Circuit breaker fault diagnosis method and system for switching AC filter of extra-high voltage converter station

Abstract

The invention relates to the technical field of circuit breakers, in particular to a circuit breaker fault diagnosis method and system for switching an alternating current filter in an extra-high voltage converter station, and the method comprises the following steps: S1, synchronously collecting multiple parameters: synchronously collecting vibration acceleration signals, opening and closing coil current waveforms, arc light intensity and environment temperature and humidity parameters; s2, time sequence feature extraction: performing time-frequency domain decomposition on the vibration acceleration signal to obtain a mechanical action time sequence spectrum; s3, operation mode classification: determining the operation mode of the circuit breaker; s4, three-dimensional fault matrix construction: generating a three-dimensional fault matrix including spatial distribution characteristics; s5, dynamic threshold analysis: generating a diagnosis threshold interval dynamically adjusted along with the environmental parameters; and S6, comprehensive diagnosis output: outputting a mechanical jam grade, a contact ablation degree and an insulation deterioration early warning signal. According to the invention, the mechanical, electromagnetic and insulation characteristics of the circuit breaker can be reflected more comprehensively, and reliable guarantee is provided for safe and stable operation of a high-voltage power grid.

Description

Technical Field

[0001] The present invention relates to the technical field of circuit breakers, and in particular to a fault diagnosis method and system for a circuit breaker used for switching an AC filter in a UHV converter station. Background Art

[0002] As the core hub of the DC transmission system, ultra-high voltage converter stations are widely used in long-distance, large-capacity transmission projects. Their AC filters play an important role in suppressing harmonics and improving the power factor. The circuit breakers used to switch the AC filters directly affect the safe and stable operation of the power grid. In high-voltage DC transmission systems, circuit breakers need to frequently switch operating conditions to adapt to load changes and different operating modes. However, due to long-term operation and the influence of complex electromagnetic, mechanical and environmental factors, circuit breakers may experience mechanical jamming, contact erosion and insulation degradation. If these faults cannot be detected and handled in time, they may cause equipment damage and even affect the safe operation of the entire converter station. Therefore, how to accurately and efficiently diagnose circuit breaker faults and provide intelligent early warnings has become a key technical issue in the maintenance of ultra-high voltage transmission systems.

[0003] At present, circuit breaker fault diagnosis mainly relies on single physical quantity monitoring and fixed threshold alarm methods. However, these methods have the following problems: (1) The single signal source is easily affected by noise and it is difficult to fully reflect the true status of the circuit breaker; (2) The fixed threshold is difficult to adapt to different operating modes and environmental changes, and it is easy to cause false alarms or missed alarms under complex working conditions; (3) The traditional method based on manual experience analysis relies on long-term monitoring and maintenance by professionals and cannot achieve real-time intelligent diagnosis. In addition, the existing systems generally lack comprehensive analysis methods for mechanical, electromagnetic and arc characteristics, making it difficult to accurately determine the type and severity of the fault and unable to provide effective predictive maintenance strategies.

[0004] The purpose of the present invention is to provide a method and system for diagnosing faults of circuit breakers used for switching AC filters in ultra-high voltage converter stations, to provide technical support for predictive maintenance of circuit breakers and to improve the safety and reliability of power systems. Summary of the Invention

[0005] The present invention provides a method and system for diagnosing faults of circuit breakers used for switching AC filters in ultra-high voltage converter stations.

[0006] A method for diagnosing a fault of a circuit breaker used for switching an AC filter in a UHV converter station comprises the following steps: S1, multi-parameter synchronous acquisition: During the circuit breaker operation, synchronously collect vibration acceleration signals, opening and closing coil current waveforms, arc intensity, and ambient temperature and humidity parameters; S2, time series feature extraction: Decompose the vibration acceleration signal in the time-frequency domain to obtain the mechanical action time series spectrum, perform differential processing on the opening and closing coil current waveform to obtain the electromagnetic characteristic curve, and perform spectrum decomposition on the arc intensity to obtain the arc feature vector; S3, operation mode classification: matching the current operation instruction parameters with the historical operating condition database to determine the operation mode of the circuit breaker, including cold standby switching mode, emergency compensation mode or planned maintenance mode; S4, three-dimensional fault matrix construction: align the mechanical action timing spectrum, electromagnetic characteristic curve, and arc characteristic vector along the time axis to generate a three-dimensional fault matrix including spatial distribution characteristics; S5, dynamic threshold analysis: Based on the results of the operating mode classification, the benchmark parameter library under the corresponding working conditions is called to generate a diagnostic threshold interval that is dynamically adjusted according to the environmental parameters; S6, comprehensive diagnostic output: Perform comprehensive diagnosis on the three-dimensional fault matrix and dynamic diagnostic threshold range, and output warning signals of mechanical jam level, contact ablation degree and insulation degradation.

