An intelligent integrated electromechanical interlocking system for high-voltage distribution cabinet and control method thereof

Abstract

The present invention discloses an intelligent integrated electromechanical interlocking system for a high-voltage power distribution cabinet and a control method thereof, which specifically relates to the field of electromechanical interlocking technology, including a data acquisition module, a data area division module, a data processing module, a data analysis module, a comprehensive analysis module, an abnormal state analysis module and a control module. The present invention significantly improves the safety and operation and maintenance efficiency of the high-voltage power distribution cabinet. By integrating intelligent sensing and data analysis technology, it realizes comprehensive monitoring and accurate evaluation of the operating status of the interlocking device, can instantly discover and warn of potential faults, and the automated control strategy effectively shortens the fault response time. The high-precision data acquisition and processing module ensures the accuracy and reliability of the data, laying a solid foundation for comprehensive analysis and operation status judgment. The implementation of the present invention not only simplifies the operation and maintenance process, but also significantly reduces safety risks, and is a solid guarantee for the stable operation of the power system.

Description

Technical Field

[0001] The present invention relates to the technical field of electromechanical interlocking, and more specifically, to an intelligent integrated electromechanical interlocking system for a high-voltage power distribution cabinet and a control method thereof. Background Art

[0002] In the core area of ​​the power industry, high-voltage distribution cabinets play a vital role. They are key equipment to ensure efficient and safe power transmission and distribution. With the rapid development of the power industry, the requirements for the operation safety, stability and intelligent management level of high-voltage distribution cabinets are also increasing. Traditional high-voltage distribution cabinet electromechanical interlocking systems mostly use mechanical or electrical interlocking mechanisms to ensure the safety of operators and the normal operation of equipment.

[0003] The existing operation process of the electromechanical interlocking system of high-voltage distribution cabinets generally includes the following steps: first, the interlocking logic is triggered by an external operation signal, and then these signals reach the corresponding interlocking device through a complex mechanical or electrical transmission path. After receiving the valid signal, the interlocking device will control the circuit breakers, switches and other equipment in the high-voltage distribution cabinet to perform corresponding actions according to the preset logic rules to achieve correct switching of the switch status and safety interlocking. Although this process can basically ensure the safety of operation, it seems to be unable to cope with emergencies, achieve precise control and real-time monitoring.

[0004] The existing system lacks comprehensive data collection and real-time analysis capabilities, making it difficult to monitor the operating status of equipment in a timely and accurate manner, and is thus unable to quickly discover potential faults or abnormal conditions. Secondly, its control strategy is relatively fixed and single, and it is difficult to make flexible adjustments based on changes in the equipment operating environment and load conditions, which to a certain extent limits the stability and efficiency of the system operation. In addition, the overall integration of the existing system is not high, and there are often information islands between modules, making it difficult to achieve rapid data transmission and sharing, as well as rapid diagnosis and processing of faults. These shortcomings make the existing system unable to cope with the increasingly complex power system operation and maintenance needs, and there is an urgent need for a more intelligent, efficient and reliable electromechanical interlocking system to replace it. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides an intelligent integrated electromechanical interlocking system for a high-voltage distribution cabinet and a control method thereof, and solves the problems raised in the above-mentioned background technology through the following scheme.

[0006] To achieve the above object, the present invention provides the following technical solution: an intelligent integrated electromechanical interlocking system for a high-voltage distribution cabinet and a control method thereof, comprising:

[0007] Data acquisition module: used to set sensors to collect vibration spectrum data, current data and displacement data of the target interlocking device in real time, store the collected data and the timestamp corresponding to the data in the database, and transmit them to the data area division module;

[0008] Data area division module: used to determine the data transmitted to the database by the data acquisition module as the target data area, divide the target data area into various sub-data areas by equal time division, mark them as 1, 2...n in sequence, and transmit the data of each sub-data area to the data processing module;

[0009] Data processing module: used to pre-process the data in each sub-data area of ​​the database and transmit the processed data to the data analysis module;

[0010] Data analysis module: including vibration spectrum data analysis unit, current data analysis unit and displacement data analysis unit, which analyzes the data pre-processed by the data processing module through the corresponding mathematical model in each analysis unit, and transmits the analysis results to the comprehensive analysis module;

[0011] Comprehensive analysis module: including a comprehensive analysis model, which is used to conduct a comprehensive analysis on the data of the target interlocking device, import the data transmitted by the data analysis module into the comprehensive analysis model, calculate the comprehensive optimization index of the target interlocking device, and transmit it to the operation status analysis module;

[0012] Operation status analysis module: including a standard model building unit, a first comparison unit, a second comparison unit and a third comparison unit, the standard model building unit is used to determine a standard value of a comprehensive optimization index, and compare the standard value of the comprehensive optimization index with the comprehensive optimization index of a target interlocking device, the first comparison unit, the second comparison unit and the third comparison unit are used to determine an operation status of a target interlocking device, and transmit the operation status of the target interlocking device to the control module;

[0013] Control module: includes a first control unit and a second control unit, which are used to send control signals according to the operating status of the target interlocking device.

[0014] Preferably, the data acquisition module, data area division module, data processing module, data analysis module, comprehensive analysis module, abnormal state analysis module and control module are connected to the CPU.

[0015] Preferably, the vibration spectrum data include high-frequency amplitude, fundamental frequency amplitude, vibration duration, maximum resonance peak, sub-large resonance peak, total spectrum energy, energy value of maximum energy frequency point, longitudinal amplitude, lateral amplitude and torsional amplitude, which are marked as Dh, Df, Dt, Pm, Ps, Es, Ev, Lo, La and Lt respectively; the current data include peak current, effective value current, pulse duration, maximum value of harmonic current, fundamental current value, current standard deviation, current average value, eddy current loss, conductor cross-sectional area and magnetic flux density, which are marked as Pc, Pm, Pd, Hm, Hf, Cs, Cm, Ec, Co and Mf respectively; the displacement data include stress, strain, instantaneous creep rate, steady-state creep rate, thermal expansion coefficient, theoretical thermal expansion coefficient, tangential force and normal force, which are marked as σ, ε, Ic, Is, Te, Te respectively. the、 Tf and Nf.

[0016] Preferably, the data acquisition module directly measures the high-frequency amplitude and the fundamental frequency amplitude at the solenoid valve of the interlocking device through a laser vibrometer, uses an accelerometer installed on the structural member of the interlocking device to collect vibration signals, obtains the maximum resonance peak and the second largest resonance peak through spectrum analysis, obtains the sum of all energy points within a specific frequency range and the energy value of the maximum energy frequency point through a high-precision spectrum analyzer installed on the interlocking device, uses a laser vibrometer to measure the longitudinal amplitude in the long axis direction of the interlocking device, uses a laser vibrometer to measure the transverse amplitude in the transverse axis direction of the interlocking device, and uses a laser vibrometer to measure the torsional vibration amplitude of the interlocking device.

[0017] Preferably, the data acquisition module uses a high-precision current probe installed in the current channel to measure the instantaneous peak current, uses a high-precision current probe installed in the current channel to obtain the effective value current through RMS algorithm processing, records the pulse duration through a high-speed data acquisition instrument, uses a power quality analyzer to collect harmonic current at the current input end of the interlocking device, extracts the maximum value and fundamental current value of the harmonic current, measures the current values ​​of different time periods in the current channel through an ammeter, and then calculates the current standard deviation and the current average value, uses an eddy current flaw detector to measure the eddy current loss generated on the conductor surface, uses a caliper to measure the cross-sectional area of ​​the conductor, and uses a gaussmeter to measure the magnetic flux density around the conductor.

[0018] Preferably, the data acquisition module is installed at the stress-bearing part of the interlocking device through a strain gauge to measure the stress and strain generated, uses a displacement sensor to measure the instantaneous creep rate at a fixed temperature, uses a displacement sensor to measure the creep rate in a stable state, measures the thermal expansion coefficient of the interlocking device under heating conditions through a laser interferometer, and measures the tangential force and normal force of the sliding contact part of the interlocking device through a micro-force sensor.

[0019] Preferably, the data area division module first reads the data and the timestamp information corresponding to the data from the database, and then sets the time interval for each sub-data area according to actual needs. The time interval is a fixed time. The data area division module traverses all the timestamp information starting from the timestamp at the beginning of the data, and divides the timestamp into different time periods according to the set time interval. Each time period corresponds to a sub-data area, and the data points whose timestamps fall in the same time period are classified into the corresponding sub-data area. Finally, each divided sub-data area is marked.

[0020] Preferably, the data processing module calculates the harmonic distortion of the ith sub-data region through the high-frequency amplitude of the ith sub-data region, the fundamental frequency amplitude of the ith sub-data region, and the vibration duration of the ith sub-data region, which is specifically expressed as: , the resonance peak ratio of the ith sub-data region is calculated by the maximum resonance peak of the ith sub-data region and the second largest resonance peak of the ith sub-data region, which is specifically expressed as: , the spectrum entropy of the i-th sub-data region is calculated by the sum of the spectrum energy of the i-th sub-data region and the energy value of the maximum energy frequency point of the i-th sub-data region, which is specifically expressed as: , the vibration modal coefficient of the ith sub-data region is calculated by the longitudinal amplitude of the ith sub-data region, the lateral amplitude of the ith sub-data region, and the torsional amplitude of the ith sub-data region, which is specifically expressed as: .

[0021] Preferably, the data processing module calculates the current pulse factor of the ith sub-data region through the peak current of the ith sub-data region, the effective value current of the ith sub-data region, and the pulse duration of the ith sub-data region, which is specifically expressed as: , the harmonic distortion rate of the ith sub-data area is calculated by the maximum value of the harmonic current of the ith sub-data area and the fundamental current value of the ith sub-data area, which is specifically expressed as: , the current fluctuation coefficient of the ith sub-data region is calculated by the current standard deviation of the ith sub-data region and the current average value of the ith sub-data region, which is specifically expressed as: , the eddy current loss coefficient of the ith sub-data region is calculated by the eddy current loss of the ith sub-data region, the conductor cross-sectional area of ​​the ith sub-data region, and the magnetic flux density of the ith sub-data region, which is specifically expressed as: .

[0022] Preferably, the data processing module calculates the strain energy density of the ith sub-data region through the stress of the ith sub-data region and the strain of the ith sub-data region, which is specifically expressed as: , the creep rate ratio of the ith sub-data region is calculated by the instantaneous creep rate of the ith sub-data region and the steady-state creep rate of the ith sub-data region, which is specifically expressed as: , the thermal expansion anomaly of the ith sub-data region is calculated by the thermal expansion coefficient of the ith sub-data region and the theoretical thermal expansion coefficient, , the fretting friction coefficient of the ith sub-data area is calculated by the tangential force of the ith sub-data area and the normal force of the ith sub-data area, which is specifically expressed as: .

