Fault analysis method and system of power supply system based on state analysis

Abstract

The invention relates to the technical field of state monitoring, in particular to a power supply system fault analysis method and system based on state analysis. The method comprises the following steps: acquiring substation equipment data; performing load structure analysis based on the substation equipment data to obtain substation load structure data; identifying an overload structure based on the substation load structure data to obtain overload structure data; detecting winding turn-to-turn short circuit based on the overload structure data to obtain winding turn-to-turn short circuit data; determining a winding insulation deterioration degree based on the winding turn-to-turn short circuit data; based on the insulation degradation degree of the winding, carrying out an impact voltage-withstanding test to generate impact voltage-withstanding data; and detecting abnormal fusion welding of the contact based on the overload structure data to obtain abnormal fusion welding data of the contact. According to the invention, the fault detection accuracy and early warning response efficiency of the power supply system are improved based on the state monitoring technology.

Description

Technical Field

[0001] The present invention relates to the technical field of condition monitoring, and particularly to a fault analysis method and system for a power supply system based on condition analysis. Background Art

[0002] Substation equipment and busbar systems include equipment such as transformers, circuit breakers, disconnectors, capacitors, and reactors, which are used for voltage conversion, power distribution, and fault protection to ensure stable power supply. Traditional power system fault analysis methods have a single monitoring means and incomplete data acquisition. They usually rely on limited sensors and off-line detection means, and cannot achieve all-round and real-time condition monitoring, resulting in blind spots in data collection and making it difficult to accurately capture sudden faults or early deterioration signs. The data analysis method lags behind and lacks intelligence. It mainly relies on empirical models and simple threshold judgments, and is difficult to process complex condition data. It lacks the in-depth mining ability of intelligent algorithms, making the accuracy and robustness of fault identification relatively low. There is a lack of a highly targeted fault diagnosis mechanism. Usually, general electrical parameter analysis means are used without combining multi-dimensional factors such as load structure, overload condition, insulation deterioration, and impulse withstand voltage characteristics, resulting in insufficient accuracy of fault location and affecting operation and maintenance decisions. It is difficult to effectively predict and warn of faults. It mainly relies on regular inspections or single-point measurements, lacks predictive maintenance capabilities based on trend analysis and state evolution, and is difficult to detect potential risks in a timely manner. It often deals with problems only after faults occur, increasing operation and maintenance costs and accident risks. The ability to identify complex faults is limited. In the face of complex faults caused by the coupling of multiple factors such as arc faults, insulation breakdown, and contact welding, traditional methods are difficult to effectively separate different fault sources, lack comprehensive diagnostic capabilities, and are prone to misjudgment or missed judgment. Summary of the Invention

[0003] Based on this, it is necessary for the present invention to provide a fault analysis method and system for a power supply system based on condition analysis to solve at least one of the above technical problems.

[0004] To achieve the above object, a fault analysis method for a power supply system based on condition analysis includes the following steps:

[0005] Step S1: Obtain substation equipment data; perform load structure analysis based on the substation equipment data to obtain substation load structure data; identify the overload load structure based on the substation load structure data to obtain overload load structure data;

[0006] Step S2: Detect inter-turn short circuit of the winding based on the overload load structure data to obtain inter-turn short circuit data of the winding; determine the degree of insulation deterioration of the winding based on the inter-turn short circuit data of the winding; perform impulse withstand voltage test based on the degree of insulation deterioration of the winding to generate impulse withstand voltage data;

[0007] Step S3: Detect abnormal welding of the contact based on the overload load structure data to obtain abnormal welding data of the contact; perform analysis on the damage of the contact material according to the abnormal welding data of the contact to obtain damage data of the contact material; measure the dielectric loss angle based on the damage data of the contact material, and evaluate the degree of contact contamination according to the dielectric loss angle;

[0008] Step S4: Conduct open - circuit fault analysis according to the degree of contact contamination and the impulse withstand voltage data to obtain open - circuit fault data; generate a fault alarm based on the open - circuit fault data and upload it to the power supply system to execute the fault early - warning task.

[0009] Through multi - dimensional data analysis and condition monitoring, the present invention can achieve all - round and real - time fault diagnosis of substation equipment, effectively overcoming the limitations of traditional power system fault analysis methods. First, by collecting substation equipment data and analyzing the load structure, the overload load structure can be identified in a timely manner, thus preventing system failures caused by abnormal loads. Secondly, through the detection of winding turn - to - turn short - circuit data, not only can potential short - circuit problems of the winding be discovered, but also impulse withstand voltage tests can be carried out according to the degree of winding insulation deterioration to evaluate the voltage impact resistance of the winding, preventing equipment failures caused by insulation deterioration. For the fault diagnosis of contacts, this method can accurately identify the damage degree of the contacts and evaluate their contamination situation through the detection of abnormal welding of the contacts and the analysis of material damage, providing a precise basis for further equipment maintenance. Through the combined analysis of the degree of contact contamination and impulse withstand voltage data, the occurrence of open - circuit faults can be accurately determined, and timely fault alarms can be generated to avoid the spread of faults and equipment damage. This method conducts multi - dimensional analysis based on multiple factors, significantly improving the accuracy and robustness of fault identification. At the same time, by combining information such as load structure, overload situation, and insulation deterioration, the root cause of the fault can be accurately located, improving the accuracy of diagnosis. With the help of these analyses, potential faults can be effectively predicted and early - warned, improving the operation and maintenance efficiency of substations and reducing the repair cost after the occurrence of faults. Through intelligent analysis means, this method realizes more refined condition monitoring and fault early - warning, reducing the deficiencies of traditional methods that rely on manual experience. Especially in the face of complex faults, different fault sources can be effectively distinguished, reducing the risk of misjudgment or missed judgment, and ultimately enhancing the stability and reliability of the power supply system.

