invention.
Claims (10)
1. An aluminum electrolysis cell short-circuit port insulation on-line monitoring method based on partial discharge signals is characterized by comprising the following steps:
s101, monitoring the voltage of a short circuit port of the aluminum electrolysis cell and an ultrasonic signal, and jumping to the next step if the voltage of the short circuit port exceeds a set value or the ultrasonic signal is detected:
s102, performing fault classification based on partial discharge signals in the short circuit port voltage to determine the insulation state of the short circuit port, and performing fault classification based on voiceprint features of ultrasonic signals to determine the insulation state of the short circuit port;
s103, fusing the two determined short-circuit port insulating states to obtain a final short-circuit port insulating state, wherein the short-circuit port insulating state is one of a plurality of insulating state grade states which are distributed continuously.
2. The online monitoring method of aluminum electrolysis cell short-circuit port insulation based on partial discharge signals according to claim 1, wherein the step S102 of performing fault classification based on the partial discharge signals in the short-circuit port voltage comprises:
s201, separating pulse signals from waveform signals of short-circuit port voltages with specified duration;
s202, extracting characteristic quantity of a pulse signal;
s203, determining the insulation state of the short-circuit opening by using a specified fault classification method according to the characteristic quantity of the pulse signal.
3. The online monitoring method for insulation of short-circuit ports of aluminum electrolysis cells based on partial discharge signals according to claim 2, wherein before separating pulse signals from the collected waveform signals of the short-circuit port voltage with specified duration in step S201, filtering the waveform signals of the short-circuit port voltage by adopting a band-pass filter to suppress field interference signals, wherein the center frequency of the band-pass filter is 300kHz, and the bandwidth of the band-pass filter is 100kHz.
4. The online monitoring method for insulation at an aluminum electrolysis cell short-circuit port based on partial discharge signals according to claim 2, wherein the feature quantities of the pulse signals extracted in step S202 comprise:
s301, respectively extracting an initial discharge voltage U, an apparent discharge quantity Q and a discharge pulse number N of pulse signals, wherein the initial discharge voltage U is a short-circuit port voltage when a first discharge pulse appears, the apparent discharge quantity Q is a discharge quantity obtained by calibration of a voltage sensor of a discharge pulse amplitude and the short-circuit port voltage, and the discharge pulse number N is the number of discharge pulses per second in a specified duration;
s302, the initial discharge voltage U, the apparent discharge quantity Q and the discharge pulse number N of the pulse signal are normalized to be within the value range [0,1] to obtain the degradation degree U of the initial discharge voltage, the degradation degree Q of the apparent discharge quantity and the degradation degree N of the discharge pulse number as the characteristic quantity of the pulse signal.
5. The online monitoring method of insulation at short circuit mouth of aluminum electrolysis cell based on partial discharge signal according to claim 4, wherein determining insulation state at short circuit mouth by using specified fault classification method in step S103 comprises:
s401, respectively representing the insulating state grade states of the continuous distributions as the relative degradation degrees of the continuous distributions in the value ranges [0,1], and determining the data mapping relation between the insulating state grade states and the relative degradation degrees;
s402, determining a decision matrix which is constructed by comparing the degradation degree u of the initial discharge voltage, the degradation degree q of the apparent discharge quantity and the degradation degree n of the discharge pulse number according to a scale method for judging the importance degree of insulation degradation effect of the short-circuit mouth of the aluminum electrolysis cell, and respectively determining the weights of the degradation degree u of the initial discharge voltage, the degradation degree q of the apparent discharge quantity and the degradation degree n of the discharge pulse number by adopting an improved analytic hierarchy process based on the decision matrix;
s403, calculating the relative degradation degree of the short-circuit port of the aluminum electrolysis cell according to the following formula:
S＝w n ·n+w q ·q+w u ·u，
in the above description, S represents the relative degradation degree of the short-circuit port of the aluminum electrolysis cell, and w n The weight of the degradation degree n of the number of discharge pulses, n is the degradation degree of the number of discharge pulses, w q The weight of the degradation degree q of the apparent discharge amount, q is the degradation degree of the apparent discharge amount, w u The weight of the degradation degree u of the initial discharge voltage is that u is the degradation degree of the initial discharge voltage;
s404, obtaining the insulation state grade state corresponding to the relative degradation degree based on the relative degradation degree of the short circuit port of the aluminum electrolysis cell, the insulation state grade state and the data mapping relation between the relative degradation degrees.