[0007] Optionally, the multi-parameter synchronous acquisition in S1 includes: S11, sensor layout optimization: install a triaxial vibration acceleration sensor at the point of maximum normal vibration of the circuit breaker operating mechanism box, install a Hall current sensor on the power supply side of the opening and closing coil, place a UV-enhanced arc sensor in the observation window of the arc extinguishing chamber, and deploy a temperature and humidity composite probe in the circuit breaker operating mechanism box; S12, synchronous trigger setting: take the rising edge of the opening and closing coil current as the main trigger signal, when the current change rate meets the When all sensor acquisition channels are started synchronously, is the closing and opening coil current, For time; S13, anti-interference acquisition: using optical isolation technology to transmit vibration signals (sampling frequency ), apply 10kHz low-pass filtering to the current signal and perform 50ns pulse shaping on the arc light signal; S14, time alignment processing: add a synchronization time stamp with an accuracy of ±1μs to each channel data, and use an interpolation algorithm to align signal sequences with different sampling rates; S15, abnormal acquisition detection: calculate the signal-to-noise ratio (SNR) of each signal channel in real time. When any channel SNR meets When the acquisition interrupt is triggered and the backup sensor is started, and are the power of signal and noise respectively; S16, data preprocessing: perform 5kHz high-pass filtering on the vibration acceleration signal to eliminate mechanical resonance interference, perform baseline correction on the current waveform, and implement dark current compensation on the arc intensity; S17, structured storage: encapsulate the pre-processed vibration acceleration, current waveform, and arc intensity into data packets according to the operation cycle, including the triple index tags of operation timestamp, environmental parameters, and device number.

[0008] Optionally, the temporal feature extraction in S2 includes: S21, Mechanical action time spectrum extraction: vibration acceleration signal Short-time Fourier transform (STFT) is used to perform time-frequency domain decomposition to obtain the mechanical motion time series spectrum. ; S22, electromagnetic characteristic curve extraction: current waveform of the opening and closing coils Perform first-order differential processing to extract the current change rate curve and use it to identify electromagnetic characteristics; S23, Arc feature vector extraction: Arc intensity signal Perform fast Fourier transform (FFT) to decompose the spectrum and extract the main frequency characteristics and energy distribution.

[0009] Optionally, the operating mode classification in S3 includes: S31, operation instruction parameter extraction: obtain the operation instruction parameter set of the current circuit breaker ; S32, Historical operating condition database retrieval: Build a historical operating condition database , which includes Group operation mode data, each group of operation mode data is expressed as: ; in, For the Group history operation command parameters, The corresponding operation mode labels include cold standby switching mode (CB), emergency compensation mode (EC), and planned maintenance mode (PM); S33, pattern matching and similarity calculation: calculate the current operation instruction parameter set The Euclidean distance of each set of operating mode data in the historical database is used, and the nearest neighbor matching principle is adopted to select the historical mode corresponding to the minimum matching distance as the operating mode of the current circuit breaker.

[0010] Optionally, the three-dimensional fault matrix construction in S4 is uncontrollable: S41, characteristic data normalization processing: normalizing the mechanical action time series spectrum, electromagnetic characteristic curve and arc characteristic vector respectively; S42, time axis alignment: Assume that the sampling time series of vibration acceleration signal, current waveform, and arc intensity are 、 、 ,interpolation algorithm is used for time alignment; S43, three-dimensional matrix construction: map the time-aligned mechanical action timing spectrum, electromagnetic characteristic curve and arc characteristic vector to three-dimensional space to construct a three-dimensional fault matrix ; S44, spatial feature extraction: Based on the constructed three-dimensional fault matrix, principal component analysis (PCA) is used to extract fault features and calculate the principal component matrix .

[0011] Optionally, the dynamic threshold analysis in S5 includes: S51, benchmark parameter matching and environment correction: according to the determined operation mode, call the benchmark parameter library of the corresponding mode , obtain the normal operating thresholds of mechanical, electromagnetic and arc characteristics, and dynamically correct the benchmark parameters in combination with environmental parameters; S52, adaptive threshold interval generation: based on the corrected reference parameters, calculate the dynamic threshold interval.

[0012] Optionally, the benchmark parameter matching and environment correction in S51 include: S511, operation mode benchmark parameter call: According to the result of operation mode classification, the current operation mode of the circuit breaker is determined and the reference parameter library is used to call the reference parameter library. Call the normal operation threshold set of the corresponding operation mode; S512, environmental parameter correction: combined with the current environmental temperature and humidity parameters The benchmark parameters are dynamically modified to adapt them to different environmental conditions.

[0013] Optionally, the generating of the adaptive threshold interval in S52 includes: S521, calculate the statistical deviation of the revised benchmark parameters: after the benchmark parameter library has been environmentally corrected, calculate the mean of the revised benchmark parameters and the statistical deviation of historical data ; S522, generating a dynamic threshold interval: based on statistical deviation , determine the dynamic threshold interval , the confidence interval method is used to set the upper and lower limits.

