Intelligent monitoring method and system for vacuum circuit breaker

Abstract

The present invention relates to the technical field of switch device monitoring, and discloses an intelligent monitoring method and system for vacuum circuit breakers. The method comprises: synchronously collecting the vibration signal of the operating mechanism and the arc current signal of the arc extinguishing chamber during opening and closing; extracting the energy proportion of the natural frequency band of the opening spring as a mechanical degradation factor through wavelet packet decomposition; extracting the arc fluctuation factor based on the time domain integration of the first-order derivative of the current; inputting the two factors into a multi-physics field correlation model, and outputting the coupling vector of the contact wear depth and the resistance torque of the transmission mechanism. The method uses the rising edge of the opening coil current to trigger the timestamp alignment mechanism of the dual-channel acquisition card to achieve synchronization of the vibration signal and the current signal. The system includes corresponding functional modules and early warning mechanisms. The present invention solves the problem of time domain separation of mechanical / electrical signals and significantly improves the state monitoring accuracy of vacuum circuit breakers.

Description

Technical Field

[0001] The present invention relates to the technical field of switchgear monitoring, and in particular to an intelligent monitoring method and system for a vacuum circuit breaker. Background Art

[0002] As the core switching device of the power system, the coordination between the mechanical mechanism and the arc extinguishing chamber of the vacuum circuit breaker directly affects the reliability of opening and closing. Existing online monitoring technologies usually independently collect and analyze mechanical vibration signals and arc current signals in a time-sharing manner. However, due to the isolation of the two signal acquisition channels and the asynchronous triggering sources, such as the mechanical signal's reliance on the vibration threshold for triggering and the current signal's reliance on the overcurrent threshold for triggering, the mechanical action moment and the electrical event moment cannot be accurately aligned in the time domain. This signal time domain fragmentation phenomenon has two serious consequences: first, the interception deviation of the arcing period is significant, which distorts the arc stability analysis; second, the mechanical vibration characteristics and arc current characteristics cannot be physically associated due to the inconsistent time base, forcing the status assessment to be limited to a single dimension of mechanical or electrical.

[0003] Traditional methods often use post-processing signal alignment algorithms to compensate for time-domain deviations. However, such methods rely on the assumption of signal waveform similarity and have low reliability in the high-noise environment of circuit breakers. More importantly, the high-frequency components of the mechanical vibration signal and the ultra-high-frequency transient components of the arc current have completely different time-frequency characteristics, making it difficult to achieve microsecond-level synchronization accuracy through post-processing alignment. This leads to inherent flaws in the input data of the multi-physics field coupling model. The calculation of the mechanical degradation factor and the arc fluctuation factor loses physical consistency due to time base drift, and the credibility of the output contact wear depth and mechanism resistance torque coupling vector drops sharply. Summary of the Invention

[0004] The present invention provides an intelligent monitoring method and system for vacuum circuit breakers, which solves the problem of time domain fragmentation caused by asynchronous acquisition of mechanical vibration signals and arc current signals in vacuum circuit breaker status monitoring, thereby failing to achieve coordinated quantitative evaluation of mechanical degradation and electrical faults.

[0005] To achieve the above objectives, the present invention provides an intelligent monitoring method for a vacuum circuit breaker, comprising:

[0006] S1. During the circuit breaker opening and closing operations, the mechanical vibration signal of the operating mechanism transmission part and the arc current signal of the arc extinguishing chamber branch are synchronously collected;

[0007] S2. Performing a wavelet packet decomposition operation on the mechanical vibration signal, extracting the energy ratio characteristics of the natural frequency band of the trip spring as a mechanical degradation factor by integrating the frequency band energy;

[0008] S3. The arc current signal is intercepted during the arcing period, and the arc fluctuation factor is extracted based on the time domain integral of the first-order derivative of the current;

[0009] S4. Based on the mechanical wear exponential decay model and the electrical stability linear mapping model, a multi-physics field correlation model is constructed, and the mechanical degradation factor and the arc fluctuation factor are used as input to output a coupling vector representing the contact wear depth and the transmission mechanism resistance torque.

[0010] In order to solve the above problems, the present invention further provides an intelligent monitoring system for a vacuum circuit breaker, the system comprising:

[0011] The signal acquisition module is used to synchronously collect the mechanical vibration signal of the transmission part of the operating mechanism and the arc current signal of the arc extinguishing chamber branch during the circuit breaker opening and closing operations;

[0012] a mechanical degradation analysis module, configured to perform a wavelet packet decomposition operation on the mechanical vibration signal and extract an energy proportion characteristic of the trip spring's natural frequency band as a mechanical degradation factor by integrating the frequency band energy;

[0013] An arc stability analysis module, configured to intercept the arcing period of the arc current signal and extract the arc fluctuation factor based on the time domain integral of the first-order derivative of the current;

[0014] The multi-physics coupling module is used to construct a multi-physics correlation model based on the mechanical wear exponential decay model and the electrical stability linear mapping model, and takes the mechanical degradation factor and the arc fluctuation factor as input to output a coupling vector representing the contact wear depth and the transmission mechanism resistance torque.

[0015] Compared with the prior art, the present invention has the following beneficial effects:

[0016] 1. This invention fundamentally solves the time domain separation problem of mechanical vibration signals and arc current signals through a dual-channel synchronous acquisition mechanism triggered by the rising edge of the trip coil current. It ensures that the vibration signal of the operating mechanism transmission part and the current signal of the arc extinguishing chamber branch are strictly synchronized with microsecond accuracy, so that mechanical action events (such as contact separation moment) and electrical arcing events (such as current zero crossing point) are accurately associated on the same time axis.