6. The online monitoring method for insulation at an aluminum electrolysis cell short-circuit port based on partial discharge signals according to claim 1, wherein the performing fault classification based on voiceprint features of ultrasonic signals in step S102 comprises:
s501, extracting voiceprint features of an ultrasonic signal, wherein the voiceprint features comprise frequency spectrums, amplitude values, mel Frequency Cepstrum Coefficients (MFCC) and gamma cepstrum coefficients (GFCC) of the ultrasonic signal;
s502, comparing the voiceprint characteristics of the ultrasonic signals with a preset characteristic library of the insulating defect discharge voiceprint of the short circuit port of the aluminum electrolysis cell to determine the insulating state of the short circuit port, wherein the characteristic library of the insulating defect discharge voiceprint of the short circuit port of the aluminum electrolysis cell comprises voiceprint characteristic values or value ranges under different insulating states of the short circuit port.
7. The on-line monitoring method for insulation at short circuit port of aluminum electrolysis cell based on partial discharge signal according to claim 1, wherein the plurality of continuously distributed insulation state grade states in step S103 includes four states of good, slight deterioration, moderate deterioration and severe deterioration.
8. The online monitoring method of aluminum electrolysis cell short-circuit port insulation based on partial discharge signals according to claim 7, wherein the step S103 of fusing to obtain a final short-circuit port insulation state comprises: and taking the two short-circuit port insulating states as sub evidence bodies of a data fusion method based on the D-S evidence theory, and obtaining the final short-circuit port insulating state by utilizing the data fusion method based on the D-S evidence theory.
9. An on-line monitoring system for insulation of an aluminum electrolysis cell short circuit port based on a partial discharge signal, comprising a microprocessor and a memory which are connected with each other, wherein the microprocessor is programmed or configured to execute the on-line monitoring method for insulation of an aluminum electrolysis cell short circuit port based on a partial discharge signal according to any one of claims 1 to 8.
10. A computer readable storage medium having a computer program stored therein, wherein the computer program is programmed or configured by a microprocessor to perform the partial discharge signal based on-line monitoring method of aluminum electrolysis cell short circuit junction insulation of any one of claims 1 to 8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310151229.4A CN116298722B (en) | 2023-02-07 | 2023-02-07 | Aluminum electrolysis cell short-circuit port insulation on-line monitoring method and system based on partial discharge signals |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310151229.4A CN116298722B (en) | 2023-02-07 | 2023-02-07 | Aluminum electrolysis cell short-circuit port insulation on-line monitoring method and system based on partial discharge signals |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116298722A true CN116298722A (en) | 2023-06-23 |
| CN116298722B CN116298722B (en) | 2024-07-12 |
Family
ID=86784462
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310151229.4A Active CN116298722B (en) | 2023-02-07 | 2023-02-07 | Aluminum electrolysis cell short-circuit port insulation on-line monitoring method and system based on partial discharge signals |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116298722B (en) |
Citations (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103105564A (en) * | 2011-11-14 | 2013-05-15 | 沈阳铝镁设计研究院有限公司 | Aluminum electrolytic cell series ground insulation intensity measuring circuit |
| CN106119897A (en) * | 2016-08-19 | 2016-11-16 | 河南科达东大国际工程有限公司 | A kind of electrolyzer electric flow distribution and safety monitoring system and electrolytic aluminium equipment |
