Method and system for evaluating residual life of high-voltage fuse based on real-time monitoring

Abstract

The invention specifically relates to a high-voltage fuse residual life evaluation method and system based on real-time monitoring, and relates to the technical field of high-voltage power equipment monitoring and life evaluation. A feature vector construction module; a differential topology analysis module; a second-order trend verification module; and a life evaluation module. According to the invention, targeted hardware model selection adapts to a high-voltage electromagnetic and high-potential isolation environment, the current and temperature acquisition units both adopt an isolation design and an anti-interference sensor, and a photoelectric isolation technology is combined to ensure that data acquisition is safe and reliable; meanwhile, current-temperature time sequence deviation is eliminated through thermal lag compensation, load fluctuation interference is stripped by means of a normalized thermal-electric coupling coefficient, systematic errors such as environment temperature change and sensor drift are counteracted through differential topology analysis, and a single-phase aging fault is positioned.

Description

Technical Field

[0001] This invention relates to the field of high-voltage power equipment monitoring and life assessment technology, and in particular to a method and system for assessing the remaining life of high-voltage fuses based on real-time monitoring. Background Technology

[0002] High-voltage fuses are critical protective components in power grids, ensuring the safe operation of equipment. Their performance stability directly affects the reliability of power supply. As the power grid ages, high-voltage fuses experience increased contact resistance due to factors such as contact oxidation and material aging, gradually losing their protective function and ultimately causing power grid faults. Therefore, accurately assessing the remaining lifespan of high-voltage fuses is crucial for implementing condition-based maintenance and reducing operation and maintenance costs.

[0003] Existing methods for assessing the lifespan of high-voltage fuses largely rely on offline testing or traditional temperature monitoring, which have several drawbacks: Offline testing cannot reflect the actual service conditions of fuses, and the evaluation results deviate significantly from the actual lifespan. Traditional temperature monitoring is susceptible to factors such as load fluctuations, changes in ambient temperature, and strong electromagnetic interference, making it difficult to distinguish between normal temperature rise and temperature rise caused by aging, resulting in a high false alarm rate. Existing technologies have difficulty accurately locating single-phase aging faults and cannot effectively distinguish between transient disturbances and irreversible aging in the system. Life assessment models often ignore the accelerated life loss caused by severe operating conditions such as overload impact and high temperature accumulation, resulting in insufficient accuracy of assessment results.

[0004] To address the aforementioned issues, a system is proposed that can adapt to high-voltage, strong electromagnetic environments, has strong anti-interference capabilities, and can monitor and accurately assess the remaining lifespan of high-voltage fuses in real time. Summary of the Invention

[0005] The purpose of this invention is to provide a method and system for assessing the remaining life of high-voltage fuses based on real-time monitoring in order to solve the above-mentioned problems.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: A high-voltage fuse remaining life assessment system based on real-time monitoring includes: The three-phase synchronous acquisition and preprocessing module is configured to acquire three-phase raw signals through synchronously sampled current and temperature sensors, and output current and temperature rise difference data after processing. The feature vector construction module is configured to calculate the normalized thermo-electric coupling coefficient of each phase based on the preprocessed current and temperature rise data, thus eliminating the interference of load fluctuations on the state judgment. The differential topology analysis module is configured to perform differential operations with the average thermal-electric coupling coefficient of adjacent phases as a reference, calculate systematic errors, and locate single-phase aging faults. The second-order trend verification module is configured to distinguish between transient disturbances and single-phase irreversible aging in the system, determine true faults by using a duration threshold, and output a fault confirmation signal. The life assessment module is configured to build a remaining life model based on fault confirmation signals and deviation thresholds to obtain the remaining life of the fuse.

[0007] Preferably, the three-phase synchronous acquisition and preprocessing module specifically includes: Current acquisition unit: Equipped with three sets of through-type current transformers or Rogowski coils, respectively installed at the incoming terminals of the A / B / C three-phase fuses; Temperature acquisition unit: Equipped with three sets of non-contact temperature sensors, which are respectively aligned with the contact surfaces of the moving and stationary contacts of the A / B / C three-phase fuses; The acquired raw signals are processed in real time, including low-pass filtering, effectiveness gating, and thermal hysteresis compensation. Output preprocessed synchronization data, including: RMS values ​​of three-phase power frequency current. , , The difference between the three-phase contact temperature and the ambient temperature after timing alignment. , , .

[0008] Preferably, the feature vector construction module specifically includes: For each phase , Real-time calculation of thermal-electric coupling coefficient : ;in, This is the difference between the contact temperature and the ambient temperature. This represents the effective value of the three-phase current. The dimensions are It is a normalized relative parameter that is only related to the contact resistance and heat dissipation conditions of the fuse. When the fuse is in normal condition, the contact resistance Constant, according to the heat balance equation ,Right now and Proportional, therefore The value is constant; Output three-phase thermo-electric coupling coefficient , , .

[0009] Preferably, the differential topology analysis module specifically includes: For each phase Calculate its normalized deviation relative to the mean of the other two phases. : The expanded formula is as follows: ; ; .

[0010] Preferably, the method further includes converting measurement errors into system constants and canceling them out, specifically through the elimination of the following two types of errors: Cancellation of systematic disturbances in ambient temperature: Assuming the overall ambient temperature rises ℃, causing all three phases to increase If the value is doubled, then: Assume the original After the change, it becomes ; ; Conclusion: After changes in ambient temperature, The value remains unchanged; Cancellation of systematic interference from sensor drift: Temperature sensor drift caused three-phase All increased If the value is doubled, then: Calculated Still 0; Conclusion: Sensor drift is a systematic error, with consistent effects on all three phases, and is completely canceled out after differential calculation; Therefore, it can be concluded that only when a single phase experiences physical damage... Only then will the value be non-zero, thereby enabling the location of the faulty phase.

[0011] Preferably, the second-order trend verification module specifically includes: The drift velocity of the deviation is calculated using first-order backward difference. ; Set the steady-state threshold for drift velocity Duration threshold Perform scenario verification, including system transient disturbances and single-phase irreversible aging. Select within the preset time period data; calculate To calculate the mean of the data, for each data point, calculate the deviation from the mean, then calculate the cube of the deviation, and finally sum the cubes of all the data points. This sum is denoted as: ; Simultaneously calculate the sample standard deviation. ; Will and Substitute the values ​​into the general finite sample skewness formula to calculate the skewness coefficient and make the corresponding judgment.

[0012] Preferably, the life assessment module specifically includes: Constructing a remaining life assessment model: ; in, Design the rated life of the fuse; The normalized deviation calculated at the current moment; The critical deviation from the preset end of life; This refers to the decaying lifetime.

[0013] Preferably, the attenuation lifetime The acquisition process includes: Set an overload threshold, obtain the number of current surges within a preset time period, and subtract the overload threshold from the current corresponding to each current surge. If the obtained value is greater than 0, it is recorded as the overload surge value. Arrange the overload impact values ​​according to the acquisition time, and sequentially acquire the time interval between two adjacent overload impact values; preset a cooling time threshold. If the time interval between two adjacent overload impact values ​​is less than the cooling time threshold, calculate the time difference between the two to obtain the abnormal quantification value. Count all outlier quantization values ​​and take the largest outlier quantization value as the maximum outlier quantization value.

[0014] Preferably, the method further includes: The system presets a high temperature threshold and a maximum allowable duration of high temperature, and obtains the ambient temperature of the high-voltage fuse within a preset time period that is greater than the high temperature threshold and the duration of the corresponding ambient temperature that is greater than the maximum allowable duration of high temperature. The abnormal temperature difference is obtained by subtracting the high temperature threshold from the ambient temperature obtained at each monitoring time point within the preset time period; the abnormal temperature difference is multiplied by the time interval between the corresponding two monitoring time points to obtain the accumulated quantification value. Obtain all accumulated quantified values ​​sequentially and sum them to obtain the total accumulated quantified value; After normalizing the maximum abnormal quantization value and the total accumulated quantization value, a weighted summation is performed to obtain the attenuation coefficient. By presetting multiple sets of attenuation lifetimes and the range of attenuation coefficient values ​​corresponding to each set of attenuation lifetimes, the range of attenuation lifetime values ​​corresponding to the attenuation coefficients will be obtained, and the attenuation lifetime corresponding to the attenuation coefficients will be obtained.

[0015] Methods for assessing the remaining life of high-voltage fuses based on real-time monitoring include: Select appropriate current and temperature sensors to synchronously acquire three-phase fuse signals; output the effective value of three-phase current and the temperature rise difference between the contact and the environment; Based on the preprocessed current and temperature rise data, the ratio of temperature rise to the square of current for each phase is calculated, and the correlation between this coefficient and the contact resistance of the fuse is established to obtain three-phase characteristic parameters that can be compared across operating conditions. Using the average value of the thermal-electric coupling coefficient of two adjacent phases as a benchmark, the normalized deviation is obtained by performing differential calculation on the coefficients of each phase; the single-phase aging fault phase is located. The normalized deviation is analyzed by the rate of change over time, and the three-phase synchronization is combined with the test to distinguish between transient disturbances in the power grid and irreversible aging of single phases; true aging faults are then identified. By obtaining the attenuation life parameters, constructing the remaining life assessment model, and finally calculating the remaining life of the high-voltage fuse.

[0016] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: 1. This invention adapts to high-voltage, strong electromagnetic and high-potential isolation environments through targeted hardware selection. The current and temperature acquisition units adopt isolation design and anti-interference sensors, and combined with opto-isolation technology, it ensures safe and reliable data acquisition. At the same time, it eliminates current-temperature timing deviation through thermal hysteresis compensation, removes load fluctuation interference by normalized thermal-electric coupling coefficient, and then offsets systematic errors such as ambient temperature changes and sensor drift through differential topology analysis to locate single-phase aging faults.

[0017] 2. This invention quantifies fuse lifespan by introducing a dual-factor approach of overload impact and high-temperature accumulation. By screening effective impact and high-temperature data, calculating quantitative indicators, and weighting them to obtain the attenuation coefficient, the remaining lifespan model breaks through the limitations of traditional theoretical design lifespan and fully reflects the actual service conditions of fuses. At the same time, the entire process adopts real-time synchronous monitoring and dynamic calculation, with no offline links from signal acquisition and processing to lifespan output. It can promptly provide feedback on the remaining lifespan status of fuses, providing accurate and timely data support for power grid condition-based maintenance, helping maintenance personnel to formulate maintenance strategies in advance, reducing equipment failure risks and maintenance costs, and ensuring the reliability of power grid supply. Attached Figure Description

[0018] Further details, features, and advantages of this application are disclosed in the following description of exemplary embodiments in conjunction with the accompanying drawings, in which: Figure 1 This is a system structure diagram of the present invention; Figure 2 This is a flowchart of the method of the present invention. Detailed Implementation

[0019] Several embodiments of this application will now be described in more detail with reference to the accompanying drawings to enable those skilled in the art to implement this application. This application may be embodied in many different forms and for various purposes and should not be limited to the embodiments set forth herein. These embodiments are provided to make this application thorough and complete, and to fully convey the scope of this application to those skilled in the art. The embodiments described do not limit this application.

[0020] Unless otherwise defined, all terms used herein (including technical and scientific terms) shall have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. It will be further understood that terms such as those defined in commonly used dictionaries shall be interpreted as having a meaning consistent with their meaning in the relevant field and / or the context of this specification, and shall not be interpreted in an idealized or overly formal sense unless expressly defined herein.

[0021] Example 1

[0022] Its specific implementation method is combined with the appendix Figure 1 and attached Figure 2 Please provide a detailed explanation.

[0023] Appendix Figure 1 The diagram below shows the structural block diagram of a high-voltage fuse remaining life assessment system based on real-time monitoring, which is provided for an embodiment of the present invention. It illustrates the connection relationship between the three-phase synchronous acquisition and preprocessing module and the life assessment module, and marks the main functional interaction flow of each module.

[0024] Appendix Figure 2 The flowchart of the high-voltage fuse remaining life assessment method based on real-time monitoring provided in the embodiments of the present invention shows the complete steps from selecting and matching current and temperature sensors, synchronously collecting three-phase fuse signals, obtaining attenuation life parameters, and constructing a remaining life assessment model.

[0025] In this embodiment, it includes: The three-phase synchronous acquisition and preprocessing module is configured to acquire three-phase raw signals through synchronously sampled current and temperature sensors, and after low-pass filtering, effectiveness gating and thermal hysteresis compensation processing, output time-aligned and noise-controllable current and temperature rise difference data to provide a reliable data source for subsequent calculations. Specifically, it includes: The hardware selection must be compatible with the high electromagnetic interference and high-potential isolation operating environment of the high-voltage fuse. The specific configuration is as follows: Current acquisition unit: Equipped with three sets of through-hole current transformers (CTs) or Rogowski coils, respectively installed at the incoming terminals of the A / B / C three-phase fuses; Current transformer (CT): Suitable for power frequency (50Hz / 60Hz) power grid scenarios, the transformation ratio range is set to 1.2~1.5 times the rated current of the fuse (for example, for a fuse with a rated current of 100A, a 150A / 5A transformation ratio CT is selected), with a measurement accuracy of 0.5 class, meeting the requirements for calculating the effective value of current.

[0026] Rogowski coils are suitable for complex power grid scenarios containing high-frequency harmonics. They require no iron core, have no risk of magnetic saturation, and have a bandwidth covering 10Hz~1MHz. They can simultaneously acquire power frequency components and transient harmonic currents.

[0027] Isolation requirements: The secondary side of the CT / Rogowski coil adopts opto-isolation technology, with a potential isolation of ≥2kV from the subsequent acquisition circuit, to avoid the impact of high-voltage side faults on the low-voltage acquisition system.

[0028] Temperature acquisition unit: Equipped with three sets of non-contact temperature sensors, which are respectively aligned with the contact surfaces of the moving and stationary contacts of the A / B / C three-phase fuses (temperature-sensitive areas). Infrared temperature probe: response time ≤100ms, temperature range -20℃~200℃, measurement accuracy ±1℃, suitable for unobstructed contact scenarios inside switch cabinets; Fiber Bragg grating temperature sensor: strong anti-electromagnetic interference capability (unaffected by high voltage electric field), temperature measurement range -50℃~300℃, measurement accuracy ±0.5℃, suitable for strong electromagnetic interference and closed scenarios where the contact is blocked.

[0029] Installation requirements: The distance between the sensor and the contact point should be controlled between 5cm and 15cm to ensure that the temperature measurement field of view completely covers the contact surface of the contact point and avoid background temperature interference.

[0030] Synchronous sampling core components: An 8-channel synchronous sampling ADC chip (such as ADS8688) is used, with 3 channels each for current and temperature signals, and the remaining 2 channels reserved for ambient temperature acquisition and calibration. Synchronization mechanism: The sampling clock of the ADC is provided by a high-precision crystal oscillator (frequency stability ±10ppm) or a GPS timing module to ensure that the sampling trigger time deviation of the three-phase current and three-phase temperature is ≤1μs; the sampling rate is set to 200Hz (4 times the power frequency of 50Hz) to satisfy the Nyquist sampling theorem and ensure that the power frequency current signal is free from aliasing distortion. The acquired raw signals are processed in real time, including low-pass filtering, effectiveness gating, and thermal hysteresis compensation. Low-pass filter: filters out high-frequency interference; Algorithm selection: A second-order Butterworth low-pass filter is used, with the cutoff frequency set to 100Hz.

[0031] Function: Filter out second and higher harmonics in the power grid (such as 1kHz harmonics generated by frequency converters), retaining only the 50Hz power frequency current component and slowly changing temperature component, to avoid high-frequency noise causing distortion in subsequent thermoelectric coupling coefficient (TECC) calculations.

[0032] Validity gating: prevents computational divergence; Threshold setting: Preset lower current threshold The value is taken as the rated current of the fuse. 0.1 times; Logic: Only if the effective values ​​of all three-phase currents satisfy , , At that time, start the subsequent Calculation; if the current in any phase is below the threshold (e.g., when the fuse is unloaded), the calculation is blocked to avoid errors caused by the formula. A small denominator can cause the calculation results to diverge.

[0033] Thermal hysteresis compensation: Achieve current-temperature timing alignment; Root cause of the problem: The temperature rise of the fuse contacts lags behind the current change (the Joule heat generated by the current needs to be transferred to the sensor through heat conduction, which involves a time delay), and this delay is the thermal time constant. ; Calibration mechanism: The module has a built-in delay calibration unit. The value of was obtained through offline experimental fitting. In a laboratory environment, a step current was applied to the fuse, and the time it took for the contact temperature to rise from the initial value to 63.2% of the steady-state value was recorded. (Usually 3-5 minutes); Compensation logic: Delay the acquired temperature signal on the time axis The time is then matched with the current signal to ensure the calculation. hour, and For physical quantities within the same time period, this eliminates errors caused by timing mismatches.

[0034] Output preprocessed synchronization data, including: RMS values ​​of three-phase power frequency current. , , The difference between the three-phase contact temperature and the ambient temperature after timing alignment. , , That is, the contact temperature minus the ambient temperature, yielding the corresponding difference.

[0035] The feature vector construction module is configured to calculate the normalized thermo-electric coupling coefficient of each phase based on the preprocessed current and temperature rise data, thus eliminating the interference of load fluctuations on the state judgment. Specifically, it includes: This module is the signal normalization processing center. Its core objective is to transform the physical quantity of current-temperature into a normalized, load-independent thermo-electric coupling coefficient. This enables the comparability of fuse states under different load conditions.

[0036] The aging of a fuse is essentially due to increased contact resistance: according to Joule's law... Contact resistance When the current increases, the same amount of current remains the same. and time Heat generated below Increased volume leads to increased contact temperature. Increase. This module is built upon... The parameter quantifies the temperature rise efficiency generated by a unit current energy and is directly related to the contact resistance state of the fuse.

[0037] For each phase , Real-time calculation of thermal-electric coupling coefficient : ;in, It is the difference between the contact temperature and the ambient temperature (unit: °C), rather than the absolute contact temperature, to eliminate the influence of changes in ambient temperature; The effective value of the three-phase current (unit: The calculation is performed using the root mean square value within one power frequency cycle (20ms), and the formula is as follows: ;in The number of sampling points within one period is given in this scheme. The value is 4.

[0038] The dimensions are ( (Ampere) is a normalized relative parameter that is only related to the contact resistance and heat dissipation conditions of the fuse. Load fluctuation is a core pain point of traditional temperature monitoring methods (for example, when the load on phase A increases, the contact temperature naturally rises, which can easily be misjudged as aging). This module addresses this issue by... The construction solves this problem: When the fuse is in normal condition, the contact resistance Constant, according to the heat balance equation ,Right now and Proportional, therefore The value is basically constant; Example verification is as follows: Normal condition: Load current increases from 50A to 100A. It became four times the original size. From 10℃ to 40℃, The value remains unchanged; Aging condition: When the contact resistance doubles and the load current is 50A, From 10℃ to 20℃, The value increased significantly.

[0039] Output three-phase thermo-electric coupling coefficient , , It serves as the input data source for the differential topology analysis module.

[0040] The differential topology analysis module is configured to perform differential operations with the average thermal-electric coupling coefficient of adjacent phases as a reference, calculate the normalized deviation of the three phases, offset systematic errors such as ambient temperature and sensor drift, achieve accurate location of single-phase aging faults, and output the normalized deviation of the three phases. Specifically, it includes: The operation of a high-voltage three-phase system exhibits symmetry: under normal operating conditions, the contact resistance and heat dissipation conditions of the three-phase fuses are essentially the same, therefore... ≈ ≈ ; When a phase experiences aging failure, its It will deviate significantly from the other two phases.

[0041] This module uses a topology with the average of adjacent phases as a reference, rather than a single fixed reference, and utilizes the symmetry of the three-phase system to offset systematic errors.

[0042] For each phase Calculate its normalized deviation relative to the mean of the other two phases. : The expanded formula is as follows: ; ; ; Results Explanation: In percentage form =0 indicates that the state of this phase is the same as that of the other two phases; >0 indicates that the phase Too large (indicating aging or malfunction); <0 indicates that the phase Smaller than normal (rare, usually due to sensor malfunction).

[0043] This also includes converting measurement errors into system constants and canceling them out, specifically through the elimination of the following two types of errors: Cancellation of systematic disturbances in ambient temperature: Assuming the overall ambient temperature rises ℃, causing all three phases to increase If the value is doubled, then: Assume the original After the change, it becomes ; ; Conclusion: The effect of ambient temperature changes on three-phase... The effects are in the same direction and proportional, and completely cancel each other out after the difference operation. The value remains unchanged; Cancellation of systematic interference from sensor drift: The temperature sensor is slowly drifting, causing three-phase... All increased If the value is doubled, then: Calculated Still 0; Calculation process: Let the original... After the change, it becomes ; ; Conclusion: Sensor drift is a systematic error with consistent effects on all three phases. It is completely canceled out after differential calculation, thus avoiding false alarms.

[0044] Therefore, it can be concluded that only when a single phase experiences physical damage... Only then will the value be significantly non-zero, thereby enabling accurate location of the faulty phase.

[0045] Example: Example: Phase A fuse is aging. Increase by 20%, , Unchanged, let , : ; ; ; Conclusion: Phase A Significantly deviates from zero, B / C phase A value close to zero can be used to directly determine that phase A has an aging fault.

[0046] The second-order trend verification module is configured to perform time-dimensional rate of change analysis and three-phase synchronization verification on the deviation, distinguish between system transient disturbances and single-phase irreversible aging, determine the true fault through the duration threshold, and output a fault confirmation signal. Specifically, it includes: The aging of fuses is a slow, unidirectional, and irreversible process, while transient disturbances to the power grid (such as closing impulses and harmonic fluctuations) are short-term, random, and bidirectional processes. This module addresses this by... Second-order trend analysis (rate of change analysis) distinguishes between the two.

[0047] Step 1: Calculate the rate of change of deviation: Due to the collection It is a discrete-time series, and the first-order backward difference is used instead of the differential to calculate the drift velocity of the deviation. : ; in, The deviation at the current moment; This represents the deviation at the previous moment. The trend analysis period should be 5-10 minutes to avoid interference from high-frequency fluctuations. The rate of change of deviation, expressed in % / min, reflects... The changing trend; Step 2: Synchronization Verification Two key thresholds are set: the drift velocity steady-state threshold. Duration threshold Perform scenario verification, including system transient disturbances and single-phase irreversible aging. Scenario 1: System transient disturbances (such as power grid oscillations): Judgment conditions: , , The absolute values ​​are all greater than Furthermore, the direction of fluctuation is irregular; Processing logic: If the disturbance is determined to be non-faulty, the alarm is locked to avoid false alarms.

[0048] Scenario 2: Single-phase irreversible aging: Judgment criteria: the target phase (e.g., phase A) Persistently greater than (Increasing unidirectionally), and the absolute values ​​of the other two phases are both less than 1 / 2. (In a steady state), and the duration of this state is... ≥ ; Processing logic: If the condition is determined to be true aging, an aging confirmation signal is output.

[0049] Step 3: Normality test For the target phase Statistical analysis of the data was performed to further distinguish between noise and fault trends: Select within a preset time period (the past hour) Data (6 data points in the past hour) =10 minutes); calculate To calculate the mean of the data, for each data point, calculate the deviation from the mean, then calculate the cube of the deviation, and finally sum the cubes of all the data points. This sum is denoted as: ; ; The mean; Simultaneously calculate the sample standard deviation. : ;use -1 is used for unbiased correction; Will and Substituting into the general finite sample skewness formula , It is a correction term for finite samples to avoid bias in skewness calculation caused by small sample size. The skewness coefficient is calculated and the corresponding judgment is made. An aging threshold is set. If the absolute value of the skewness coefficient is greater than the aging threshold, it is judged as aging. A noise threshold is set. If the absolute value of the skewness coefficient is less than the noise threshold, it is judged as measurement noise.

[0050] The life assessment module is configured to build a remaining life model based on fault confirmation signals and deviation thresholds to obtain the remaining life of the fuse. Specifically, it includes: Constructing a remaining life assessment model: ; in, Design the rated life of the fuse (in years); The normalized deviation calculated at the current moment; The critical deviation from the preset end of life; Decay lifetime (unit: years).

[0051] Decaying lifetime The acquisition process includes: Set an overload threshold (1.5 times the rated current), obtain the number of current surges (such as motor starting, downstream short circuit clearing) within a preset time period, and subtract the overload threshold from the current corresponding to each current surge. If the value obtained is greater than 0, it is recorded as the overload surge value; if it is less than 0, it is discarded. Arrange the overload impact values ​​according to the acquisition time, and obtain the time interval between two adjacent overload impact values ​​in turn; preset the cooling time threshold. If the time interval between two adjacent overload impact values ​​is less than the cooling time threshold, calculate the time difference between the two and take the absolute value to obtain the abnormal quantification value. Count all outlier quantization values ​​and take the largest outlier quantization value as the maximum outlier quantization value.

[0052] A scientific overload damage quantification logic was designed for current surge conditions such as motor startup and short circuit clearing.

[0053] By setting overload thresholds to filter effective impact data, and focusing on severe operating conditions where the interval between adjacent overload impacts is less than the cooling time threshold, these continuous impacts that have not been adequately cooled are transformed into abnormal quantitative values. The maximum value is selected as the core parameter, which accurately captures the overload scenarios that have the most significant impact on fuse lifespan and avoids damage assessment bias caused by simply counting the number of impacts.

[0054] The system presets a high-temperature threshold and a maximum allowable duration of high temperature. It then obtains the ambient temperature of the high-voltage fuse within a preset time period that is greater than the high-temperature threshold and the duration of the corresponding ambient temperature that is greater than the maximum allowable duration of high temperature. If the ambient temperature detected at one of two adjacent monitoring time points is lower than the high-temperature threshold, that monitoring time point is removed. The abnormal temperature difference is obtained by subtracting the high temperature threshold from the ambient temperature obtained at each monitoring time point within the preset time period; the abnormal temperature difference is multiplied by the time interval between the corresponding two monitoring time points to obtain the accumulated quantification value. Obtain all accumulated quantified values ​​sequentially and sum them to obtain the total accumulated quantified value; After normalizing the maximum abnormal quantization value and the total accumulated quantization value, a weighted summation is performed to obtain the attenuation coefficient. Weighted summation calculation: Preset weight factors for the maximum abnormal quantization value and the total accumulated quantization value, and multiply the maximum abnormal quantization value and the total accumulated quantization value with their corresponding weight factors to calculate the attenuation coefficient; By presetting multiple sets of attenuation lifetimes and the range of attenuation coefficient values ​​corresponding to each set of attenuation lifetimes, the range of attenuation lifetime values ​​corresponding to the attenuation coefficients will be obtained, and the attenuation lifetime corresponding to the attenuation coefficients will be obtained.

[0055] By combining two key factors that accelerate aging—high temperature accumulation and overload impact—this approach addresses the shortcomings of traditional life assessment models that rely solely on a single electrical parameter and neglect the impact of harsh operating conditions on fuse lifespan.

[0056] Actual operating data such as the duration of ambient temperature exceeding the standard and the overload impact interval are converted into calculable accumulated quantitative values ​​and abnormal quantitative values. Then, through normalization and weighted summation, an attenuation coefficient is formed, so that the remaining life assessment is no longer limited to the theoretical design life, but closely matches the actual service conditions of high-voltage fuses, thereby improving the accuracy and reliability of the assessment results.

[0057] Example 2

[0058] Please see Figure 2 The method for assessing the remaining life of high-voltage fuses based on real-time monitoring includes the following parts: For high-voltage, high-electromagnetic, and high-potential isolation environments, select and adapt current (CT / Rogowski coil) and temperature (infrared / fiber grating) sensors to simultaneously acquire three-phase fuse signals; use low-pass filtering to filter out high-frequency interference, effectiveness gating to avoid calculation divergence, and thermal hysteresis compensation to align the current-temperature timing, and finally output clean and timing-matched three-phase current RMS values ​​and contact-ambient temperature rise differences; Based on the preprocessed current and temperature rise data, the ratio of temperature rise to the square of current in each phase (thermal-electric coupling coefficient) is calculated, and the direct correlation between this coefficient and the contact resistance of the fuse is established. By normalization, the interference of load fluctuation on aging judgment is removed, and three-phase characteristic parameters that can be compared across operating conditions are obtained. By utilizing the operational symmetry of a high-voltage three-phase system, and taking the average value of the thermal-electric coupling coefficient of two adjacent phases as a benchmark, the coefficients of each phase are differentially calculated to obtain the normalized deviation. This calculation is used to offset systematic errors such as changes in ambient temperature and sensor drift, and to accurately locate the single-phase aging fault phase. The normalized deviation is analyzed by the rate of change over time. Combined with the three-phase synchronization check, the transient disturbances of the power grid (such as closing impact) are distinguished from single-phase irreversible aging. Then, by setting a duration threshold, the stable true aging faults are screened out and the fault confirmation signal is output. Based on the fault confirmation signal, the preset deviation threshold, and the decay life parameters obtained by quantifying the abnormal overload impact interval and high temperature accumulation effect, a remaining life assessment model is constructed, and the remaining life of the high voltage fuse is finally calculated.

[0059] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0060] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

[0061] It should be noted that, in this document, the use of relational terms such as "first" and "second" is merely for distinguishing one entity or operation from another, and does not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0062] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0063] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0064] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0065] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0066] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0067] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0068] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A high-voltage fuse remaining life assessment system based on real-time monitoring, characterized in that, include: The three-phase synchronous acquisition and preprocessing module is configured to acquire three-phase raw signals through synchronously sampled current and temperature sensors, and output current and temperature rise difference data after processing. The feature vector construction module is configured to calculate the normalized thermo-electric coupling coefficient of each phase based on the preprocessed current and temperature rise data, thus eliminating the interference of load fluctuations on the state judgment. The differential topology analysis module is configured to perform differential operations with the average thermal-electric coupling coefficient of adjacent phases as a reference, calculate systematic errors, and locate single-phase aging faults. The second-order trend verification module is configured to distinguish between transient disturbances and single-phase irreversible aging in the system, determine true faults by using a duration threshold, and output a fault confirmation signal. The life assessment module is configured to build a remaining life model based on fault confirmation signals and deviation thresholds to obtain the remaining life of the fuse.

2. The high-voltage fuse remaining life assessment system based on real-time monitoring according to claim 1, characterized in that, The three-phase synchronous acquisition and preprocessing module specifically includes: Current acquisition unit: Equipped with three sets of through-type current transformers or Rogowski coils, respectively installed at the incoming terminals of the A / B / C three-phase fuses; Temperature acquisition unit: Equipped with three sets of non-contact temperature sensors, which are respectively aligned with the contact surfaces of the moving and stationary contacts of the A / B / C three-phase fuses; The acquired raw signals are processed in real time, including low-pass filtering, effectiveness gating, and thermal hysteresis compensation. Output preprocessed synchronization data, including: RMS values ​​of three-phase power frequency current. , , The temperature difference between the three-phase contacts after timing alignment and the ambient temperature. , , .

3. The high-voltage fuse remaining life assessment system based on real-time monitoring according to claim 1, characterized in that, The feature vector construction module specifically includes: For each phase , Real-time calculation of thermal-electric coupling coefficient : ;in, This is the difference between the contact temperature and the ambient temperature. This represents the effective value of the three-phase current. The dimensions are It is a normalized relative parameter that is only related to the contact resistance and heat dissipation conditions of the fuse. When the fuse is in normal condition, the contact resistance Constant, according to the heat balance equation ,Right now and Proportional, therefore The value is constant; Output three-phase thermo-electric coupling coefficient , , .