[0017] 2. The sudden increase point of the envelope curve of the mechanical vibration signal (the moment of contact separation) can be directly used to intercept the arcing period of the arc current, eliminating the period interception distortion caused by signal offset in traditional methods; the calculation of the energy proportion of the natural frequency band of the tripping spring and the integral of the arc current change rate are time-consistent, and the physical meanings of the two are clear and can be cross-verified. The mechanical degradation factor and arc fluctuation factor input into the multi-physics field correlation model are intrinsically correlated, and the output contact wear depth and transmission mechanism resistance torque coupling vector truly reflect the interaction between mechanical wear and arc erosion. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A schematic flow chart of an intelligent monitoring method for a vacuum circuit breaker provided in one embodiment of the present invention;

[0019] Figure 2 A functional module diagram of an intelligent monitoring system for a vacuum circuit breaker provided by one embodiment of the present invention;

[0020] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0021] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0022] An embodiment of the present application provides an intelligent monitoring method for a vacuum circuit breaker. The execution subject of the intelligent monitoring method for a vacuum circuit breaker includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided by the embodiment of the present application. In other words, the intelligent monitoring method for a vacuum circuit breaker can be executed by software or hardware installed on a terminal device or a server device. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc. The server can be an independent server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content distribution networks, and big data and artificial intelligence platforms.

[0023] Reference Figure 1 FIG. 1 is a flow chart of an intelligent monitoring method for a vacuum circuit breaker according to an embodiment of the present invention. In this embodiment, the intelligent monitoring method for a vacuum circuit breaker includes:

[0024] S1. During the opening and closing operation of the circuit breaker, the mechanical vibration signal of the transmission part of the operating mechanism and the arc current signal of the arc extinguishing chamber branch are synchronously collected.

[0025] In the embodiment of the present application, the circuit breaker opening and closing operation process refers to the mechanical action process of the moving and static contacts in the vacuum circuit breaker separating (opening) or contacting (closing). During this process, the operating mechanism and the arc extinguishing chamber will generate characteristic physical signals, which is a critical period for monitoring the status of the equipment.

[0026] In the embodiments of this application, the operating mechanism transmission part is the mechanical component in the circuit breaker that transmits power to achieve opening and closing, including connecting rods, springs, etc. Its vibration signal can reflect the wear and jamming of mechanical components. Mechanical vibration signals are vibration waves generated by the collision and deformation of components when the transmission part moves.

[0027] In the embodiments of the present application, the arc extinguishing chamber branch is the circuit path through which the arc current passes in the circuit breaker. The arc extinguishing chamber is the core component that extinguishes the arc generated during opening and closing. The arc current signal is the current change signal generated by the arc between the contacts during opening and closing.

[0028] In an embodiment of the present application, during the opening and closing operations of the circuit breaker, the mechanical vibration signal of the transmission part of the operating mechanism and the arc current signal of the arc extinguishing chamber branch are synchronously collected, including: when the circuit breaker performs the opening or closing operation, the two types of signals are collected respectively by a vibration sensor deployed at the transmission part and a current sensor connected in series to the arc extinguishing chamber branch, and the timestamp alignment mechanism is used to ensure that the signals are aligned on the time axis, thereby solving the problem of state assessment fragmentation caused by separate collection of mechanical and electrical signals and time asynchrony in the prior art.

[0029] In some embodiments, during the circuit breaker opening and closing operation, synchronously collecting the mechanical vibration signal of the operating mechanism transmission part and the arc current signal of the arc extinguishing chamber branch includes:

[0030] Detect the rising edge of the trip coil current as a trigger signal;

[0031] In response to the trigger signal, a timestamp alignment mechanism of the dual-channel acquisition card is started;

[0032] Collect mechanical vibration signals from the transmission parts of the operating mechanism through high-frequency channels;

[0033] The arc current signal of the arc extinguishing chamber branch is collected through the ultra-high frequency channel;

[0034] The mechanical vibration signal and the arc current signal are aligned based on the timestamp alignment mechanism.

[0035] In the embodiments of the present application, the trip coil is the electromagnetic coil that controls the circuit breaker's opening operation. When current is passed through it, it generates magnetic force to drive the operating mechanism. The rising edge of the trip coil current refers to the initial stage when the current in the trip coil increases from its initial value, marking the start of the opening operation (the closing operation can similarly detect the rising edge of the closing coil current). The trigger signal is the command signal used to initiate the signal acquisition process, and its function is to determine the start time of acquisition.

[0036] In an embodiment of the present application, detecting the rising edge of the trip coil current as a trigger signal includes: using a current sensor to monitor the current changes in the trip coil in real time, and generating an electrical pulse as a trigger signal when the current value is detected to rise from 0 (i.e., a rising edge). The rising edge of the trip coil current precisely corresponds to the initiation moment of the opening and closing operation, ensuring that the collected signal fully covers the entire operation process, avoiding data redundancy or loss caused by too early or too late collection. For example, when the rising edge of the trip coil current rises from 0 to 0.5A, it is determined that the trip operation has started, triggering the subsequent collection process.

[0037] In the embodiments of this application, a dual-channel acquisition card is a hardware device with two independent signal input channels, capable of simultaneously acquiring two different signals (such as a mechanical vibration signal and an arc current signal). The timestamp alignment mechanism adds a timestamp to each sampling point of each signal based on the acquisition card's internal clock, allowing the sampling moments of the two signals to be accurately compared using the timestamps.