[0023] Preferably, the vibration spectrum data processed by the data processing module include harmonic distortion, resonance peak ratio, spectrum entropy and vibration modal coefficient, which are marked as Fd, Fp, Fe and Fl respectively; the current data include current pulse factor, harmonic distortion rate, current fluctuation coefficient and eddy current loss coefficient, which are marked as Mp, Mh, Mc and Me respectively; the displacement data include strain energy density, creep rate ratio, thermal expansion anomaly and micro-friction coefficient, which are marked as Vp, Vc, Vt and Vf respectively.

[0024] Preferably, the vibration spectrum data analysis unit is used to establish a vibration spectrum data analysis model, import the vibration spectrum data transmitted by the data processing module into the vibration spectrum data analysis unit, and calculate the vibration spectrum characteristic value of each sub-data area, which is specifically expressed as:

[0025] ,

[0026] KF i represents the vibration spectrum characteristic value of the ith sub-data area, Fd i Indicates the harmonic distortion of the ith sub-data region, Fp i represents the resonance peak ratio of the ith sub-data region, Fe i represents the spectrum entropy of the ith sub-data region, Fl i represents the vibration modal coefficient of the i-th sub-data area, and n represents the number of sub-data areas.

[0027] Preferably, the current data analysis unit is used to establish a current data analysis model, import the current data transmitted by the data processing module into the current data analysis unit, and calculate the current characteristic value of each sub-data area, which is specifically expressed as:

[0028] ,

[0029] KM i represents the current characteristic value of the ith sub-data area, Mp i Represents the current pulse factor of the ith sub-data area, Mh irepresents the harmonic distortion rate of the ith sub-data region, Mc i represents the current fluctuation coefficient of the ith sub-data area, Me i represents the eddy current loss coefficient of the i-th sub-data area, and n represents the number of sub-data areas.

[0030] Preferably, the displacement data analysis unit is used to establish a displacement data analysis model, import the displacement data transmitted by the data processing module into the displacement data analysis unit, and calculate the displacement characteristic value of each sub-data area, which is specifically expressed as:

[0031] ,

[0032] KV i represents the displacement characteristic value of the ith sub-data region, Vp i represents the strain energy density of the ith sub-data region, Vc i represents the creep rate ratio of the ith sub-data region, Vt i Indicates the thermal expansion anomaly of the ith sub-data region, Vf i represents the fretting friction coefficient of the i-th sub-data area, and n represents the number of sub-data areas.

[0033] Preferably, the comprehensive analysis model is specifically expressed as:

[0034] ,

[0035] η represents the comprehensive optimization index of the target interlocking device, KF i represents the vibration spectrum characteristic value of the ith sub-data area, KM i Indicates the current characteristic value of the i-th sub-data area, KV i Represents the displacement characteristic value of the i-th sub-data region.

[0036] Preferably, the standard model building unit is used to establish a standard model, which is specifically expressed as: , η sta Indicates the standard value of comprehensive optimization index, KF sta Indicates the standard value of vibration spectrum characteristics, KM sta Indicates the characteristic standard value of current, KV sta The displacement characteristic standard value is represented, and the comprehensive optimization index standard value is compared with the comprehensive optimization index of the target interlocking device.

[0037] Preferably, the first comparison unit is used to mark the target interlocking device as being in a good state when the comprehensive optimization index standard value is less than the comprehensive optimization index of the target interlocking device.

[0038] Preferably, the second comparison unit is used to mark the target interlocking device as a normal state when the comprehensive optimization index standard value is equal to the comprehensive optimization index of the target interlocking device.

[0039] Preferably, the third comparison unit is used to mark the target interlocking device as an abnormal state when the comprehensive optimization index standard value is greater than the comprehensive optimization index of the target interlocking device.

[0040] Preferably, the first control unit updates the comprehensive optimization index of the target interlocking device to a new comprehensive optimization index standard value when the operating state of the target interlocking device is in a good state.

[0041] Preferably, the second control unit sends a warning signal to the administrator terminal when the operating state of the target interlocking device is abnormal.

[0042] Preferably, an intelligent integrated electromechanical interlocking control method for a high-voltage distribution cabinet comprises the following specific steps:

[0043] S1: Data acquisition: used to set sensors to collect vibration spectrum data, current data and displacement data of the target interlocking device in real time, store the collected data and the timestamp corresponding to the data in the database, and transmit them to S2;

[0044] S2: Data area division: used to determine the data transmitted to the database by S1 as the target data area, divide the target data area into various sub-data areas by equal time division, mark them as 1, 2...n in sequence, and transmit the data of each sub-data area to S3;

[0045] S3: Data processing: used to pre-process the data in each sub-data area in the database and transmit the processed data to S4;

[0046] S4: Data analysis: including vibration spectrum data analysis method, current data analysis method and displacement data analysis method, analyzing the data pre-processed by the data processing module through the corresponding mathematical model in each analysis unit, and transmitting the analysis results to S5;

[0047] S5: Comprehensive analysis: including a comprehensive analysis model, which is used to conduct a comprehensive analysis on the data of the target interlocking device. The data transmitted by S4 is imported into the comprehensive analysis model, the comprehensive optimization index of the target interlocking device is calculated, and transmitted to S6;

[0048] S6: Operation status analysis: including a standard model building unit, a first comparison unit, a second comparison unit and a third comparison unit, the standard model building unit is used to determine a standard value of a comprehensive optimization index, and compare the standard value of the comprehensive optimization index with the comprehensive optimization index of a target interlocking device, the first comparison unit, the second comparison unit and the third comparison unit are used to determine the operation status of the target interlocking device, and transmit the operation status of the target interlocking device to S7;

[0049] S7: Control: including a first control unit and a second control unit, configured to send a control signal according to the operating state of the target interlocking device.

[0050] Technical effects and advantages of the present invention:

[0051] The present invention uses a data acquisition module to collect vibration spectrum, current and displacement data of a high-voltage distribution cabinet interlocking device in real time and accurately through high-precision sensors, and stores them in a database, thereby ensuring the comprehensiveness and accuracy of the data source and laying a solid foundation for subsequent data analysis; a data area division module is used to divide a continuous data stream into a plurality of sub-data areas at equal time intervals for the convenience of subsequent data processing and analysis, and timestamp management is used to ensure data orderliness and continuity, thereby improving data processing efficiency; a data processing module is used to clean and pre-process the collected raw data, including deduplication, outlier detection and missing value filling, and calculation is performed, thereby improving data accuracy and reliability, and providing a high-quality data source for subsequent in-depth analysis; a data analysis module is used to conduct in-depth analysis of vibration spectrum, current and displacement data, and characteristic values ​​of each sub-data area are extracted through a specific mathematical model. , including vibration spectrum eigenvalues, current eigenvalues ​​and displacement eigenvalues. The modular design enhances the flexibility and scalability of the system. Through the comprehensive analysis module, various data eigenvalues ​​are integrated, and the comprehensive optimization index of the target interlocking device is calculated using the comprehensive analysis model, which fully reflects the performance status of the interlocking device and provides a scientific basis for the overall operation status evaluation. Through the abnormal state analysis module, the calculated comprehensive optimization index is compared with the preset standard model to quickly judge the operation status of the interlocking device, and automatically take corresponding control strategies, including updating standard values ​​or issuing early warning signals to ensure the safe operation of the system. Through the control module, according to the results of the operation status analysis, the control signal is automatically issued to realize the real-time monitoring and effective management of the operation status of the high-voltage distribution cabinet interlocking device. When the equipment is abnormal, an early warning can be quickly issued to notify the management personnel to deal with it in time, reducing potential safety risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 It is a schematic diagram of the overall structure of the present invention.

[0053] Figure 2It is a schematic diagram of the structure of the data analysis module of the present invention.

[0054] Figure 3 It is a schematic diagram of the control method structure of the present invention. DETAILED DESCRIPTION

[0055] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0056] refer to Figure 1 An intelligent integrated electromechanical interlocking system for a high-voltage distribution cabinet is shown, comprising a data acquisition module, a data area division module, a data processing module, a data analysis module, a comprehensive analysis module, an abnormal state analysis module and a control module.

[0057] The data acquisition module, data area division module, data processing module, data analysis module, comprehensive analysis module, abnormal state analysis module and control module are connected to the CPU.

[0058] The data acquisition module is used to set sensors to collect vibration spectrum data, current data and displacement data of the target interlocking device in real time, store the collected data and the timestamp corresponding to the data in a database, and transmit them to the data area division module.

[0059] The vibration spectrum data include high-frequency amplitude, fundamental frequency amplitude, vibration duration, maximum resonance peak, second largest resonance peak, total spectrum energy, energy value of maximum energy frequency point, longitudinal amplitude, lateral amplitude and torsional amplitude, which are marked as Dh, Df, Dt, Pm, Ps, Es, Ev, Lo, La and Lt respectively; the current data include peak current, effective value current, pulse duration, maximum value of harmonic current, fundamental current value, current standard deviation, current average value, eddy current loss, conductor cross-sectional area and magnetic flux density, which are marked as Pc, Pm, Pd, Hm, Hf, Cs, Cm, Ec, Co and Mf respectively; the displacement data include stress, strain, instantaneous creep rate, steady-state creep rate, thermal expansion coefficient, theoretical thermal expansion coefficient, tangential force and normal force, which are marked as σ, ε, Ic, Is, Te, Te the、 Tf and Nf.

[0060] The data acquisition module directly measures the high-frequency amplitude and the fundamental frequency amplitude at the electromagnetic valve of the interlocking device by means of a laser vibrometer, uses an accelerometer installed on a structural member of the interlocking device to collect vibration signals, obtains a maximum resonance peak value and a second-largest resonance peak value by means of spectrum analysis, obtains the sum of all energy points within a specific frequency range and the energy value of the maximum energy frequency point by means of a high-precision spectrum analyzer installed on the interlocking device, measures the longitudinal amplitude in the long-axis direction of the interlocking device by means of a laser vibrometer, measures the transverse amplitude in the transverse axis direction of the interlocking device by means of a laser vibrometer, and measures the torsional vibration amplitude of the interlocking device by means of a laser vibrometer.

[0061] The data acquisition module uses a high-precision current probe installed in the current channel to measure the instantaneous peak current, uses a high-precision current probe installed in the current channel, obtains the effective value current through RMS algorithm processing, records the pulse duration through a high-speed data acquisition instrument, uses a power quality analyzer to collect harmonic current at the current input end of the interlocking device, extracts the maximum value and fundamental current value of the harmonic current, measures the current values ​​of different time periods in the current channel through an ammeter, and then calculates the current standard deviation and the current average value, uses an eddy current flaw detector to measure the eddy current loss generated on the conductor surface, uses a caliper to measure the cross-sectional area of ​​the conductor, and uses a gauss meter to measure the magnetic flux density around the conductor.

[0062] The data acquisition module is installed at the stress-bearing part of the interlocking device through a strain gauge to measure the stress and strain generated, uses a displacement sensor to measure the instantaneous creep rate at a fixed temperature, uses a displacement sensor to measure the creep rate in a stable state, measures the thermal expansion coefficient of the interlocking device under heating conditions through a laser interferometer, and measures the tangential force and normal force of the sliding contact part of the interlocking device through a micro-force sensor.

[0063] The data collection module performs data cleaning on the collected data, including data deduplication, outlier detection and missing value filling, to improve the accuracy and reliability of subsequent data analysis.

[0064] The data area division module is used to determine the data transmitted to the database by the data acquisition module as the target data area, divide the target data area into various sub-data areas by equal time division, mark them as 1, 2...n in sequence, and transmit the data of each sub-data area to the data processing module.

[0065] The data area division module first reads the data and the timestamp information corresponding to the data from the database, and then sets the time interval of each sub-data area according to actual needs. The time interval is a fixed time. The data area division module traverses all the timestamp information from the timestamp at the beginning of the data, and divides the timestamp into different time periods according to the set time interval. Each time period corresponds to a sub-data area, and the data points with timestamps falling in the same time period are classified into the corresponding sub-data area. Finally, each divided sub-data area is marked.

[0066] The data processing module is used to pre-process the data in each sub-data area in the database and transmit the processed data to the data analysis module.

[0067] The data processing module calculates the harmonic distortion of the ith sub-data region through the high-frequency amplitude of the ith sub-data region, the fundamental frequency amplitude of the ith sub-data region, and the vibration duration of the ith sub-data region, which is specifically expressed as: , the resonance peak ratio of the ith sub-data region is calculated by the maximum resonance peak of the ith sub-data region and the second largest resonance peak of the ith sub-data region, which is specifically expressed as: , the spectrum entropy of the i-th sub-data region is calculated by the sum of the spectrum energy of the i-th sub-data region and the energy value of the maximum energy frequency point of the i-th sub-data region, which is specifically expressed as: , the vibration modal coefficient of the ith sub-data region is calculated by the longitudinal amplitude of the ith sub-data region, the lateral amplitude of the ith sub-data region, and the torsional amplitude of the ith sub-data region, which is specifically expressed as: .

[0068] The data processing module calculates the current pulse factor of the ith sub-data region through the peak current of the ith sub-data region, the effective value current of the ith sub-data region, and the pulse duration of the ith sub-data region, which is specifically expressed as: , the harmonic distortion rate of the ith sub-data area is calculated by the maximum value of the harmonic current of the ith sub-data area and the fundamental current value of the ith sub-data area, which is specifically expressed as: , the current fluctuation coefficient of the ith sub-data region is calculated by the current standard deviation of the ith sub-data region and the current average value of the ith sub-data region, which is specifically expressed as: , the eddy current loss coefficient of the ith sub-data region is calculated by the eddy current loss of the ith sub-data region, the conductor cross-sectional area of ​​the ith sub-data region, and the magnetic flux density of the ith sub-data region, which is specifically expressed as: .

[0069] The data processing module calculates the strain energy density of the ith sub-data region through the stress of the ith sub-data region and the strain of the ith sub-data region, which is specifically expressed as: , the creep rate ratio of the ith sub-data region is calculated by the instantaneous creep rate of the ith sub-data region and the steady-state creep rate of the ith sub-data region, which is specifically expressed as: , the thermal expansion anomaly of the ith sub-data region is calculated by the thermal expansion coefficient of the ith sub-data region and the theoretical thermal expansion coefficient, , the fretting friction coefficient of the ith sub-data area is calculated by the tangential force of the ith sub-data area and the normal force of the ith sub-data area, which is specifically expressed as: .

[0070] The vibration spectrum data processed by the data processing module include harmonic distortion, resonance peak ratio, spectrum entropy and vibration modal coefficient, which are marked as Fd, Fp, Fe and Fl respectively; the current data include current pulse factor, harmonic distortion rate, current fluctuation coefficient and eddy current loss coefficient, which are marked as Mp, Mh, Mc and Me respectively; the displacement data include strain energy density, creep rate ratio, thermal expansion anomaly and micro-friction coefficient, which are marked as Vp, Vc, Vt and Vf respectively.

[0071] refer to Figure 2 The data analysis module includes a vibration spectrum data analysis unit, a current data analysis unit and a displacement data analysis unit. The data preprocessed by the data processing module is analyzed through the corresponding mathematical model in each analysis unit, and the analysis results are transmitted to the comprehensive analysis module.

[0072] The vibration spectrum data analysis unit is used to establish a vibration spectrum data analysis model, import the vibration spectrum data transmitted by the data processing module into the vibration spectrum data analysis unit, and calculate the vibration spectrum characteristic value of each sub-data area, which is specifically expressed as:

[0073] ,

[0074] KF i represents the vibration spectrum characteristic value of the ith sub-data area, Fd i Indicates the harmonic distortion of the ith sub-data region, Fp i represents the resonance peak ratio of the ith sub-data region, Fe i represents the spectrum entropy of the ith sub-data region, Fl i represents the vibration modal coefficient of the i-th sub-data area, and n represents the number of sub-data areas.

[0075] The current data analysis unit is used to establish a current data analysis model, import the current data transmitted by the data processing module into the current data analysis unit, and calculate the current characteristic value of each sub-data area, which is specifically expressed as:

[0076] ,

[0077] KM i represents the current characteristic value of the ith sub-data area, Mp i Represents the current pulse factor of the ith sub-data area, Mh i represents the harmonic distortion rate of the ith sub-data region, Mc i represents the current fluctuation coefficient of the ith sub-data area, Me i represents the eddy current loss coefficient of the i-th sub-data area, and n represents the number of sub-data areas.

[0078] The displacement data analysis unit is used to establish a displacement data analysis model, import the displacement data transmitted by the data processing module into the displacement data analysis unit, and calculate the displacement characteristic value of each sub-data area, which is specifically expressed as:

[0079] ,

[0080] KV i represents the displacement characteristic value of the ith sub-data region, Vp i represents the strain energy density of the ith sub-data region, Vc i represents the creep rate ratio of the ith sub-data region, Vt i Indicates the thermal expansion anomaly of the ith sub-data region, Vf i represents the fretting friction coefficient of the i-th sub-data area, and n represents the number of sub-data areas.

[0081] The comprehensive analysis module includes a comprehensive analysis model, which is used to perform comprehensive analysis on the data of the target interlocking device. The data transmitted by the data analysis module is imported into the comprehensive analysis model, and the comprehensive optimization index of the target interlocking device is calculated and transmitted to the operation status analysis module.

[0082] The comprehensive analysis model is specifically expressed as:

[0083] ,

[0084] η represents the comprehensive optimization index of the target interlocking device, KF i represents the vibration spectrum characteristic value of the ith sub-data area, KM i Indicates the current characteristic value of the i-th sub-data area, KV i Represents the displacement characteristic value of the i-th sub-data region.

[0085] It should be specifically explained in this embodiment that other influencing factors of the comprehensive optimization index specifically represent maintenance conditions.

[0086] The operating status analysis module includes a standard model construction unit, a first comparison unit, a second comparison unit and a third comparison unit. The standard model construction unit is used to determine a standard value of a comprehensive optimization index and compare the standard value of the comprehensive optimization index with the comprehensive optimization index of a target interlocking device. The first comparison unit, the second comparison unit and the third comparison unit are used to determine the operating status of the target interlocking device and transmit the operating status of the target interlocking device to the control module.

[0087] The standard model building unit is used to establish a standard model, which is specifically expressed as: , η sta Indicates the standard value of comprehensive optimization index, KF sta Indicates the standard value of vibration spectrum characteristics, KM sta Indicates the characteristic standard value of current, KV sta The displacement characteristic standard value is represented, and the comprehensive optimization index standard value is compared with the comprehensive optimization index of the target interlocking device.

[0088] The first comparison unit is used for marking the target interlocking device as being in a good state when the comprehensive optimization index standard value is less than the comprehensive optimization index of the target interlocking device.

[0089] The second comparison unit is used for marking the target interlocking device as a normal state when the comprehensive optimization index standard value is equal to the comprehensive optimization index of the target interlocking device.

[0090] The third comparison unit is used for marking the target interlocking device as an abnormal state when the comprehensive optimization index standard value is greater than the comprehensive optimization index of the target interlocking device.

[0091] The control module includes a first control unit and a second control unit, which are used to send a control signal according to the operating state of the target interlocking device.

[0092] The first control unit updates the comprehensive optimization index of the target interlocking device to a new comprehensive optimization index standard value when the operating state of the target interlocking device is in a good state.

[0093] The second control unit sends a warning signal to the management terminal when the operating state of the target interlocking device is abnormal.

[0094] refer to Figure 3 , an intelligent integrated electromechanical interlocking control method for a high-voltage distribution cabinet, the specific steps comprising:

[0095] S1: Data acquisition: used to set sensors to collect vibration spectrum data, current data and displacement data of the target interlocking device in real time, store the collected data and the timestamp corresponding to the data in the database, and transmit them to S2;

[0096] S2: Data area division: used to determine the data transmitted to the database by S1 as the target data area, divide the target data area into various sub-data areas by equal time division, mark them as 1, 2...n in sequence, and transmit the data of each sub-data area to S3;

[0097] S3: Data processing: used to pre-process the data in each sub-data area in the database and transmit the processed data to S4;

[0098] S4: Data analysis: including vibration spectrum data analysis method, current data analysis method and displacement data analysis method, analyzing the data pre-processed by the data processing module through the corresponding mathematical model in each analysis unit, and transmitting the analysis results to S5;

[0099] S5: Comprehensive analysis: including a comprehensive analysis model, which is used to conduct a comprehensive analysis on the data of the target interlocking device. The data transmitted by S4 is imported into the comprehensive analysis model, the comprehensive optimization index of the target interlocking device is calculated, and transmitted to S6;

[0100] S6: Operation status analysis: including a standard model building unit, a first comparison unit, a second comparison unit and a third comparison unit, the standard model building unit is used to determine a standard value of a comprehensive optimization index, and compare the standard value of the comprehensive optimization index with the comprehensive optimization index of a target interlocking device, the first comparison unit, the second comparison unit and the third comparison unit are used to determine the operation status of the target interlocking device, and transmit the operation status of the target interlocking device to S7;

[0101] S7: Control: including a first control unit and a second control unit, configured to send a control signal according to the operating state of the target interlocking device.