[0010] Preferably, step S1 is specifically as follows:

[0011] Step S11: Obtain substation equipment data;

[0012] Step S12: Analyze the substation equipment structure based on the substation equipment data; identify the core power structure according to the substation equipment structure; identify the auxiliary power structure according to the substation equipment structure;

[0013] Step S13: Perform bus connection analysis based on the core power structure and the auxiliary power structure to obtain bus connection data;

[0014] Step S14: Construct a substation equipment connection structure based on the core power structure, the auxiliary power structure, and the bus connection data;

[0015] Step S15: Perform load flow simulation based on the substation equipment connection structure to obtain substation load structure data;

[0016] Step S16: Identify the overloaded load structure based on the substation load structure data to obtain overloaded load structure data.

[0017] By acquiring substation equipment data and parsing the equipment structure, the present invention can comprehensively understand the composition of the substation and the relationships between various equipment, thereby avoiding the limitations of insufficient understanding of the system structure and incomplete data acquisition in traditional methods. By identifying the core power structure and the auxiliary power structure, the functions and interdependencies of various types of equipment can be clearly determined, providing an accurate basis for subsequent fault diagnosis and predictive maintenance. Bus connection analysis can effectively reveal the electrical connection conditions of the bus system and provide an important basis for constructing the equipment connection structure, thereby helping the system quickly locate the source of problems when a fault occurs. Performing load flow simulation based on the equipment connection structure can achieve load analysis of substation equipment, further identify the overloaded load structure, timely detect the overloaded parts in the power grid, and reduce the risk of equipment damage due to overload. The intelligent and multi-dimensional data analysis in this process enables the system to monitor and analyze the equipment status in real time, avoiding the limitations of relying on traditional inspections and single-point measurements, and can dynamically adjust the system operation strategy according to the changes in the load structure and equipment status, improving the fault warning and handling capabilities. Through this comprehensive data collection and analysis method, the accuracy and robustness of fault identification are effectively improved, avoiding misjudgment or missed judgment problems caused by the lack of in-depth data mining and intelligent algorithm support in traditional fault analysis, enhancing the overall safety and stability of the power supply system, and reducing the operation and maintenance costs and the risk of sudden accidents.

[0018] Preferably, step S16 is specifically as follows:

[0019] Step S161: Calculate the load rate based on the substation load structure data; divide the substation load structure data according to the load rate to obtain high-load-rate structure data;

[0020] Step S162: Calculate the load time of the high-load-rate structure data;

[0021] Step S163: Calculate the current density of the high-load-rate structure data;

[0022] Step S164: Determine the overload load structure data for the high load rate structure data based on the load time and current density, and obtain the overload load structure data.

[0023] By calculating the load rate based on the substation load structure data, the present invention can effectively evaluate the load condition of the substation, reveal the regularity of the load distribution, and provide a basis for identifying high load areas. By dividing the substation load structure data into high load rate structures, it is possible to accurately locate the areas with higher load rates and timely discover potential overload risks. This division of high load areas helps to identify the bottlenecks in the equipment's bearing capacity, avoiding the problem that traditional methods cannot discover these high load areas due to data collection blind spots, and thus preventing equipment damage caused by overload. Calculating the load time and current density of the high load rate structure data can further refine the evaluation of high load areas, understand the load duration and current pressure in these areas, provide key data for load overload prediction, and reduce the uncertainty in traditional experience-based analysis methods. Through the analysis of the load time and current density, it is possible to accurately determine whether there is an overload load structure, and thus provide an accurate basis for subsequent fault warning and risk assessment. Overall, this process can comprehensively improve the monitoring ability of the substation load structure through multi-dimensional load analysis, combining factors such as time and current density, optimize the equipment operation status, enhance the fault prediction ability of the power system, effectively reduce the risk of faults occurring, and be able to better allocate resources and give early warnings to ensure the stable operation of the power system.

[0024] Preferably, the detection of winding inter-turn short circuit in step S2 includes:

[0025] Collect the current sensing data of the overload load structure data;

[0026] Perform signal conditioning on the current sensing data to obtain conditioned current sensing signal data;

[0027] Draw a current distribution map based on the conditioned current sensing signal data;

[0028] Calculate the winding heat source based on the current distribution map to obtain winding heat source data;

[0029] Obtain the winding heat dissipation path and insulation material data;

[0030] Construct a winding thermal equivalent model based on the winding heat dissipation path and insulation material data;

[0031] Input the winding heat source data into the winding thermal equivalent model and generate a winding temperature field;

[0032] Perform winding insulation aging assessment based on the winding temperature field to obtain winding insulation aging data;

[0033] Diagnose short - circuit faults based on winding insulation aging data to obtain inter - turn short - circuit data of the winding.

[0034] The present invention can effectively eliminate noise and interference by collecting current sensing data of overload load structure data and performing signal conditioning, ensuring the accuracy of current data and providing high - quality signal input for subsequent analysis. The conditioned current signal can accurately reflect load changes, helping to more precisely identify overload conditions. Based on these conditioned current signal data, an electric current distribution map is drawn, which can vividly show the distribution of current in the system, identify current - intensive areas, provide key data for calculating the heat source of the winding, further determine the position and magnitude of the heat source generated during current overload, and thus provide an accurate basis for subsequent thermal analysis. By obtaining the winding heat dissipation path and insulation material data and constructing a thermal equivalent model of the winding, the thermal behavior of the winding can be accurately simulated, thereby predicting the temperature change of the winding and its impact on the insulation material. By inputting the winding heat source data into the thermal equivalent model to generate a winding temperature field, the temperature rise of the winding under actual load conditions can be accurately evaluated, and further analyze the impact of temperature rise on the aging of the insulation material, providing data support for early fault warning. According to the temperature field data, the winding insulation aging is evaluated, which can clearly identify the degree of insulation aging, help to timely detect the risk of insulation degradation, and prevent short - circuit faults caused by insulation aging. On this basis, by diagnosing short - circuit faults, the inter - turn short - circuit problem of the winding can be effectively identified, providing accurate fault information for equipment maintenance, reducing the occurrence of faults, improving the operation reliability of power equipment, and ensuring the stability and safety of the power system.

[0035] Preferably, determining the degree of winding insulation deterioration in step S2 includes:

[0036] Calculate the short - circuit impedance based on the inter - turn short - circuit data of the winding to obtain short - circuit impedance data;

[0037] Conduct impedance change analysis based on the preset standard impedance data and the short - circuit impedance data to obtain impedance change data;

[0038] Conduct high - frequency pulse current simulation according to the inter - turn short - circuit data of the winding to obtain pulse current data;

[0039] Calculate the pulse amplitude according to the pulse current data; calculate the single - shot partial discharge amount according to the pulse amplitude; perform time accumulation based on the single - shot partial discharge amount to obtain the total discharge amount;

[0040] Evaluate the severity of the discharge according to the impedance change data and the total discharge amount;

[0041] Statistically calculate the winding heat based on the severity of the discharge;

[0042] Determine the degree of winding insulation deterioration according to the winding heat.

[0043] The short-circuit impedance data obtained by calculating the inter-turn short-circuit data of the winding in the present invention can accurately reflect the impedance characteristics in the current path, helping to identify whether there is a local short-circuit condition. Based on the short-circuit impedance data and the preset standard impedance data for impedance change analysis, the change trend of the impedance can be effectively identified, providing a basis for diagnosing winding short-circuit faults and local hot-spot areas, thereby more accurately locating the fault source and real-time monitoring the health status of the equipment. Using the inter-turn short-circuit data of the winding for high-frequency pulse current simulation can simulate the instantaneous current fluctuations that occur during the short-circuit fault, obtain pulse current data, and by analyzing the amplitudes of these pulse current data, the pulse amplitude can be further calculated, and the occurrence and severity of the partial discharge phenomenon can be evaluated. The amount of each partial discharge can be obtained according to the calculated pulse amplitude, and the total discharge amount can be obtained through time accumulation, which can comprehensively evaluate the degree of influence of the discharge process on the winding insulation, and further provide important data for predicting the deterioration of the winding insulation. Combining the impedance change data and the total discharge amount to evaluate the severity of the discharge, thereby judging the health status of the winding and the fault risk. This process helps to improve the accuracy of fault prediction, timely discover potential risks and take necessary maintenance measures. Statistically analyzing the winding heat based on the severity of the discharge provides support for further analyzing the winding temperature rise and thermal damage, and then determining the degree of deterioration of the winding insulation through the analysis of the winding heat, helping to achieve accurate insulation aging assessment and early identification of potential fault risks. The combination of this series of steps makes the fault diagnosis more accurate and the intelligent level higher, thus greatly improving the operation safety and operation and maintenance efficiency of power equipment.

[0044] Preferably, the impulse withstand voltage test in step S2 includes:

[0045] Determining the insulation deteriorated winding based on the degree of winding insulation deterioration, and using a high-frequency current probe to measure the impulse current of the insulation deteriorated winding to obtain impulse current data;

[0046] Performing envelope detection on the impulse current data to generate an envelope signal;

[0047] Identifying the decaying envelope signal based on the envelope signal;

[0048] Calculating the envelope decay rate of the decaying envelope signal;

[0049] Evaluating the insulation withstand ability of the insulation deteriorated winding according to the envelope decay rate to obtain winding insulation withstand data;

[0050] Performing impulse withstand voltage determination based on the winding insulation withstand data to obtain impulse withstand voltage data.

[0051] By determining the insulation deteriorated windings based on the degree of winding insulation deterioration and measuring their impulse currents, the present invention can accurately identify the severely damaged windings, and thus conduct targeted further monitoring and analysis. The impulse current data measured by the high-frequency current probe can capture the impulse current characteristics in detail, providing a preliminary basis for evaluating the withstand capacity of the windings. Envelope detection is performed on the impulse current data to generate an envelope signal, which can clearly show the change trend of the current signal, especially the attenuation phenomenon, helping to accurately identify the key indicators during the current attenuation process, thereby revealing the change of the winding insulation performance. Based on the envelope signal, the decaying envelope signal is further identified and the envelope decay rate is calculated, providing a quantitative basis for analyzing the decay speed of the winding insulation, which can reflect the aging degree of the insulating material. By evaluating the insulation withstand capacity of the windings through the envelope decay rate, it can be determined whether the insulation still has the ability to withstand the impulse, thus providing a scientific basis for the subsequent impulse withstand voltage test. Through this process, the impulse withstand voltage performance of the windings can be accurately determined, providing guarantee for the long-term operation of the equipment, ensuring that the equipment can withstand sudden current impulses, and reducing accidents caused by insulation failure. This series of steps can improve the accuracy and intelligent level of equipment fault diagnosis, achieve more effective early warning and fault prediction, thereby reducing the operation and maintenance costs and improving the operation safety of the substation.

[0052] Preferably, step S3 is specifically as follows:

[0053] Step S31: Extract the overload contact structure data based on the overload load structure data;

[0054] Step S32: Conduct an overload current application simulation according to the contact structure data to obtain the overload current contact data; calculate the temperature rise value of the contacts of the overload current contact data; calculate the contact voltage drop value of the overload current contact data;

[0055] Step S33: Conduct a welding determination based on the contact temperature rise value and the contact voltage drop value to obtain the welding data;

[0056] Step S34: Calculate the contact welding energy based on the welding data; conduct an abnormal welding determination on the contact welding energy according to the preset standard contact welding energy to obtain the abnormal contact welding data;

[0057] Step S35: Identify the abnormal contact welding area based on the abnormal contact welding data;

[0058] Step S36: Irradiate the abnormal contact welding area with X-rays to generate an X-ray energy spectrum; detect the surface oxides of the contacts based on the X-ray energy spectrum;

[0059] Step S37: Conduct a simulation of applying a metallographic etchant to the abnormal contact welding area to obtain the surface corrosion area of the contacts; identify the molten recrystallization area based on the surface corrosion area of the contacts;

[0060] Step S38: Integrate the contact material damage based on the oxide on the contact surface and the molten recrystallization region to obtain contact material damage data;

[0061] Step S39: Measure the dielectric loss angle based on the contact material damage data, and evaluate the degree of contact contamination according to the dielectric loss angle.

[0062] By extracting the overloaded contact structure data based on the overload load structure data, the present invention can provide detailed basic data for the overload condition of the contact, which provides reliable data support for subsequent fault prediction and analysis. Simulating the application of overcurrent to the contact structure can accurately obtain the overcurrent contact data, and further calculate the contact temperature rise value and the contact voltage drop value, which helps to analyze the thermal effect and electrical performance of the contact under overload conditions. These data are crucial for evaluating the reliability of the contact and can timely reveal whether there are problems such as overheating and poor electrical contact of the contact. By judging the welding based on the temperature rise value and the voltage drop value, it is possible to effectively identify whether the contact is welded, and thus provide an accurate basis for contact maintenance and replacement. By calculating the welding energy and judging the abnormal welding, by comparing with the preset standard welding energy, it is possible to identify whether the contact is in an abnormal working state, thereby effectively preventing further faults caused by contact welding. Identifying the abnormal welding area based on the abnormal contact welding data and irradiating these areas with X-rays can effectively detect whether there is oxide on the contact surface. Further, by simulating with a metallographic etchant, the molten recrystallization region can be identified, and the damage degree of the contact surface can be analyzed in detail. These steps help to comprehensively understand the physical and chemical deterioration of the contact, help to predict the occurrence of contact faults in advance, and perform timely maintenance or replacement on it. Finally, measuring the dielectric loss angle based on the contact material damage data and evaluating the degree of contact contamination according to the dielectric loss angle can quantitatively evaluate the contamination and deterioration status of the contact, ensuring the long-term stable operation of substation equipment. This series of steps greatly improves the accuracy of fault identification, can realize the all-round monitoring and prediction of the contact and related equipment, reduces the risk of equipment failures, and improves the reliability and safety of the power system.

[0063] Preferably, step S39 is specifically as follows:

[0064] Step S391: Identify the damaged contact material based on the contact material damage data, and apply an alternating voltage to the damaged contact material to obtain alternating voltage data;

[0065] Step S392: Collect the current data of the damaged contact material based on the alternating voltage data; calculate the current phase difference based on the current data of the damaged contact material;

[0066] Step S393: Calculate the active power based on the AC voltage data and the current phase difference; calculate the reactive power based on the AC voltage data and the current phase difference; calculate the dielectric loss angle based on the active power and the reactive power;

[0067] Step S394: Establish a pollution assessment level model based on the dielectric loss angle;

[0068] Step S395: Determine the contact contamination degree for the contact material damage data according to the pollution assessment level model, and generate the contact contamination degree.

[0069] The present invention can identify the damaged contact material based on the contact material damage data and apply an AC voltage thereto, so as to simulate the electrical behavior of the contact under actual operating conditions in real time, thereby obtaining the electrical response data of the contact. This provides intuitive current characteristic data for subsequent diagnosis and helps to accurately evaluate the health status of the contact. By collecting the current data of the damaged contact material based on the AC voltage data and combining with the calculation of the current phase difference, the electrical characteristics of the contact material can be deeply understood, especially for identifying the early signs of contact damage. Calculating the active power and the reactive power, and further calculating the dielectric loss angle based on these data can provide key parameters of contact damage and reveal the performance degradation of the contact material under overload or harsh working conditions. The calculation of these parameters enables the quantitative evaluation of the pollution and deterioration state of the contact material, improving the accuracy and reliability of fault identification. By establishing a pollution assessment level model, the pollution degree of the contact can be classified and evaluated based on the dielectric loss angle, and then precise decision-making support can be provided for operation and maintenance to ensure timely maintenance or replacement. The finally generated contact contamination degree data provides a clear judgment basis for the operation and maintenance personnel, making the equipment maintenance of the substation more scientific and accurate, reducing unnecessary equipment downtime and maintenance costs, and at the same time improving the stability and safety of the power system. This series of steps helps to achieve the comprehensive health monitoring and intelligent early warning of the contact and related components, providing a guarantee for the efficient operation of the power system.

[0070] Preferably, step S4 is specifically as follows:

[0071] Step S41: Perform contact surface topography detection according to the contact contamination degree to obtain contact surface topography data;

[0072] Step S42: Measure the contact wear amount according to the contact surface topography data; extract the high-contact-wear area of the contact wear amount;

[0073] Step S43: Identify the continuous high-value current according to the impulse withstand voltage data;

[0074] Step S44: Identify the instantaneous drop voltage according to the impulse withstand voltage data;

[0075] Step S45: Determine an arc based on the continuous high-value current and the instantaneous voltage drop to obtain arc data;

[0076] Step S46: Count the arc duration of the arc data;

[0077] Step S47: Determine an open-circuit fault based on the high-wear area of the contact and the arc duration to obtain open-circuit fault data;

[0078] Step S48: Generate a fault alarm based on the open-circuit fault data and upload it to the power supply system to execute a fault early warning task.

[0079] According to the present invention, by detecting the surface topography of the contact based on the degree of contact contamination, detailed information on the surface condition of the contact can be obtained, providing accurate data for further wear and damage assessment. This step can help detect minor defects on the contact surface in a timely manner, providing an effective basis for subsequent fault prediction and early warning. By measuring the wear amount of the contact and extracting the high-wear area, the most severely worn part can be accurately identified, providing a clear direction for regular inspection and local repair. By identifying continuous high-value current and instantaneous voltage drop, the performance of the contact under high load or abnormal conditions can be detected, revealing potential electrical fault risks. The arc determination is based on the data of continuous high-value current and instantaneous voltage drop, which helps to detect the initial signs of arc faults and take timely measures to avoid further equipment damage or accidents. Counting the duration of the arc helps to further evaluate the danger of the arc and the degree of damage to the equipment, providing a basis for subsequent maintenance decisions. By combining the high-wear area of the contact and the arc duration, an accurate open-circuit fault determination can be made to ensure that equipment faults can be captured at an early stage, reducing downtime and maintenance costs. Finally, by generating a fault alarm and uploading it to the power supply system, the operation and maintenance personnel can be notified in real time and the fault early warning task can be started, improving the fault response speed and processing efficiency of the system, thereby ensuring the stable operation of the power system and the reliability of the equipment.

[0080] Preferably, this specification further provides a fault analysis system for a power supply system based on state analysis, which is used to execute the fault analysis method for a power supply system based on state analysis as described above. The fault analysis system for a power supply system based on state analysis includes:

[0081] An overload load structure identification module, configured to obtain substation equipment data; perform load structure analysis based on the substation equipment data to obtain substation load structure data; identify an overload load structure based on the substation load structure data to obtain overload load structure data;

[0082] The impulse withstand voltage test module is used to detect the inter-turn short circuit of the winding based on the overload load structure data to obtain the inter-turn short circuit data of the winding; determine the degree of winding insulation deterioration based on the inter-turn short circuit data of the winding; perform an impulse withstand voltage test based on the degree of winding insulation deterioration to generate impulse withstand voltage data;

[0083] The contact contamination degree evaluation module is used to detect abnormal contact welding based on the overload load structure data to obtain abnormal contact welding data; perform an analysis of contact material damage based on the abnormal contact welding data to obtain contact material damage data; measure the dielectric loss angle based on the contact material damage data, and evaluate the contact contamination degree according to the dielectric loss angle;

[0084] The fault alarm generation module is used to perform an open circuit fault analysis based on the contact contamination degree and the impulse withstand voltage data to obtain open circuit fault data; generate a fault alarm based on the open circuit fault data and upload it to the power supply system to execute the fault warning task.

[0085] The fault analysis system of the power supply system based on state analysis of the present invention can implement any one of the fault analysis methods of the power supply system based on state analysis of the present invention, and is used as a medium for coordinating the operations and signal transmissions between each module. With the fault analysis method of the power supply system based on state analysis, the internal modules of the system cooperate with each other, improving the accuracy of fault detection and the early warning response efficiency of the power supply system. Description of the Drawings

[0086] Other features, objects, and advantages of the present invention will become more apparent by reading the detailed description of the non-limiting embodiments with reference to the following drawings:

[0087] Figure 1 It is a schematic flow chart of the steps of a fault analysis method for a power supply system based on state analysis of the present invention;

[0088] Figure 2 It is a detailed schematic flow chart of step S1 in the present invention;

[0089] Figure 3 It is a detailed schematic flow chart of step S16 in the present invention;

[0090] The realization, functional characteristics, and advantages of the object of the present invention will be further described with reference to the embodiments and the drawings. Detailed Embodiments

[0091] The technical method of the present invention patent will be clearly and completely described below with reference to the drawings. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of them. All other embodiments obtained by those skilled in the art within the scope of the present invention without creative efforts belong to the scope of protection of the present invention.

[0092] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus repeated descriptions thereof will be omitted. Some of the block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities may be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor methods and / or microcontroller methods.

[0093] It should be understood that although terms such as "first" and "second" may be used herein to describe various units, these units should not be limited by these terms. These terms are only used to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly the second unit may be referred to as the first unit. The term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0094] To achieve the above object, please refer to Figures 1 to 3 , the present invention provides a fault analysis method for a power supply system based on state analysis, and the method includes the following steps:

[0095] Step S1: Obtain substation equipment data; perform load structure analysis based on the substation equipment data to obtain substation load structure data; identify overloaded load structures based on the substation load structure data to obtain overloaded load structure data;

[0096] In this embodiment, an online monitoring system is required to obtain substation equipment data, which mainly includes current sensors, voltage sensors, temperature sensors, and intelligent terminals. The key parameters for data acquisition include bus current, voltage, power factor, temperature change rate, etc. After these data are stored in the database, based on the load flow analysis method, combined with power flow calculation (such as Newton-Raphson method), load structure analysis is performed to obtain substation load structure data. The load structure data includes information such as power distribution and current density of different transformers, buses, and feeders. By setting an overload threshold, for example, 80% of the rated load of the transformer as the warning line and 100% as the overload judgment benchmark, analyze the equipment exceeding this threshold and extract the overloaded load structure data.

[0097] Step S2: Detect winding turn-to-turn short circuits based on the overloaded load structure data to obtain winding turn-to-turn short circuit data; determine the degree of winding insulation deterioration based on the winding turn-to-turn short circuit data; perform impulse withstand voltage tests based on the degree of winding insulation deterioration to generate impulse withstand voltage data;

[0098] In this embodiment, the detection of winding turn-to-turn short circuit needs to be based on the analysis of abnormal short-circuit current and the acquisition of partial discharge signals. A high-frequency current transformer (HFCT) is used to extract the high-frequency current signal of the winding, wavelet transform is used to analyze the spectral characteristics, and the characteristic signal of partial discharge pulse is extracted. Based on the overload load structure data, the equivalent short-circuit impedance of the winding is calculated and compared with the standard short-circuit impedance curve. If the impedance drops by more than 10%, it is determined that there is a turn-to-turn short circuit in the winding. The evaluation of the degree of winding insulation deterioration is based on dielectric spectrum measurement. A dielectric spectrum analyzer is used to scan the tangent value of the dielectric loss angle (tanδ) of the winding in the range of 10 Hz to 1 MHz. When tanδ exceeds 0.02, it indicates that the winding insulation is severely aged. The impulse withstand voltage test applies a standard lightning impulse wave (1.2 / 50 μs) to the winding, monitors the impulse current waveform, calculates the withstand voltage threshold of the voltage-time curve, and generates impulse withstand voltage data.

[0099] Step S3: Detect abnormal contact welding based on the overload load structure data to obtain abnormal contact welding data; perform contact material damage analysis according to the abnormal contact welding data to obtain contact material damage data; measure the dielectric loss angle based on the contact material damage data, and evaluate the contact contamination degree according to the dielectric loss angle;

[0100] In this embodiment, the abnormal welding detection of the contact is based on infrared thermal imaging and contact resistance measurement. The infrared thermal imager is used to detect the temperature rise of the contact, collect the temperature distribution data on the surface of the contact, and analyze the thermal distribution through the infrared image analysis software. The normal operating temperature rise of the contact generally does not exceed 65°C. If the detected temperature rise exceeds 80°C, it indicates that there is an abnormal high-temperature area locally on the contact, and a welding phenomenon has occurred in this area. The contact resistance measurement uses the DC voltage drop method. A large current source is used to apply a constant direct current of 100A, and a high-precision digital millivoltmeter is used to measure the voltage drop across the contact. The ratio of the voltage drop to the applied current is the contact resistance. According to the national standard, the contact resistance of a normal contact is generally lower than 100 μΩ. If the measured value exceeds 200 μΩ, it can be determined that the contact has a welding phenomenon. The material damage analysis uses a scanning electron microscope (SEM) to obtain the microscopic morphology of the contact surface, with the magnification range between 1000 times and 5000 times, to observe the wear morphology, cracks, and metal melting traces on the contact surface. The X-ray energy spectrometer (EDS) is used for elemental composition analysis to determine the distribution of metal elements such as copper, silver, and tungsten in the contact material, and at the same time to detect whether there is an oxide layer or pollutant accumulation. If the thickness of the oxide layer exceeds 5 μm, it indicates that the contact has been in a high-temperature oxidation environment for a long time, affecting the electrical conductivity of the contact. The dielectric loss angle measurement uses an LCR tester to apply an AC voltage of 50 Hz or 1 kHz across the contact, measure the current phase angle flowing through the contact, and calculate the dielectric loss angle (tanδ). The calculation formula is tanδ = P_loss / P_reactive, where P_loss is the active power loss of the contact and P_reactive is the reactive power. If the measured loss angle value is greater than 0.05, it indicates that there is a serious pollution layer or insulation degradation on the contact surface, which will cause the insulation characteristics of the contact to decline and affect the normal opening and closing performance of the contact.

[0101] Step S4: Perform an open-circuit fault analysis based on the contact contamination degree and the impulse withstand voltage data to obtain open-circuit fault data; generate a fault alarm based on the open-circuit fault data and upload it to the power supply system to execute the fault early warning task.

[0102] In this embodiment, based on the contact resistance measurement and the contamination degree assessment, the surface morphology of the contact is determined, and a three-dimensional profiler is used to measure the wear depth. If the depth exceeds 0.3 mm, it is a severely worn area. The impulse withstand voltage data is used to identify the arc discharge characteristics and analyze the impulse current decay rate. A signal higher than 1 kA / μs indicates the presence of an arc. The arc duration is recorded by a high-speed oscilloscope by measuring the impulse withstand voltage waveform, and the arc discharge maintenance time is calculated. If the time exceeds 10 ms, it indicates that the circuit breaker is abnormal. Finally, based on the arc duration and the contact wear area, an open-circuit fault is determined, a fault alarm is generated, and it is uploaded to the power supply system for real-time monitoring and early warning.

[0103] Preferably, step S1 is specifically:

[0104] Step S11: Obtain substation equipment data;

[0105] In this embodiment, obtaining substation equipment data is achieved through sensors installed at various important nodes in the substation. These sensors include current sensors, voltage sensors, temperature sensors, pressure sensors, etc., which are used to monitor the operating status of all key equipment in the substation in real time. Specifically, the current sensor should be able to cover a current range of 0A to 5000A, with an error range of ±1%, and ensure real-time response to current fluctuations. The voltage sensor needs to be able to measure voltages in the range of 0V to 500kV with an accuracy of ±0.5%. The temperature sensor is used to monitor the surface temperature of the equipment, ranging from -40°C to 120°C, with the error controlled within ±0.5°C, ensuring that the temperatures of transformers, switchgear, and busbars in the substation are always within a safe range. The data of all sensors is uploaded to the central control system through the data acquisition system and is displayed and analyzed on the real-time monitoring platform. The collected data includes not only the voltage, current, and temperature information of the equipment but also abnormal data such as overload or overheat alarm information.

[0106] Step S12: Analyze the substation equipment structure based on the substation equipment data; identify the core power structure according to the substation equipment structure; identify the auxiliary power structure according to the substation equipment structure;

[0107] In this embodiment, based on the obtained equipment data, specialized power system analysis software is used to analyze the power equipment structure of the substation. All the equipment in the substation is identified through the topological structure diagram of the substation, and the core power structure and the auxiliary power structure are further distinguished. The core power structure includes main power transmission equipment such as transformers, busbars, main switchgear, etc., which carry out the functions of power transmission and distribution. The auxiliary power structure includes control and protection equipment, standby power supplies, etc., which support the operation and safety of the power system. The purpose of equipment analysis is to establish a basic framework diagram of the substation equipment, clarify the electrical connections and function allocations between each equipment. By calibrating the parameters of each equipment (such as rated current, rated voltage, rated power, etc.), basic data is provided for subsequent load flow analysis and fault diagnosis.

[0108] Step S13: Conduct bus connection analysis based on the core power structure and the auxiliary power structure to obtain bus connection data;

[0109] In this embodiment, based on the analysis of the substation equipment structure, through the analysis of the core power structure and the auxiliary power structure, a detailed analysis of the bus connection is carried out. The bus connection analysis is performed by power system software, which simulates the current distribution, voltage change, and their connection relationship between buses. First, current sensors and voltage sensors are used to measure the actual current and voltage data of the buses to obtain the electrical characteristics of the bus connection points. These data include the resistance, reactance, and current flow direction between the connection points. By analyzing the current flow between the buses, the existing current overload phenomenon or uneven current distribution can be identified. For each connection point, the current distribution is calculated and bus connection data are generated, including the current load condition, voltage change, and power flow of the buses.

[0110] Step S14: Construct the substation equipment connection structure based on the core power structure, auxiliary power structure, and bus connection data;

[0111] In this embodiment, according to the bus connection data and combined with the substation equipment structure information, a power system modeling tool (such as ETAP, PowerWorld, etc.) is used to construct a substation equipment connection structure model. This model details the electrical connections and functional relationships of all equipment inside the substation, covering the core and auxiliary power structures of the substation. The specific operations include inputting the electrical parameters of equipment such as buses, current sensors, and transformers (such as rated voltage, rated current, power factor, etc.) into the modeling software, and the software automatically generates the electrical connection diagram and power flow diagram between each equipment. At this time, each equipment node in the model is marked with the corresponding voltage, current, and power information, and the electrical connection relationship between the equipment is clearly shown, providing detailed power system structure data for subsequent load flow simulation and fault analysis.

[0112] Step S15: Conduct a load flow simulation based on the substation equipment connection structure to obtain substation load structure data;

[0113] In this embodiment, the load flow simulation is carried out by power system analysis software, which simulates the power flow in the entire system and provides the load distribution of each electrical node. The input parameters include the rated load of each equipment, the current and voltage values of the buses, and the power data of the loads. During the simulation process, the load flow analysis software calculates the current, voltage, and power distribution of the entire substation according to the current and voltage flow rules and the power balance condition of the power system. The simulation results include the voltage value of each bus, the power flow of each equipment, the power loss between the equipment, etc., and important electrical parameters such as current density, power factor, and load ratio are given. The simulation results can also identify the electrical fault points in the substation, providing a basis for subsequent overload identification and fault analysis.

[0114] Step S16: Identify the overloaded load structure based on the substation load structure data to obtain the overloaded load structure data.

[0115] In this embodiment, by analyzing the current density and power distribution in the load flow simulation data, the equipment or busbars with a current exceeding 80% of the rated value are identified, and these equipment or busbars will be marked as overloaded areas. Next, combined with the working time and load change of the equipment, an accurate determination of the overloaded load is carried out. For each equipment and busbar, its current density is calculated to determine whether it exceeds the rated current density of the equipment. The calculation formula for current density is: current density = current / cross-sectional area, where the cross-sectional area is obtained according to the design parameters of the equipment. In addition, it is also necessary to judge the duration of overload and the load fluctuation situation. For example, if the load current of the equipment continuously exceeds the rated value for more than 5 minutes, it can be considered that the equipment is in an overloaded state. Through these detailed calculations and analyses, the overloaded load structure data in the substation is finally obtained, providing a basis for subsequent detection of inter-turn short circuit of windings and abnormal welding of contacts.

[0116] Preferably, step S16 is specifically as follows:

[0117] Step S161: Calculate the load rate based on the substation load structure data; divide the substation load structure data according to the load rate to obtain the high-load-rate structure data;

[0118] In this embodiment, the calculation formula for the load rate is load rate = actual load / rated load of the equipment. In this process, the actual load is obtained through the current sensor in the substation. The current sensor should be able to provide a current measurement range of 0A to 5000A with an accuracy of ±1%. The rated load of the equipment is set according to the specification parameters of the equipment (such as rated current, rated power), and the rated load of each substation equipment has been clearly marked in the design document. The calculation result of the load rate will compare the actual operating load of the equipment with its maximum tolerable load. Then, according to the calculated load rate, each load structure in the substation is divided into high-load-rate structures. The specific standard is that when the load rate exceeds 90%, it is considered that the load structure belongs to the high-load-rate structure. By calculating the load rate of all equipment one by one, a list containing all high-load-rate structures is obtained. These structure data will be marked as high-load-rate structure data, and relevant equipment numbers, load rates, and other parameters will be recorded.

