CN115096626A - Method and device for detecting failure frequency of coal machine equipment, electronic equipment and medium - Google Patents
Method and device for detecting failure frequency of coal machine equipment, electronic equipment and medium Download PDFInfo
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Abstract
The disclosure provides a method and a device for detecting failure frequency of coal mining equipment. The method comprises the following steps: acquiring a signal to be detected of coal equipment, constructing a differential oscillator detection model, adjusting model parameters of the differential oscillator detection model until the differential oscillator detection model is in an optimal polar ring state to obtain a reference phase diagram output by the differential oscillator detection model, inputting the signal to be detected into the differential oscillator detection model to output a phase diagram to be detected, performing Fourier transform processing on the reference phase diagram and the phase diagram to be detected respectively to obtain a reference phase diagram frequency spectrum corresponding to the reference phase diagram and a phase diagram frequency spectrum corresponding to the phase diagram to be detected, and determining whether the signal to be detected contains other fault detection frequencies according to the phase diagram frequency spectrum to be detected and the reference phase diagram frequency spectrum, thereby breaking through the limitation that the differential oscillator detection model can only detect known single frequency, and realizing the condition that the specific value of the detected fault frequency cannot be determined, and detecting multiple fault frequencies.
Description
Technical Field
The disclosure relates to the technical field of failure diagnosis of coal mining equipment, and in particular relates to a method and a device for detecting failure frequency of coal mining equipment, electronic equipment and a storage medium.
Background
With the increasing improvement of the intelligentization level of the coal equipment, particularly the rise of the heat tide of the smart mine construction, people reduction, efficiency improvement and safety increase become important indexes for measuring the construction effect of the smart mine, one of the precondition for realizing the indexes is safe and reliable operation of the coal equipment, so that the coal equipment fault diagnosis technology becomes a hotspot of research of numerous research institutions and scientific research institutes, but the coal equipment fault frequency detection has great difficulty due to factors such as special working condition environments (impact, dustiness and humidity), variable superposed working conditions, variable load, lack of effective data samples on site and the like of the coal equipment.
In the related art, the method for detecting the fault frequency of the coal equipment cannot perform frequency detection on other unknown fault frequencies in a signal to be detected, so that the method for detecting the fault frequency of the coal equipment has large detection limitation, and cannot meet the detection requirement of the fault frequency of the coal equipment under complex working condition environments such as variable working conditions, variable loads and the like.
Disclosure of Invention
The present disclosure is directed to solving, at least to some extent, one of the technical problems in the related art.
Therefore, the present disclosure aims to provide a method, an apparatus, an electronic device and a storage medium for detecting a failure frequency of a coal mining device, which can implement multi-failure frequency detection of the coal mining device by combining a differential oscillator detection model, thereby breaking through the limitation that the differential oscillator detection model can only detect a known single frequency, and implementing multi-failure frequency detection under the condition that a specific value of a detected failure frequency cannot be determined.
The method for detecting the failure frequency of the coal equipment provided by the embodiment of the first aspect of the disclosure comprises the following steps: acquiring a signal to be detected of coal equipment; constructing a differential oscillator detection model, wherein the differential oscillator detection model is used for carrying out frequency detection on a signal to be detected; adjusting model parameters of the differential oscillator detection model until the differential oscillator detection model is in an optimal polar ring state to obtain a reference phase diagram output by the differential oscillator detection model; inputting a signal to be detected into the differential oscillator detection model to obtain a phase diagram to be detected output by the differential oscillator detection model; respectively carrying out Fourier transform processing on the reference phase diagram and the phase diagram to be detected to obtain a reference phase diagram frequency spectrum corresponding to the reference phase diagram and a phase diagram frequency spectrum to be detected corresponding to the phase diagram to be detected; and determining whether the signal to be detected contains other fault detection frequencies according to the phase diagram frequency spectrum to be detected and the reference phase diagram frequency spectrum.
The method for detecting the fault frequency of the coal equipment, which is provided by the embodiment of the first aspect of the disclosure, includes obtaining a signal to be detected of the coal equipment, and constructing a differential oscillator detection model, wherein the differential oscillator detection model is used for performing frequency detection on the signal to be detected, then adjusting model parameters of the differential oscillator detection model until the differential oscillator detection model is in an optimal polar ring state, so as to obtain a reference phase diagram output by the differential oscillator detection model, inputting the signal to be detected into the differential oscillator detection model, so as to obtain a phase diagram to be detected output by the differential oscillator detection model, performing fourier transform processing on the reference phase diagram and the phase diagram to be detected respectively, so as to obtain a reference phase diagram frequency spectrum corresponding to the reference phase diagram and a phase diagram frequency spectrum to be detected corresponding to the phase diagram to be detected, and determining whether the signal to be detected contains other fault detection frequencies according to the phase diagram frequency spectrum to be detected and the reference phase diagram frequency spectrum, therefore, the differential oscillator detection model can be combined to realize multi-fault-frequency detection of the coal machine equipment, so that the limitation that the differential oscillator detection model can only detect known single frequency is broken through, and the multi-fault-frequency detection is realized under the condition that the specific value of the detected fault frequency cannot be determined.