4. The high-voltage fuse remaining life assessment system based on real-time monitoring according to claim 1, characterized in that, The differential topology analysis module specifically includes: For each phase Calculate its normalized deviation relative to the mean of the other two phases. : The expanded formula is as follows: ； ； 。 5. The high-voltage fuse remaining life assessment system based on real-time monitoring according to claim 4, characterized in that, This also includes converting measurement errors into system constants and canceling them out, specifically through the elimination of the following two types of errors: Cancellation of systematic disturbances in ambient temperature: Assuming the overall ambient temperature rises ℃, causing all three phases to increase If the value is doubled, then: Assume the original After the change, it becomes ; ; Conclusion: After changes in ambient temperature, The value remains unchanged; Cancellation of systematic interference from sensor drift: Temperature sensor drift caused three-phase All increased If the value is doubled, then: Calculated Still 0; Conclusion: Sensor drift is a systematic error, with consistent effects on all three phases, and is completely canceled out after differential calculation; Therefore, it can be concluded that only when a single phase experiences physical damage... Only then will the value be non-zero, thereby enabling the location of the faulty phase.

6. The high-voltage fuse remaining life assessment system based on real-time monitoring according to claim 1, characterized in that, The second-order trend verification module specifically includes: The drift velocity of the deviation is calculated using first-order backward difference. ; Set the steady-state threshold for drift velocity Duration threshold Perform scenario verification, including system transient disturbances and single-phase irreversible aging. Select within the preset time period data; calculate To calculate the mean of the data, for each data point, calculate the deviation from the mean, then calculate the cube of the deviation, and finally sum the cubes of all the data points. This sum is denoted as: ; Simultaneously calculate the sample standard deviation. ; Will and Substitute the values ​​into the general finite sample skewness formula to calculate the skewness coefficient and make the corresponding judgment.

7. The high-voltage fuse remaining life assessment system based on real-time monitoring according to claim 1, characterized in that, The life assessment module specifically includes: Constructing a remaining life assessment model: ; in, Design the rated life of the fuse; The normalized deviation calculated at the current moment; The critical deviation from the preset end of life; This refers to the decaying lifetime.

8. The high-voltage fuse remaining life assessment system based on real-time monitoring according to claim 7, characterized in that, Decaying lifetime The acquisition process includes: Set an overload threshold, obtain the number of current surges within a preset time period, and subtract the overload threshold from the current corresponding to each current surge. If the obtained value is greater than 0, it is recorded as the overload surge value. Arrange the overload impact values ​​according to the acquisition time, and sequentially acquire the time interval between two adjacent overload impact values; preset a cooling time threshold. If the time interval between two adjacent overload impact values ​​is less than the cooling time threshold, calculate the time difference between the two to obtain the abnormal quantification value. Count all outlier quantization values ​​and take the largest outlier quantization value as the maximum outlier quantization value.

9. The high-voltage fuse remaining life assessment system based on real-time monitoring according to claim 8, characterized in that, Also includes: The system presets a high temperature threshold and a maximum allowable duration of high temperature, and obtains the ambient temperature of the high-voltage fuse within a preset time period that is greater than the high temperature threshold and the duration of the corresponding ambient temperature that is greater than the maximum allowable duration of high temperature. The abnormal temperature difference is obtained by subtracting the high temperature threshold from the ambient temperature obtained at each monitoring time point within the preset time period; the abnormal temperature difference is multiplied by the time interval between the corresponding two monitoring time points to obtain the accumulated quantification value. Obtain all accumulated quantified values ​​sequentially and sum them to obtain the total accumulated quantified value; After normalizing the maximum abnormal quantization value and the total accumulated quantization value, a weighted summation is performed to obtain the attenuation coefficient. By presetting multiple sets of attenuation lifetimes and the range of attenuation coefficient values ​​corresponding to each set of attenuation lifetimes, the range of attenuation lifetime values ​​corresponding to the attenuation coefficients will be obtained, and the attenuation lifetime corresponding to the attenuation coefficients will be obtained.

10. A method for assessing the remaining life of high-voltage fuses based on real-time monitoring, and a system for assessing the remaining life of high-voltage fuses based on real-time monitoring according to any one of claims 1-9, characterized in that, include: Select appropriate current and temperature sensors to synchronously acquire three-phase fuse signals; Output three-phase current RMS value and contact-ambient temperature rise difference; Based on the preprocessed current and temperature rise data, the ratio of temperature rise to the square of current for each phase is calculated, and the correlation between this coefficient and the contact resistance of the fuse is established to obtain three-phase characteristic parameters that can be compared across operating conditions. Using the average value of the thermal-electric coupling coefficient of two adjacent phases as a benchmark, the coefficients of each phase are differentially calculated to obtain the normalized deviation; the single-phase aging fault phase is located. The normalized deviation is analyzed by the rate of change over time, and the three-phase synchronization is combined with the test to distinguish between transient disturbances in the power grid and irreversible aging of single phases; true aging faults are then identified. By obtaining the attenuation life parameters, constructing the remaining life assessment model, and finally calculating the remaining life of the high-voltage fuse.

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