[0038] In an embodiment of the present application, the timestamp alignment mechanism of the dual-channel acquisition card is activated in response to the trigger signal, including: when the acquisition card receives the trigger signal generated by the rising edge of the trip coil current, it immediately activates the internal clock module and assigns a synchronized time base to the high-frequency channel and the ultra-high-frequency channel respectively, so that the two channels start sampling on the same time axis, and the timestamp error of each sampling point is controlled within 1μs. For example, after the trigger signal arrives, the acquisition card clock marks this moment as t=0, and subsequently generates a timestamp every 100μs (high-frequency sampling) for the high-frequency channel and a timestamp every 10μs (ultra-high-frequency sampling) for the ultra-high-frequency channel, ensuring that the time stamps of the two signals are derived from the same clock base, solving the time deviation problem caused by clock drift during dual-channel acquisition, and ensuring the time correlation of subsequent signal analysis.

[0039] In an embodiment of the present application, the high-frequency channel is a channel in a dual-channel acquisition card specifically used to collect mechanical vibration signals. Its hardware circuit adapts to the output characteristics of the vibration sensor (such as the voltage signal range). Among them, the sampling frequency is higher than the sampling method of the highest frequency of the mechanical vibration signal, ensuring that the frequency components of the vibration signal are fully retained.

[0040] In an embodiment of the present application, a high-frequency channel is used to collect mechanical vibration signals from the transmission part of the operating mechanism. This includes: fixing an acceleration sensor to the connecting rod transmission part of the operating mechanism, connecting the vibration voltage signal output by the sensor to the high-frequency channel, and after the trigger signal is activated, the acquisition card performs analog-to-digital conversion on the voltage signal at a frequency of 10kHz, and adds a time stamp based on the timestamp alignment mechanism to each sampling point. For example, within 0.1 seconds of the trip operation, the high-frequency channel can collect 1000 vibration signal data points, completely recording the vibration process of the transmission part from startup to stabilization, accurately capturing the detailed characteristics of the mechanical vibration (such as the natural frequency component of the trip spring), and providing high-quality data for the subsequent extraction of mechanical degradation factors.

[0041] In an embodiment of the present application, the ultra-high frequency channel is a channel in the dual-channel acquisition card specifically used to collect arc current signals. Its hardware circuit has a higher bandwidth to adapt to rapidly changing current signals. Among them, the sampling frequency is much higher than the sampling method of the arc current signal change frequency, because the arc current may oscillate at high frequency when the switch is opened. Assuming the maximum frequency is 50kHz, the sampling frequency needs to be set to 100kHz to capture the instantaneous changes in current.

[0042] In this embodiment, the arc current signal from the arc extinguishing chamber branch is collected via an ultrahigh frequency channel. This includes connecting a Rogowski coil (current sensor) in series with the arc extinguishing chamber branch. The coil outputs a voltage signal proportional to the arc current, which is then fed into the ultrahigh frequency channel. Upon activation by a trigger signal, the acquisition card collects the arc current signal at a frequency of 100 kHz and adds a timestamp.

[0043] For example, during the opening process, the arc lasts for 20ms, and the UHF channel can collect 2000 current data points, completely recording the current waveform from the generation to the extinction of the arc.

[0044] In an embodiment of the present application, the mechanical vibration signal and the arc current signal are aligned based on the timestamp alignment mechanism, including: using the unified clock reference in the timestamp alignment mechanism to calibrate the timestamps of the two signals. For example, the mechanical vibration signal collected by the high-frequency channel at t = 100 μs and the arc current signal collected by the ultra-high-frequency channel at t = 100 μs are marked as signals at the same time; if the time points do not overlap due to different sampling frequencies (10 kHz vs. 100 kHz), the corresponding values ​​of the two signals at any time can be obtained through linear interpolation, ensuring that the temporal correlation between mechanical actions (such as contact separation) and arc phenomena (such as arc generation) can be accurately analyzed.

[0045] For example, the time difference between the contact separation moment (t1) of the mechanical vibration signal and the arc termination moment (t2) of the arc current signal can be used to accurately calculate the arc duration, thereby solving the problem of arc duration calculation error caused by time asynchrony in the existing technology.

[0046] In general, by accurately triggering the acquisition through the rising edge of the trip coil current, starting the dual-channel acquisition card and the timestamp alignment mechanism, two types of signals are collected, and the time synchronization is achieved based on the timestamp alignment, which overall solves the problem of asynchronous acquisition and feature loss of mechanical and electrical signals in the existing technology.

[0047] S2. Perform a wavelet packet decomposition operation on the mechanical vibration signal, and extract the energy proportion characteristics of the inherent frequency band of the trip spring as a mechanical degradation factor through frequency band energy integration.

[0048] In the embodiments of the present application, the wavelet packet decomposition operation decomposes the signal into different frequency bands while retaining time information, making it more suitable for analyzing non-stationary vibration signals. Frequency band energy integration is achieved by squaring the time domain signal and then integrating it. The natural frequency band of the trip spring refers to the frequency band within which the natural frequency exhibited by the trip spring during vibration occurs. Energy changes in this frequency band reflect changes in spring properties such as stiffness and elasticity. The energy proportion characteristic refers to the ratio of the energy in a specific frequency band to the total energy and can be expressed as a percentage.

[0049] In the embodiment of the present application, the mechanical degradation factor is an indicator that quantifies the degradation of the mechanical performance of the operating mechanism. The larger the value of the mechanical degradation factor, the better the spring performance. Conversely, a smaller value indicates that the spring is fatigued, aged, or stuck. This is because the mechanical state of the trip spring (such as fatigue, aging, and sticking) will change its vibration characteristics. This change is mainly reflected in the vibration energy of a specific frequency band (i.e., the "natural frequency band") where the spring's natural vibration frequency is located. By calculating the proportion of the energy of this specific frequency band in the entire vibration signal energy, the degree of spring degradation can be quantified. This proportion is the mechanical degradation factor.