The detection device for the failure frequency of the coal equipment provided by the embodiment of the second aspect of the disclosure comprises: the acquisition module is used for acquiring a signal to be detected of the coal equipment; the device comprises a construction module, a frequency detection module and a frequency detection module, wherein the construction module is used for constructing a differential oscillator detection model, and the differential oscillator detection model is used for carrying out frequency detection on a signal to be detected; the adjusting module is used for adjusting the model parameters of the differential oscillator detection model until the differential oscillator detection model is in the optimal polar ring state so as to obtain a reference phase diagram output by the differential oscillator detection model; the first processing module is used for inputting the signal to be detected into the differential oscillator detection model so as to obtain a phase diagram to be detected output by the differential oscillator detection model; the second processing module is used for respectively carrying out Fourier transform processing on the reference phase diagram and the phase diagram to be detected so as to obtain a reference phase diagram frequency spectrum corresponding to the reference phase diagram and a phase diagram frequency spectrum to be detected corresponding to the phase diagram to be detected; and the first determining module is used for determining whether the signal to be detected contains other fault detection frequencies according to the phase diagram frequency spectrum to be detected and the reference phase diagram frequency spectrum.
The detection device for the fault frequency of the coal equipment, which is provided by the embodiment of the second aspect of the disclosure, obtains a signal to be detected of the coal equipment, and constructs a differential oscillator detection model, wherein the differential oscillator detection model is used for performing frequency detection on the signal to be detected, then adjusts model parameters of the differential oscillator detection model until the differential oscillator detection model is in an optimal polar ring state, so as to obtain a reference phase diagram output by the differential oscillator detection model, inputs the signal to be detected into the differential oscillator detection model, so as to obtain a phase diagram to be detected output by the differential oscillator detection model, performs fourier transform processing on the reference phase diagram and the phase diagram to be detected respectively, so as to obtain a reference phase diagram frequency spectrum corresponding to the reference phase diagram and a phase diagram frequency spectrum to be detected corresponding to the phase diagram to be detected, and determines whether the signal to be detected contains other fault detection frequencies according to the phase diagram frequency spectrum to be detected and the reference phase diagram frequency spectrum, therefore, the detection of multiple fault frequencies of the coal equipment can be realized by combining the differential oscillator detection model, so that the limitation that the differential oscillator detection model can only detect known single frequency is broken through, and the detection of multiple fault frequencies is realized under the condition that the specific numerical value of the detected fault frequency cannot be determined.
The embodiment of the third aspect of the present disclosure provides an electronic device, which includes a memory, a processor, and a computer program that is stored in the memory and is executable on the processor, and when the processor executes the program, the method for detecting a failure frequency of a coal mining device as set forth in the embodiment of the first aspect of the present disclosure is implemented.
A fourth aspect of the present disclosure provides a non-transitory computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the method for detecting a failure frequency of a coal equipment as set forth in the first aspect of the present disclosure.
In an embodiment of a fifth aspect of the present disclosure, a computer program product is provided, and when executed by an instruction processor in the computer program product, the method for detecting a failure frequency of a coal equipment as set forth in an embodiment of the first aspect of the present disclosure is performed.
Additional aspects and advantages of the disclosure will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the disclosure.
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The above and/or additional aspects and advantages of the present disclosure will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
fig. 1 is a schematic flow chart of a method for detecting a failure frequency of a coal equipment according to an embodiment of the present disclosure;
fig. 2 is a schematic diagram of a phase diagram to be detected according to an embodiment of the disclosure;
FIG. 3 is a schematic diagram of a reference phase diagram according to an embodiment of the present disclosure;
fig. 4 is a schematic diagram of a phase diagram spectrum to be detected according to an embodiment of the present disclosure;
FIG. 5 is a schematic diagram of a reference phase diagram spectrum according to an embodiment of the present disclosure;
fig. 6 is a schematic diagram of a phase diagram spectrum to be detected after amplification according to an embodiment of the disclosure;
FIG. 7 is a schematic flow chart diagram of a method for detecting a failure frequency of a coal equipment according to another embodiment of the present disclosure;
fig. 8 is a schematic structural diagram of a detection apparatus for detecting a failure frequency of a coal equipment according to an embodiment of the present disclosure;
fig. 9 is a schematic structural diagram of a detection device for detecting a failure frequency of a coal equipment according to another embodiment of the present disclosure;
FIG. 10 illustrates a block diagram of an exemplary electronic device suitable for use in implementing embodiments of the present disclosure.
Detailed Description
Reference will now be made in detail to the embodiments of the present disclosure, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are exemplary only for the purpose of illustrating the present disclosure and should not be construed as limiting the same. On the contrary, the embodiments of the disclosure include all changes, modifications and equivalents coming within the spirit and terms of the claims appended hereto.
Fig. 1 is a schematic flow chart of a method for detecting a failure frequency of a coal equipment according to an embodiment of the present disclosure.
It should be noted that the main execution body of the method for detecting the failure frequency of the coal equipment in this embodiment is a device for detecting the failure frequency of the coal equipment, the device may be implemented in a software and/or hardware manner, the device may be configured in an electronic device, and the electronic device may include, but is not limited to, a terminal, a server, and the like.