[0102] The present invention uses a data acquisition module to collect vibration spectrum, current and displacement data of a high-voltage distribution cabinet interlocking device in real time and accurately through high-precision sensors, and stores them in a database, thereby ensuring the comprehensiveness and accuracy of the data source and laying a solid foundation for subsequent data analysis; a data area division module is used to divide a continuous data stream into a plurality of sub-data areas at equal time intervals for the convenience of subsequent data processing and analysis, and timestamp management is used to ensure data orderliness and continuity, thereby improving data processing efficiency; a data processing module is used to clean and pre-process the collected raw data, including deduplication, outlier detection and missing value filling, and calculation is performed, thereby improving data accuracy and reliability, and providing a high-quality data source for subsequent in-depth analysis; a data analysis module is used to conduct in-depth analysis of vibration spectrum, current and displacement data, and characteristic values ​​of each sub-data area are extracted through a specific mathematical model. , including vibration spectrum eigenvalues, current eigenvalues ​​and displacement eigenvalues. The modular design enhances the flexibility and scalability of the system. Through the comprehensive analysis module, various data eigenvalues ​​are integrated, and the comprehensive optimization index of the target interlocking device is calculated using the comprehensive analysis model, which fully reflects the performance status of the interlocking device and provides a scientific basis for the overall operation status evaluation. Through the abnormal state analysis module, the calculated comprehensive optimization index is compared with the preset standard model to quickly judge the operation status of the interlocking device, and automatically take corresponding control strategies, including updating standard values ​​or issuing early warning signals to ensure the safe operation of the system. Through the control module, according to the results of the operation status analysis, the control signal is automatically issued to realize the real-time monitoring and effective management of the operation status of the high-voltage distribution cabinet interlocking device. When the equipment is abnormal, an early warning can be quickly issued to notify the management personnel to deal with it in time, reducing potential safety risks.

[0103] Secondly: In the drawings of the embodiments disclosed in the present invention, only the structures related to the embodiments disclosed in the present invention are involved, and other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of the present invention can be combined with each other;

[0104] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. An intelligent integrated electromechanical interlocking system for a high-voltage distribution cabinet, characterized in that: include: Data acquisition module: used to set sensors to collect vibration spectrum data, current data and displacement data of the target interlocking device in real time, store the collected data and the timestamp corresponding to the data in the database, and transmit them to the data area division module; Data area division module: used to determine the data transmitted to the database by the data acquisition module as the target data area, divide the target data area into various sub-data areas by equal time division, mark them as 1, 2...n in sequence, and transmit the data of each sub-data area to the data processing module; Data processing module: used to pre-process the data in each sub-data area of ​​the database and transmit the processed data to the data analysis module; Data analysis module: including vibration spectrum data analysis unit, current data analysis unit and displacement data analysis unit, which analyzes the data pre-processed by the data processing module through the corresponding mathematical model in each analysis unit, and transmits the analysis results to the comprehensive analysis module; Comprehensive analysis module: including a comprehensive analysis model, which is used to conduct a comprehensive analysis on the data of the target interlocking device, import the data transmitted by the data analysis module into the comprehensive analysis model, calculate the comprehensive optimization index of the target interlocking device, and transmit it to the operation status analysis module; The comprehensive analysis model is specifically expressed as: ， η represents the comprehensive optimization index of the target interlocking device, KF i represents the vibration spectrum characteristic value of the ith sub-data area, KM i Indicates the current characteristic value of the i-th sub-data area, KV i represents the displacement characteristic value of the i-th sub-data area; Operation status analysis module: including a standard model building unit, a first comparison unit, a second comparison unit and a third comparison unit, the standard model building unit is used to determine a standard value of a comprehensive optimization index, and compare the standard value of the comprehensive optimization index with the comprehensive optimization index of a target interlocking device, the first comparison unit, the second comparison unit and the third comparison unit are used to determine an operation status of a target interlocking device, and transmit the operation status of the target interlocking device to the control module; The standard model building unit is used to establish a standard model, which is specifically expressed as: ， η sta Indicates the standard value of comprehensive optimization index, KF sta Indicates the standard value of vibration spectrum characteristics, KM sta Indicates the characteristic standard value of current, KV sta representing a displacement characteristic standard value, and comparing the comprehensive optimization index standard value with the comprehensive optimization index of the target interlocking device; The first comparison unit is used to mark the target interlocking device as being in a good state when the comprehensive optimization index standard value is less than the comprehensive optimization index of the target interlocking device; The second comparison unit is used to mark the target interlocking device as a normal state when the comprehensive optimization index standard value is equal to the comprehensive optimization index of the target interlocking device; The third comparison unit is used to mark the target interlocking device as an abnormal state when the comprehensive optimization index standard value is greater than the comprehensive optimization index of the target interlocking device; Control module: includes a first control unit and a second control unit, which are used to send control signals according to the operating status of the target interlocking device.