| CN207738861U (en) * | 2017-12-05 | 2018-08-17 | 中国铝业股份有限公司 | A kind of aluminium electrolytic cell short-circuit port insulated monitoring warning device |
| CN108614199A (en) * | 2018-04-26 | 2018-10-02 | 广州供电局有限公司 | Power cable defect model test platform |
| CN110988635A (en) * | 2020-01-02 | 2020-04-10 | 天津安源科技发展有限公司 | High-low voltage electrical equipment insulation online detection loop, system and method |
| CN112285496A (en) * | 2020-09-22 | 2021-01-29 | 中国电力科学研究院有限公司 | Quantitative method and system for partial discharge of high-voltage electrical equipment |
| CN113049985A (en) * | 2021-04-27 | 2021-06-29 | 重庆大学 | Aluminum cell series earth leakage fault positioning and early warning detection system and method |
| CN113073361A (en) * | 2021-03-10 | 2021-07-06 | 谷泽竑 | Electrolytic polar plate short-circuit early warning detection method and device and electrolytic system |
| CN113640629A (en) * | 2021-07-26 | 2021-11-12 | 国网电力科学研究院武汉南瑞有限责任公司 | GIS partial discharge state evaluation method, recording medium and system |
| CN114034990A (en) * | 2021-10-22 | 2022-02-11 | 中核核电运行管理有限公司 | High-voltage electrical equipment online diagnosis system and method |
| CN114236332A (en) * | 2021-12-06 | 2022-03-25 | 深圳供电局有限公司 | Power cable insulation state judgment method and system |
| CN217077819U (en) * | 2022-03-25 | 2022-07-29 | 邹平县宏正新材料科技有限公司 | Insulating detection control system of generating line lifting frame for 600KA aluminum cell |
| CN115113031A (en) * | 2022-06-27 | 2022-09-27 | 国网上海市电力公司 | High tension switchgear insulation fault on-line monitoring device |
| CN115453283A (en) * | 2022-08-25 | 2022-12-09 | 贵州电网有限责任公司 | Two-in-one partial discharge sensor detection device and method |
| CN115469198A (en) * | 2022-09-28 | 2022-12-13 | 国网江苏省电力有限公司电力科学研究院 | High-confidence-level partial discharge joint detection method and detection system |
| CN115494427A (en) * | 2022-09-26 | 2022-12-20 | 内蒙古霍煤鸿骏铝电有限责任公司 | Method for detecting ground insulation fault of aluminum electrolytic cell |
-
2023
- 2023-02-07 CN CN202310151229.4A patent/CN116298722B/en active Active
Patent Citations (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103105564A (en) * | 2011-11-14 | 2013-05-15 | 沈阳铝镁设计研究院有限公司 | Aluminum electrolytic cell series ground insulation intensity measuring circuit |
| CN106119897A (en) * | 2016-08-19 | 2016-11-16 | 河南科达东大国际工程有限公司 | A kind of electrolyzer electric flow distribution and safety monitoring system and electrolytic aluminium equipment |
| CN207738861U (en) * | 2017-12-05 | 2018-08-17 | 中国铝业股份有限公司 | A kind of aluminium electrolytic cell short-circuit port insulated monitoring warning device |
| CN108614199A (en) * | 2018-04-26 | 2018-10-02 | 广州供电局有限公司 | Power cable defect model test platform |
| CN110988635A (en) * | 2020-01-02 | 2020-04-10 | 天津安源科技发展有限公司 | High-low voltage electrical equipment insulation online detection loop, system and method |
| CN112285496A (en) * | 2020-09-22 | 2021-01-29 | 中国电力科学研究院有限公司 | Quantitative method and system for partial discharge of high-voltage electrical equipment |
| WO2022188684A1 (en) * | 2021-03-10 | 2022-09-15 | 谷泽竑 | Short circuit early warning detection method and device for electrolysis electrode plate, and electrolysis system |
| CN113073361A (en) * | 2021-03-10 | 2021-07-06 | 谷泽竑 | Electrolytic polar plate short-circuit early warning detection method and device and electrolytic system |
| CN113049985A (en) * | 2021-04-27 | 2021-06-29 | 重庆大学 | Aluminum cell series earth leakage fault positioning and early warning detection system and method |
| CN113640629A (en) * | 2021-07-26 | 2021-11-12 | 国网电力科学研究院武汉南瑞有限责任公司 | GIS partial discharge state evaluation method, recording medium and system |
| CN114034990A (en) * | 2021-10-22 | 2022-02-11 | 中核核电运行管理有限公司 | High-voltage electrical equipment online diagnosis system and method |