[0050] In the embodiment of the present application, the healthy spring has an intact structure and normal stiffness. When it is released, its vibration energy will be highly concentrated near its natural frequency, and the value of the mechanical degradation factor will be high.

[0051] In the embodiment of the present application, the degraded spring is fatigued, aged, stuck, etc., and the vibration energy is no longer mainly concentrated in the inherent narrow frequency band, but is dispersed to other frequency bands, which will lead to a decrease in the value of the mechanical degradation factor.

[0052] In some embodiments, performing a wavelet packet decomposition operation on the mechanical vibration signal includes:

[0053] Performing multi-layer decomposition on the mechanical vibration signal using a preset wavelet basis;

[0054] The target monitoring frequency band is divided into multiple equal-width sub-bands, and the time domain signal of each sub-band is reconstructed.

[0055] In an embodiment of the present application, a preset wavelet basis is used to perform multi-layer decomposition on the mechanical vibration signal, and each sub-band of the previous layer is divided into two to form a narrower equal-width frequency band, and finally output as several time domain sub-signals, each sub-signal only contains the component of the original signal within a specific narrow frequency band, and the mechanical vibration signal can be completely reconstructed after all sub-signals are superimposed.

[0056] In the embodiment of the present application, a preset wavelet basis is used to perform multi-layer decomposition on the mechanical vibration signal, including: performing a 3-layer decomposition on the mechanical vibration signal using the db4 wavelet basis to obtain 8 sub-bands (2 3 =8), each sub-band corresponds to a different frequency range (for example, in the first layer of decomposition, the full frequency band 0-10kHz is divided into a low frequency band 0-5kHz and a high frequency band 5-10kHz. In the second layer of decomposition, the low frequency band 0-5kHz is further divided into a second low frequency band 0-2.5kHz and a second high frequency band 2.5-5kHz. This process is repeated until the target number of layers is reached (for example, 8 sub-bands are obtained after 3 layers of decomposition).

[0057] In this embodiment of the present application, the target monitoring frequency band refers to the frequency range that includes the natural frequency of the trip spring and is pre-set based on the mechanical characteristics of the circuit breaker. Equal-width sub-bands refer to evenly dividing the target monitoring frequency band into several sub-bands of equal bandwidth (e.g., each sub-band has a width of 1 kHz).

[0058] In an embodiment of the present application, the target monitoring frequency band is divided into multiple equal-width sub-bands, and the time domain signal of each sub-band is reconstructed, including: dividing the 0-10kHz target monitoring frequency band into 10 equal-width sub-bands, multiplying the wavelet coefficients extracted from each equal-width sub-band by the corresponding wavelet basis function waveform fragment, and superimposing all the product results in chronological order to generate the time domain waveform of the sub-band. For example, if the target frequency band (0-10kHz) is divided into 10 1kHz equal-width sub-bands, 10 independent time domain signals are obtained after reconstruction, wherein, (0-1kHz component), ..., (9-10kHz component).

[0059] In an embodiment of the present application, the vibration signal is sliced ​​layer by layer from coarse to fine frequency to form a fine spectrum segmentation, and the mathematical parameters of each frequency slice are restored to a physical waveform. Through this operation, the key frequency band reflecting the health status of the spring (such as 2-4kHz) can be accurately separated, and its energy proportion can be calculated to quantify the degree of mechanical degradation.

[0060] In some embodiments, extracting the energy proportion characteristic of the trip spring's natural frequency band as the mechanical degradation factor through frequency band energy integration includes:

[0061] Determining a movement period of the opening movement, wherein the movement period is defined by identifying a rising edge inflection point and a falling edge inflection point of an envelope curve of the mechanical vibration signal;

[0062] Select a sub-band index set corresponding to the natural vibration characteristics of the trip spring;

[0063] Based on the sub-band index set, the wavelet packet decomposition operation generates each sub-band time domain signal, and a frequency band energy integration operation is performed within the opening movement period to obtain the energy proportion characteristics of the opening spring's inherent frequency band.

[0064] In the embodiments of this application, the envelope of a mechanical vibration signal refers to a curve formed by connecting the peak points of the signal, reflecting the amplitude variation trend of the signal. The rising inflection point is the point where the envelope changes from a slow rise to a rapid rise, corresponding to the moment when the trip spring begins to release energy to drive the mechanism. The falling inflection point is the point where the envelope changes from a rapid decline to a gentle decline, corresponding to the moment when the trip action is completed and the mechanism stabilizes.

[0065] In an embodiment of the present application, determining the movement period of the opening movement includes: identifying the inflection point of the rising edge of the envelope of the mechanical vibration signal as the starting time of the opening movement; identifying the inflection point of the falling edge of the envelope of the mechanical vibration signal as the ending time of the opening movement.

[0066] In an embodiment of the present application, a movement period of the tripping movement is determined, and the movement period is defined by identifying the rising edge inflection point and the falling edge inflection point of the envelope of the mechanical vibration signal, including: obtaining the envelope of the vibration signal, calculating the first-order derivative of the envelope with respect to time, and when the derivative changes from less than a threshold value (such as 0.1) to greater than the threshold value, it is determined to be a rising edge inflection point; when the derivative changes from greater than the threshold value to less than the threshold value, it is determined to be a falling edge inflection point.