2. The intelligent integrated electromechanical interlocking system for a high-voltage power distribution cabinet according to claim 1, characterized in that: The vibration spectrum data include high-frequency amplitude, fundamental frequency amplitude, vibration duration, maximum resonance peak, second largest resonance peak, total spectrum energy, energy value of maximum energy frequency point, longitudinal amplitude, lateral amplitude and torsional amplitude, which are marked as Dh, Df, Dt, Pm, Ps, Es, Ev, Lo, La and Lt respectively; the current data include peak current, effective value current, pulse duration, maximum value of harmonic current, fundamental current value, current standard deviation, current average value, eddy current loss, conductor cross-sectional area and magnetic flux density, which are marked as Pc, Pm, Pd, Hm, Hf, Cs, Cm, Ec, Co and Mf respectively; the displacement data include stress, strain, instantaneous creep rate, steady-state creep rate, thermal expansion coefficient, theoretical thermal expansion coefficient, tangential force and normal force, which are marked as σ, ε, Ic, Is, Te, Te the、 Tf and Nf.

3. The intelligent integrated electromechanical interlocking system for a high-voltage power distribution cabinet according to claim 1, characterized in that: The vibration spectrum data processed by the data processing module include harmonic distortion, resonance peak ratio, spectrum entropy and vibration modal coefficient, which are marked as Fd, Fp, Fe and Fl respectively; the current data include current pulse factor, harmonic distortion rate, current fluctuation coefficient and eddy current loss coefficient, which are marked as Mp, Mh, Mc and Me respectively; the displacement data include strain energy density, creep rate ratio, thermal expansion anomaly and micro-friction coefficient, which are marked as Vp, Vc, Vt and Vf respectively.

4. The intelligent integrated electromechanical interlocking system for a high-voltage power distribution cabinet according to claim 1, characterized in that: The vibration spectrum data analysis unit is used to establish a vibration spectrum data analysis model, import the vibration spectrum data transmitted by the data processing module into the vibration spectrum data analysis unit, and calculate the vibration spectrum characteristic value of each sub-data area, which is specifically expressed as: ， KF i represents the vibration spectrum characteristic value of the ith sub-data area, Fd i Indicates the harmonic distortion of the ith sub-data region, Fp i represents the resonance peak ratio of the ith sub-data region, Fe i represents the spectrum entropy of the ith sub-data region, Fl i represents the vibration modal coefficient of the i-th sub-data area, and n represents the number of sub-data areas.

5. The intelligent integrated electromechanical interlocking system for a high-voltage power distribution cabinet according to claim 1, characterized in that: The current data analysis unit is used to establish a current data analysis model, import the current data transmitted by the data processing module into the current data analysis unit, and calculate the current characteristic value of each sub-data area, which is specifically expressed as: ， KM i represents the current characteristic value of the ith sub-data area, Mp i Represents the current pulse factor of the ith sub-data area, Mh i represents the harmonic distortion rate of the ith sub-data region, Mc i represents the current fluctuation coefficient of the ith sub-data area, Me i represents the eddy current loss coefficient of the i-th sub-data area, and n represents the number of sub-data areas.

6. The intelligent integrated electromechanical interlocking system for a high-voltage power distribution cabinet according to claim 1, characterized in that: The displacement data analysis unit is used to establish a displacement data analysis model, import the displacement data transmitted by the data processing module into the displacement data analysis unit, and calculate the displacement characteristic value of each sub-data area, which is specifically expressed as: , KV i represents the displacement characteristic value of the ith sub-data region, Vp i represents the strain energy density of the ith sub-data region, Vc i represents the creep rate ratio of the ith sub-data region, Vt i Indicates the thermal expansion anomaly of the ith sub-data region, Vf i represents the fretting friction coefficient of the i-th sub-data area, and n represents the number of sub-data areas.

7. The intelligent integrated electromechanical interlocking system for a high-voltage power distribution cabinet according to claim 1, characterized in that: The first control unit updates the comprehensive optimization index of the target interlocking device to a new comprehensive optimization index standard value when the target interlocking device is in a good operating state; The second control unit sends a warning signal to the management terminal when the operating state of the target interlocking device is abnormal.

8. An intelligent integrated electromechanical interlocking control method for a high-voltage power distribution cabinet, according to an intelligent integrated electromechanical interlocking system for a high-voltage power distribution cabinet according to any one of claims 1 to 7, characterized in that: The method comprises the following steps: S1: data collection, S2: data area division, S3: data processing, S4: data analysis, S5: comprehensive analysis, S6: operation status analysis and S7: control.

9. According to claim 8, an intelligent integrated electromechanical interlocking control method for a high-voltage distribution cabinet is characterized in that: S6: operating status analysis: including a standard model construction unit, a first comparison unit, a second comparison unit and a third comparison unit, the standard model construction unit is used to determine the standard value of the comprehensive optimization index, and compare the standard value of the comprehensive optimization index with the comprehensive optimization index of the target interlocking device, the first comparison unit, the second comparison unit and the third comparison unit are used to determine the operating status of the target interlocking device, and transmit the operating status of the target interlocking device to S7.

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