As shown in fig. 1, the method for detecting the failure frequency of the coal equipment includes:
s101: and acquiring a signal to be detected of the coal mining equipment.
The signals acquired by the coal mining equipment and used for fault detection of the coal mining equipment can be called signals to be detected.
That is to say, in the embodiment of the present disclosure, a reference detection signal having a determined frequency and a determined amplitude may be predetermined, and then, in the execution process of the subsequent method for detecting a failure frequency of a coal equipment, the determined frequency and the determined amplitude of the reference detection signal may be combined to determine a signal frequency and a signal amplitude existing in a signal to be detected, so as to assist in executing the subsequent method for detecting a failure frequency of a coal equipment, which may be specifically referred to in the subsequent embodiments.
In some embodiments, the obtaining of the signal to be detected of the coal equipment may be that a plurality of sensors are deployed in advance in a roadway where the coal equipment works, and the vibration acceleration signal of the coal equipment is obtained as the signal to be detected during the working process of the coal equipment through the sensors, which is not limited in this respect.
In other embodiments, the signal to be detected of the coal equipment may be obtained by configuring a corresponding monitoring device in advance for the coal equipment, continuously monitoring the operation process of the coal equipment through the monitoring device, and obtaining the signal to be detected of the coal equipment through a data transmission interface configured in advance for a detection device of a failure frequency of the coal equipment when it is monitored that the coal equipment fails, which is not limited to this.
S102: and constructing a differential oscillator detection model, wherein the differential oscillator detection model is used for carrying out frequency detection on a signal to be detected.
In the embodiment of the disclosure, because the coal equipment is influenced by factors such as gangue, load distribution, rotating speed and the like in actual operation, the fault frequency of the coal equipment is not consistent with a theoretical or empirical calculation value, but a micro-frequency band with the theoretical or empirical calculation value as a center frequency is adopted, the differential oscillator is used for detecting the micro-frequency band with the frequency to be detected as the center, and in addition, the differential oscillator has strong anti-noise capability, so that the differential oscillator has better anti-interference performance under the condition that the coal equipment is influenced by variable working conditions and variable loads.
In the embodiment of the present disclosure, a differential oscillator detection model for performing fault frequency detection on a signal to be detected may be constructed, for example, after a signal to be detected of a coal equipment is obtained, an initial differential oscillator detection model is obtained, and then parameter tuning is performed on the initial differential oscillator detection model, so as to obtain a differential oscillator detection model that can be used for implementing the method for detecting a fault frequency of a coal equipment according to the embodiment of the present disclosure, or a differential oscillator detection model may be constructed in any other possible manner, which is not limited to this.
Optionally, in some embodiments, the differential oscillator detection model may be constructed by acquiring a plurality of fault frequencies and reference detection signals of the coal equipment, determining a reference fault detection frequency from the plurality of fault frequencies, and constructing the differential oscillator detection model according to the signal to be detected, the reference detection signal, and the reference fault detection frequency.
The reference detection signal can be used as a reference for determining the frequency spectrum amplitude to be detected of the signal to be detected in the subsequent execution process of the method for detecting the fault frequency of the coal equipment.
In the embodiment of the disclosure, after determining a plurality of fault frequencies of the coal equipment, a certain fault frequency may be determined from the plurality of fault frequencies as a reference fault detection frequency, for example, 123.14Hz of the motor support bearing inner ring may be selected as the reference fault detection frequency, which is not limited in this regard.
In the embodiment of the present disclosure, the differential oscillator detection model may be expressed as:
x k+1 ＝ax k +by k ；
wherein k is a function variable, a, b, c and d are parameters of the differential oscillator detection model, p is a magnification factor, f e Is the system excitation frequency, T (k) is the signal to be detected, f d Is a reference fault detection frequency, f s Is the sampling frequency, f g Is the natural frequency of the differential oscillator detection model, h (k) ═ sin (2k pi f) d ) Which represents the reference detection signal.
S103: and adjusting the model parameters of the differential oscillator detection model until the differential oscillator detection model is in the optimal polar ring state so as to obtain a reference phase diagram output by the differential oscillator detection model.
In the embodiment of the present disclosure, the model parameters of the differential oscillator detection model may be adjusted, that is, when only the reference detection signal is input to the differential oscillator detection model (that is, the signal to be detected t (k) is set to 0), the phase diagram output by the differential oscillator detection model can converge to the optimal polar ring state (when the phase diagram output by the differential oscillator detection model can converge to the optimal polar ring state, the phase diagram output by the differential oscillator detection model may be referred to as a reference phase diagram, as shown in fig. 3, where fig. 3 is a schematic diagram of the reference phase diagram provided in an embodiment of the present disclosure), and then, a subsequent method for detecting a failure frequency of a coal equipment may be performed in combination with the reference phase diagram, which may be specifically referred to the subsequent embodiments.
S104: and inputting the signal to be detected into the differential oscillator detection model to obtain a phase diagram to be detected output by the differential oscillator detection model.
In the embodiment of the disclosure, when the model parameters of the differential oscillator detection model are adjusted until the differential oscillator detection model is in the optimal polar ring state, a signal to be detected may be input into the differential oscillator detection model to obtain a phase diagram output by the differential oscillator detection model in this state, where the phase diagram may be referred to as a phase diagram to be detected.
That is to say, in the embodiment of the present disclosure, when a signal to be detected of a coal equipment is obtained, the signal to be detected (i.e., the signal to be detected t (k) (t (k)) (k) ≠ 0)) may be input into the differential oscillator detection model obtained by the aforementioned construction, so as to obtain a phase diagram to be detected (as shown in fig. 2, fig. 2 is a schematic diagram of the phase diagram to be detected provided in the embodiment of the present disclosure), and then, a subsequent method for detecting a fault frequency of the coal equipment may be executed in combination with the phase diagram to be detected, which may be specifically referred to in the subsequent embodiments.
S105: and respectively carrying out Fourier transform processing on the reference phase diagram and the phase diagram to be detected so as to obtain a reference phase diagram frequency spectrum corresponding to the reference phase diagram and a phase diagram frequency spectrum to be detected corresponding to the phase diagram to be detected.
For example, the phase diagram spectrum corresponding to the phase diagram to be detected shown in fig. 2 may be subjected to fourier transform processing to obtain the phase diagram spectrum to be detected shown in fig. 4, and fig. 4 is a schematic diagram of the phase diagram spectrum to be detected provided in an embodiment of the present disclosure.
The phase diagram spectrum corresponding to the reference phase diagram may be referred to as a reference phase diagram spectrum, for example, the phase diagram to be detected shown in fig. 3 may be subjected to fourier transform processing to obtain the reference phase diagram spectrum shown in fig. 5, and fig. 5 is a schematic diagram of the reference phase diagram spectrum provided in an embodiment of the present disclosure.
S104: and determining whether the signal to be detected contains other fault detection frequencies according to the phase diagram frequency spectrum to be detected and the reference phase diagram frequency spectrum.
In the implementation process of the method for detecting the fault frequency of the coal equipment, the fault detection frequency except for the reference fault detection frequency is not calibrated in advance, and the fault detection frequency can be called as other fault detection frequencies.
That is to say, the method for detecting the fault frequency of the coal equipment described in the embodiment of the present disclosure can detect the fault frequency under the condition of unknown fault frequency based on the differential oscillator detection model.
In the implementation of the present disclosure, after the reference phase diagram frequency spectrum and the phase diagram frequency spectrum to be detected are obtained, it may be determined that the signal to be detected does not include other fault detection frequencies when the frequency components of the phase diagram frequency spectrum to be detected and the reference phase diagram frequency spectrum are the same, and when the frequency components of the phase diagram frequency spectrum to be detected and the reference phase diagram frequency spectrum are different, other phase diagram frequencies [ f ] in the phase diagram frequency spectrum to be detected are extracted 1 ,f 2 ,....f n ]And converting other phase diagram frequencies to realize the phase diagram frequency f i To its corresponding true frequency (other fault detection frequency) F i The conversion process specifically comprises the following steps:
wherein, F i Detecting frequency, f, for other faults i Is the phase diagram frequency, f d Is the frequency to be detected, f e Is the system excitation frequency, f g Is the natural frequency of the differential oscillator detection model.
For example, the phase diagram spectrum to be detected shown in fig. 4 may be enlarged to obtain the amplified phase diagram spectrum to be detected shown in fig. 6 (fig. 6 is a schematic diagram of the amplified phase diagram spectrum to be detected according to an embodiment of the present disclosure), and as shown in fig. 6, it may be determined that f exists in the frequency diagram to be detected 1 5160 and f 2 5210.63 two phase diagram frequencies.
Then, can be paired with f 1 5160 and f 2 5210.63 two-phase diagram frequencyThe rate is converted to obtain the corresponding fault detection frequency F 1 ＝76.27Hz，F 2 25.64Hz, so that it can be determined that other fault detection frequencies are included in the signal to be detected.
It should be noted that the method for detecting the failure frequency of the coal equipment described in the embodiment of the present disclosure may be applied to a scenario of performing failure detection on the coal equipment, that is, acquiring a signal to be detected of the coal equipment, determining whether the signal to be detected includes other failure detection frequencies, and determining that the coal equipment corresponding to the other failure detection frequencies has a failure when determining that the signal to be detected includes other failure detection frequencies (for example, determining that F is the case 1 76.27Hz is consistent with the fault frequency of the motor bearing outer ring, F 2 The frequency of 25.64Hz is consistent with the failure frequency of the motor, so that the inner ring failure and the outer ring failure of the motor bearing of the coal machine equipment can be determined at the same time, and the method is not limited.
In the embodiment, a signal to be detected of coal equipment is obtained, a differential oscillator detection model is constructed, wherein the differential oscillator detection model is used for performing frequency detection on the signal to be detected, model parameters of the differential oscillator detection model are adjusted until the differential oscillator detection model is in an optimal polar ring state, so as to obtain a reference phase diagram output by the differential oscillator detection model, the signal to be detected is input into the differential oscillator detection model, so as to obtain a phase diagram to be detected output by the differential oscillator detection model, the reference phase diagram and the phase diagram to be detected are subjected to fourier transform processing respectively, so as to obtain a reference phase diagram frequency spectrum corresponding to the reference phase diagram and a phase diagram frequency spectrum corresponding to the phase diagram to be detected, and whether other fault detection frequencies are included in the signal to be detected is determined according to the phase diagram frequency spectrum to be detected and the reference phase diagram frequency spectrum, so that the differential oscillator detection model can be combined, the method has the advantages that the multi-fault frequency detection of the coal machine equipment is realized, so that the limitation that a differential oscillator detection model can only detect known single frequency is broken through, and the multi-fault frequency detection is realized under the condition that the specific numerical value of the detected fault frequency cannot be determined.
Fig. 7 is a schematic flow chart of a method for detecting a failure frequency of a coal equipment according to another embodiment of the disclosure.
As shown in fig. 7, the method for detecting the failure frequency of the coal equipment includes:
s701: and acquiring a signal to be detected of the coal mining equipment.
S702: and constructing a differential oscillator detection model, wherein the differential oscillator detection model is used for carrying out frequency detection on the signal to be detected.
S703: and adjusting the model parameters of the differential oscillator detection model until the differential oscillator detection model is in the optimal polar ring state so as to obtain a reference phase diagram output by the differential oscillator detection model.
S704: and inputting the signal to be detected into the differential oscillator detection model to obtain a phase diagram to be detected output by the differential oscillator detection model.
S705: and respectively carrying out Fourier transform processing on the reference phase diagram and the phase diagram to be detected so as to obtain a reference phase diagram frequency spectrum corresponding to the reference phase diagram and a phase diagram frequency spectrum to be detected corresponding to the phase diagram to be detected.
For the description of S701-S705, reference may be made to the above embodiments, which are not described herein again.
S706: and determining whether the signal to be detected contains the reference fault detection frequency or not according to the reference frequency spectrum amplitude, the reference phase diagram frequency spectrum and the phase diagram frequency spectrum to be detected.
The method for detecting the fault frequency of the coal mining equipment, which is described in the embodiment of the disclosure, can also support detection of a reference fault detection frequency calibrated in advance, that is, it can be determined whether a signal to be detected contains the reference fault detection frequency.
Optionally, in some embodiments, whether the signal to be detected includes the reference fault detection frequency is determined according to the reference spectrum amplitude, the phase diagram spectrum to be detected and the reference phase diagram spectrum, which may be that the frequency spectrum to be detected of the signal to be detected is obtained by analyzing the phase diagram spectrum to be detected according to the reference spectrum amplitude and the reference phase diagram spectrum, when the frequency spectrum amplitude to be detected is greater than the reference spectrum amplitude, it is determined that the signal to be detected includes the reference fault detection frequency, and when the frequency spectrum amplitude to be detected is less than or equal to the reference spectrum amplitude, it is determined that the signal to be detected does not include the reference fault detection frequency.
The signal frequency domain amplitude corresponding to the reference detection signal may be referred to as a reference spectrum amplitude, and the reference spectrum amplitude may be, for example, a 1 。
The signal frequency domain amplitude corresponding to the signal to be detected can be called as the spectrum amplitude to be detected, and the spectrum amplitude to be detected can be expressed as A 2 。
In the embodiment of the present disclosure, the to-be-detected spectrum amplitude may be obtained by analyzing the to-be-detected phase diagram spectrum according to the reference spectrum amplitude and the reference phase diagram spectrum, that is, the amplitude change ratio of the to-be-detected phase diagram spectrum compared to the reference phase diagram spectrum may be determined, the to-be-detected spectrum amplitude is determined in combination with the reference spectrum amplitude, and then, the to-be-detected spectrum amplitude a may be determined 2 And reference spectral amplitude A 1 And comparing, and when the frequency spectrum amplitude to be detected is greater than the reference frequency spectrum amplitude, determining that the signal to be detected contains the reference fault detection frequency, and when the frequency spectrum amplitude to be detected is less than or equal to the reference frequency spectrum amplitude, determining that the signal to be detected does not contain the reference fault detection frequency.
For example, assume that the reference spectrum amplitude of the reference detection signal is A 1 1197.97, the spectral amplitude A to be detected 2 When 1792.78, A can be determined 1 <A 2 It can be determined that the signal to be detected includes the reference detection frequency, which is not limited to this.
It should be noted that the method for detecting the failure frequency of the coal equipment described in the embodiment of the present disclosure may be applied to a scenario of performing failure detection on the coal equipment, that is, acquiring a signal to be detected of the coal equipment, determining whether the signal to be detected includes a reference failure detection frequency (for example, the failure frequency of the inner ring of the motor support bearing is 123.14Hz), and determining that the inner ring of the motor support bearing has a failure when the signal to be detected includes the reference failure detection frequency, which is not limited to this.
S707: and determining whether the signal to be detected contains other fault detection frequencies according to the phase diagram frequency spectrum to be detected and the reference phase diagram frequency spectrum.
For the description of S707, reference may be made to the foregoing embodiments, which are not described herein again.
In the embodiment of the disclosure, a differential oscillator detection model is constructed by obtaining a signal to be detected of a coal equipment, wherein the differential oscillator detection model is used for performing frequency detection on the signal to be detected, adjusting model parameters of the differential oscillator detection model until the differential oscillator detection model is in an optimal polar ring state to obtain a reference phase diagram output by the differential oscillator detection model, inputting the signal to be detected into the differential oscillator detection model to obtain a phase diagram to be detected output by the differential oscillator detection model, performing fourier transform processing on the reference phase diagram and the phase diagram to be detected respectively to obtain a reference phase diagram frequency spectrum corresponding to the reference phase diagram and a phase diagram frequency spectrum corresponding to the phase diagram to be detected, and determining whether the signal to be detected contains a reference fault detection frequency according to a reference frequency spectrum amplitude, the reference phase diagram frequency spectrum and the phase diagram frequency spectrum to be detected, and determining whether the signal to be detected contains other fault detection frequencies according to the phase diagram frequency spectrum to be detected and the reference phase diagram frequency spectrum, so that the differential oscillator detection model can be combined to realize the multi-fault frequency detection of the coal equipment, the differential oscillator detection model can detect other unknown fault detection frequencies on the basis of detecting known and single reference fault detection, the limitation that the differential oscillator detection model can only detect known and single frequencies is broken through, and the multi-fault frequency detection is realized under the condition that the specific numerical value of the detected fault frequency cannot be determined.
Fig. 8 is a schematic structural diagram of a detection apparatus for detecting a failure frequency of a coal equipment according to an embodiment of the present disclosure.
As shown in fig. 8, the coal equipment failure frequency detection apparatus 80 includes:
the acquisition module 801 is used for acquiring a signal to be detected of coal mining equipment;
the constructing module 802 is configured to construct a differential oscillator detection model, where the differential oscillator detection model is used to perform frequency detection on a signal to be detected;
the adjusting module 803 is configured to adjust a model parameter of the differential oscillator detection model until the differential oscillator detection model is in an optimal polar ring state, so as to obtain a reference phase diagram output by the differential oscillator detection model;
the first processing module 804 is configured to input a signal to be detected into the differential oscillator detection model to obtain a phase diagram to be detected output by the differential oscillator detection model;
a second processing module 805, configured to perform fourier transform processing on the reference phase diagram and the phase diagram to be detected respectively to obtain a reference phase diagram frequency spectrum corresponding to the reference phase diagram and a phase diagram frequency spectrum to be detected corresponding to the phase diagram to be detected;
the first determining module 806 is configured to determine whether the signal to be detected includes other fault detection frequencies according to the phase diagram spectrum to be detected and the reference phase diagram spectrum.
In some embodiments of the present disclosure, as shown in fig. 9, fig. 9 is a schematic structural diagram of a detection apparatus for a failure frequency of a coal equipment according to another embodiment of the present disclosure, and the building module 802 is further configured to:
acquiring a plurality of fault frequencies and reference detection signals of coal equipment;
determining a reference fault detection frequency from a plurality of fault frequencies;
and constructing a differential oscillator detection model according to the signal to be detected, the reference detection signal and the reference fault detection frequency.
In some embodiments of the present disclosure, the reference detection signal has a corresponding reference spectral magnitude;
wherein, the detection device 80 of coal machine equipment fault frequency still includes:
the second determining module 807 is configured to, after performing fourier transform processing on the reference phase diagram and the phase diagram to be detected respectively to obtain a reference phase diagram frequency spectrum corresponding to the reference phase diagram and a phase diagram frequency spectrum to be detected corresponding to the phase diagram to be detected, determine whether the signal to be detected includes the reference fault detection frequency according to the reference frequency spectrum amplitude, the reference phase diagram frequency spectrum, and the phase diagram frequency spectrum to be detected.
In some embodiments of the present disclosure, the second determining module 807 is further configured to:
analyzing the phase diagram frequency spectrum to be detected according to the reference frequency spectrum amplitude and the reference phase diagram frequency spectrum to obtain a frequency spectrum amplitude to be detected of the signal to be detected;
if the frequency spectrum amplitude to be detected is larger than the reference frequency spectrum amplitude, determining that the signal to be detected contains the reference fault detection frequency;
and if the frequency spectrum amplitude to be detected is smaller than or equal to the reference frequency spectrum amplitude, determining that the signal to be detected does not contain the reference fault detection frequency.
In some embodiments of the present disclosure, the first determining module 806 is further configured to:
if the frequency components of the phase diagram frequency spectrum to be detected and the reference phase diagram frequency spectrum are the same, determining that the signal to be detected does not contain other fault detection frequencies;
and if the frequency components of the phase diagram frequency spectrum to be detected and the reference phase diagram frequency spectrum are different, performing conversion processing on the phase diagram frequency in the reference phase diagram frequency spectrum to determine that the signal to be detected contains other fault detection frequencies.
Corresponding to the method for detecting the failure frequency of the coal equipment provided in the embodiments of fig. 1 to 7, the present disclosure also provides a device for detecting the failure frequency of the coal equipment, and since the device for detecting the failure frequency of the coal equipment provided in the embodiments of the present disclosure corresponds to the method for detecting the failure frequency of the coal equipment provided in the embodiments of fig. 1 to 7, the embodiment of the method for detecting the failure frequency of the coal equipment provided in the embodiments of the present disclosure is also applicable to the device for detecting the failure frequency of the coal equipment provided in the embodiments of the present disclosure, and will not be described in detail in the embodiments of the present disclosure.