[0067] In this embodiment, the rising inflection point of the envelope curve is the point where the slope of the envelope curve changes suddenly, corresponding to the moment when the trip spring begins to release its elastic potential energy, driving the operating mechanism. The accuracy of identifying this moment directly affects the effectiveness of subsequent energy calculations. If the starting moment is identified too early, noise energy before the trip is introduced; if it is too late, critical information from the initial release phase of the spring is missed.

[0068] In the embodiment of the present application, the inflection point of the falling edge of the envelope is the mutation point where the envelope changes from rapid attenuation to gentle attenuation, corresponding to the moment when the opening action is completed, the contacts are separated into place, and the vibration of the mechanism tends to be stable. The inflection point of the falling edge of the envelope is determined as the moment when the opening movement ends, which can avoid counting the residual vibration energy after the opening into the effective movement period.

[0069] In the embodiment of the present application, the natural vibration characteristics of the trip spring refer to the natural frequency characteristics exhibited by the spring during elastic deformation and recovery, which are determined by factors such as the spring material, stiffness, and mass.

[0070] In the embodiment of the present application, the sub-band index set corresponding to the natural vibration characteristics of the trip spring is selected, including: determining the natural frequency range of the trip spring (such as 2-4kHz) through finite element simulation, corresponding to the 3rd to 5th sub-bands after wavelet packet decomposition, so the sub-band index set For example, the natural frequency of a certain type of circuit breaker spring is 2.5kHz. In the decomposition result of 10 sub-bands (each 1kHz), the third sub-band (2-3kHz) contains this frequency.

[0071] In the embodiment of the present application, the frequency band energy integration operation is to integrate the time domain signal after squaring it within a specified time period to calculate the energy of the signal within the time period. The numerator part calculates the total energy of the spring's natural frequency band, and the denominator part calculates the total energy of all sub-frequency bands. The ratio of the two is the energy proportion feature.

[0072] In this embodiment of the present application, a band energy integration operation is performed during the opening movement period on each sub-band time domain signal generated by the wavelet packet decomposition operation based on the sub-band index set. The operation includes: squaring and integrating each sub-band time domain signal in the spring's natural frequency band index set, and summing the squares to obtain a numerator; square-integrating all sub-band time domain signals and summing the squares to obtain a denominator; dividing the squares and multiplying by 100% to obtain a mechanical degradation factor. For example, if the energy in the spring's natural frequency band (2-4kHz) is 2.5J and the total energy is 10J, the mechanical degradation factor is 25%.

[0073] In the embodiment of the present application, a frequency band energy integration operation is performed during the opening movement period:

[0074] in, is the energy proportion characteristic of the natural frequency band of the trip spring, is the sub-band index set corresponding to the natural frequency band of the trip spring, is the total number of sub-bands, For the The time domain signal of the sub-bands, This is the opening movement period. is the sub-band index corresponding to the inherent frequency band, is the sub-band index corresponding to the full band.

[0075] The physical meaning of this formula is that when the spring performance is good, the energy in its natural frequency band accounts for a high proportion; when the spring is fatigued or aged, the energy is dispersed to other frequency bands and the mechanical degradation factor decreases.

[0076] In general, step S2 solves the problem that traditional methods cannot accurately evaluate spring performance. It realizes the quantitative evaluation of the trip spring status through the mechanical degradation factor, providing a key indicator for early warning of mechanical failure of the circuit breaker. When the mechanical degradation factor is lower than the preset fault threshold, it can timely warn of spring fatigue or jamming.

[0077] S3. Intercept the arcing period of the arc current signal, and extract the arc fluctuation factor based on the time domain integration of the first-order derivative of the current.

[0078] In the embodiments of the present application, arcing period extraction precisely separates the time period during which the arc is actually generated from the continuous arc current signal. This period begins at contact separation and ends at arc extinction. The time-domain integration of the first-order derivative of current integrates the rate of change of the arc current over the arcing period to quantify the severity of the arc current variation. The arc fluctuation factor measures the arc's ability to maintain stable combustion during the arcing process. A larger value indicates more dramatic arc current variations and poorer arc stability.

[0079] In an embodiment of the present application, the arc burning period of the arc current signal is intercepted, and the arc fluctuation factor is extracted based on the time domain integration of the first-order derivative of the current, including: determining the contact separation moment by analyzing the mechanical vibration signal, and determining the arc burning period in combination with the arc current zero crossing point; derivatizing and integrating the current signal within the period to obtain the arc fluctuation factor.

[0080] In some embodiments, intercepting the arcing period of the arc current signal includes:

[0081] Taking the sudden increase point in the envelope as the contact separation moment;

[0082] The zero crossing point of the arc current signal is detected as the arc termination time, and the arcing period is defined as the time from the contact separation time to the arc termination time.

[0083] In this embodiment, the sudden increase point refers to the point in the envelope where the rate of change of amplitude suddenly increases. This corresponds to the sudden change in vibration amplitude caused by the mechanical impact generated at the moment of contact separation. The contact separation moment refers to the precise moment when the contacts begin to separate during the circuit breaker opening process and is the starting point of the arcing period.

[0084] In this embodiment, the sudden increase point in the envelope is used as the contact separation moment. This method involves calculating the first-order derivative of the envelope with respect to time. When the derivative exceeds a preset sudden change threshold, the corresponding time point is the sudden increase point. The accuracy of this method depends on the setting of the preset sudden change threshold. If the threshold is too low, background noise may be misjudged, while if it is too high, a true contact separation signal may be missed.