[0014] Optionally, the comprehensive diagnostic output in S6 includes: S61, fault feature deviation calculation: the three-dimensional fault matrix Real-time monitoring data and dynamic threshold intervals Compare and calculate the deviation matrix of fault characteristics ; S62, Fault level classification and diagnostic output: Determine different types of fault levels based on the calculation results of the fault characteristic deviation and output diagnostic results, specifically including: Mechanical jam level: Deviation matrix based on fault characteristics , calculate the mechanical status level, including normal, mild jam, moderate jam, and severe jam; Contact erosion degree calculation: deviation matrix based on fault characteristics , calculate the degree of contact ablation, including normal, mild ablation, moderate ablation, and severe ablation; Insulation degradation warning signal calculation: deviation matrix based on fault characteristics , calculate insulation degradation warning signals, including no warning, warning level 1, and warning level 2.

[0015] The UHV converter station AC filter switching circuit breaker fault diagnosis system is used to implement the above-mentioned UHV converter station AC filter switching circuit breaker fault diagnosis method, including the following modules: Data acquisition module: synchronously collects vibration acceleration signals, opening and closing coil current waveforms, arc intensity, and ambient temperature and humidity parameters during circuit breaker operation; Feature extraction module: Decompose the vibration acceleration signal in the time-frequency domain to obtain the mechanical action time series spectrum, perform differential processing on the opening and closing coil current waveform to obtain the electromagnetic characteristic curve, and perform spectrum decomposition on the arc intensity to obtain the arc characteristic vector; Operation mode classification module: matches the current operation instruction parameters with the historical operating condition database to determine the operation mode of the circuit breaker, including cold standby switching mode, emergency compensation mode or planned maintenance mode; 3D fault matrix construction module: aligns the mechanical action timing spectrum, electromagnetic characteristic curve, and arc characteristic vector along the time axis to generate a 3D fault matrix including spatial distribution characteristics; Dynamic threshold analysis module: Based on the results of the operating mode classification, the benchmark parameter library under the corresponding working conditions is called to generate a diagnostic threshold range that is dynamically adjusted according to the environmental parameters; Comprehensive diagnosis output module: performs comprehensive diagnosis on the three-dimensional fault matrix and dynamic diagnosis threshold range, and outputs warning signals of mechanical jam level, contact ablation degree and insulation degradation.

[0016] Beneficial effects of the present invention: The present invention realizes comprehensive monitoring of the circuit breaker operating status and intelligent fault diagnosis through multi-parameter synchronous acquisition, time series feature extraction, operation mode classification, three-dimensional fault matrix construction, dynamic threshold analysis and comprehensive diagnostic output. The method integrates the multi-physical quantity characteristics of vibration, electromagnetic and arc, and accurately extracts key feature information during the circuit breaker operation process through short-time Fourier transform, differential operation and fast Fourier transform. It can more comprehensively reflect the mechanical, electromagnetic and insulation characteristics of the circuit breaker, providing reliable protection for the safe and stable operation of the high-voltage power grid.

[0017] The present invention establishes an intelligent fault identification mechanism that adapts to different operating environments through operating mode classification and dynamic threshold analysis based on historical data. By matching current operating instructions with historical operating conditions through Euclidean distance calculation, it can accurately distinguish between cold standby switching mode, emergency compensation mode and planned maintenance mode. In combination with factors such as ambient temperature and humidity, load fluctuations, etc., the benchmark parameters are dynamically corrected, and an adaptive threshold interval is adopted to enable the system to maintain high sensitivity and low false alarm rate under different operating conditions. This overcomes the limitations of traditional fixed threshold methods under complex environmental conditions and improves the adaptability and accuracy of fault diagnosis. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0019] Figure 1 This is a flow chart of a diagnostic method according to an embodiment of the present invention; Figure 2 Schematic diagram of system function modules according to an embodiment of the present invention. DETAILED DESCRIPTION

[0020] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments. It is also noted that, to provide a more detailed description, the following embodiments are best and preferred embodiments, and those skilled in the art may employ alternative methods for implementing certain known technologies. Furthermore, the accompanying drawings are intended only to provide a more detailed description of the embodiments and are not intended to limit the present invention.

[0021] It should be noted that references in the specification to "one embodiment," "an embodiment," "exemplary embodiments," "some embodiments," etc. indicate that the described embodiments may include specific features, structures, or characteristics, but not necessarily every embodiment will include such specific features, structures, or characteristics. Furthermore, when specific features, structures, or characteristics are described in conjunction with an embodiment, it is within the knowledge of persons skilled in the relevant art to implement such features, structures, or characteristics in conjunction with other embodiments (whether or not explicitly described).

[0022] In general, terms can be understood, at least in part, from their use in context. For example, depending at least in part on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in the singular sense, or can be used to describe a combination of features, structures, or characteristics in the plural sense. Additionally, the term "based on" can be understood as not necessarily intended to convey an exclusive set of factors, but can instead, depending at least in part on the context, allow for the presence of other factors that are not necessarily explicitly described.