In the embodiment, a signal to be detected of coal equipment is obtained, a differential oscillator detection model is constructed, wherein the differential oscillator detection model is used for performing frequency detection on the signal to be detected, model parameters of the differential oscillator detection model are adjusted until the differential oscillator detection model is in an optimal polar ring state, so as to obtain a reference phase diagram output by the differential oscillator detection model, the signal to be detected is input into the differential oscillator detection model, so as to obtain a phase diagram to be detected output by the differential oscillator detection model, the reference phase diagram and the phase diagram to be detected are subjected to fourier transform processing respectively, so as to obtain a reference phase diagram frequency spectrum corresponding to the reference phase diagram and a phase diagram frequency spectrum corresponding to the phase diagram to be detected, and whether other fault detection frequencies are included in the signal to be detected is determined according to the phase diagram frequency spectrum to be detected and the reference phase diagram frequency spectrum, so that the differential oscillator detection model can be combined, the method has the advantages that the multi-fault frequency detection of the coal machine equipment is realized, so that the limitation that a differential oscillator detection model can only detect known single frequency is broken through, and the multi-fault frequency detection is realized under the condition that the specific numerical value of the detected fault frequency cannot be determined.
In order to implement the above embodiments, the present disclosure further provides an electronic device, including: the detection method for the failure frequency of the coal equipment provided by the foregoing embodiments of the disclosure is realized when the processor executes the program.
In order to achieve the above embodiments, the present disclosure also proposes a non-transitory computer readable storage medium, on which a computer program is stored, which when executed by a processor, implements the method for detecting the failure frequency of a coal equipment as proposed in the foregoing embodiments of the present disclosure.
In order to implement the foregoing embodiments, the present disclosure further provides a computer program product, which when executed by an instruction processor in the computer program product, performs the method for detecting the failure frequency of the coal equipment according to the foregoing embodiments of the present disclosure.
FIG. 10 illustrates a block diagram of an exemplary electronic device suitable for use in implementing embodiments of the present disclosure. The electronic device 12 shown in fig. 10 is only an example and should not impose any limitations on the functionality and scope of use of the disclosed embodiments.
As shown in FIG. 10, electronic device 12 is embodied in the form of a general purpose computing device. The components of electronic device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that couples various system components including the system memory 28 and the processing unit 16.
Electronic device 12 typically includes a variety of computer system readable media. Such media may be any available media that is accessible by electronic device 12 and includes both volatile and nonvolatile media, removable and non-removable media.
Although not shown in FIG. 10, a disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a Compact disk Read Only Memory (CD-ROM), a Digital versatile disk Read Only Memory (DVD-ROM), or other optical media) may be provided. In these cases, each drive may be connected to bus 18 by one or more data media interfaces. Memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the disclosure.
A program/utility 40 having a set (at least one) of program modules 42 may be stored, for example, in memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 42 generally carry out the functions and/or methodologies of the embodiments described in this disclosure.
Electronic device 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), with one or more devices that enable a user to interact with electronic device 12, and/or with any devices (e.g., network card, modem, etc.) that enable electronic device 12 to communicate with one or more other computing devices. Such communication may be through an input/output (I/O) interface 22. Also, the electronic device 12 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public Network such as the Internet) via the Network adapter 20. As shown, the network adapter 20 communicates with other modules of the electronic device 12 via the bus 18. It should be understood that although not shown in the figures, other hardware and/or software modules may be used in conjunction with electronic device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, and data backup storage systems, among others.
The processing unit 16 executes various functional applications and data processing by running programs stored in the system memory 28, for example, to implement the method for detecting the failure frequency of the coal equipment mentioned in the foregoing embodiments.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
It should be noted that, in the description of the present disclosure, the terms "first", "second", etc. are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. Further, in the description of the present disclosure, "a plurality" means two or more unless otherwise specified.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and the scope of the preferred embodiments of the present disclosure includes other implementations in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the embodiments of the present disclosure.
It should be understood that portions of the present disclosure may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are well known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried out in the method for implementing the above embodiment may be implemented by hardware that is related to instructions of a program, and the program may be stored in a computer readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiment.
In addition, functional units in the embodiments of the present disclosure may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated modules, if implemented in the form of software functional modules and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present disclosure. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Although embodiments of the present disclosure have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present disclosure, and that changes, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present disclosure.
Claims (10)
1. A method for detecting the failure frequency of coal equipment is characterized by comprising the following steps:
acquiring a signal to be detected of coal equipment;
constructing a differential oscillator detection model, wherein the differential oscillator detection model is used for carrying out frequency detection on the signal to be detected;
adjusting model parameters of the differential oscillator detection model until the differential oscillator detection model is in an optimal polar ring state to obtain a reference phase diagram output by the differential oscillator detection model;
inputting the signal to be detected into the differential oscillator detection model to obtain a phase diagram to be detected output by the differential oscillator detection model;
respectively carrying out Fourier transform processing on the reference phase diagram and the phase diagram to be detected so as to obtain a reference phase diagram frequency spectrum corresponding to the reference phase diagram and a phase diagram frequency spectrum to be detected corresponding to the phase diagram to be detected;
and determining whether the signal to be detected contains other fault detection frequencies according to the phase diagram frequency spectrum to be detected and the reference phase diagram frequency spectrum.
2. The method of claim 1, wherein constructing a differential element detection model comprises:
acquiring a plurality of fault frequencies and reference detection signals of the coal mining equipment;
determining a reference fault detection frequency from the plurality of fault frequencies;
and constructing the differential oscillator detection model according to the signal to be detected, the reference detection signal and the reference fault detection frequency.
3. The method of claim 2, wherein the reference detection signal has a corresponding reference spectral amplitude;
after the fourier transform processing is performed on the reference phase diagram and the phase diagram to be detected respectively to obtain a reference phase diagram frequency spectrum corresponding to the reference phase diagram and a phase diagram frequency spectrum to be detected corresponding to the phase diagram to be detected, the method further includes:
and determining whether the reference fault detection frequency is contained in the signal to be detected or not according to the reference frequency spectrum amplitude, the reference phase diagram frequency spectrum and the phase diagram frequency spectrum to be detected.
4. The method according to claim 3, wherein the determining whether the reference fault detection frequency is included in the signal to be detected according to the reference spectrum amplitude, the reference phase diagram spectrum and the phase diagram spectrum to be detected comprises:
analyzing the reference frequency spectrum amplitude and the reference phase diagram frequency spectrum to obtain a frequency spectrum amplitude to be detected of the signal to be detected;
if the frequency spectrum amplitude to be detected is larger than the reference frequency spectrum amplitude, determining that the signal to be detected contains the reference fault detection frequency;
and if the frequency spectrum amplitude to be detected is smaller than or equal to the reference frequency spectrum amplitude, determining that the signal to be detected does not contain the reference fault detection frequency.
5. The method according to claim 1, wherein the determining whether the signal to be detected contains other fault detection frequencies according to the phase diagram spectrum to be detected and the reference phase diagram spectrum comprises:
if the frequency components of the phase diagram frequency spectrum to be detected and the reference phase diagram frequency spectrum are the same, determining that the signal to be detected does not contain other fault detection frequencies;
and if the frequency components of the phase diagram frequency spectrum to be detected and the reference phase diagram frequency spectrum are different, performing conversion processing on the phase diagram frequency in the reference phase diagram frequency spectrum to determine that the signal to be detected contains other fault detection frequencies.
6. A coal machine equipment failure frequency detection device is characterized by comprising:
the acquisition module is used for acquiring a signal to be detected of the coal equipment;
the device comprises a construction module, a detection module and a detection module, wherein the construction module is used for constructing a differential oscillator detection model, and the differential oscillator detection model is used for carrying out frequency detection on a signal to be detected;
the adjusting module is used for adjusting the model parameters of the differential oscillator detection model until the differential oscillator detection model is in the optimal polar ring state so as to obtain a reference phase diagram output by the differential oscillator detection model;
the first processing module is used for inputting the signal to be detected into the differential oscillator detection model so as to obtain a phase diagram to be detected output by the differential oscillator detection model;
the second processing module is used for respectively carrying out Fourier transform processing on the reference phase diagram and the phase diagram to be detected so as to obtain a reference phase diagram frequency spectrum corresponding to the reference phase diagram and a phase diagram frequency spectrum to be detected corresponding to the phase diagram to be detected;
and the first determining module is used for determining whether the signal to be detected contains other fault detection frequencies according to the phase diagram frequency spectrum to be detected and the reference phase diagram frequency spectrum.
7. The apparatus of claim 6, wherein the build module is further configured to:
acquiring a plurality of fault frequencies and reference detection signals of the coal mining equipment;
determining a reference fault detection frequency from the plurality of fault frequencies;
and constructing the differential oscillator detection model according to the signal to be detected, the reference detection signal and the reference fault detection frequency.
8. The apparatus of claim 7, wherein the reference detection signal has a corresponding reference spectral amplitude;
wherein, the device still includes:
and a second determining module, configured to determine whether the signal to be detected includes the reference fault detection frequency according to the reference spectrum amplitude, the reference phase diagram frequency spectrum, and the phase diagram frequency spectrum to be detected after performing fourier transform processing on the reference phase diagram and the phase diagram to be detected respectively to obtain a reference phase diagram frequency spectrum corresponding to the reference phase diagram and a phase diagram frequency spectrum to be detected corresponding to the phase diagram to be detected.
9. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-5.
10. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-5.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115935250A (en) * | 2022-11-10 | 2023-04-07 | 天地(常州)自动化股份有限公司北京分公司 | Fault diagnosis method and system based on differential oscillator and domain adaptive hybrid model |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115935250A (en) * | 2022-11-10 | 2023-04-07 | 天地(常州)自动化股份有限公司北京分公司 | Fault diagnosis method and system based on differential oscillator and domain adaptive hybrid model |
| CN115935250B (en) * | 2022-11-10 | 2023-10-27 | 天地(常州)自动化股份有限公司北京分公司 | Fault diagnosis method and system based on differential vibrator and field self-adaptive hybrid model |
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