CN107420725B - Lubricating oil environmental protection pumping system with novel overpressure protection apparatus - Google Patents

Lubricating oil environmental protection pumping system with novel overpressure protection apparatus Download PDF

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CN107420725B
CN107420725B CN201710289798.XA CN201710289798A CN107420725B CN 107420725 B CN107420725 B CN 107420725B CN 201710289798 A CN201710289798 A CN 201710289798A CN 107420725 B CN107420725 B CN 107420725B
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value
probability value
judged
module
failure
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CN107420725A (en
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Nanjing Innovation Lubricating Oil Pump Manufacturing Co., Ltd.
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NANJING INNOVATION LUBRICATING OIL PUMP MANUFACTURING Co Ltd
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    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
    • F16N—LUBRICATING
    • F16N7/00—Arrangements for supplying oil or unspecified lubricant from a stationary reservoir or the equivalent in or on the machine or member to be lubricated
    • F16N7/38—Arrangements for supplying oil or unspecified lubricant from a stationary reservoir or the equivalent in or on the machine or member to be lubricated with a separate pump; Central lubrication systems
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
    • F16N—LUBRICATING
    • F16N29/00—Special means in lubricating arrangements or systems providing for the indication or detection of undesired conditions; Use of devices responsive to conditions in lubricating arrangements or systems
    • F16N29/04—Special means in lubricating arrangements or systems providing for the indication or detection of undesired conditions; Use of devices responsive to conditions in lubricating arrangements or systems enabling a warning to be given; enabling moving parts to be stopped
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
    • F16N—LUBRICATING
    • F16N2260/00—Fail safe
    • F16N2260/20—Emergency

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  • Engineering & Computer Science (AREA)
  • General Engineering & Computer Science (AREA)
  • Mechanical Engineering (AREA)
  • Housings And Mounting Of Transformers (AREA)

Abstract

Lubricating oil environmental protection pumping system with novel overpressure protection apparatus; it is characterized in that; including oily transformer, motor, grease pump, electro connecting pressure gauge, stop controller and transformer fault diagnosis device, fuel feeding is driven by motor in the lateral motor power supply of the low pressure of oily transformer, grease pump；Electro connecting pressure gauge is arranged in the intermediate conduit being connected to outlet conduit, and two alarm opened points of electro connecting pressure gauge are electrically connected to stop controller；Transformer fault diagnosis device is used to carry out fault diagnosis to oily transformer comprising standardized module, matrix module, vector machine model parameter calculating module, iteration module, standardization input parameters revision module, breakdown judge module and sinusoidal breakdown judge module.

