An isolating switch full-life-cycle digital twin operation and maintenance system and a construction method thereof

Abstract

The application discloses a kind of disconnectors full life cycle digital twin operation and maintenance systems and construction method, it is related to electrical equipment technical field, the method is combined by early screening mechanism of cold state deviation index F1 and structural evolution confirmation mechanism of degradation confirmation index F2, and further constructs layered operation and maintenance strategy and feedback write-back mechanism, forms "signal sensing, structure mapping, degradation confirmation, strategy output and model self-updating" closed-loop operation and maintenance system. On the one hand, F1 realizes the rapid identification of micro-voltage oscillation anomaly, on the other hand, F2 confirms and accelerates the judgment of interface impedance evolution trend, and the synergistic effect can complete risk classification and intervention strategy adjustment before degradation causes obvious temperature rise or operation failure, thereby shortening the abnormal identification response cycle, reducing the probability of false detection and missed detection, and improving the proactivity and initiative of the disconnectors full life cycle operation and maintenance.

Description

Technical Field

[0001] This invention relates to the field of electrical equipment technology, specifically to a digital twin operation and maintenance system and construction method for the entire life cycle of disconnecting switches. Background Technology

[0002] As a critical primary device in substations and traction power supply systems, disconnecting switches bear the functions of electrical isolation and maintenance safety assurance. The contact state of their contacts directly affects the operational safety and reliability of the system. During long-term operation, disconnecting switches spend a significant amount of time in a cold, floating voltage state, i.e., operating under energized conditions but without significant load current. The degradation of the contact interface under this operating state is highly concealed and difficult to identify through traditional temperature rise or current characteristics. Therefore, there is an urgent need to establish a full lifecycle operation and maintenance construction method based on the concept of digital twins to achieve the perception and assessment of cold-state degradation.

[0003] Currently, the assessment of disconnector contact condition mainly relies on temperature rise monitoring, resistance measurement, or current anomaly analysis under load. These methods typically use thermal effects or changes in conduction current as the basis for judgment and are effective to some extent under high load or current-carrying conditions. However, under cold-state floating voltage conditions, because the current flowing through the contacts is extremely small or nearly zero, interface degradation does not produce a significant temperature rise. Traditional infrared thermography, loop resistance testing, and periodic manual inspections are insufficient to promptly reflect early degradation phenomena such as oxide film thickening, contact area reduction, or increased micro-gap. Furthermore, existing monitoring methods mostly remain at the level of single-point signal analysis, lacking a modeling mechanism that combines microscopic electrical disturbances with interface structure evolution, making it difficult to form a continuous state evolution judgment model.

[0004] Under long-term suspended voltage conditions, the contact interface of the contactor is affected by factors such as humidity, oxidation, and mechanical stress relaxation. The actual contact area of ​​the metal gradually decreases, the oxide film thickness increases, and the local electric field distribution becomes uneven, leading to micro-voltage oscillations and transient spike disturbances. Since this stage does not involve obvious heating, the aforementioned interface degradation often goes undetected in its early stages. When degradation progresses further, it may cause abnormal phenomena such as poor contact, enhanced arcing, localized overheating, or even ablation damage during load connection or closing operations. In severe cases, it can lead to switch failure, maloperation, or insulation breakdown accidents. Therefore, establishing a full lifecycle digital twin operation and maintenance method based on micro-voltage oscillation energy spectrum analysis and dynamic surface modeling of interface impedance under cold, low-current conditions is of great significance for early degradation identification and proactive risk control of disconnectors. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a digital twin operation and maintenance system and construction method for the entire lifecycle of disconnecting switches, solving the problems mentioned in the background technology.

[0006] To achieve the above objectives, the present invention provides the following technical solution, comprising the following steps: S1. Set up a collection point on the disconnect switch, acquire the switch status data through the corresponding acquisition device, and transmit the switch status data to the life cycle digital twin operation and maintenance system through the station control communication interface. Then, perform preprocessing in the life cycle digital twin operation and maintenance system to obtain a standardized status dataset. S2. Calculate the cold deviation index F1 based on the standardized state dataset, and perform a preliminary comparative evaluation between the healthy baseline value Fth and the cold deviation index F1. S3. Based on the preliminary comparative evaluation results, trigger the interface impedance evolution layer in the life cycle digital twin operation and maintenance system, map the cold state deviation index F1 to the interface impedance dynamic surface model, update the equivalent interface impedance value Z, and calculate the degradation confirmation index F2. S4. Combine the cold deviation index F1 and the degradation confirmation index F2 for analysis and output the combined results. Then, output the hierarchical operation and maintenance strategy based on the combined results and write the actual operation and maintenance feedback results back to the interface impedance dynamic surface model to update the health baseline data.

[0007] Preferably, S1 includes S11; S11. Set up several collection points on the disconnect switch, and use the equipment set in the collection points to acquire switch status data. Mark the switch status data with a unified timestamp through the bay layer monitoring and control device. After marking with a unified timestamp, encapsulate the switch status data into a standard communication message. After acquiring the standard communication message, access the station control network through the station control communication interface and wirelessly transmit it to the life cycle digital twin operation and maintenance system. The collection points include a first collection point P1, a second collection point P2, a third collection point P3, a fourth collection point P4, and a fifth collection point P5; The switch status data includes voltage waveform data, position status data, auxiliary contact status data, control power ripple data, and cabinet humidity data.

[0008] Preferably, S1 further includes S12; S12. The lifecycle digital twin operation and maintenance system includes a data processing layer, a cold state perception and assessment layer, an interface impedance evolution layer, and a lifecycle strategy control layer. The data processing layer receives switch status data uploaded via the station control communication interface and preprocesses the switch status data to obtain a standardized status dataset. The preprocessing includes data integrity verification, dimensional normalization, and feature extraction and integration. The data integrity verification process uses a timestamp continuity verification algorithm and cyclic redundancy check technology to perform packet sequence continuity detection and bit error detection on the switch state data, and uses a sliding time window comparison method to determine the existence of missing sampling points and duplicate sampling points. When timestamp breaks and abnormal sampling intervals are detected, the corresponding data segments are marked. The dimension normalization process employs a minimum-maximum interval mapping method to scale the intervals of each feature parameter, transforming different physical quantities into dimensionless feature quantities.

[0009] Preferably, S12 further includes S112; S112. After completing the dimensional normalization process, feature extraction and integration processing is performed on the switch state data. This feature extraction and integration process involves extracting the voltage V(t) at time t from the voltage waveform data, calculating the voltage derivative dV(t) / dt using the finite difference method, and then setting a derivative threshold. When the derivative reaches its absolute value... Count once when the value exceeds the derivative threshold, and count the number of times the derivative exceeds the threshold, Ntb. Edge detection and jitter duration determination are performed on the position status data and auxiliary contact status data. The number of repeated flips of the auxiliary contact signal in the stable range within a unit time window is counted to obtain the contact jitter count parameter Dcs. The humidity component in the humidity data inside the cabinet is integrated over time. When the humidity value is higher than the preset baseline humidity, the cumulative sum is calculated to obtain the cumulative humidity exposure Hlj. After feature extraction, the obtained voltage derivative dV(t) / dt, number of derivative exceedances Ntb, number of contact jitters Dcs, and cumulative humidity exposure Hlj are integrated and summarized to obtain a standardized state dataset, which is then input into the cold state perception evaluation layer.

[0010] Preferably, S2 includes S21; S21. In the cold state perception and evaluation layer, receive the standardized state dataset in real time, extract the voltage derivative dV(t) / dt and the number of times the derivative exceeds the threshold Ntb, and calculate the cold state deviation index F1 within the controlled window time interval. The cold-state deviation index F1 is calculated and output using the following algorithm formula; In the formula, te represents the start time of the controlled window determined by the controlled window construction module, ts represents the end time of the controlled window determined by the controlled window construction module, exp represents the exponential function, dt represents the time integral derivative, Tck represents the duration of the controlled window, and Vjz represents the reference voltage of the same type of controlled window in the healthy phase. This represents the mutation density amplification factor, with a value ranging from 0.2 to 0.9. This represents the nonlinear enhancement index, with a value range of 0.2-0.9.

[0011] Preferably, S2 further includes S22; S22. During the healthy operation phase of the disconnector switch, collect sample values ​​of the cold deviation index F1 within all controlled windows, calculate the mean, and obtain the healthy baseline value Fth. During the operational phase, the cold deviation index F1, calculated in real time, will be initially compared and evaluated with the healthy baseline value Fth. The specific comparison details are as follows: When the cold deviation index F1 is less than or equal to the healthy baseline value Fth, it is considered to be in the healthy range. When the cold deviation index F1 is greater than the healthy baseline value Fth, and the three consecutive controlled windows exceed Fth, it is determined to be an abnormal cold deviation range. When the cold state is determined to deviate from the abnormal range, a trigger condition signal is generated to start the interface impedance evolution layer.

[0012] Preferably, S3 includes S31; S31. Construct a dynamic surface model of interface impedance in the interface impedance evolution layer of the lifecycle digital twin operation and maintenance system. The construction process includes: based on electrical contact theory, the contact interface is regarded as a composite contact surface composed of a metal contact area, an oxide film covering area, and a micro-gap electric field area. In the interface impedance evolution layer, the metal contact area, oxide film covering area, and micro-gap electric field area are corresponding to contact conduction unit, interface barrier unit, and electric field coupling unit, respectively. The initial reference value Z0 of the interface equivalent impedance is defined by parameterization. During the healthy phase, the cold deviation index F1 and the corresponding interface voltage disturbance characteristics in multiple controlled windows are collected to establish the mapping relationship between F1 and impedance increment. The impedance update model is constructed by linear incremental mapping to obtain the equivalent interface impedance value Z. The change in equivalent interface impedance Z is calculated using the formula for calculating the change in the change, and the change in interface impedance ΔZ is obtained. The cold deviation index F1 is used as the horizontal axis variable, time t is used as the vertical axis variable, and the change in interface impedance ΔZ is used as the surface height value to establish a dynamic surface model of interface impedance. The real-time cold deviation index F1 is then mapped to the dynamic surface model of the interface impedance, and the equivalent interface impedance value Z(t) at all times t in the continuous evolution is obtained. S3 further includes S32; S32. Based on the obtained equivalent interface impedance value Z(t) at time t, combined with the cold deviation index F1 and the cumulative humidity exposure Hlj, calculate and output the degradation confirmation index F2. The degradation confirmation index F2 is calculated and output using the following algorithm formula: In the formula, ln represents the natural logarithm function, and H0 represents the baseline humidity during the healthy period.

[0013] Preferably, S4 includes S41; S41. After calculating and outputting the degradation confirmation index F2, the life cycle strategy control layer is started. The life cycle strategy control layer extracts the degradation confirmation index F2 during the healthy stage and calculates the average value to extract the healthy stage confirmation threshold F2th. The deviations of the cold state deviation index F1 and the degradation confirmation index F2 are calculated by comparing them with the health baseline value Fth and the health stage confirmation threshold F2th, respectively, to obtain the deviations of the cold state deviation index F1' and the degradation confirmation index F2'. And perform product to construct the portfolio evaluation factor R; Among them, when the combined evaluation factor R≥1, it means that the interface is in a state where both deviation and confirmation are simultaneously established; The health status of the disconnector switch under the current cold-state floating voltage condition is determined by combining the cold-state deviation index deviation F1', the degradation confirmation index deviation F2', and the combined evaluation factor R; the specific combination is as follows: When the deviation of the cold state deviation index F1' is less than 1 and the deviation of the degradation confirmation index F2' is less than 1, it is determined to be in the health monitoring stage; When the deviation of the cold state deviation index F1' is greater than or equal to 1 and the deviation of the degradation confirmation index F2' is less than 1, it is determined to be in the cold state abnormality pending confirmation stage. When the deviation of the cold state deviation index F1' is greater than or equal to 1, the deviation of the degradation confirmation index F2' is greater than or equal to 1, and the combined evaluation factor R is less than or equal to 1, it is determined to be the initial stage of degradation. When the deviation of the cold state deviation index F1' is greater than or equal to 1, the deviation of the degradation confirmation index F2' is greater than or equal to 1, and the combined evaluation factor R is greater than or equal to 1, it is determined to be in the degradation acceleration stage.

[0014] Preferably, S4 further includes S42; S42. Based on the health status of the disconnecting switch after combination, a hierarchical strategy is implemented for output. The specific output results are as follows: When the health monitoring phase is determined, the original controlled window duration Tck remains unchanged. When the cold state is determined to be in the stage of pending confirmation, the controlled window duration Tck acquisition cycle is shortened by 50% from the original controlled window duration Tck, while the population comparison frequency is increased to twice the original frequency, and no less than 3 windows are continuously monitored. When it is determined to be in the early stage of degradation, the controlled window duration Tck is shortened to 25%, and no less than one manual review check is arranged during a low-disturbance period. When the degradation is determined to be in an accelerated degradation phase, maintenance recommendations are prioritized, and the recommended maintenance time is advanced to within 0.5 times the original planned cycle. The subsequent monitoring window cycle is fixed at 25% of the controlled window duration Tck until the degradation trend stabilizes.

[0015] A digital twin operation and maintenance system for the entire life cycle of a disconnector switch includes a data acquisition and mapping module, a cold-state deviation analysis module, an impedance analysis module, and a combined analysis module. The acquisition and mapping module obtains switch status data by setting acquisition points on the disconnect switch and acquiring corresponding acquisition devices. The switch status data is then transmitted to the lifecycle digital twin operation and maintenance system through the station control communication interface. The data is then preprocessed in the lifecycle digital twin operation and maintenance system to obtain a standardized status dataset. The cold-state deviation analysis module calculates the cold-state deviation index F1 based on a standardized state dataset, and sets the health baseline value Fth and the cold-state deviation index F1 for preliminary comparison and evaluation. The resistance analysis module triggers the interface impedance evolution layer in the lifecycle digital twin operation and maintenance system based on the preliminary comparative evaluation results, maps the cold state deviation index F1 to the interface impedance dynamic surface model, updates the equivalent interface impedance value Z, and calculates the degradation confirmation index F2. The combined analysis module performs combined analysis on the cold deviation index F1 and the degradation confirmation index F2, outputs the combined results, and then outputs a hierarchical operation and maintenance strategy based on the combined results. The actual operation and maintenance feedback results are written back to the interface impedance dynamic surface model to update the health baseline data.

[0016] This invention provides a digital twin operation and maintenance system and construction method for the entire lifecycle of disconnect switches. It has the following beneficial effects: (1) This method extracts characteristic parameters such as voltage derivative dV(t) / dt and the number of times the derivative exceeds the threshold Ntb under cold floating voltage conditions, and constructs a cold deviation index F1 to achieve quantitative characterization of the micro-voltage oscillation intensity and fragmentation trend at the contact interface. Compared with existing monitoring methods that rely on temperature rise or abnormal current flow, this scheme can identify early degradation signs such as reduced contact area, thickened oxide film, or increased micro-gap under conditions of no load current and no obvious thermal effect. This breaks through the blind spot of traditional thermal effect monitoring in cold scenarios, realizes early warning under low current environment, and improves the accuracy and sensitivity of state perception during the cold operation phase of disconnecting switches.

[0017] (2) This method introduces a dynamic surface model of interface impedance based on the cold deviation index F1, mapping the signal layer anomaly to the equivalent interface impedance value Z of the structural layer, and calculates the degradation confirmation index F2 in conjunction with the cumulative humidity exposure Hlj, thereby confirming the rate of evolution of the contact interface conductivity. By coupling the impedance change rate with environmental stress, it can effectively distinguish between short-term external disturbances and continuous structural degradation, avoid misjudgment caused by a single signal anomaly, improve the reliability and physical interpretability of degradation identification, and upgrade the digital twin model from "anomaly detection" to "degradation confirmation and evolution tracking".

[0018] (3) This method combines the early screening mechanism of the cold deviation index F1 with the structural evolution confirmation mechanism of the degradation confirmation index F2, and further constructs a hierarchical operation and maintenance strategy and a feedback write-back mechanism to form a closed-loop operation and maintenance system of "signal perception, structural mapping, degradation confirmation, strategy output and model self-updating". On the one hand, F1 enables rapid identification of micro-voltage oscillation anomalies, and on the other hand, F2 confirms and accelerates the judgment of the interface impedance evolution trend. The synergistic effect of the two can complete risk classification and intervention strategy adjustment before degradation causes obvious temperature rise or operational failure, thereby shortening the anomaly identification response cycle, reducing the probability of false detection and missed detection, and improving the foresight and initiative of the operation and maintenance of the disconnector throughout its entire life cycle. Attached Figure Description

[0019] Figure 1 This is a schematic diagram illustrating the steps of a digital twin operation and maintenance construction method for the entire lifecycle of a disconnecting switch according to the present invention. Figure 2 This is a schematic diagram of the process of a digital twin operation and maintenance system for the entire life cycle of a disconnecting switch according to the present invention; Figure 3 This is a schematic diagram showing the spatial distribution of the data collection points; Figure 4 This is a 3D diagram of the dynamic surface model of interface impedance. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] Example 1 Please see Figure 1 This invention provides a method for constructing a digital twin operation and maintenance system for the entire lifecycle of disconnect switches. To achieve the above objectives, this invention employs the following technical solution, comprising the following steps: S1. Set up a collection point on the disconnect switch, acquire the switch status data through the corresponding acquisition device, and transmit the switch status data to the life cycle digital twin operation and maintenance system through the station control communication interface. Then, perform preprocessing in the life cycle digital twin operation and maintenance system to obtain a standardized status dataset. S2. Calculate the cold deviation index F1 based on the standardized state dataset, and perform a preliminary comparative evaluation between the healthy baseline value Fth and the cold deviation index F1. S3. Based on the preliminary comparative evaluation results, trigger the interface impedance evolution layer in the life cycle digital twin operation and maintenance system, map the cold state deviation index F1 to the interface impedance dynamic surface model, update the equivalent interface impedance value Z, and calculate the degradation confirmation index F2. S4. Combine the cold deviation index F1 and the degradation confirmation index F2 for analysis and output the combined results. Then, output the hierarchical operation and maintenance strategy based on the combined results and write the actual operation and maintenance feedback results back to the interface impedance dynamic surface model to update the health baseline data.

[0022] In this embodiment, the method arranges collection points P1 to P5 on the disconnector switch bay side, completes unified timestamp and message encapsulation through the bay layer measurement and control device, and then uploads them to the lifecycle digital twin operation and maintenance system via the station control communication interface. The purpose of this setting is to synchronize "minor voltage disturbances caused by interface degradation" with "mechanical status, power supply ripple, and cabinet humidity stress" to the same time reference, avoiding misjudgments caused by only looking at voltage: for example, short-term spikes may occur when the traction substation bus is switched. Without position status data, auxiliary contact status data, and control power supply ripple data constraints, external disturbances will be regarded as contact degradation. Through controlled windows and integrity verification, abnormal segment elimination, and dimension normalization, such external factors can be eliminated to form a comparable standardized status dataset. In S2, the cold state deviation index F1 is calculated and compared with the healthy baseline Fth. The purpose is not to draw conclusions directly, but to complete "early cold state screening". Physically, under cold-state floating voltage, there is almost no current and no temperature rise. Thickening of the contact oxide film or increase in micro-gap will first manifest as steeper and more fragmented voltage micro-oscillations. F1 quantifies the degree of "disruption of electric field stability". Using Fth as a comparison is to eliminate the sampling gain differences between different sites and ensure that F1 > Fth represents a true deviation rather than a range difference. In S3, after the initial comparison anomaly is triggered, F1 is mapped to the dynamic surface of the interface impedance to obtain the equivalent interface impedance value Z, and then the degradation confirmation index F2 is calculated. The purpose is to transform "signal layer anomaly" into "structural layer degradation confirmation". The physical meaning of Z is the equivalent electrical characterization of the contact interface conductivity and micro-gap coupling effect. F2 uses the evolution rate of Z superimposed with the cumulative humidity exposure to confirm "continuous degradation rather than occasional disturbance". For example, short-term external disturbances may cause F1 to rise, but Z will not rise continuously and humidity exposure will be mismatched. In this case, F2 will not be high, which can avoid false triggering of maintenance. However, when humidity is consistently high and oxide film growth accelerates, Z rises over time, and F2 increases synchronously, allowing for early risk identification. In S4, F1 and F2 are combined and a hierarchical operation and maintenance strategy is output. At the same time, the maintenance or review results are written back to update the baseline. The purpose is to form a closed loop: F1 is responsible for "fast screening," and F2 is responsible for "confirmation and accelerated judgment." Only by combining them can the system achieve both sensitivity and robustness. The strategy-level actions such as shortening the window, increasing the comparison frequency, and early maintenance are corresponding responses to the "degradation speed" and "risk level," thereby transforming the traditional "wait-and-see" approach into "trend-driven pre-intervention." The final improvement is: without changing the hardware, early identification under cold operating conditions is achieved, false alarms and missed alarms are reduced, the interpretability and auditability of operation and maintenance decisions are improved, and the system adaptively converges with the life cycle through write-back updates, maintaining long-term judgment stability.

[0023] Example 2 Please see Figure 3 Specifically: S1 includes S11; S11. Set up several collection points on the disconnect switch, and use the equipment set in the collection points to acquire switch status data. Mark the switch status data with a unified timestamp through the bay layer monitoring and control device. After marking with a unified timestamp, encapsulate the switch status data into a standard communication message. After acquiring the standard communication message, access the station control network through the station control communication interface and wirelessly transmit it to the life cycle digital twin operation and maintenance system. It should be noted that the station control communication interface is not a single hardware device, but refers to a communication connection unit located in the substation or traction substation automation system, used to connect data collected at the bay level or equipment level to the station control layer network. The data collection points include the first data collection point P1, the second data collection point P2, the third data collection point P3, the fourth data collection point P4, and the fifth data collection point P5; The switch status data includes voltage waveform data, position status data, auxiliary contact status data, control power ripple data, and cabinet humidity data; The first acquisition point P1 is set at the secondary circuit terminal of the voltage transformer in the interval where the disconnecting switch is located, and high-resolution voltage waveform data is obtained through the existing voltage sampling channel of the voltage transformer. The second acquisition point P2 is set at the end of the travel inside the operating mechanism of the disconnector switch, and position status data is acquired through the limit switch and angular displacement sensor. The third acquisition point P3 is set at the terminal of the auxiliary contact circuit of the disconnector switch, and the auxiliary contact status data is obtained through the auxiliary contact detection module. The fourth data acquisition point, P4, is located at the control power input terminal of the disconnect switch, and acquires control power ripple data through the power monitoring module. The fifth data collection point, P5, is located in the upper middle part of the control cabinet of the disconnector switch, and acquires humidity data inside the cabinet through a humidity sensor.

[0024] S1 also includes S12; S12, The lifecycle digital twin operation and maintenance system includes a data processing layer, a cold state perception and assessment layer, an interface impedance evolution layer, and a lifecycle strategy control layer. The data processing layer receives switch status data uploaded via the station control communication interface and preprocesses the switch status data to obtain a standardized status dataset. Preprocessing includes data integrity verification, dimensional normalization, and feature extraction and integration. The data integrity verification process uses a timestamp continuity verification algorithm and cyclic redundancy check technology to perform packet sequence continuity detection and bit error detection on the switch status data. It also uses a sliding time window comparison method to determine the presence of missing and duplicate sampling points. When timestamp breaks and abnormal sampling intervals are detected, the corresponding data segments are marked. The dimension normalization process uses the minimum-maximum interval mapping method to scale each feature parameter across intervals, transforming different physical quantities into dimensionless feature quantities to facilitate subsequent multidimensional feature fusion calculations.

[0025] S12 also includes S112; S112. After completing the dimensional normalization process, feature extraction and integration processing is performed on the switch state data. This process involves extracting the voltage V(t) at time t from the voltage waveform data and calculating the voltage derivative dV(t) / dt using the finite difference method. Then, by setting a derivative threshold, when the derivative reaches its absolute value... Each time a value exceeds the derivative threshold, a count is made, and the number of times the derivative exceeds the threshold, Ntb, is obtained. The threshold is determined by the mean and standard deviation of the derivative during the healthy phase. It should be noted that the derivative threshold range is selected by covering 99.7% of the fluctuation range during the healthy phase. Edge detection and jitter duration determination are performed on the position status data and auxiliary contact status data. The number of repeated flips of the auxiliary contact signal in the stable range within a unit time window is counted to obtain the contact jitter count parameter Dcs. The humidity component in the humidity data inside the cabinet is integrated over time. When the humidity value is higher than the preset reference humidity, the cumulative sum is calculated to obtain the cumulative humidity exposure Hlj, which is used to represent the long-term environmental stress intensity. After feature extraction, the obtained voltage derivative dV(t) / dt, number of derivative exceedances Ntb, number of contact jitters Dcs, and cumulative humidity exposure Hlj are integrated and summarized to obtain a standardized state dataset, which is then input into the cold state perception evaluation layer.

[0026] In this embodiment, the method sets up first acquisition points P1 to fifth acquisition points P5 at key locations of the disconnecting switch, and acquires voltage waveform data, position status data, auxiliary contact status data, control power supply ripple data, and cabinet humidity data respectively. Then, the bay-level monitoring and control device completes unified timestamp marking and standard communication message encapsulation, and uploads the data to the lifecycle digital twin operation and maintenance system via the station control communication interface. The purpose is to align four types of information—"electrical disturbance, mechanical positioning status, control power supply quality, and environmental stress"—to the same time reference, avoiding errors caused by isolated judgment of single signals. For example, bus switching or external electromagnetic interference may cause short-term voltage waveform spikes. If only P1 is acquired, external disturbances may be misjudged as contact interface degradation. By simultaneously introducing P2 and P3, the switch can be confirmed to be in a stable positioning state. Introducing P4 can eliminate sampling pseudo-fluctuations caused by control power supply ripple. Introducing P5 can quantify the driving conditions of humidity stress on oxide film growth, reducing the risk of false alarms from the data source. After entering the data processing layer, data integrity verification is achieved through timestamp continuity check and cyclic redundancy check, which can identify packet loss, incorrect packets, and time breaks, avoiding abnormally high derivatives due to missing points. Then, dimensional normalization is performed through minimum-maximum interval mapping, making different dimensional parameters such as voltage derivative, jitter count, and humidity exposure fusionable. Subsequently, in the feature extraction and integration processing, the voltage derivative dV(t) / dt is calculated using finite difference and the number of times the derivative exceeds the threshold Ntb is counted (the threshold covers 99.7% of the fluctuation range in the healthy stage), which physically corresponds to "the abrupt change event caused by the destruction of electric field stability under cold-state suspension voltage". The contact jitter count parameter Dcs is obtained through edge detection, which corresponds to "mechanical positioning stability and contact consistency". The cumulative humidity exposure Hlj is obtained by integrating the humidity exceeding the benchmark, which corresponds to "long-term environmental stress of oxide film growth and micro-gap risk". The resulting standardized state dataset can be used for subsequent cold-state deviation calculations, and can also significantly improve data credibility and comparison consistency, achieving the effect of "separating external disturbances, sampling artifacts and real degradation signals", thereby improving the accuracy of cold-state degradation identification, reducing the false judgment rate, and providing an auditable and reproducible input basis for subsequent digital twin modeling.

[0027] Example 3 Please see Figure 2 Specifically: S2 includes S21; S21. In the cold state sensing and evaluation layer, the standardized state dataset is received in real time, and the voltage derivative dV(t) / dt and the number of times the derivative exceeds the threshold Ntb are extracted. The cold state deviation index F1 in the controlled window time interval is calculated, and the degree of deviation of the voltage transient disturbance intensity caused by the microstructure change of the contact interface under the cold state floating voltage condition from the healthy state is analyzed. The cold deviation index F1 is calculated and output using the following algorithm formula; In the formula, te represents the start time of the controlled window determined by the controlled window construction module, ts represents the end time of the controlled window determined by the controlled window construction module, exp represents the exponential function, dt represents the time integral derivative, Tck represents the duration of the controlled window, Tck = te - ts, and Vjz represents the reference voltage of the same type of controlled window in the healthy phase. This represents the mutation density amplification factor, ranging from 0.2 to 0.9, used to make the "fragmentation" trend explicit. This represents the nonlinear enhancement index, with a value range of 0.2-0.9, used to amplify the "peak changes caused by micro-gap at the interface"; Among them, the nonlinear enhancement index Based on the adaptive determination of the peak state coefficient of the voltage derivative sequence in the healthy phase, it is used to enhance the voltage spike changes caused by the micro-gap at the interface in fractional order. Mutation density amplification factor It is adaptively generated based on the ratio of mutation rate in the healthy stage to the current stage, and is used to adjust the weight of the influence of mutation density per unit time on the cold state deviation index. and All values ​​are limited to between 0 and 1 to ensure model stability and physical interpretability; The initial source of the formula: The cold-state deviation index F1 is based on the combination of signal processing theory and electromagnetic transient physics. Mathematically, the rate of change of a signal is a fundamental tool for characterizing the degree of transient changes in a signal; physically, the rate of change of voltage with respect to time directly reflects the steepness of transient electric field disturbances. When the contact interface evolves from a state of actual metal contact to a state of oxide film or micro-gap, local electric field concentration and micro-discharge behavior will cause sudden spikes and micro-oscillations in the voltage waveform. Therefore, the derivative term becomes the most sensitive characterization quantity. The window integral form originates from L... p Energy measurement theory is used to convert local peak changes into an overall intensity index within a window; meanwhile, mutation event density is derived from the event counting model in statistics, which uses the number of events per unit time to characterize the degree of "fragmentation" and uses an exponential mapping to represent the nonlinear growth characteristics of risk. Physical sensitivity of the derivative term: Compared to directly analyzing electric V(t), the derivative term |dV(t) / dt| is more sensitive to "sudden changes, spikes, and abrupt changes". When the number of interfacial gaps increases or the oxide film thickness changes, the uneven distribution of the electric field will lead to enhanced transient disturbances, but the voltage amplitude itself may change very little. At this time, the derivative term can significantly amplify these abrupt changes, thereby capturing signs of cold degradation in advance. Therefore, the derivative reflects the degree of transient disruption of electric field stability. Window integration summarization is used: a single spike may be sporadic noise or external disturbance and does not indicate a change in the interface structure; by integrating the derivative within a controlled window, local sudden behavior can be transformed into an overall intensity index. This summarization method has two functions: eliminating the influence of single-point anomalies on the judgment; and characterizing the overall energy level of micro-oscillations during cold suspension; therefore, the integral term represents the overall intensity of the interface electric field disturbance in the cold stage. A health benchmark ratio structure is adopted: Different sites have different voltage levels, sampling channel gains, and hardware amplification factors. Directly using absolute values ​​will lead to incomparability. By constructing the derivative energy of the health benchmark window and forming a ratio, we can achieve the following: eliminate individual equipment differences; unify dimensions; obtain dimensionless comparison indicators; and support cross-window and cross-time comparisons. Therefore, the ratio term represents the amplification factor of the current cold-state disturbance intensity relative to the healthy state. Introducing the number of mutations and employing an exponential mapping: The characteristics of contact interface degradation are not only manifested in "larger" peaks, but also in "more frequent and more fragmented" peaks. A simple energy ratio can only characterize intensity changes, but cannot characterize the "fragmentation trend." By defining a ratio, the density of mutation events per unit time is characterized, and an exponential mapping is used to achieve the following: when the mutation density increases slightly, the exponential term changes little; when the mutation density increases significantly, the exponential term accelerates. The exponential mapping is derived from the risk growth model in reliability engineering and is used to represent nonlinear acceleration phenomena. By binding it to the window scale, the exponent remains dimensionless, ensuring physical rationality and model stability; therefore, the exponent term represents the nonlinear amplification factor of the interface fragmentation trend.

[0028] S2 also includes S22; S22. During the healthy operation phase of the disconnector switch, collect sample values ​​of the cold deviation index F1 in all controlled windows, calculate the mean, and obtain the healthy baseline value Fth. During the operational phase, the cold deviation index F1, calculated in real time, will be initially compared and evaluated with the healthy baseline value Fth. The specific comparison details are as follows: When the cold deviation index F1 is less than or equal to the healthy baseline value Fth, it is considered to be in the healthy range. When the cold deviation index F1 is greater than the healthy baseline value Fth, and the three consecutive controlled windows exceed Fth, it is determined to be an abnormal cold deviation range. When a cold state is determined to deviate from the abnormal range, a trigger condition signal is generated to activate the interface impedance evolution layer for further degradation confirmation.

[0029] In this embodiment, the cold-state perception evaluation layer of the method receives and processes the standardized state dataset in real time through windowing. Within each controlled window Tck, it extracts the voltage derivative dV(t) / dt and the number of times the derivative exceeds the threshold Ntb, constructing a cold-state deviation index F1 to quantify the amplification of transient electric field disturbances relative to the healthy state under cold-state floating voltage conditions. The derivative is used instead of the direct voltage amplitude because contact degradation under cold-state conditions does not lead to significant changes in voltage amplitude, but it can cause local electric field concentration and abrupt changes in micro-oscillations. If only the V(t) amplitude is compared, slight degradation can easily be overlooked. By performing window integration on the derivative and superimposing the mutation density index mapping, "occasional spikes" and "continuous fragmentation trends" can be distinguished. For example, external grid disturbances may cause a large spike within a single window. Without window integration and density amplification mechanisms, it may be misjudged as degradation. However, after statistical analysis using the exponential term and controlled window, such single disturbances will not significantly increase F1, thus avoiding false alarms. In S22, the health baseline value Fth is obtained through multi-window statistics during the health phase, and "three consecutive controlled windows exceeding the threshold" is used as the anomaly judgment condition. The purpose is to further filter out sporadic fluctuations. In actual operation, short-term electromagnetic interference or communication jitter may cause a single window F1 to exceed Fth. If subsequent processing is triggered immediately, it will increase unnecessary maintenance actions. Through continuous judgment, it can be ensured that the interface impedance evolution layer is triggered only after the anomaly has persistent characteristics, which physically corresponds to "the interface structure has indeed undergone stable changes". Through the above implementation method, a front-end identification mechanism from "transient changes in electric field" to "structural degradation screening" is realized, enabling the system to detect early contact interface anomalies in the cold state stage without current and temperature rise, reducing the dependence on traditional thermal effect monitoring. At the same time, through windowed statistics and continuous judgment strategy, the false judgment rate is significantly reduced, the judgment stability and reliability are improved, and a reliable triggering basis is provided for subsequent degradation confirmation and hierarchical maintenance decision-making, thereby improving the foresight and refinement level of the entire life cycle management of disconnect switches.

[0030] Example 4 Please see Figure 4 Specifically: S3 includes S31; S31. Construct a dynamic surface model of interface impedance in the interface impedance evolution layer of the life cycle digital twin operation and maintenance system. The dynamic surface model of interface impedance is used to describe the impedance evolution law of the contact interface under the cold floating voltage state. The construction process includes: based on electrical contact theory, the contact interface is regarded as a composite contact surface composed of a metal contact area, an oxide film covering area, and a micro-gap electric field area. In the interface impedance evolution layer, the metal contact area, oxide film covering area, and micro-gap electric field area are corresponding to contact conduction unit, interface barrier unit, and electric field coupling unit. The initial reference value Z0 of the interface equivalent impedance is defined by parameterization. During the healthy phase, the cold state deviation index F1 and the corresponding interface voltage disturbance characteristics are collected in multiple controlled windows. The mapping relationship between F1 and impedance increment is established. The impedance update model is constructed by linear incremental mapping to obtain the equivalent interface impedance value Z. The equivalent interface impedance value Z is obtained by the following impedance update model: Z = Z0·(1+a·(F1-1)), where a is the impedance sensitivity coefficient, which ranges from 0 to 1 and is used to represent the proportion of the influence of the cold state deviation degree on the interface impedance change. The change in equivalent interface impedance Z is calculated using the formula for calculating the change, and the change in interface impedance ΔZ is obtained. The cold deviation index F1 is used as the horizontal axis variable, time t is used as the vertical axis variable, and the change in interface impedance ΔZ is used as the surface height value to establish a dynamic surface model of interface impedance. The dynamic surface model of interface impedance is used to describe the trend of interface impedance change with the degree of cold deviation and the cumulative effect of time. The real-time cold deviation index F1 is then mapped to the dynamic surface model of the interface impedance, and the equivalent interface impedance value Z(t) at all times t in the continuous evolution is obtained. It should be noted that the interface impedance estimate Z represents the equivalent electrical characterization of the overall conductivity and interface electric field coupling characteristics of the disconnector contact interface under cold floating voltage conditions. In simpler terms, Z is a "virtual but physically interpretable" quantity used to represent the current electrical health of the contact interface. Based on the theory of electrical contact, the contact interface between two metal contacts is not an ideal surface contact, but rather: multiple micro-contact points, an oxide film layer, micro-gap, and local electric field concentration. Therefore, the electrical behavior of the interface can be equivalent to: the actual contact resistance of the metal (conduction component), the oxide film impedance (blocking component), and the micro-gap capacitance effect (coupling component) can be combined into an equivalent "interface composite impedance"; so the essence of Z comes from: electrical contact theory + equivalent circuit model. S3 also includes S32; S32. Based on the obtained equivalent interface impedance value Z(t) at time t, combined with the cold deviation index F1 and the cumulative humidity exposure Hlj, calculate and output the degradation confirmation index F2. The degradation confirmation index F2 is calculated and output using the following algorithm: In the formula, ln represents the natural logarithm function, and H0 represents the baseline humidity during the healthy period; The degradation confirmation index F2 is constructed based on electrical contact theory and the stress-degradation coupling concept in reliability engineering. Its core purpose is to confirm whether the contact interface is in a state of continuous degradation under cold floating voltage conditions. The interface impedance estimate Z is used to characterize the equivalent electrical conductivity of the contact interface. Its value change reflects the combined effects of the actual metal contact area, oxide film thickness, and micro-gap electric field coupling effect. When the oxide film thickens or the number of micro-gap increases, the interface equivalent impedance will increase over time. Therefore, the impedance change rate |dZ(t) / dt| is used as the dynamic index of degradation evolution. Its physical meaning is to represent the evolution rate of interface conductivity degradation. The larger the change rate, the faster the degradation process. Relying solely on the rate of change of impedance is insufficient to distinguish between short-term disturbances and long-term degradation. Therefore, the ratio of cumulative humidity exposure Hcumulative to the health baseline Hbenchmark is introduced, and ln(1+Hlj / H0) is used for mapping. This logarithmic function is derived from the stress accumulation model in reliability engineering. It is characterized by monotonically increasing and having saturation characteristics, which can reflect the promoting effect of environmental stress on the degradation process, while avoiding distortion caused by linear amplification. The physical meaning of this term is to represent the constraining effect of long-term environmental humidity stress on the growth of interfacial oxide film and the probability of micro-discharge. From a dimensional perspective, the unit of |dZ(t) / dt| is dimensionless, and ln(1+Hlj / H0) is also dimensionless. The product of the two remains reasonably dimensionless, which is in line with engineering common sense. This index has both a clear physical meaning and can serve as a bridge variable between state evolution and operation and maintenance decisions in the digital twin model, realizing a closed-loop logic from signal deviation to structural degradation confirmation.

[0031] In this embodiment, the interface impedance evolution layer of this method first decomposes the contact interface into three interpretable structures based on electrical contact theory: "contact conduction unit, interface barrier unit, and electric field coupling unit." The initial reference value Z0 of the equivalent interface impedance in the healthy phase is used as a reference. Then, the cold-state deviation index F1 obtained from S2 screening is mapped to the impedance increment to obtain the equivalent interface impedance value Z(t). The purpose of this is to transform "voltage waveform anomaly" (signal layer) into a state variable of "conductivity degradation" (structural layer): because external power grid disturbances may cause F1 to rise temporarily, but will not cause the interface conductivity to continuously decrease; by introducing Z(t), it is possible to directly observe whether the interface shows a continuous deterioration trend. Subsequently, a dynamic surface model of interface impedance is established with ΔZ as the surface height and F1 and time t as the surface coordinates. Essentially, this solidifies the "deviation degree—time cumulative effect—impedance change" into a traceable evolution trajectory, making it easier to see whether the degradation is sporadic or cumulative. Furthermore, in S32, the rate of change of Z(t) |dZ(t) / dt| is used as evidence of degradation kinetics, and a logarithmic mapping term of the cumulative humidity exposure Hlj is superimposed to address the problem that "short-term fluctuations may still be mistaken for degradation if only the rate of change of impedance is considered": for example, if the equipment experiences a short-term operational shock that causes Z(t) to fluctuate, but the humidity inside the cabinet remains at a low level for a long time, the logarithmic term is small, and F2 will not be amplified, thus avoiding false confirmation; conversely, when the humidity is high for a long time and the conditions for oxide film growth are met, Z(t) continues to rise and the rate of change increases, and F2 increases synchronously, which can confirm the degradation entering the evolution stage earlier. Through this "F1, Z(t) to F2" link, a closed-loop progression from early anomaly screening to structural degradation confirmation is achieved, which improves the physical interpretability and anti-interference capability of the judgment, reduces false alarms and false negatives, and provides a quantifiable and auditable basis for subsequent hierarchical operation and maintenance strategies.

[0032] Example 5 Please see Figure 2 Specifically: S4 includes S41; S41. After calculating and outputting the degradation confirmation index F2, start the life cycle strategy control layer. The life cycle strategy control layer extracts the degradation confirmation index F2 during the healthy phase, calculates the average value, and extracts the healthy phase confirmation threshold F2th. The deviations of the cold state deviation index F1 and the degradation confirmation index F2 are calculated by comparing them with the health baseline value Fth and the health stage confirmation threshold F2th, respectively, to obtain the deviations of the cold state deviation index F1' and the degradation confirmation index F2'. And perform product to construct the portfolio evaluation factor R; Among them, when the combined evaluation factor R≥1, it means that the interface is in a state where both deviation and confirmation are simultaneously established; The health status of the disconnector switch under the current cold-state floating voltage condition is determined by combining the cold-state deviation index deviation F1', the degradation confirmation index deviation F2', and the combined evaluation factor R; the specific combination is as follows: When the deviation of the cold state deviation index F1' is less than 1 and the deviation of the degradation confirmation index F2' is less than 1, it is determined to be in the health monitoring stage; When the deviation of the cold state deviation index F1' is greater than or equal to 1 and the deviation of the degradation confirmation index F2' is less than 1, it is determined to be in the cold state abnormality pending confirmation stage. When the deviation of the cold state deviation index F1' is greater than or equal to 1, the deviation of the degradation confirmation index F2' is greater than or equal to 1, and the combined evaluation factor R is less than or equal to 1, it is determined to be the initial stage of degradation. When the deviation of the cold state deviation index F1' is greater than or equal to 1, the deviation of the degradation confirmation index F2' is greater than or equal to 1, and the combined evaluation factor R is greater than or equal to 1, it is determined to be in the degradation acceleration stage.

[0033] S4 also includes S42; S42. Based on the health status of the disconnecting switch after combination, a hierarchical strategy is implemented for output. The specific output results are as follows: When the health monitoring phase is determined, the original controlled window duration Tck remains unchanged. When the cold state is determined to be in the stage of pending confirmation, the controlled window duration Tck acquisition cycle is shortened by 50% from the original controlled window duration Tck, while the population comparison frequency is increased to twice the original frequency, and no less than 3 windows are continuously monitored. When it is determined to be in the early stage of degradation, the controlled window duration Tck is shortened to 25%, and no less than one manual review check is arranged during a low-disturbance period. When the degradation is determined to be in an accelerated degradation phase, maintenance recommendations are prioritized, and the recommended maintenance time is advanced to within 0.5 times the original planned cycle. The subsequent monitoring window cycle is fixed at 25% of the controlled window duration Tck until the degradation trend stabilizes.

[0034] In this embodiment, during the implementation of S4, the lifecycle strategy control layer first uses the degradation confirmation index F2 of the healthy stage to calculate the average and obtain the confirmation threshold F2th. Then, it divides the cold-state deviation index F1 and the degradation confirmation index F2 by the healthy baseline value Fth and the confirmation threshold F2th, respectively, to obtain the deviations F1' and F2'. The product is then used to construct a combined evaluation factor R, achieving joint judgment of "screening signal strength" and "structural degradation evidence" on the same scale. The purpose of this setting is to avoid erroneous actions caused by single-index decision-making: for example, external disturbances may cause F1'≥1, but the interface impedance has not continued to evolve (F2'<1). Directly triggering maintenance would result in over-maintenance. The combined judgment limits such cases to the "cold-state abnormality pending confirmation stage," shortening the controlled window duration Tck by 50%, increasing the group comparison frequency to twice, and continuously monitoring no less than 3 windows to confirm the trend with higher resolution, thereby improving response speed and controlling false alarm costs. Conversely, when both F1' and F2' are ≥1, it indicates that the micro-oscillation deviation corresponds to the actual degradation of the interface conductivity. The system then uses R to distinguish whether the degradation has entered an accelerated phase: R < 1 is considered "early stage of degradation," and the Tck is shortened to 25% of its original value, with at least one manual review scheduled during a low-disturbance period to prevent misjudgment of acceleration due to short-term fluctuations; R ≥ 1 is considered "accelerated degradation," and a maintenance priority is directly given, with the recommended maintenance time advanced to within 0.5 times the original planned cycle, while the monitoring cycle is fixed at 25% of Tck until the trend stabilizes, thereby shifting risk control forward. The physical meaning of this hierarchical strategy is that F1' corresponds to electric field disturbance deviation, F2' corresponds to interface impedance evolution, and R corresponds to the "coupling strength between deviation and evolution." Through the combination of these three, a closed-loop control is achieved from "anomaly detection, degradation confirmation, and acceleration judgment" to "intensified monitoring, review, and maintenance," ultimately improving the accuracy of cold-state degradation handling, reducing the risk of falsely triggered maintenance and missed detection, and significantly improving the matching degree between maintenance actions and degradation levels.

[0035] Example 6 Please see Figure 1 and Figure 2 A digital twin operation and maintenance system for the entire life cycle of disconnect switches, comprising a data acquisition and mapping module, a cold-state deviation analysis module, an impedance analysis module, and a combined analysis module; The data acquisition and mapping module acquires switch status data by setting acquisition points on the disconnect switch and using corresponding acquisition devices. It then transmits the switch status data to the lifecycle digital twin operation and maintenance system via the station control communication interface. The data is preprocessed in the lifecycle digital twin operation and maintenance system to obtain a standardized status dataset. The cold-state deviation analysis module calculates the cold-state deviation index F1 based on a standardized state dataset and sets a health baseline value Fth to perform a preliminary comparative assessment with the cold-state deviation index F1. The resistance analysis module triggers the interface impedance evolution layer in the lifecycle digital twin operation and maintenance system based on the preliminary comparative evaluation results, maps the cold state deviation index F1 to the interface impedance dynamic surface model, updates the equivalent interface impedance value Z, and calculates the degradation confirmation index F2. The combined analysis module combines the cold deviation index F1 and the degradation confirmation index F2 for analysis and outputs the combined results. Based on the combined results, it outputs a hierarchical operation and maintenance strategy and writes the actual operation and maintenance feedback results back to the interface impedance dynamic surface model to update the health baseline data.

[0036] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention.

Claims

1. A method for constructing a digital twin operation and maintenance system for the entire lifecycle of a disconnecting switch, characterized in that: Includes the following steps: S1. Set up a collection point on the disconnect switch, acquire the switch status data through the corresponding acquisition device, and transmit the switch status data to the life cycle digital twin operation and maintenance system through the station control communication interface. Then, perform preprocessing in the life cycle digital twin operation and maintenance system to obtain a standardized status dataset. S2. Calculate the cold deviation index F1 based on the standardized state dataset, and perform a preliminary comparative evaluation between the healthy baseline value Fth and the cold deviation index F1. S3. Based on the preliminary comparative evaluation results, trigger the interface impedance evolution layer in the life cycle digital twin operation and maintenance system, map the cold state deviation index F1 to the interface impedance dynamic surface model, update the equivalent interface impedance value Z, and calculate the degradation confirmation index F2. S4. Combine the cold deviation index F1 and the degradation confirmation index F2 for analysis and output the combined results. Then, output the hierarchical operation and maintenance strategy based on the combined results and write the actual operation and maintenance feedback results back to the interface impedance dynamic surface model to update the health baseline data.

2. The method for constructing a digital twin operation and maintenance system for the entire lifecycle of a disconnecting switch according to claim 1, characterized in that: S1 includes S11; S11. Set up several collection points on the disconnect switch, and use the equipment set in the collection points to acquire switch status data. Mark the switch status data with a unified timestamp through the bay layer monitoring and control device. After marking with a unified timestamp, encapsulate the switch status data into a standard communication message. After acquiring the standard communication message, access the station control network through the station control communication interface and wirelessly transmit it to the life cycle digital twin operation and maintenance system. The collection points include a first collection point P1, a second collection point P2, a third collection point P3, a fourth collection point P4, and a fifth collection point P5; The switch status data includes voltage waveform data, position status data, auxiliary contact status data, control power ripple data, and cabinet humidity data.

3. The method for constructing a digital twin operation and maintenance system for the entire lifecycle of a disconnecting switch according to claim 2, characterized in that: S1 further includes S12; S12. The lifecycle digital twin operation and maintenance system includes a data processing layer, a cold state perception and assessment layer, an interface impedance evolution layer, and a lifecycle strategy control layer. The data processing layer receives switch status data uploaded via the station control communication interface and preprocesses the switch status data to obtain a standardized status dataset. The preprocessing includes data integrity verification, dimensional normalization, and feature extraction and integration. The data integrity verification process uses a timestamp continuity verification algorithm and cyclic redundancy check technology to perform packet sequence continuity detection and bit error detection on the switch state data, and uses a sliding time window comparison method to determine the existence of missing sampling points and duplicate sampling points. When timestamp breaks and abnormal sampling intervals are detected, the corresponding data segments are marked. The dimension normalization process employs a minimum-maximum interval mapping method to scale the intervals of each feature parameter, transforming different physical quantities into dimensionless feature quantities.

4. The method for constructing a digital twin operation and maintenance system for the entire lifecycle of a disconnecting switch according to claim 3, characterized in that: S12 also includes S112; S112. After completing the dimensional normalization process, feature extraction and integration processing is performed on the switch state data. This feature extraction and integration process involves extracting the voltage V(t) at time t from the voltage waveform data, calculating the voltage derivative dV(t) / dt using the finite difference method, and then setting a derivative threshold. When the derivative reaches its absolute value... Count once when the value exceeds the derivative threshold, and count the number of times the derivative exceeds the threshold, Ntb. Edge detection and jitter duration determination are performed on the position status data and auxiliary contact status data. The number of repeated flips of the auxiliary contact signal in the stable range within a unit time window is counted to obtain the contact jitter count parameter Dcs. The humidity component in the humidity data inside the cabinet is integrated over time. When the humidity value is higher than the preset baseline humidity, the cumulative sum is calculated to obtain the cumulative humidity exposure Hlj. After feature extraction, the obtained voltage derivative dV(t) / dt, number of derivative exceedances Ntb, number of contact jitters Dcs, and cumulative humidity exposure Hlj are integrated and summarized to obtain a standardized state dataset, which is then input into the cold state perception evaluation layer.

5. The method for constructing a digital twin operation and maintenance system for the entire lifecycle of a disconnecting switch according to claim 4, characterized in that: S2 includes S21; S21. In the cold state perception and evaluation layer, receive the standardized state dataset in real time, extract the voltage derivative dV(t) / dt and the number of times the derivative exceeds the threshold Ntb, and calculate the cold state deviation index F1 within the controlled window time interval. The cold-state deviation index F1 is calculated and output using the following algorithm formula; In the formula, te represents the start time of the controlled window determined by the controlled window construction module, ts represents the end time of the controlled window determined by the controlled window construction module, exp represents the exponential function, dt represents the time integral derivative, Tck represents the duration of the controlled window, and Vjz represents the reference voltage of the same type of controlled window in the healthy phase. This represents the mutation density amplification factor, with a value ranging from 0.2 to 0.

9. This represents the nonlinear enhancement index, with a value range of 0.2-0.

9.

6. The method for constructing a digital twin operation and maintenance system for the entire lifecycle of a disconnecting switch according to claim 5, characterized in that: S2 further includes S22; S22. During the healthy operation phase of the disconnector switch, collect sample values ​​of the cold deviation index F1 in all controlled windows, calculate the mean, and obtain the healthy baseline value Fth. During the operational phase, the cold deviation index F1, calculated in real time, will be initially compared and evaluated with the healthy baseline value Fth. The specific comparison details are as follows: When the cold deviation index F1 is less than or equal to the healthy baseline value Fth, it is considered to be in the healthy range. When the cold deviation index F1 is greater than the healthy baseline value Fth, and the three consecutive controlled windows exceed Fth, it is determined to be an abnormal cold deviation range. When the cold state is determined to deviate from the abnormal range, a trigger condition signal is generated to start the interface impedance evolution layer.

7. The method for constructing a digital twin operation and maintenance system for the entire lifecycle of a disconnecting switch according to claim 6, characterized in that: S3 includes S31; S31. Construct a dynamic surface model of interface impedance in the interface impedance evolution layer of the lifecycle digital twin operation and maintenance system. The construction process includes: based on electrical contact theory, the contact interface is regarded as a composite contact surface composed of a metal contact area, an oxide film covering area, and a micro-gap electric field area. In the interface impedance evolution layer, the metal contact area, oxide film covering area, and micro-gap electric field area are corresponding to contact conduction unit, interface barrier unit, and electric field coupling unit, respectively. The initial reference value Z0 of the interface equivalent impedance is defined by parameterization. During the healthy phase, the cold deviation index F1 and the corresponding interface voltage disturbance characteristics in multiple controlled windows are collected to establish the mapping relationship between F1 and impedance increment. The impedance update model is constructed by linear incremental mapping to obtain the equivalent interface impedance value Z. The change in equivalent interface impedance Z is calculated using the formula for calculating the change in the change, and the change in interface impedance ΔZ is obtained. The cold deviation index F1 is used as the horizontal axis variable, time t is used as the vertical axis variable, and the change in interface impedance ΔZ is used as the surface height value to establish a dynamic surface model of interface impedance. The real-time cold deviation index F1 is then mapped to the dynamic surface model of the interface impedance, and the equivalent interface impedance value Z(t) at all times t in the continuous evolution is obtained. S3 further includes S32; S32. Based on the obtained equivalent interface impedance value Z(t) at time t, combined with the cold deviation index F1 and the cumulative humidity exposure Hlj, calculate and output the degradation confirmation index F2. The degradation confirmation index F2 is calculated and output using the following algorithm formula: In the formula, ln represents the natural logarithm function, and H0 represents the baseline humidity during the healthy period.

8. The method for constructing a digital twin operation and maintenance system for the entire lifecycle of a disconnecting switch according to claim 7, characterized in that: S4 includes S41; S41. After calculating and outputting the degradation confirmation index F2, the life cycle strategy control layer is started. The life cycle strategy control layer extracts the degradation confirmation index F2 during the healthy stage and calculates the average value to extract the healthy stage confirmation threshold F2th. The deviations of the cold state deviation index F1 and the degradation confirmation index F2 are calculated by comparing them with the health baseline value Fth and the health stage confirmation threshold F2th, respectively, to obtain the deviations of the cold state deviation index F1' and the degradation confirmation index F2'. And perform product to construct the portfolio evaluation factor R; Among them, when the combined evaluation factor R≥1, it means that the interface is in a state where both deviation and confirmation are simultaneously established; The health status of the disconnector switch under the current cold-state floating voltage condition is determined by combining the cold-state deviation index deviation F1', the degradation confirmation index deviation F2', and the combined evaluation factor R; the specific combination is as follows: When the deviation of the cold state deviation index F1' is less than 1 and the deviation of the degradation confirmation index F2' is less than 1, it is determined to be in the health monitoring stage; When the deviation of the cold state deviation index F1' is greater than or equal to 1 and the deviation of the degradation confirmation index F2' is less than 1, it is determined to be in the cold state abnormality pending confirmation stage. When the deviation of the cold state deviation index F1' is greater than or equal to 1, the deviation of the degradation confirmation index F2' is greater than or equal to 1, and the combined evaluation factor R is less than or equal to 1, it is determined to be the initial stage of degradation. When the deviation of the cold state deviation index F1' is greater than or equal to 1, the deviation of the degradation confirmation index F2' is greater than or equal to 1, and the combined evaluation factor R is greater than or equal to 1, it is determined to be in the degradation acceleration stage.

9. A method for constructing a digital twin operation and maintenance system for the entire lifecycle of a disconnecting switch according to claim 8, characterized in that: S4 further includes S42; S42. Based on the health status of the disconnecting switch after combination, a hierarchical strategy is implemented for output. The specific output results are as follows: When the health monitoring phase is determined, the original controlled window duration Tck remains unchanged. When the cold state is determined to be in the stage of pending confirmation, the controlled window duration Tck acquisition cycle is shortened by 50% from the original controlled window duration Tck, while the population comparison frequency is increased to twice the original frequency, and no less than 3 windows are continuously monitored. When it is determined to be in the early stage of degradation, the controlled window duration Tck is shortened to 25%, and no less than one manual review check is arranged during a low-disturbance period. When the degradation is determined to be in an accelerated degradation phase, maintenance recommendations are prioritized, and the recommended maintenance time is advanced to within 0.5 times the original planned cycle. The subsequent monitoring window cycle is fixed at 25% of the controlled window duration Tck until the degradation trend stabilizes.

10. A digital twin operation and maintenance system for the entire lifecycle of a disconnecting switch, applied to the digital twin operation and maintenance construction method for the entire lifecycle of a disconnecting switch as described in any one of claims 1-9, characterized in that: It includes a data acquisition and mapping module, a cold-state deviation analysis module, a resistance analysis module, and a combined analysis module; The acquisition and mapping module obtains switch status data by setting acquisition points on the disconnect switch and acquiring corresponding acquisition devices. The switch status data is then transmitted to the lifecycle digital twin operation and maintenance system through the station control communication interface. The data is then preprocessed in the lifecycle digital twin operation and maintenance system to obtain a standardized status dataset. The cold-state deviation analysis module calculates the cold-state deviation index F1 based on a standardized state dataset, and sets the health baseline value Fth and the cold-state deviation index F1 for preliminary comparison and evaluation. The resistance analysis module triggers the interface impedance evolution layer in the lifecycle digital twin operation and maintenance system based on the preliminary comparative evaluation results, maps the cold state deviation index F1 to the interface impedance dynamic surface model, updates the equivalent interface impedance value Z, and calculates the degradation confirmation index F2. The combined analysis module performs combined analysis on the cold deviation index F1 and the degradation confirmation index F2, outputs the combined results, and then outputs a hierarchical operation and maintenance strategy based on the combined results. The actual operation and maintenance feedback results are written back to the interface impedance dynamic surface model to update the health baseline data.

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