| CN114236332A (en) * | 2021-12-06 | 2022-03-25 | 深圳供电局有限公司 | Power cable insulation state judgment method and system |
| CN217077819U (en) * | 2022-03-25 | 2022-07-29 | 邹平县宏正新材料科技有限公司 | Insulating detection control system of generating line lifting frame for 600KA aluminum cell |
| CN115113031A (en) * | 2022-06-27 | 2022-09-27 | 国网上海市电力公司 | High tension switchgear insulation fault on-line monitoring device |
| CN115453283A (en) * | 2022-08-25 | 2022-12-09 | 贵州电网有限责任公司 | Two-in-one partial discharge sensor detection device and method |
| CN115494427A (en) * | 2022-09-26 | 2022-12-20 | 内蒙古霍煤鸿骏铝电有限责任公司 | Method for detecting ground insulation fault of aluminum electrolytic cell |
| CN115469198A (en) * | 2022-09-28 | 2022-12-13 | 国网江苏省电力有限公司电力科学研究院 | High-confidence-level partial discharge joint detection method and detection system |
Non-Patent Citations (2)
| Title |
|---|
| 李特: "《变压器油纸绝缘老化诊断方法研究》", 中国优秀硕士学位论文全文数据库 工程科技II辑, 15 January 2020 (2020-01-15), pages 3 * |
| 黄迪: "《基于数据驱动的超低能耗铝电解槽况诊断研究及应用》", 中国优秀硕士学位论文全文数据库, 15 October 2016 (2016-10-15), pages 023 - 30 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116298722B (en) | 2024-07-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107024654B (en) | Monitoring system and method for an electric machine | |
| CN109116193B (en) | Electrical equipment dangerous discharge distinguishing method based on partial discharge signal comprehensive entropy | |
| Schichler et al. | Risk assessment on defects in GIS based on PD diagnostics | |
| JP4726654B2 (en) | Insulation drive motor insulation evaluation method, design method using the method, inspection method, diagnosis method, and apparatus thereof | |
| JP6633006B2 (en) | Partial discharge monitoring device and partial discharge monitoring method | |
| CN109001602B (en) | Partial discharge severity evaluation method based on extreme learning machine algorithm | |
| CN112505500B (en) | Partial discharge severity evaluation method based on ultrahigh frequency detection mode | |
| CN106526436B (en) | A kind of Transformer Insulation Aging state evaluating method based on vibratory drilling method | |
| Behrmann et al. | State of the Art in GIS PD Diagnostics | |
| CN116298722B (en) | Aluminum electrolysis cell short-circuit port insulation on-line monitoring method and system based on partial discharge signals | |
| JP2010071945A (en) | Ae measuring device and ae measuring method | |
| CN117517966A (en) | Fault diagnosis method for battery pack | |
| CN106771902B (en) | method for determining GIS corona discharge degree | |
| CN116699304A (en) | GIS partial discharge positioning algorithm based on multi-parameter joint detection | |
| CN116865672A (en) | Photovoltaic module abnormality recognition method and device and computer readable storage medium | |
| JP6153844B2 (en) | Arrestor failure determination system and failure determination program | |
| CN115456196A (en) | Fault diagnosis model establishing method, fault diagnosis device and storage medium | |
| CN102288881A (en) | Method for diagnosing severity of discharging shortcoming of oil paper insulation thorn of transformer | |
| JP2011158479A (en) | Inspection diagnosis method for inverter driving motor | |
| CN117849560B (en) | Valve side sleeve insulation monitoring method and system combining end screen voltage and partial discharge | |
| JP3833865B2 (en) | Quantitative evaluation method of pressure resistance test results for rubber and plastic insulated cables | |
| CN114252737B (en) | State identification and evaluation method and system for power cable partial discharge development process | |
| Contin et al. | Comparing different stochastic models for the identification and separation of concurrent partial discharge phenomena | |
| Meijer et al. | Risk assessment of fixed defects in GIS under different voltage wave shapes | |
| CN105242151A (en) | Evaluation method for influence of intruding wave impact on degradation of transformation equipment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant |