Fault diagnosis method and device of circuit breaker, electronic equipment and storage medium

Abstract

The invention relates to the technical field of electronic equipment fault vibration, and discloses a circuit breaker fault diagnosis method and device, electronic equipment and a storage medium. The method comprises the following steps: collecting a vibration signal and a sound signal in the working process of the circuit breaker; performing fusion processing on the vibration signal and the sound signal based on a cross spectrum to obtain a cross amplitude spectrum and a cross phase spectrum; constructing a chaotic spectrum under polar coordinates based on the cross amplitude spectrum and the cross phase spectrum; determining a vector of each data point based on the point coordinate of each data point in the chaotic spectrum; determining a chaos length entropy based on the vector length of each data point, and determining a chaos angle entropy based on the vector angle of each data point; and inputting the chaos length entropy and the chaos angle entropy into a support vector machine for identification, and determining the working state of the circuit breaker. According to the invention, the circuit breaker mechanical fault diagnosis function can be realized by combining the vibration signal and the sound signal, and the fault diagnosis accuracy is improved.

Description

Technical Field

[0001] The present disclosure relates to the technical field of electrical equipment fault diagnosis, and in particular to a circuit breaker fault diagnosis method and device, electronic equipment, and storage medium. Background Art

[0002] As an important action-type equipment in the power system, it plays an important role in controlling and protecting the power grid. In order to meet the grid stability requirements during the current switching process, the circuit breaker moves quickly during operation, generating strong and short-term impact vibrations, which puts high demands on the reliability of the mechanical components of the circuit breaker. Research shows that mechanical failure is the main fault of the circuit breaker. Research on intelligent diagnosis methods for mechanical failures of circuit breakers is of great significance to the safe and stable operation of the power grid. Summary of the invention

[0003] In view of the above situation, the embodiments of the present application provide a circuit breaker fault diagnosis method and device, electronic device, and storage medium, which aim to solve the above problems or at least partially solve the above problems.

[0004] In a first aspect, an embodiment of the present application provides a fault diagnosis method for a circuit breaker, the method comprising: collecting vibration signals and sound signals during the operation of the circuit breaker; fusing the vibration signals and the sound signals based on a cross-spectrum to obtain a cross-amplitude spectrum and a cross-phase spectrum; constructing a chaotic spectrum in polar coordinates based on the cross-amplitude spectrum and the cross-phase spectrum; determining a vector of each data point based on the point coordinates of each data point in the chaotic spectrum; determining a chaotic length entropy based on the vector length of each data point, and determining a chaotic angle entropy based on the vector angle of each data point; inputting the chaotic length entropy and the chaotic angle entropy into a support vector machine for identification to determine the working state of the circuit breaker.

[0005] In some embodiments, the vibration signal and the sound signal are fused based on the cross-spectrum to obtain a cross-amplitude spectrum and a cross-phase spectrum, including: determining a cross-correlation function between the vibration signal and the sound signal; determining the real and imaginary parts of the cross-spectrum based on the cross-correlation function; and generating the cross-amplitude spectrum and cross-phase spectrum based on the real and imaginary parts of the cross-spectrum.

[0006] In some embodiments, the real part of the cross spectrum is expressed as: The imaginary part of the cross spectrum is expressed as: Wherein, R(k) represents the cross-correlation function, k represents the lag time length, k=0, 1, 2, ..., T, T represents the maximum lag time length, ω represents the frequency, M(ω) represents the real part of the cross spectrum, and G(ω) represents the imaginary part of the cross spectrum; the cross amplitude spectrum is expressed as: The cross-phase spectrum is expressed as:

[0007] In some embodiments, constructing a chaotic spectrum in polar coordinates based on the cross-amplitude spectrum and the cross-phase spectrum includes: using the ordinate data of the cross-amplitude spectrum as the polar radius coordinate data of the chaotic spectrum, and using the ordinate data of the cross-phase spectrum as the polar angle coordinate data of the chaotic spectrum to generate the chaotic spectrum.

[0008] In some embodiments, the vectors of each data point determined based on the point coordinates of each data point in the chaotic spectrum include: determining the vector of the i-th data point based on the point coordinates of the i-th data point and the point coordinates of the i+1-th data point, where i is a positive integer greater than 0.

[0009] In some embodiments, the chaotic length entropy is determined based on the following formula: Where n represents the number of data points of the cross spectrum, i = 1, 2, 3, ..., n, (r i ,θ i ) and (r i+1 ,θ i+1 ) are the coordinates of two adjacent points in the chaotic spectrum.

[0010] In some embodiments, the chaotic angle entropy is determined based on the following formula: Where n represents the number of data points of the cross spectrum, i = 1, 2, 3, ..., n, (r i ,θ i ) and (r i+1 ,θ i+1 ) are the coordinates of two adjacent points in the chaotic spectrum.

[0011] In a second aspect, an embodiment of the present application further provides a fault diagnosis device for a circuit breaker, the device comprising:

[0012] The invention relates to an acquisition module, which is used to acquire vibration signals and sound signals during the operation of the circuit breaker; a processing module, which is used to fuse the vibration signal and the sound signal based on a cross spectrum to obtain a cross amplitude spectrum and a cross phase spectrum; a chaotic spectrum in polar coordinates is constructed based on the cross amplitude spectrum and the cross phase spectrum; a vector of each data point is determined based on the point coordinates of each data point in the chaotic spectrum; a chaotic length entropy is determined based on the vector length of each data point, and a chaotic angle entropy is determined based on the vector angle of each data point; and an identification module, which is used to input the chaotic length entropy and the chaotic angle entropy into a support vector machine for identification to determine the working state of the circuit breaker.

[0013] In some embodiments, the processing module is specifically used to determine the cross-correlation function of the vibration signal and the sound signal; determine the real part and the imaginary part of the cross spectrum based on the cross-correlation function; and generate the cross-amplitude spectrum and the cross-phase spectrum based on the real part and the imaginary part of the cross spectrum.

[0014] In some embodiments, the real part of the cross spectrum is expressed as: The imaginary part of the cross spectrum is expressed as: Wherein, R(k) represents the cross-correlation function, k represents the lag time length, k=0, 1, 2, ..., T, T represents the maximum lag time length, ω represents the frequency, M(ω) represents the real part of the cross spectrum, and G(ω) represents the imaginary part of the cross spectrum; the cross amplitude spectrum is expressed as: The cross-phase spectrum is expressed as:

[0015] In some embodiments, the processing module is specifically used to use the ordinate data of the cross-amplitude spectrum as the polar coordinate data of the chaotic spectrum, and use the ordinate data of the cross-phase spectrum as the polar angle coordinate data of the chaotic spectrum to generate the chaotic spectrum.

[0016] In some embodiments, the processing module is specifically used to determine the vector of the i-th data point based on the point coordinates of the i-th data point and the point coordinates of the (i+1)-th data point, where i is a positive integer greater than 0.

[0017] In some embodiments, the processing module is specifically configured to determine the chaotic length entropy based on the following formula:

[0018]

[0019] Where n represents the number of data points of the cross spectrum, i = 1, 2, 3, ..., n, (r i ,θ i ) and (r i+1 ,θ i+1 ) are the coordinates of two adjacent points in the chaotic spectrum.

[0020] In some embodiments, the processing module is specifically configured to determine the chaotic angle entropy based on the following formula:

[0021]

[0022] Where n represents the number of data points of the cross spectrum, i = 1, 2, 3, ..., n, (r i ,θ i ) and (r i+1 ,θ i+1 ) are the coordinates of two adjacent points in the chaotic spectrum.

[0023] In a third aspect, an embodiment of the present application further provides an electronic device, comprising: a processor; and a memory arranged to store computer executable instructions, wherein the executable instructions, when executed, cause the processor to perform the steps of the first aspect described above.

[0024] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, which stores one or more programs. When the one or more programs are executed by an electronic device including multiple application programs, the electronic device executes the steps of the first aspect above.

[0025] At least one of the above-mentioned technical solutions adopted in the embodiments of the present application can achieve the following beneficial effects: the vibration signal and the sound signal are fused through the cross spectrum to obtain the cross amplitude spectrum and the cross phase spectrum, giving full play to the integrity of the vibration signal and the sound signal, and then constructing a chaotic spectrum through the cross amplitude spectrum and the cross phase spectrum. The chaotic spectrum can take into account the relevant information between the vibration and the sound reflected by the cross amplitude spectrum and the time lag information between the vibration and the sound signal reflected by the cross phase spectrum, and then the chaotic length entropy and the chaotic angle entropy are respectively obtained by the length and angle of the vector of each data point in the chaotic spectrum, and are input into the support vector machine for pattern recognition to realize the mechanical fault diagnosis function of the circuit breaker, and the diagnostic accuracy of the fault diagnosis is improved by fusing the sound signal and the vibration signal, so as to improve the safety, reliability and maintainability of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0027] Figure 1 A schematic diagram showing a flow chart of a circuit breaker fault diagnosis method provided in an embodiment of the present application;

[0028] Figure 2 The time domain waveform diagram of the vibration signal and the sound signal under the normal closing operation provided by the embodiment of the present application is shown;

[0029] Figure 3 The waveform diagram of the cross-amplitude spectrum and the cross-phase spectrum provided by the embodiment of the present application is shown;

[0030] Figure 4 The identification result of the support vector machine provided in the embodiment of the present application is shown;

[0031] Figure 5 A structural diagram of a fault diagnosis device for a circuit breaker provided in an embodiment of the present application is shown;

[0032] Figure 6A schematic structural diagram of an electronic device provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0033] In order to make the purpose, technical solution and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described below in combination with the specific embodiments of the present application and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application.

[0034] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that such use is interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the term "including" and its variants are to be interpreted as open-ended terms meaning "including but not limited to".

[0035] As described in the background technology, as an important action-type equipment in the power system, it plays an important role in controlling and protecting the power grid. In order to meet the requirements of power grid stability during the current switching process, the high-voltage circuit breaker moves quickly during operation, generating strong and short-term impact vibrations, which puts higher requirements on the reliability of the mechanical components of the high-voltage circuit breaker. Studies have shown that mechanical failure is the main failure of high-voltage circuit breakers. Research on intelligent diagnosis methods for mechanical failures of high-voltage circuit breakers is of great significance to the safe and stable operation of the power grid.

[0036] Under strong impact, high-voltage circuit breakers generate vibration and sound signals during operation. The vibration signal transmission process has low attenuation and high accuracy, but is greatly affected by the signal acquisition location; the sound signal is mainly transmitted through the air medium, which is convenient for evaluating the overall situation of the equipment, but is greatly affected by environmental noise. At present, most people use a single vibration signal or sound signal to diagnose high-voltage circuit breaker faults, but the comprehensive diagnosis effect on the operating status of high-voltage circuit breakers is not ideal, and there is a lack of methods based on vibration and sound fusion analysis.

[0037] Based on this, an embodiment of the present application provides a fault diagnosis method for a circuit breaker, which fuses the vibration signal and the sound signal through a cross spectrum to obtain a cross amplitude spectrum and a cross phase spectrum, giving full play to the integrity of the vibration signal and the sound signal, and then constructing a chaotic spectrum through the cross amplitude spectrum and the cross phase spectrum. The chaotic spectrum can take into account the relevant information between the vibration and sound reflected by the cross amplitude spectrum and the time lag information between the vibration and sound signals reflected by the cross phase spectrum, and then obtain the chaotic length entropy and the chaotic angle entropy respectively through the length and angle of the vector of each data point in the chaotic spectrum, and input them into a support vector machine for pattern recognition, so as to realize the mechanical fault diagnosis function of the circuit breaker, and improve the diagnostic accuracy of the fault diagnosis by fusing the sound signal and the vibration signal, so as to improve the safety, reliability and maintainability of the power system.

[0038] The present application is described in detail below through specific embodiments.

[0039] Figure 1 A schematic diagram of a flow chart of a circuit breaker fault diagnosis method provided in an embodiment of the present application is shown, from Figure 1 It can be seen that the present application at least includes steps S101 to S105:

[0040] Step S101: collecting vibration signals and sound signals during the operation of the circuit breaker.