[0085] In the embodiments of the present application, the zero crossing of the arc current signal refers to the moment when the current value changes from positive to negative or vice versa, at which point the arc plasma loses energy to sustain it and extinguishes. The arc termination moment refers to the moment when the arc is completely extinguished, marking the end of the arcing period. The arcing period is the time period from contact separation to arc extinction. The arc characteristics during this period directly reflect the performance of the arc extinguishing chamber.

[0086] In the embodiment of the present application, the zero crossing point of the arc current signal is detected as the arc termination moment, and the arcing period is defined as the time from the contact separation moment to the arc termination moment, including: after the contact separation moment, the first zero crossing point of the arc current signal is detected, that is, the arcing period is satisfied. and Moment The arcing period is defined as .

[0087] For example, in a certain test, the contact separation time is 0.03 seconds, and the first current zero crossing point is 0.05 seconds, so the arcing period is 0.02 seconds. Accurately defining the arcing period is the basis for subsequent analysis of arc stability. If the period is not accurately intercepted, it will lead to deviations in the calculation of the arc fluctuation factor.

[0088] In some embodiments, the extracting of the arc fluctuation factor based on the time domain integration of the first-order derivative of the current includes:

[0089] performing a differential operation on the arc current signal during the arcing period to obtain a current change rate;

[0090] The current change rate is integrated in the time domain based on the arcing period to obtain an arc fluctuation factor, wherein the calculation formula of the arc fluctuation factor is:

[0091]

[0092] Where, is the arc fluctuation factor, is the arc termination moment, is the contact separation moment, is the current change rate, is the differential step size, is the arc current signal.

[0093] In the embodiment of the present application, performing a differential operation on the arc current signal during the arcing period to obtain the current change rate includes: using numerical differentiation to calculate the current change rate during the arcing period. For example, when the sampling frequency is 100kHz, the time interval is , if the current values ​​of two adjacent sampling points are 5A and 5.2A respectively, then the current change rate of the point is The greater the current change rate, the more violent the dynamic characteristics of the arc plasma and the worse the arc stability.

[0094] In this embodiment, the time-domain integral calculation integrates the absolute value of the current rate of change over the arcing period to obtain the overall severity of the arc current variation. The arc fluctuation factor is a normalized value of the integral result. By dividing it by the arcing duration, the arc fluctuation factor eliminates the influence of arcing time differences, making the arc fluctuation factor comparable across different circuit breakers or under different operating conditions, and directly reflecting the arc instability density.

[0095] In an embodiment of the present application, the current change rate is integrated in time domain based on the arcing period to obtain the arc fluctuation factor, including: integrating the absolute value of the current change rate within the arcing period, and then dividing it by the arcing duration to obtain the arc fluctuation factor.

[0096] For example, if the absolute value of the current change rate after time domain integration during the arcing period is 10,000A and the arcing duration is 0.02 seconds, then The larger the arc fluctuation factor value, the more drastic the arc current change and the worse the arc stability.

[0097] Overall, step S3 addresses the difficulty of directly monitoring arc stability with traditional methods. It uses the arc fluctuation factor to quantitatively evaluate arc extinguishing chamber performance. When the arc fluctuation factor exceeds a threshold, a warning of a decrease in the arc extinguishing chamber vacuum level can be issued, providing a scientific basis for condition-based maintenance of the circuit breaker.

[0098] S4. Based on the mechanical wear exponential decay model and the electrical stability linear mapping model, a multi-physics field correlation model is constructed, and the mechanical degradation factor and the arc fluctuation factor are used as input to output a coupling vector representing the contact wear depth and the transmission mechanism resistance torque.

[0099] In some embodiments, the multi-physics field correlation model is specifically:

[0100]

[0101] in, is the wear attenuation coefficient, is the arc gain coefficient, is the mechanical degradation factor, is the contact wear depth, is the resistance torque of the transmission mechanism, is the mechanical proportional coefficient, is the electrical proportionality coefficient.

[0102] In an embodiment of the present application, when the contact wear depth exceeds a preset wear threshold, a contact replacement warning is triggered, and when the transmission mechanism resistance torque exceeds a preset torque threshold, a mechanism maintenance instruction is triggered.

[0103] In the embodiment of the present application, the characterization of the contact wear depth is determined by the synergistic effect of the mechanical degradation factor (reflecting the performance degradation of components such as the trip spring) and the arc fluctuation factor (reflecting the stability of arc burning): the more severe the mechanical degradation (the lower the value of the mechanical degradation factor), the slower the tripping action and the longer the arc duration; the more intense the arc fluctuation (the higher the value of the arc fluctuation factor), the greater the arc energy and the more obvious the evaporation and splashing of the contact material.

[0104] In an embodiment of the present application, the characterization of the resistance torque of the transmission mechanism is determined by the synergistic effect of the mechanical degradation factor and the arc fluctuation factor: mechanical degradation directly leads to deformation or loosening of the transmission components, and the basic resistance torque increases; the impact force generated by the arc fluctuation will aggravate the deformation or loosening of the transmission components, further amplifying the resistance torque; the model integrates the influence of both, and the output resistance torque can quantitatively reflect the actual load capacity of the transmission mechanism.

[0105] In an embodiment of the present application, an iterative coupling mechanism can also be introduced. After each opening and closing operation, the value of the mechanical degradation factor will be updated (because the spring continues to fatigue). The updated mechanical degradation factor will change the next arcing process, thereby affecting the arc fluctuation factor. The input variables mechanical degradation factor and arc fluctuation factor themselves are calculated based on the previous state, forming a long-term coupling.

[0106] In the embodiment of the present application, the core of the multi-physics field correlation model is to reveal the intrinsic connection between mechanical state and electrical performance through a physical model. The mechanical wear exponential decay model describes the change law of the contact wear depth with the mechanical degradation factor, and uses an exponential function to reflect the characteristics of slow wear in the early stage and accelerated wear in the later stage. The electrical stability linear mapping indicates that the transmission mechanism resistance torque is linearly related to the arc fluctuation factor. The more unstable the arc, the greater the resistance torque. The coupling vector is the specific value of the contact wear depth and the transmission mechanism resistance torque obtained after considering both mechanical and electrical factors.

[0107] In an embodiment of the present application, the mechanical degradation factor obtained in S2 and the arc fluctuation factor obtained in S3 are substituted into the multi-physics field correlation model, and the output contact wear depth and the transmission mechanism resistance torque are calculated through the model, thereby overcoming the limitation of the traditional monitoring method that only focuses on a single physical quantity, realizing a comprehensive evaluation of the mechanical and electrical performance of the circuit breaker, and providing a basis for precise maintenance.

[0108] In the embodiment of the present application, the multi-physics field correlation model uses a matrix form to combine two physical quantities ( and ) and two factors ( and ) association.

[0109] In the embodiment of the present application, the contact wear depth model is: , when the mechanical degradation factor is close to 1, the exponential term approaches 0, When the mechanical degradation factor decreases, the exponential term increases and the contact wear depth increases rapidly, reflecting the accelerating effect of mechanical performance degradation on contact wear.

[0110] In the embodiment of the present application, the wear attenuation coefficient determines the rate at which wear changes with the mechanical degradation factor and is obtained by fitting the circuit breaker type test data.

[0111] In the embodiment of the present application, the transmission mechanism resistance torque model is: The resistance torque is proportional to the arc fluctuation factor. The more unstable the arc is (the larger the arc fluctuation factor is), the greater the resistance torque is, which reflects the impact effect of the arc energy on the transmission mechanism.

[0112] In the embodiments of this application, the preset wear threshold is the maximum allowable wear depth of the contacts. Exceeding this value will result in increased contact resistance, excessive temperature rise, and even short circuit failure. The preset torque threshold is the maximum resistance torque allowed for normal operation of the transmission mechanism. Exceeding this value will result in prolonged opening and closing times and unreliable operation.

[0113] In an embodiment of the present application, when the contact wear depth is greater than a preset wear threshold, the system automatically triggers an early warning message, prompting the operation and maintenance personnel to replace the contacts and issuing a red early warning; when the transmission mechanism resistance torque is greater than the preset torque threshold, the system generates a maintenance work order, instructing to check the lubrication status of the transmission mechanism, tighten the connecting parts, etc., and trigger an orange early warning, where the setting of the threshold depends on the circuit breaker design standards and operating experience.

[0114] like Figure 2 FIG. 1 is a functional module diagram of an intelligent monitoring system for vacuum circuit breakers provided by an embodiment of the present invention.

[0115] The intelligent monitoring system 100 for vacuum circuit breakers described in the present invention can be installed in an electronic device. Depending on the functionality implemented, the intelligent monitoring system 100 for vacuum circuit breakers can include a signal acquisition module 101, a mechanical degradation analysis module 102, an arc stability analysis module 103, a multi-physics coupling module 104, and an early warning module 105. A module, also referred to as a unit, is a series of computer program segments that can be executed by an electronic device processor and perform a fixed function. These are stored in the electronic device's memory.

[0116] In this embodiment, the functions of each module / unit are as follows:

[0117] The signal acquisition module 101 is used to synchronously acquire the mechanical vibration signal of the transmission part of the operating mechanism and the arc current signal of the arc extinguishing chamber branch during the circuit breaker opening and closing operations;

[0118] A mechanical degradation analysis module 102 is configured to perform a wavelet packet decomposition operation on the mechanical vibration signal and extract an energy proportion characteristic of the trip spring's natural frequency band as a mechanical degradation factor by integrating the frequency band energy;

[0119] An arc stability analysis module 103 is configured to intercept the arcing period of the arc current signal and extract an arc fluctuation factor based on a time domain integral of the first-order derivative of the current;

[0120] The multi-physics coupling module 104 is used to construct a multi-physics correlation model based on the mechanical wear exponential decay model and the electrical stability linear mapping model, and uses the mechanical degradation factor and the arc fluctuation factor as input to output a coupling vector representing the contact wear depth and the transmission mechanism resistance torque.

[0121] The system further comprises an early warning module 105, which is configured to:

[0122] receiving the contact wear depth and the transmission mechanism resistance torque output by the multi-physics field coupling module;

[0123] When the contact wear depth exceeds a preset wear threshold, a contact replacement warning signal is generated;

[0124] When the transmission mechanism resistance torque exceeds a preset torque threshold, a mechanism maintenance instruction signal is generated.

[0125] In the several embodiments provided by the present invention, it should be understood that the disclosed methods and systems can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For example, the module division is merely a logical function division, and other division methods may be used in actual implementation.

[0126] The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed across multiple network elements. Some or all of the modules may be selected to achieve the purpose of the solution of this embodiment according to actual needs.

[0127] In addition, the functional modules in various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or hardware plus software functional modules.

[0128] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0129] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence refers to the theories, methods, technologies, and application systems that use digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use knowledge to achieve optimal results.