[0023] like Figure 1 As shown, a method for diagnosing a fault of a circuit breaker for switching an AC filter in a UHV converter station includes the following steps: S1, multi-parameter synchronous acquisition: During the circuit breaker operation, synchronously collect vibration acceleration signals, opening and closing coil current waveforms, arc intensity, and ambient temperature and humidity parameters; S2, time series feature extraction: Decompose the vibration acceleration signal in the time-frequency domain to obtain the mechanical action time series spectrum, perform differential processing on the opening and closing coil current waveform to obtain the electromagnetic characteristic curve, and perform spectrum decomposition on the arc intensity to obtain the arc feature vector; S3, operation mode classification: matching the current operation instruction parameters with the historical operating condition database to determine the operation mode of the circuit breaker, including cold standby switching mode, emergency compensation mode or planned maintenance mode; S4, three-dimensional fault matrix construction: align the mechanical action timing spectrum, electromagnetic characteristic curve, and arc characteristic vector along the time axis to generate a three-dimensional fault matrix including spatial distribution characteristics; S5, dynamic threshold analysis: Based on the results of the operating mode classification, the benchmark parameter library under the corresponding working conditions is called to generate a diagnostic threshold interval that is dynamically adjusted according to the environmental parameters; S6, comprehensive diagnostic output: Perform comprehensive diagnosis on the three-dimensional fault matrix and dynamic diagnostic threshold range, and output warning signals of mechanical jam level, contact ablation degree and insulation degradation.

[0024] Multi-parameter simultaneous acquisition in S1 includes: S11, sensor layout optimization: install a triaxial vibration acceleration sensor at the point of maximum normal vibration of the circuit breaker operating mechanism box, install a Hall current sensor on the power supply side of the opening and closing coil, place a UV-enhanced arc sensor in the observation window of the arc extinguishing chamber, and deploy a temperature and humidity composite probe in the circuit breaker operating mechanism box; S12, synchronous trigger setting: take the rising edge of the opening and closing coil current as the main trigger signal, when the current change rate meets the When all sensor acquisition channels are started synchronously, is the closing and opening coil current, For time; S13, anti-interference acquisition: using optical isolation technology to transmit vibration signals (sampling frequency ), apply 10kHz low-pass filtering to the current signal and perform 50ns pulse shaping on the arc light signal; S14, time alignment processing: add a synchronization time stamp with an accuracy of ±1μs to each channel data, and use an interpolation algorithm to align signal sequences with different sampling rates; S15, abnormal acquisition detection: calculate the signal-to-noise ratio (SNR) of each signal channel in real time. When any channel SNR meets When the acquisition interrupt is triggered and the backup sensor is started, and are the power of signal and noise respectively; S16, data preprocessing: perform 5kHz high-pass filtering on the vibration acceleration signal to eliminate mechanical resonance interference, perform baseline correction on the current waveform, and implement dark current compensation on the arc intensity; S17, structured storage: encapsulate the pre-processed vibration acceleration, current waveform, and arc intensity into data packets according to the operation cycle, including the triple index tags of operation timestamp, environmental parameters, and device number.

[0025] Temporal feature extraction in S2 includes: S21, Mechanical action time spectrum extraction: vibration acceleration signal Short-time Fourier transform (STFT) is used to perform time-frequency domain decomposition to obtain the mechanical motion time series spectrum. , expressed as: ; in, is the mechanical action timing spectrum, indicating that The spectral components at is the vibration acceleration signal, is a sliding window function, which is used to ensure the extraction of local time-frequency features. is the frequency component, is the time variable; S22, electromagnetic characteristic curve extraction: current waveform of opening and closing coils Perform first-order differential processing to extract the current change rate curve, which is used to identify electromagnetic characteristics and is expressed as: ; in, is the current signal of the opening and closing coil, is the current change rate curve, is the sampling time interval; S23, Arc feature vector extraction: Arc intensity signal Perform fast Fourier transform (FFT) to decompose the spectrum and extract the main frequency characteristics and energy distribution, which can be expressed as: ; in, is the arc characteristic signal in the frequency domain, is the arc intensity signal in the time domain, is the frequency component; Through the above content, the mechanical, electromagnetic and arc state characteristics of the circuit breaker during operation can be fully captured to ensure high precision and high robustness of fault diagnosis. By extracting mechanical action laws through time-frequency domain decomposition, analyzing electromagnetic dynamic responses through differential operations, and identifying arc characteristics through spectrum decomposition, normal operation and abnormal operating conditions can be effectively distinguished, thereby improving the reliability of circuit breaker status monitoring and fault warning, and providing data support for precise maintenance and intelligent diagnosis.