[0041] In some embodiments, the vibration signal and sound signal of the circuit breaker are collected by an acquisition card, a vibration acceleration sensor and a sound sensor. In one embodiment, the vibration sensor is fixed to the circuit breaker housing by magnetic attraction, and the sound sensor is placed at a preset distance from the circuit breaker. Of course, the positions of the vibration sensor and the sound sensor are not specified, and the sample data participating in the support vector machine model training can be collected at the same position.

[0042] In some embodiments, Figure 2 As shown, the amplitudes of the vibration signals and sound signals collected during the operation of the circuit breaker are exemplarily shown.

[0043] Step S102: fusing the vibration signal and the sound signal based on the cross spectrum to obtain a cross amplitude spectrum and a cross phase spectrum.

[0044] In some embodiments, the cross spectrum is a mathematical tool used to study the correlation between two signals, which can explain the correlation between signals at different frequencies. Furthermore, the cross spectrum includes a cross amplitude spectrum and a cross phase spectrum. The cross amplitude spectrum is used to measure the correlation between two signals, describes the amplitude relationship between the two signals at each frequency, and can detect the frequency components related to the signals; the cross phase spectrum is used to describe the lead-lag relationship between the two signals, provides the phase difference information of the signals at different frequencies, and can analyze the timing relationship between the signals.

[0045] In some embodiments, Figure 3 As shown, the cross-amplitude spectrum and cross-phase spectrum obtained after the fusion processing of the vibration signal and the sound signal based on the cross spectrum are exemplified, wherein the horizontal coordinates of the cross-amplitude spectrum and the cross-phase spectrum are frequency, the vertical coordinate of the cross-amplitude spectrum is amplitude, and the vertical coordinate of the cross-phase spectrum is angle.

[0046] Step S103: constructing a chaotic spectrum in polar coordinates based on the cross-amplitude spectrum and the cross-phase spectrum.

[0047] In some embodiments, the ordinate data of the cross-amplitude spectrum is used as the polar coordinate data, and the ordinate data of the cross-phase spectrum is used as the polar coordinate data, and the chaotic spectrum θ=H(r) proposed under polar coordinates is obtained, where r is the ordinate data of the cross-amplitude spectrum, and θ is the ordinate data of the cross-phase spectrum. The chaotic spectrum takes into account the relevant information between the vibration signal and the sound signal embodied by the cross-amplitude spectrum, and the time lag information between the vibration signal and the sound signal embodied by the cross-phase spectrum.

[0048] Step S104: determining the vector of each data point based on the point coordinates of each data point in the chaotic spectrum.

[0049] In some embodiments, the data points in the chaotic spectrum are connected end to end in sequence, with the polar coordinate pole pointing to the first data point, the first data point pointing to the second data point, and so on, to obtain i vectors W1, W2., ..., Wi, where i = 0, 1, 2, 3, ..., n, n is the number of data points in the cross spectrum, and when i = 0, θ0 = 0, r0 = 0. Assume that the point coordinates of two adjacent points in the chaotic spectrum are A (r i ,θ i )、B(r i+1 ,θ i+1 ), then the vector W i It can be expressed as W i =(r i+1 -r i ,θ i+1 -θ i ).

[0050] Step S105: determining the chaotic length entropy based on the vector length of each data point, and determining the chaotic angle entropy based on the vector angle of each data point.

[0051] In some embodiments, chaotic length entropy and chaotic angle entropy are defined, wherein the chaotic length entropy is calculated by the length information of each vector in the vector Wi and the probability function in the information entropy theory, and the chaotic angle entropy is calculated by the angle information of each vector in the vector Wi and the probability function in the information entropy theory.

[0052] In one implementation, the chaotic length entropy is determined based on the following formula:

[0053]

[0054] Where n represents the number of data points of the cross spectrum, i = 1, 2, 3, ..., n, (r i ,θ i ) and (r i+1 ,θ i+1 ) are the coordinates of two adjacent points in the chaotic spectrum.

[0055] In one implementation, the chaotic angle entropy is determined based on the following formula:

[0056]

[0057] Where n represents the number of data points of the cross spectrum, i = 1, 2, 3, ..., n, (r i ,θ i ) and (r i+1 ,θ i+1 ) are the coordinates of two adjacent points in the chaotic spectrum.

[0058] Step S106: input the chaotic length entropy and the chaotic angle entropy into a support vector machine for identification to determine the working state of the circuit breaker.