[0130] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. An intelligent monitoring method for vacuum circuit breakers, characterized in that the method include: S1. During the circuit breaker opening and closing operations, the mechanical vibration signal of the operating mechanism transmission part and the arc current signal of the arc extinguishing chamber branch are synchronously collected; S2. Performing a wavelet packet decomposition operation on the mechanical vibration signal and extracting the energy proportion characteristics of the natural frequency band of the trip spring as a mechanical degradation factor through frequency band energy integration includes: determining the movement period of the trip movement, the movement period is defined by identifying the rising edge inflection point and the falling edge inflection point of the envelope of the mechanical vibration signal; selecting a sub-band index set corresponding to the natural vibration characteristics of the trip spring; performing a frequency band energy integration operation on each sub-band time domain signal generated by the wavelet packet decomposition operation within the trip movement period to obtain the energy proportion characteristics of the natural frequency band of the trip spring; is the energy proportion characteristic of the natural frequency band of the trip spring, is the sub-band index set corresponding to the natural frequency band of the trip spring, is the total number of sub-bands, For the The time domain signal of the sub-bands, This is the opening movement period. is the sub-band index corresponding to the inherent frequency band, is the sub-band index corresponding to the full band; S3. The arc current signal is intercepted during the arcing period, and the arc fluctuation factor is extracted based on the time domain integral of the first-order derivative of the current; the arcing time is defined as the time from the contact separation moment to the arcing termination moment; S4. Based on the mechanical wear exponential decay model and the electrical stability linear mapping model, a multi-physics field correlation model is constructed. Taking the mechanical degradation factor and the arc fluctuation factor as input, the model outputs a coupling vector representing the contact wear depth and the transmission mechanism resistance torque. This includes: inputting the mechanical degradation factor into the mechanical wear exponential decay model to obtain the intermediate value of the contact wear depth; inputting the arc fluctuation factor into the electrical stability linear mapping model to obtain the intermediate value of the transmission mechanism resistance torque; and calibrating the intermediate values ​​of the contact wear depth and the transmission mechanism resistance torque using a proportional coefficient to obtain the coupling vector representing the contact wear depth and the transmission mechanism resistance torque. The multi-physics field correlation model is: is the wear attenuation coefficient, is the arc gain coefficient, is the mechanical degradation factor, is the contact wear depth, is the resistance torque of the transmission mechanism, is the mechanical proportional coefficient, is the electrical proportionality coefficient.

2. The intelligent monitoring method for vacuum circuit breaker according to claim 1, characterized in that: During the circuit breaker opening and closing operations, the mechanical vibration signal of the operating mechanism transmission part and the arc current signal of the arc extinguishing chamber branch are synchronously collected, including: Detect the rising edge of the trip coil current as a trigger signal; In response to the trigger signal, a timestamp alignment mechanism of the dual-channel acquisition card is started; Collect mechanical vibration signals from the transmission parts of the operating mechanism through high-frequency channels; The arc current signal of the arc extinguishing chamber branch is collected through the ultra-high frequency channel; The mechanical vibration signal and the arc current signal are aligned based on the timestamp alignment mechanism.

3. The intelligent monitoring method for vacuum circuit breaker according to claim 1, characterized in that: Performing a wavelet packet decomposition operation on the mechanical vibration signal includes: Performing multi-layer decomposition on the mechanical vibration signal using a preset wavelet basis; The target monitoring frequency band is divided into multiple equal-width sub-bands, and the time domain signal of each sub-band is reconstructed.

4. The intelligent monitoring method for vacuum circuit breaker according to claim 1, characterized in that: Intercepting the arcing period of the arc current signal, comprising: Taking the sudden increase point in the envelope as the contact separation moment; The zero crossing point of the arc current signal is detected as the arc termination time, and the arcing period is defined as the time from the contact separation time to the arc termination time.

5. The intelligent monitoring method for vacuum circuit breaker according to claim 1, characterized in that: The arc fluctuation factor extraction based on the time domain integration of the first-order derivative of the current includes: performing a differential operation on the arc current signal during the arcing period to obtain a current change rate; The current change rate is integrated in the time domain based on the arcing period to obtain an arc fluctuation factor.

6. The intelligent monitoring method for vacuum circuit breaker according to claim 5, characterized in that: The calculation formula of the arc fluctuation factor is: Where, is the arc fluctuation factor, is the arc termination moment, is the contact separation moment, is the current change rate, is the differential step size, is the arc current signal.

7. An intelligent monitoring system for a vacuum circuit breaker, used to implement the intelligent monitoring method for a vacuum circuit breaker according to any one of claims 1 to 6, characterized in that: The system comprises: The signal acquisition module is used to synchronously collect the mechanical vibration signal of the transmission part of the operating mechanism and the arc current signal of the arc extinguishing chamber branch during the circuit breaker opening and closing operations; a mechanical degradation analysis module, configured to perform a wavelet packet decomposition operation on the mechanical vibration signal and extract an energy proportion characteristic of the trip spring's natural frequency band as a mechanical degradation factor by integrating the frequency band energy; An arc stability analysis module, configured to intercept the arcing period of the arc current signal and extract the arc fluctuation factor based on the time domain integral of the first-order derivative of the current; The multi-physics coupling module is used to construct a multi-physics correlation model based on the mechanical wear exponential decay model and the electrical stability linear mapping model, and takes the mechanical degradation factor and the arc fluctuation factor as input to output a coupling vector representing the contact wear depth and the transmission mechanism resistance torque.

8. The intelligent monitoring system for vacuum circuit breaker according to claim 7, characterized in that: The system further includes an early warning module configured to: receiving the contact wear depth and transmission mechanism resistance torque output by the multi-physics field coupling module; When the contact wear depth exceeds a preset wear threshold, a contact replacement warning signal is generated; When the transmission mechanism resistance torque exceeds a preset torque threshold, a mechanism maintenance instruction signal is generated.

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