[0026] The operating mode categories in S3 include: S31, operation instruction parameter extraction: obtain the operation instruction parameter set of the current circuit breaker , expressed as: ; in, is the operation timestamp, To control the command voltage (open / close signal), is the characteristic value of the opening and closing coil current, is the arc energy level, is the ambient temperature and humidity parameters; S32, Historical operating condition database retrieval: Build a historical operating condition database , which includes Group operation mode data, each group of operation mode data is expressed as: ; in, For the Group history operation command parameters, The corresponding operation mode labels include cold standby switching mode (CB), emergency compensation mode (EC), and planned maintenance mode (PM); S33, pattern matching and similarity calculation: calculate the current operation instruction parameter set The Euclidean distance of each set of operating mode data in the historical database is used, and the nearest neighbor matching principle is adopted to select the historical mode corresponding to the minimum matching distance as the operating mode of the current circuit breaker, which is expressed as: ; in, The current operation instruction and The matching distance of the group historical data, The first parameter in the current parameter values, For the historical data parameter values, is the parameter weight coefficient, is the number of parameter dimensions; ; ; in, The current circuit breaker operation mode; Through the above content, accurate identification of the current operating status of the circuit breaker is achieved. Comprehensive analysis using multi-parameter characteristics makes pattern recognition more adaptable and robust. Through the weighted optimization similarity calculation method, the most matching historical operating conditions can be quickly screened out, thereby accurately distinguishing between cold standby switching, emergency compensation and planned maintenance modes.

[0027] The three-dimensional fault matrix construction in S4 is uncontrollable: S41, characteristic data normalization processing: normalize the mechanical action time series spectrum, electromagnetic characteristic curve and arc characteristic vector respectively to eliminate the dimensional influence of different physical quantities, expressed as: ; in, is the normalized data, is the original feature data, 、 are the minimum and maximum values ​​of the feature data respectively; S42, time axis alignment: Assume that the sampling time series of vibration acceleration signal, current waveform, and arc intensity are 、 、 ,To ensure that data with different sampling rates are analyzed under the same time base, an interpolation algorithm is used for time alignment, which is expressed as: ; in, is the time-aligned data, and are adjacent sampled data points, Align time points for goals, meet ; S43, three-dimensional matrix construction: map the time-aligned mechanical action timing spectrum, electromagnetic characteristic curve and arc characteristic vector to three-dimensional space to construct a three-dimensional fault matrix , expressed as: ; in, are the elements of the three-dimensional fault matrix, For the Moment, Mechanical action time series spectrum data of frequency components, For the Electromagnetic characteristic curve data at the moment, For the The arc feature vector data at time , Dimensions represent the spatial distribution information of data, that is, the distribution of data under different operating modes or different load conditions; S44, spatial feature extraction: Based on the constructed three-dimensional fault matrix, principal component analysis (PCA) is used to extract fault features and calculate the principal component matrix , expressed as: ; in, is the feature matrix after dimensionality reduction, is the eigenvector matrix calculated by PCA; Through the above, a three-dimensional analysis of the circuit breaker's operating status is achieved. Data standardization and time alignment technologies ensure the synchronization of different signal sources and improve feature matching accuracy. The matrix-based construction method not only preserves the spatiotemporal relationships between various physical quantities but also extracts core fault features through methods such as principal component analysis (PCA), improving diagnostic accuracy and stability.

[0028] Dynamic threshold analysis in S5 includes: S51, benchmark parameter matching and environment correction: according to the determined operation mode, call the benchmark parameter library of the corresponding mode , obtain the normal operating thresholds of mechanical, electromagnetic and arc characteristics, and dynamically correct the benchmark parameters in combination with environmental parameters; S52, adaptive threshold interval generation: calculating the dynamic threshold interval based on the corrected reference parameter; This allows for dynamic adaptation to varying operating conditions, avoiding the false alarms and missed alarms associated with fixed thresholds. Using an environmental correction model, the system optimizes diagnostic criteria in real time, improving the accuracy of anomaly detection. Furthermore, deviation calculations based on historical data ensure that threshold intervals are both sensitive and tolerant of reasonable fluctuations, thereby enhancing the reliability and stability of circuit breaker status monitoring.

[0029] The benchmark parameter matching and environmental correction in S51 include: S511, operation mode benchmark parameter call: According to the result of operation mode classification, the current operation mode of the circuit breaker is determined and the reference parameter library is used to call the reference parameter library. Call the normal operation threshold set of the corresponding operation mode, expressed as: ; in, is the mechanical action characteristic threshold (vibration acceleration peak value, timing characteristics), is the electromagnetic characteristic threshold (coil current mutation rate, electromagnetic attraction time), is the arc characteristic threshold (arc energy, arcing time); Mechanical action feature threshold , electromagnetic property threshold 、 The arc characteristic threshold is set using historical data statistics and is expressed as: ; in, is the mean value of the mechanical characteristics in the historical operation data, is the standard deviation, which indicates the fluctuation range of the mechanical vibration signal. is the confidence interval adjustment coefficient (taken as 1.96, indicating confidence interval); ; in, is the historical average of the coil current change rate or the pull-in time, is the standard deviation, which indicates the fluctuation range of electromagnetic characteristics. is the confidence interval adjustment coefficient; ; in, is the mean value of historical arc characteristics, is the standard deviation, is the confidence interval adjustment coefficient; S512, environmental parameter correction: combined with the current environmental temperature and humidity parameters The benchmark parameters are dynamically modified to adapt to different environmental conditions, which can be expressed as: ; in, is the corrected benchmark parameter, is the environmental impact coefficient.