[0059] In some embodiments, the working state of the circuit breaker includes a normal closing state and a fault state. In one embodiment, the fault state includes loose base (loosening of the fixing device of the body), spring fatigue (aging fatigue of the closing spring), and core jamming (jamming of the closing electromagnet core movement). Of course, the embodiments of the present application do not limit the type of fault state, which is only illustrated here.

[0060] In some embodiments, vibration signals and sound signals of the circuit breaker in normal closing state, loose base, spring fatigue, and core jamming are collected in advance as sample sets for the support vector machine. Specifically, 60% of the sample set is used for model training, and 40% of the sample set is used for model testing. Figure 4As shown, the accuracy of diagnosing the working status of the circuit breaker by the support vector machine is shown. It can be seen that the diagnosis accuracy is above 90%, the fault diagnosis rate is high and the type of fault status can be identified.

[0061] In an embodiment of the present application, the vibration signal and the sound signal are fused through a cross spectrum to obtain a cross amplitude spectrum and a cross phase spectrum, giving full play to the integrity of the vibration signal and the sound signal, and then constructing a chaotic spectrum through the cross amplitude spectrum and the cross phase spectrum. The chaotic spectrum can take into account the relevant information between the vibration and sound reflected by the cross amplitude spectrum and the time lag information between the vibration and sound signals reflected by the cross phase spectrum. Then, the chaotic length entropy and the chaotic angle entropy are respectively obtained by the length and angle of the vector of each data point in the chaotic spectrum, and are input into a support vector machine for pattern recognition to realize the mechanical fault diagnosis function of the circuit breaker. The diagnostic accuracy of the fault diagnosis is improved by fusing the sound signal and the vibration signal, so as to improve the safety, reliability and maintainability of the power system.

[0062] In some embodiments of the present application, in the above method, step 102 obtains the cross-amplitude spectrum and the cross-phase spectrum in the following manner: determine the cross-correlation function of the vibration signal and the sound signal, determine the real part and the imaginary part of the cross-spectrum based on the cross-correlation function, and then generate the cross-amplitude spectrum and the cross-phase spectrum based on the real part and the imaginary part of the cross-spectrum.

[0063] In some embodiments, the cross-correlation function of the vibration signal and the sound signal is expressed as

[0064]

[0065] Where f1(ω) and f2(ω) are the complex spectra of z(t) and s(t), respectively, k = 0, 1, 2, … T, T is the maximum lag time length, k is the lag time length, j is the imaginary unit, ω is the frequency, M(ω) is the real part of the cross spectrum, and G(ω) is the imaginary part of the cross spectrum.

[0066] From the cross-correlation function, we can see that the real part of the cross spectrum is expressed as: The imaginary part of the cross spectrum is expressed as:

[0067] Therefore, the cross-amplitude spectrum r(ω) can be expressed as: The cross-phase spectrum θ(ω) is expressed as:

[0068] In the embodiment of the present application, the vibration signal and the sound signal are fused through cross-spectrum processing, which can reflect the relevant information and time lag information between the vibration signal and the sound signal, and then perform fault diagnosis based on the fused information of the vibration signal and the sound signal, thereby improving the diagnostic accuracy of fault diagnosis.

[0069] In some embodiments of the present application, a circuit breaker fault diagnosis device is provided, and the optical fiber connection relationship troubleshooting device corresponds to the circuit breaker fault diagnosis method in the above embodiment. Figure 5 As shown, the fault diagnosis device for the circuit breaker includes: a collection module 201, a processing module 202 and an identification module 203. The detailed description of each functional module is as follows:

[0070] The acquisition module 201 is used to acquire vibration signals and sound signals during the operation of the circuit breaker;

[0071] The processing module 202 is used to perform fusion processing on the vibration signal and the sound signal based on the cross spectrum to obtain a cross amplitude spectrum and a cross phase spectrum; construct a chaotic spectrum in polar coordinates based on the cross amplitude spectrum and the cross phase spectrum; determine the vector of each data point based on the point coordinates of each data point in the chaotic spectrum; determine the chaotic length entropy based on the vector length of each data point, and determine the chaotic angle entropy based on the vector angle of each data point;

[0072] The identification module 203 is used to input the chaotic length entropy and the chaotic angle entropy into the support vector machine for identification to determine the working state of the circuit breaker.