Description

Lubricating oil environmental protection pumping system with novel overpressure protection apparatus
Technical field
The present invention relates to grease pump fields, and in particular to the lubricating oil environment protecting pump system with novel overpressure protection apparatus System.
Background technique
In industrial circle, grease pump is a kind of very common lubricating power circulator.For powerful lubrication For oil pump, the overpressure protection of pipeline and for pump motor power supply transformer protection be all it is highly important, if pump discharge Pipeline there is a phenomenon where blocking and grease pump can not stop that pump will be suppressed in time, cause overheat and pump damage.
Summary of the invention
In view of the above-mentioned problems, the present invention provides a kind of lubricating oil environmental protection pumping system with novel overpressure protection apparatus.
The purpose of the present invention is realized using following technical scheme:
Lubricating oil environmental protection pumping system with novel overpressure protection apparatus, characterized in that including oily transformer, motor, profit Oil pump, electro connecting pressure gauge, stop controller and transformer fault diagnosis device, the lateral motor of the low pressure of oily transformer supply Fuel feeding is driven by motor in electricity, grease pump；Electro connecting pressure gauge is arranged in the intermediate conduit being connected to outlet conduit, electric contact Two alarm opened points of pressure gauge are electrically connected to stop controller；Transformer fault diagnosis device is used to carry out oily transformer Fault diagnosis comprising standardized module, matrix module, vector machine model parameter calculating module, iteration module, standardization input Parameters revision module, breakdown judge module and sinusoidal breakdown judge module.
The invention has the benefit that the grease pump system can effectively stop when blocking superpressure occurs for outlet conduit Motor operation implements protection to pump, while being provided with accurate effective oily transformer fault diagnosis device, improves system General safety performance.
Detailed description of the invention
The present invention will be further described with reference to the accompanying drawings, but the embodiment in attached drawing is not constituted to any limit of the invention System, for those of ordinary skill in the art, without creative efforts, can also obtain according to the following drawings Other attached drawings.
Fig. 1 is overall structure diagram of the invention；
Fig. 2 is the structural schematic diagram of transformer fault diagnosis device.
Specific embodiment
The invention will be further described with the following Examples.
Refer to the lubricating oil environmental protection pumping system with novel overpressure protection apparatus as shown in Figs. 1-2, including oily transformation Device 1, motor 2, grease pump 3, electro connecting pressure gauge 4, stop controller 5 and transformer fault diagnosis device 6, oily transformer 1 The lateral motor 2 of low pressure power, grease pump 3 drives fuel feeding by motor 2.The setting of electro connecting pressure gauge 4 connects with outlet conduit 7 In logical intermediate conduit 8, two alarm opened points of electro connecting pressure gauge 4 are electrically connected to stop controller 5.Transformer fault is examined Disconnected device 6 is used to carry out fault diagnosis to oily transformer 1 comprising standardized module 601, matrix module 602, vector machine model Parameter calculating module 603, iteration module 604, standardization input parameters revision module 605, breakdown judge module 606 and sine event Hinder judgment module 607.
Scheme as a further preference, the high-pressure side external high voltage power supply of the oil transformer 1.
Scheme as a further preference, when the blocking of outlet conduit 7 leads to superpressure, the normally opened of electro connecting pressure gauge 4 is connect Point is closed since the pressure value received is more than preset value, and transmits signals to stop controller 5, and stop controller 5 is controlled Motor 2 processed is stopped transport.
Transformer fault diagnosis device 6 includes:
(1) standardized module 601: H is chosen2、CH4、C2H6、C2H4、C2H2Five kinds of characteristic gas contents are classified as vector machine The input feature vector variable x ' of device, and input feature vector variable is standardized as the following formula:
Wherein x is the input feature vector variable after standardization, xminFor the minimum value of gas content, xmaxMost for gas content Big value, Up are that the standardized upper limit of gas content sets constant, and Lo=is the standardized lower limit set constant of gas content；The mark Quasi-ization processing improves the rate of correct diagnosis of diagnostic model.
The data of the 3 above-mentioned five kinds of characteristic gas contents of times array are chosen as sample data.
(2) matrix module 602: setting weight restrains desired value ws, hyper parameter restrain desired value ɑsWith maximum number of iterations N, Obtain φ (x as the following formula in sample datan):
φ(xn)=[1, K (xn,x1),K(xn,x2),…,K(xn,xN)]T
Wherein n is iteration variable, xnFor the input feature vector variable of nth iteration, K(xn,x2),…,K(xn,xN) the rest may be inferred, U is the function coefficients of K function, and ‖ ‖ is norm sign；