[0030] The adaptive threshold interval generation in S52 includes: S521, calculate the statistical deviation of the revised benchmark parameters: after the benchmark parameter library has been environmentally corrected, calculate the mean of the revised benchmark parameters and the statistical deviation of historical data , expressed as: ; in, is the standard deviation of the corrected benchmark parameter, For the The corrected baseline parameter value of the group, is the mean of the corrected benchmark parameters, is the number of historical sample data; S522, generating a dynamic threshold interval: based on statistical deviation , determine the dynamic threshold interval , the confidence interval method is used to set the upper and lower limits, which can be expressed as: ; in, The dynamic threshold interval is finally calculated. When the real-time monitoring value exceeds When the system triggers an abnormal alarm, 、 are dynamic adjustment coefficients respectively.

[0031] Comprehensive diagnostic outputs in the S6 include: S61, fault feature deviation calculation: the three-dimensional fault matrix Real-time monitoring data and dynamic threshold intervals Compare and calculate the deviation matrix of fault characteristics , expressed as: ; in, is the normalized fault feature deviation matrix, is the fault feature matrix for real-time monitoring, is the baseline parameter after environmental correction, is the standard deviation of the benchmark parameter; S62, Fault level classification and diagnostic output: Determine different types of fault levels based on the calculation results of the fault characteristic deviation and output diagnostic results, specifically including: Mechanical jam level: Deviation matrix based on fault characteristics , calculate the mechanical status level, including normal, mild jam, moderate jam, and severe jam, expressed as: ; in, It is the mechanical jam level. is the mild fault threshold, set to 1.0, is the moderate fault threshold, set to 2.0, is the critical failure threshold, set to 3.0, The degree of deviation of mechanical action characteristics (such as vibration peak value, operation time); Contact erosion degree calculation: deviation matrix based on fault characteristics , calculate the contact ablation degree, including normal, mild ablation, moderate ablation, and severe ablation, expressed as: ; in, is the degree of contact ablation, is the mild ablation threshold, set to 0.8, is the moderate ablation threshold, set to 1.8, is the severe ablation threshold, set to 2.5, The deviation degree of contact current characteristics (current mutation rate, electromagnetic attraction time); Insulation degradation warning signal calculation: deviation matrix based on fault characteristics , calculate the insulation degradation warning signal, including no warning, warning level 1, and warning level 2, expressed as: ; in, It is an early warning signal for insulation degradation. is the deviation between arc energy and arcing time, is the moderate warning threshold, set to 1.5, is the severe warning threshold, set to 2.5; Through the above content, an accurate assessment of the operating status of the circuit breaker is achieved. By using standardized fault deviation calculations, the degree of abnormality of mechanical, electromagnetic and arc characteristics is effectively quantified, and mild, moderate and severe fault levels are set, making the diagnosis more scientific and robust. It can dynamically adapt to different working conditions and environmental changes, reduce false alarms and missed alarms, and improve the accuracy and real-time performance of diagnosis.

[0032] like Figure 2 As shown, the UHV converter station switching AC filter circuit breaker fault diagnosis system is used to implement the above-mentioned UHV converter station switching AC filter circuit breaker fault diagnosis method, including the following modules: Data acquisition module: synchronously collects vibration acceleration signals, opening and closing coil current waveforms, arc intensity, and ambient temperature and humidity parameters during circuit breaker operation; Feature extraction module: Decompose the vibration acceleration signal in the time-frequency domain to obtain the mechanical action time series spectrum, perform differential processing on the opening and closing coil current waveform to obtain the electromagnetic characteristic curve, and perform spectrum decomposition on the arc intensity to obtain the arc characteristic vector; Operation mode classification module: matches the current operation instruction parameters with the historical operating condition database to determine the operation mode of the circuit breaker, including cold standby switching mode, emergency compensation mode or planned maintenance mode; 3D fault matrix construction module: aligns the mechanical action timing spectrum, electromagnetic characteristic curve, and arc characteristic vector along the time axis to generate a 3D fault matrix including spatial distribution characteristics; Dynamic threshold analysis module: Based on the results of the operating mode classification, the benchmark parameter library under the corresponding working conditions is called to generate a diagnostic threshold range that is dynamically adjusted according to the environmental parameters; Comprehensive diagnosis output module: performs comprehensive diagnosis on the three-dimensional fault matrix and dynamic diagnosis threshold range, and outputs warning signals of mechanical jam level, contact ablation degree and insulation degradation.