[0073] In some embodiments of the present application, in the above-mentioned device, the processing module 202 is specifically used to determine the cross-correlation function of the vibration signal and the sound signal; determine the real part and the imaginary part of the cross-spectrum based on the cross-correlation function; and generate a cross-amplitude spectrum and a cross-phase spectrum based on the real part and the imaginary part of the cross-spectrum.

[0074] In some embodiments of the present application, in the above device, the real part of the cross spectrum is expressed as: The imaginary part of the cross spectrum is expressed as: Where R(k) represents the cross-correlation function, k represents the lag time length, k = 0, 1, 2, ..., T, T represents the maximum lag time length, ω represents the frequency, M(ω) represents the real part of the cross spectrum, and G(ω) represents the imaginary part of the cross spectrum; the cross amplitude spectrum is expressed as: The cross-phase spectrum is expressed as:

[0075] In some embodiments of the present application, in the above-mentioned device, the processing module 202 is specifically used to use the ordinate data of the cross-amplitude spectrum as the polar coordinate data of the chaotic spectrum, and use the ordinate data of the cross-phase spectrum as the polar coordinate data of the chaotic spectrum to generate a chaotic spectrum.

[0076] In some embodiments of the present application, in the above-mentioned device, the processing module 202 is specifically used to determine the vector of the i-th data point based on the point coordinates of the i-th data point and the point coordinates of the i+1-th data point, where i is a positive integer greater than 0.

[0077] In some embodiments of the present application, in the above device, the processing module 202 is specifically used to determine the chaotic length entropy based on the following formula:

[0078]

[0079] Where n represents the number of data points of the cross spectrum, i = 1, 2, 3, ..., n, (r i ,θ i ) and (r i+1 ,θ i+1 ) are the coordinates of two adjacent points in the chaotic spectrum.

[0080] In some embodiments of the present application, in the above device, the processing module 202 is specifically used to determine the chaotic angle entropy based on the following formula:

[0081]

[0082] Where n represents the number of data points of the cross spectrum, i = 1, 2, 3, ..., n, (r i ,θ i ) and (r i+1 ,θ i+1 ) are the coordinates of two adjacent points in the chaotic spectrum.

[0083] It should be noted that any of the above-mentioned circuit breaker fault diagnosis devices can implement the above-mentioned circuit breaker fault diagnosis method in a one-to-one correspondence, which will not be described in detail here.

[0084] Figure 6 FIG. 1 is a schematic diagram showing the structure of an electronic device provided in an embodiment of the present application. Figure 6 As shown, at the hardware level, the electronic device includes a processor, and optionally also includes an internal bus, a network interface, and a memory. Among them, the memory may include a memory, such as a high-speed random access memory (RAM), and may also include a non-volatile memory (non-volatile memory), such as at least one disk storage, etc. Of course, the electronic device may also include hardware required for other services.

[0085] The processor, network interface and memory can be interconnected through an internal bus, which can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 6 Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0086] The memory is used to store programs. Specifically, the program may include program code, and the program code includes computer operation instructions. The memory may include internal memory and non-volatile memory, and provides instructions and data to the processor.

[0087] The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs it, forming a fault diagnosis device for the circuit breaker at the logical level. The processor executes the program stored in the memory and is specifically used to execute the above method.

[0088] The processor may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by an integrated logic circuit of hardware in the processor or an instruction in the form of software. The above processor may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present application can be implemented or executed. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method disclosed in the embodiments of the present application can be directly embodied as a hardware decoding processor to be executed, or a combination of hardware and software modules in the decoding processor to be executed. The software module may be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware.

[0089] The electronic device can execute the circuit breaker fault diagnosis method provided by multiple embodiments of the present application, and realize the circuit breaker fault diagnosis device in Figure 5 The functions of the illustrated embodiment will not be described in detail in the embodiments of the present application.

[0090] An embodiment of the present application also proposes a computer-readable storage medium, which stores one or more programs, and the one or more programs include instructions. When the instructions are executed by an electronic device including multiple application programs, the electronic device can execute the circuit breaker fault diagnosis method provided by multiple embodiments of the present application.

[0091] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0092] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0093] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0094] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0095] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0096] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0097] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0098] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity or device including the element.

[0099] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0100] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A circuit breaker fault diagnosis method, characterized in that: The method comprises: Collect vibration and sound signals during the operation of the circuit breaker; The vibration signal and the sound signal are fused based on the cross spectrum to obtain a cross amplitude spectrum and a cross phase spectrum; Based on the cross-amplitude spectrum and the cross-phase spectrum, constructing a chaotic spectrum in polar coordinates; Determine the vector of each data point based on the point coordinates of each data point in the chaotic spectrum; Determine the chaotic length entropy based on the vector length of each data point, and determine the chaotic angle entropy based on the vector angle of each data point; The chaotic length entropy and the chaotic angle entropy are input into a support vector machine for identification to determine the working state of the circuit breaker.

2. The method according to claim 1, characterized in that The fusing process of the vibration signal and the sound signal based on the cross spectrum to obtain a cross amplitude spectrum and a cross phase spectrum includes: determining a cross-correlation function of the vibration signal and the sound signal; determining a real part and an imaginary part of a cross spectrum based on the cross-correlation function; The cross-amplitude spectrum and the cross-phase spectrum are generated based on the real part and the imaginary part of the cross-spectrum.

3. The method according to claim 2, characterized in that The real part of the cross spectrum is expressed as: The imaginary part of the cross spectrum is expressed as: Wherein, R(k) represents the cross-correlation function, k represents the lag time length, k=0, 1, 2, …, T, T represents the maximum lag time length, ω represents the frequency, M(ω) represents the real part of the cross spectrum, and G(ω) represents the imaginary part of the cross spectrum; The cross-amplitude spectrum is expressed as: The cross-phase spectrum is expressed as:

4. The method according to claim 1, characterized in that: The constructing a chaotic spectrum in polar coordinates based on the cross-amplitude spectrum and the cross-phase spectrum includes: The chaotic spectrum is generated by using the ordinate data of the cross-amplitude spectrum as the polar coordinate data of the chaotic spectrum and using the ordinate data of the cross-phase spectrum as the polar coordinate data of the chaotic spectrum.

5. The method according to claim 1, characterized in that The vectors of each data point determined based on the point coordinates of each data point in the chaotic spectrum include: The vector of the ith data point is determined based on the point coordinates of the ith data point and the point coordinates of the (i+1)th data point, where i is a positive integer greater than 0.

6. The method according to claim 1, characterized in that The chaos length entropy is determined based on the following formula: Where n represents the number of data points of the cross spectrum, i = 1, 2, 3, ..., n, (r i ,θ i ) and (r i+1 ,θ i+1 ) are the coordinates of two adjacent points in the chaotic spectrum.

7. The method according to claim 1, characterized in that The chaotic angle entropy is determined based on the following formula: Where n represents the number of data points of the cross spectrum, i = 1, 2, 3, ..., n, (r i ,θ i ) and (r i+1 ,θ i+1 ) are the coordinates of two adjacent points in the chaotic spectrum.

8. A fault diagnosis device for a circuit breaker, characterized in that: The device comprises: A collection module, used to collect vibration signals and sound signals during the operation of the circuit breaker; A processing module is used to perform fusion processing on the vibration signal and the sound signal based on the cross spectrum to obtain a cross amplitude spectrum and a cross phase spectrum; construct a chaotic spectrum in polar coordinates based on the cross amplitude spectrum and the cross phase spectrum; determine the vector of each data point based on the point coordinates of each data point in the chaotic spectrum; determine the chaotic length entropy based on the vector length of each data point, and determine the chaotic angle entropy based on the vector angle of each data point; The identification module is used to input the chaotic length entropy and the chaotic angle entropy into a support vector machine for identification, so as to determine the working state of the circuit breaker.

9. An electronic device, comprising: processor; as well as A memory arranged to store computer executable instructions, wherein when the executable instructions are executed, the processor executes the steps of the circuit breaker fault diagnosis method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing one or more programs, which, when executed by an electronic device including a plurality of application programs, enables the electronic device to execute the steps of the circuit breaker fault diagnosis method according to any one of claims 1 to 7.

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