(3) gradient vector g vector machine model parameter calculating module 603: is calculated as follows:
G=[φ (xn)]T×[t(n)-y(n)]
Wherein, y (n)=wn×K(xn,xN)+w0, t (n)=(ε+1) × y (n), wnFor present weight, w0To be manually set Weight base unit weight, ε be manually set noise error coefficient；As n=1, w is enabled1For the constant value weight of artificial settings；
Matrix H is calculated as follows:
H=- φ (xn)×[φ(xn)]T×B-A0
Wherein, B=diag [1, y (1) (1-y (1)), y (2) (1-y (2)) ..., y (N) (1-y (N))], A0Artificially to set Fixed definite value matrix, is apparent from as n and xnH is N+1 row N+1 column matrix when determining；
After obtaining gradient vector g and matrix H, update present weight is w 'n=wn-|g×H×φ(xn) |, wherein w 'nFor Updated weight；
Hyper parameter ɑ is sought as the following formulan:Wherein For covariance, and work as n= When 1,And ɑn-1=ɑ0It is artificial settings value；∑i,iFor matrixI-th diagonal entry, i is integer less than or equal to N+1, association Variance uses quantitative covariance, i.e.,It is people's setting value.
(4) iteration module 604: being incremented by iteration variable n, until obtained w 'nAnd ɑnRespective desired value is converged on respectively ws、ɑs, then output vector machine probabilistic model Z (w ' as the following formulan|ɑn):
Wherein N () is normal distyribution function.
The diagnostic device can export diagnostic result in the form of probability, convenient for the uncertainty of problem analysis, Neng Gouyou Effect ground solves the problems, such as the diagnosis in the case of few sample data, and rate of correct diagnosis is excellent, and diagnosis speed is faster.
(5) standardization input parameters revision module 605: national standard DL/T722-2000 Gases Dissolved in Transformer Oil point is introduced Analyse and judge the gas content demand value x provided in directive/guides, quasi- early warning item Q is recorded as the following formula:
Wherein, M1 is x ' >=xsCumulative time, the unit second；
(6) breakdown judge module 606: inputting the vector machine probabilistic model for five kinds of characteristic gas contents to be detected, Intermediate probability value P is obtained, when Q is less than the setting value Q of quasi- early warning itemSWhen, P value is updated to P-0.05 as final probability value, Otherwise directly using obtained intermediate probability value P as final probability value；If obtained final probability value is greater than 0.5, judge It is otherwise malfunction for normal condition；If obtained final probability value is judged as electrical failure between 0~0.25, If being judged as non-electrical failure between 0.25~0.5；If obtained final probability value between 0~0.125, It is judged as high-energy discharge failure, is judged as fault caused by low energy discharge if obtained final probability value is between 0.125~0.25； If obtained final probability value is judged as hyperthermia and superheating failure between 0.25~0.375, if obtained final probability Value is then judged as cryogenic overheating failure between 0.375~0.5；
It is introduced into the analysis of national standard DL/T722-2000 Gases Dissolved in Transformer Oil and judges the gas content provided in directive/guide Demand value and amendment foundation of the cumulative time as probability P that transfinite can largely overcome gas content acquisition bring to miss Difference improves more reliable foundation for final breakdown judge.
(7) sinusoidal breakdown judge module 606: intermediate probability value P is converted as the following formula and obtains sinusoidal probability Psin:
If obtained sinusoidal probability value is greater than 0.5, it is judged as normal shape Otherwise state is malfunction；If obtained sinusoidal probability value is judged as electrical failure between 0~0.25, if Between 0.25~0.5, then it is judged as non-electrical failure；If obtained sinusoidal probability value is judged as between 0~0.125 High-energy discharge failure is judged as fault caused by low energy discharge if obtained sinusoidal probability value is between 0.125~0.25；If The sinusoidal probability value arrived is then judged as hyperthermia and superheating failure between 0.25~0.375, if obtained sinusoidal probability value exists Then it is judged as cryogenic overheating failure between 0.375~0.5；The breakdown judge and P of final probability value in breakdown judge modulesin's Breakdown judge, for relationship, then issued when the two is all satisfied corresponding failure alarm.Five kinds of characteristic variables are any, any one Meet the i.e. capable of emitting alarm of alert if.
By increasing the transformation and judgement of sinusoidal probability, overcomes previous probability output and be not enough smoothly easy to happen false alarm The problem of, improve the reliability of breakdown judge.
Finally it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention, rather than the present invention is protected The limitation of range is protected, although explaining in detail referring to preferred embodiment to the present invention, those skilled in the art are answered Work as understanding, it can be with modification or equivalent replacement of the technical solution of the present invention are made, without departing from the reality of technical solution of the present invention Matter and range.