[0033] The present invention encompasses any alternatives, modifications, equivalents, and solutions that fall within the spirit and scope of the present invention. To provide a thorough understanding of the present invention, specific details are described in detail below in connection with the preferred embodiments of the present invention, but those skilled in the art will be able to fully understand the present invention without these detailed descriptions. Furthermore, to avoid unnecessary confusion regarding the essence of the present invention, well-known methods, processes, procedures, components, and circuits have not been described in detail.

[0034] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A fault diagnosis method for a circuit breaker used for switching AC filters in a UHV converter station, characterized in that: The following steps are involved: S1, multi-parameter synchronous acquisition: During the circuit breaker operation, synchronously collect vibration acceleration signals, opening and closing coil current waveforms, arc intensity, and ambient temperature and humidity parameters; S2, time series feature extraction: Decompose the vibration acceleration signal in the time-frequency domain to obtain the mechanical action time series spectrum, perform differential processing on the opening and closing coil current waveform to obtain the electromagnetic characteristic curve, and perform spectrum decomposition on the arc intensity to obtain the arc feature vector; S3, operation mode classification: matching the current operation instruction parameters with the historical operating condition database to determine the operation mode of the circuit breaker, including cold standby switching mode, emergency compensation mode or planned maintenance mode; S4, three-dimensional fault matrix construction: align the mechanical action timing spectrum, electromagnetic characteristic curve, and arc characteristic vector along the time axis to generate a three-dimensional fault matrix including spatial distribution characteristics; S5, dynamic threshold analysis: Based on the results of the operating mode classification, the benchmark parameter library under the corresponding working conditions is called to generate a diagnostic threshold interval that is dynamically adjusted according to the environmental parameters; S6, comprehensive diagnostic output: Perform comprehensive diagnosis on the three-dimensional fault matrix and dynamic diagnostic threshold range, and output warning signals of mechanical jam level, contact ablation degree and insulation degradation.

2. The method for diagnosing faults of a circuit breaker for switching AC filters in a UHV converter station according to claim 1, characterized in that: The multi-parameter synchronous acquisition in S1 includes: S11, sensor layout optimization: install a triaxial vibration acceleration sensor at the point of maximum normal vibration of the circuit breaker operating mechanism box, install a Hall current sensor on the power supply side of the opening and closing coil, place a UV-enhanced arc sensor in the observation window of the arc extinguishing chamber, and deploy a temperature and humidity composite probe in the circuit breaker operating mechanism box; S12, synchronous trigger setting: take the rising edge of the opening and closing coil current as the main trigger signal, when the current change rate meets the When all sensor acquisition channels are started synchronously, is the closing and opening coil current, For time; S13, anti-interference acquisition: uses optical isolation technology to transmit vibration signals, applies 10kHz low-pass filtering to current signals, and performs 50ns pulse shaping on arc light signals; S14, time alignment processing: add a synchronization time stamp with an accuracy of ±1μs to each channel data, and use an interpolation algorithm to align signal sequences with different sampling rates; S15, abnormal acquisition detection: calculate the signal-to-noise ratio of each signal channel in real time, when any channel SNR meets When the acquisition interrupt is triggered and the backup sensor is started, and are the power of signal and noise respectively; S16, data preprocessing: perform 5kHz high-pass filtering on the vibration acceleration signal to eliminate mechanical resonance interference, perform baseline correction on the current waveform, and implement dark current compensation on the arc intensity; S17, structured storage: encapsulate the pre-processed vibration acceleration, current waveform, and arc intensity into data packets according to the operation cycle, including the triple index tags of operation timestamp, environmental parameters, and device number.

3. The method for diagnosing faults of a circuit breaker for switching AC filters in a UHV converter station according to claim 1, characterized in that: The temporal feature extraction in S2 includes: S21, Mechanical action time spectrum extraction: vibration acceleration signal Short-time Fourier transform is used to perform time-frequency domain decomposition to obtain the mechanical motion time series spectrum ; S22, electromagnetic characteristic curve extraction: current waveform of opening and closing coils Perform first-order differential processing to extract the current change rate curve and use it to identify electromagnetic characteristics; S23, Arc feature vector extraction: Arc intensity signal Perform fast Fourier transform to decompose the spectrum and extract the main frequency characteristics and energy distribution.

4. The method for diagnosing faults of a circuit breaker for switching AC filters in a UHV converter station according to claim 1, characterized in that: The operating mode classification in S3 includes: S31, operation instruction parameter extraction: obtain the operation instruction parameter set of the current circuit breaker ; S32, Historical operating condition database retrieval: Build a historical operating condition database , which includes Group operation mode data, each group of operation mode data is expressed as: ； in, For the Group history operation command parameters, The corresponding operation mode labels include cold standby switching mode, emergency compensation mode and planned maintenance mode; S33, pattern matching and similarity calculation: calculate the current operation instruction parameter set The Euclidean distance of each set of operating mode data in the historical database is used, and the nearest neighbor matching principle is adopted to select the historical mode corresponding to the minimum matching distance as the operating mode of the current circuit breaker.

5. The method for diagnosing faults of a circuit breaker for switching AC filters in a UHV converter station according to claim 4, characterized in that: The three-dimensional fault matrix in S4 is constructed to be uncontrollable: S41, characteristic data normalization processing: normalizing the mechanical action time series spectrum, electromagnetic characteristic curve and arc characteristic vector respectively; S42, time axis alignment: Assume that the sampling time series of vibration acceleration signal, current waveform, and arc intensity are 、 、 ,interpolation algorithm is used for time alignment; S43, three-dimensional matrix construction: map the time-aligned mechanical action timing spectrum, electromagnetic characteristic curve and arc characteristic vector to three-dimensional space to construct a three-dimensional fault matrix ; S44, spatial feature extraction: Based on the constructed three-dimensional fault matrix, principal component analysis is used to extract fault features and calculate the principal component matrix .

6. The method for diagnosing faults of a circuit breaker for switching AC filters in a UHV converter station according to claim 5, characterized in that: The dynamic threshold analysis in S5 includes: S51, benchmark parameter matching and environment correction: according to the determined operation mode, call the benchmark parameter library of the corresponding mode , obtain the normal operating thresholds of mechanical, electromagnetic and arc characteristics, and dynamically correct the benchmark parameters in combination with environmental parameters; S52, adaptive threshold interval generation: based on the corrected reference parameters, calculate the dynamic threshold interval.

7. The method for diagnosing faults of a circuit breaker for switching AC filters in a UHV converter station according to claim 6, characterized in that: The benchmark parameter matching and environment correction in S51 include: S511, operation mode benchmark parameter call: According to the result of operation mode classification, the current operation mode of the circuit breaker is determined and the reference parameter library is used to call the reference parameter library. Call the normal operation threshold set of the corresponding operation mode; S512, environmental parameter correction: combined with the current environmental temperature and humidity parameters The benchmark parameters are dynamically modified to adapt them to different environmental conditions.

8. The method for diagnosing faults of a circuit breaker for switching AC filters in a UHV converter station according to claim 7, characterized in that: The adaptive threshold interval generation in S52 includes: S521, calculate the statistical deviation of the revised benchmark parameters: after the benchmark parameter library has been environmentally corrected, calculate the mean of the revised benchmark parameters and the statistical deviation of historical data ; S522, generating a dynamic threshold interval: based on statistical deviation , determine the dynamic threshold interval , the confidence interval method is used to set the upper and lower limits.

9. The method for diagnosing faults of a circuit breaker for switching AC filters in a UHV converter station according to claim 8, characterized in that: The comprehensive diagnostic outputs of the S6 include: S61, fault feature deviation calculation: the three-dimensional fault matrix Real-time monitoring data and dynamic threshold intervals Compare and calculate the deviation matrix of fault characteristics ; S62, Fault level classification and diagnostic output: Determine different types of fault levels based on the calculation results of the fault characteristic deviation and output diagnostic results, specifically including: Mechanical jam level: Deviation matrix based on fault characteristics , calculate the mechanical status level, including normal, mild jam, moderate jam, and severe jam; Contact erosion degree calculation: deviation matrix based on fault characteristics , calculate the degree of contact ablation, including normal, mild ablation, moderate ablation, and severe ablation; Insulation degradation warning signal calculation: deviation matrix based on fault characteristics , calculate insulation degradation warning signals, including no warning, warning level 1, and warning level 2.

10. A fault diagnosis system for a circuit breaker used for switching an AC filter in a UHV converter station, configured to implement a fault diagnosis method for a circuit breaker used for switching an AC filter in a UHV converter station according to any one of claims 1 to 9, characterized in that: Includes the following modules: Data acquisition module: synchronously collects vibration acceleration signals, opening and closing coil current waveforms, arc intensity, and ambient temperature and humidity parameters during circuit breaker operation; Feature extraction module: Decompose the vibration acceleration signal in the time-frequency domain to obtain the mechanical action time series spectrum, perform differential processing on the opening and closing coil current waveform to obtain the electromagnetic characteristic curve, and perform spectrum decomposition on the arc intensity to obtain the arc characteristic vector; Operation mode classification module: matches the current operation instruction parameters with the historical operating condition database to determine the operation mode of the circuit breaker, including cold standby switching mode, emergency compensation mode or planned maintenance mode; 3D fault matrix construction module: aligns the mechanical action timing spectrum, electromagnetic characteristic curve, and arc characteristic vector along the time axis to generate a 3D fault matrix including spatial distribution characteristics; Dynamic threshold analysis module: Based on the results of the operating mode classification, the benchmark parameter library under the corresponding working conditions is called to generate a diagnostic threshold range that is dynamically adjusted according to the environmental parameters; Comprehensive diagnosis output module: performs comprehensive diagnosis on the three-dimensional fault matrix and dynamic diagnosis threshold range, and outputs warning signals of mechanical jam level, contact ablation degree and insulation degradation.

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