Claims (3)

1. the lubricating oil environmental protection pumping system with novel overpressure protection apparatus, characterized in that including oily transformer, motor, lubrication Oil pump, electro connecting pressure gauge, stop controller and transformer fault diagnosis device, the lateral motor power supply of the low pressure of oily transformer, Fuel feeding is driven by motor in grease pump；Electro connecting pressure gauge is arranged in the intermediate conduit being connected to outlet conduit, electric contact pressure Two alarm opened points of power table are electrically connected to stop controller；Transformer fault diagnosis device is used to carry out event to oily transformer Barrier diagnosis comprising standardized module, matrix module, vector machine model parameter calculating module, iteration module, standardization input ginseng Number correction module, breakdown judge module and sinusoidal breakdown judge module；
The high-pressure side external high voltage power supply of the oil transformer；
When outlet conduit blocking leads to superpressure, the normal opened contact of electro connecting pressure gauge is since the pressure value received is more than default It is worth and is closed, and transmit signals to stop controller, stop controller controls motor and stops transport；
The standardized module specifically executes: choosing H2、CH4、C2H6、C2H4、C2H2Five kinds of characteristic gas contents are as vector machine point The input feature vector variable x ' of class device, and input feature vector variable is standardized as the following formula:
Wherein, x is the input feature vector variable after standardization, xminFor the minimum value of gas content, xmaxFor the maximum of gas content Value, Up are that the standardized upper limit of gas content sets constant, and Lo is the standardized lower limit set constant of gas content；
The data of the 3 above-mentioned five kinds of characteristic gas contents of times array are chosen as sample data；
The matrix module specifically executes:
It sets weight and restrains desired value ws, hyper parameter restrain desired value ɑsWith maximum number of iterations N, in sample data as the following formula Obtain φ (xn):
φ(xn)=[1, K (xn,x1),K(xn,x2),…,K(xn,xN)]T
Wherein, n is iteration variable, xnFor the input feature vector variable of nth iteration, K (xn,x2),…,K(xn,xN) the rest may be inferred, U is the function coefficients of K function, and ‖ ‖ is norm sign；
The vector machine model parameter calculating module specifically executes:
Gradient vector g is calculated as follows:
G=[φ (xn)]T×[t(n)-y(n)]
Wherein, y (n)=wn×K(xn,xN)+w0, t (n)=(ε+1) × y (n), wnFor present weight, w0For the power of artificial settings Weight base unit weight, ε are the noise error coefficient being manually set；As n=1, w is enabled1For the constant value weight of artificial settings；
Matrix H is calculated as follows:
H=- φ (xn)×[φ(xn)]T×B-A0
Wherein, B=diag [1, y (1) (1-y (1)), y (2) (1-y (2)) ..., y (N) (1-y (N))], A0For determining for artificial settings Value matrix is apparent from as n and xnH is N+1 row N+1 column matrix when determining；
After obtaining gradient vector g and matrix H, update present weight is w 'n=wn-|g×H×φ(xn) |, wherein w 'nAfter updating Weight；
Hyper parameter ɑ is sought as the following formulan:Wherein γn=1- ɑn-1×∑i,i,For covariance, and as n=1,And ɑn-1=ɑ0It is artificial settings value；∑i,iFor matrixI-th diagonal entry, i is integer less than or equal to N+1, association Variance uses quantitative covariance, i.e.,It is people's setting value；
The iteration module specifically executes:
It is incremented by iteration variable n, until obtained w 'nAnd ɑnRespective desired value w is converged on respectivelys、ɑs, then output vector as the following formula Machine probabilistic model Z (w 'nɑn):
Wherein N () is normal distyribution function；
The standardization input parameters revision module specifically executes:
It is introduced into the analysis of national standard DL/T722-2000 Gases Dissolved in Transformer Oil and judges that the gas content provided in directive/guide pays attention to Value xs, quasi- early warning item Q is recorded as the following formula:
Wherein, M1 is x ' >=xsCumulative time, the unit second.
2. the lubricating oil environmental protection pumping system according to claim 1 with novel overpressure protection apparatus, characterized in that described Breakdown judge module specifically executes:
Five kinds of characteristic gas contents to be detected are inputted into the vector machine probabilistic model, intermediate probability value P are obtained, when Q is less than The setting value Q of quasi- early warning itemSWhen, P value is updated to P-0.05, it is otherwise directly that obtained centre is general as final probability value Rate value P is as final probability value；If obtained final probability value is greater than 0.5, it is judged as normal condition, is otherwise failure shape State；If obtained final probability value is judged as electrical failure between 0~0.25, if between 0.25~0.5, It is judged as non-electrical failure；If obtained final probability value is judged as high-energy discharge failure between 0~0.125, if Obtained final probability value is then judged as fault caused by low energy discharge between 0.125~0.25；If obtained final probability value exists Between 0.25~0.375, then it is judged as hyperthermia and superheating failure, sentences if obtained final probability value is between 0.375~0.5 Break as cryogenic overheating failure.
3. the lubricating oil environmental protection pumping system according to claim 2 with novel overpressure protection apparatus, characterized in that described Sinusoidal breakdown judge module specifically executes:
Intermediate probability value P is converted as the following formula and obtains sinusoidal probability Psin:
If obtained sinusoidal probability value is greater than 0.5, it is judged as normal condition, it is no It is then malfunction；If obtained sinusoidal probability value is judged as electrical failure between 0~0.25, if obtained just String probability value is then judged as non-electrical failure between 0.25~0.5；If obtained sinusoidal probability value 0~0.125 it Between, then it is judged as high-energy discharge failure, is judged as that low energy is discharged if obtained sinusoidal probability value is between 0.125~0.25 Failure；If obtained sinusoidal probability value is judged as hyperthermia and superheating failure between 0.25~0.375, if obtained just String probability value is then judged as cryogenic overheating failure between 0.375~0.5；The failure of final probability value is sentenced in breakdown judge module Disconnected and PsinBreakdown judge, for relationship, then issued when the two is all satisfied corresponding failure alarm.
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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103198175A (en) * 2013-03-04 2013-07-10 辽宁省电力有限公司鞍山供电公司 Transformer fault diagnosis method based on fuzzy cluster
CN203131399U (en) * 2013-03-19 2013-08-14 路伯润滑油（苏州）有限公司 Protective device for lubricant pump
CN103745119A (en) * 2014-01-22 2014-04-23 浙江大学 Oil-immersed transformer fault diagnosis method based on fault probability distribution model
CN106093612A (en) * 2016-05-26 2016-11-09 国网江苏省电力公司电力科学研究院 A kind of method for diagnosing fault of power transformer

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Publication number Priority date Publication date Assignee Title
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Publication number Priority date Publication date Assignee Title
CN103198175A (en) * 2013-03-04 2013-07-10 辽宁省电力有限公司鞍山供电公司 Transformer fault diagnosis method based on fuzzy cluster
CN203131399U (en) * 2013-03-19 2013-08-14 路伯润滑油（苏州）有限公司 Protective device for lubricant pump
CN103745119A (en) * 2014-01-22 2014-04-23 浙江大学 Oil-immersed transformer fault diagnosis method based on fault probability distribution model
CN106093612A (en) * 2016-05-26 2016-11-09 国网江苏省电力公司电力科学研究院 A kind of method for diagnosing fault of power transformer

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