[0119] Step S162: Calculate the load time of the high-load-rate structure data;

[0120] In this embodiment, the load time refers to the load duration of the high-load-rate structure in the substation. This process is carried out by analyzing the historical load data and real-time load data of the equipment. In the acquisition system, the load data is updated every 5 seconds. By checking the load change trend of these high-load-rate equipment within the past 24 hours, the time periods when the load exceeds the set threshold (such as the load rate exceeds 90%) are marked. This process requires analyzing the load change curve of each equipment through the load monitoring system and recording the duration when the load of the equipment exceeds 90%. If an equipment operates continuously at a high load for a certain period of time (for example, continuously exceeds 30 minutes), this period of time will be calculated as the load time. By summarizing the load times of all high-load-rate equipment, a total load time data including each high-load-rate structure is obtained, and these data provide an important basis for subsequent overload determination.

[0121] Step S163: Calculate the current density of the high-load-rate structure data;

[0122] In this embodiment, the calculation formula of the current density is current density = current / cross-sectional area, where the current is collected by the current sensors in the substation. The rated range of the current sensors is 0A to 5000A, and the accuracy is ±1%, which can capture the current flow conditions of each bus and equipment in real time. The cross-sectional area is given according to the physical specifications of the equipment. For example, for a certain bus, the cross-sectional area is 20 cm 2 , or for a certain cable, the cross-sectional area is 10 mm 2 . The cross-sectional area of each bus or cable can be found and obtained from the equipment technical parameter book or engineering drawings. The calculation process of the current density requires analyzing the current and cross-sectional area of each high-load-rate structure equipment. If the current density of an equipment exceeds the specified threshold (for example, the current density exceeds 500 A / cm 2 ), it is considered that the equipment is in a state of excessive current density. These data will be recorded and marked as data with excessive current density, and provided for subsequent determination of the overload load structure.

[0123] Step S164: Determine the overload load structure of the high-load-rate structure data according to the load time and the current density, and obtain the overload load structure data.

[0124] In this embodiment, based on the load time and current density data, the overload load structure of the high-load-rate structure data is determined. In this process, the load time and the current density are the key determination criteria. For each high-load-rate structure, if its load time exceeds 30 minutes and the current density exceeds 500 A / cm 2, it is determined that the structure is an overloaded load structure. During specific operations, the load time data is obtained from step S162, and the current density data is from the calculation result in step S163. If both the load time and current density of the high load rate structure exceed the set thresholds, the structure is marked as an overloaded load structure. In addition, the threshold setting of the current density can be adjusted according to the rated design of the equipment. For example, the current density threshold for the power bus can be set to 400 A / cm 2 , if the current density of the equipment exceeds this value, it is considered that there is an overload risk. The determination process will judge all high load rate structures one by one according to these criteria, generate overloaded load structure data, and record parameters such as the information of relevant equipment, load time, and current density.

[0125] Preferably, the detection of inter-turn short circuit of the winding in step S2 includes:

[0126] Collect the current sensing data of the overloaded load structure data;

[0127] In this embodiment, data collection is performed by current sensors installed at each load point in the substation. The sampling frequency of the current sensor is set to 100 times per second. The sensor can measure the current range from 0 A to 5000 A, and the accuracy is ±1%. The collected data includes current values, timestamps, and device identification information. The current data is transmitted to the central monitoring system through the data acquisition system. The output signal of each sensor is an analog signal, which is converted into a digital signal by an analog-to-digital converter for subsequent analysis. When performing data collection, it is necessary to ensure that the installation position of the current sensor exactly matches the load point to avoid current collection deviation caused by position error.

[0128] Perform signal conditioning on the current sensing data to obtain conditioned current sensing signal data;

[0129] In this embodiment, the conditioning of the current signal mainly includes processing such as noise filtering, amplification, and calibration. High-frequency noise is filtered through a low-pass filter to ensure the stability of the current signal. The cut-off frequency of the filter is set to 50 Hz. Then, the signal is amplified, and the amplification factor is set to 10 times to ensure that the signal can meet the requirements of subsequent analysis. Then, the signal is calibrated using the known load current value to ensure that the measured current value is consistent with the actual load value. The conditioned signal data will be stored in the central monitoring system and associated with the status data of other devices for subsequent drawing of the current distribution map.

[0130] Draw a current distribution map according to the conditioned current sensing signal data;

[0131] In this embodiment, the current distribution map is drawn by performing spatial position mapping on the data of multiple current sensors. Specifically, the conditioned current signal data is extracted from the current acquisition system, distributed according to the installation position of each current sensor, and the spatial distribution of the current in the substation equipment and bus system is drawn. Each node of the current distribution map represents a current sensor, and the current value between adjacent nodes is estimated through an interpolation algorithm, so as to obtain the spatial distribution of the current within the entire substation system. This current distribution map will provide data support for subsequent heat source calculations. The key parameters in the drawing process include the position coordinates of the sensors, the acquisition time period, and the current values.

[0132] Based on the current distribution map, the winding heat source is calculated to obtain the winding heat source data;

[0133] In this embodiment, the winding heat source calculation is based on the current data in the current distribution map and is combined with the resistance characteristics of the winding. Using the current value of each current sensor in the current distribution map, combined with the winding resistance data of equipment such as transformers and buses in the substation, the heat generation formula Q = I 2 ²R is used for calculation, where I is the current value, R is the winding resistance, and Q is the heat. This calculation needs to consider the material characteristics (such as copper or aluminum) of the winding and its resistivity, and calculate the heat source value of each winding according to the current density distribution of different equipment. The obtained heat source data will be stored in the central control system and provide basic data for subsequent construction of the thermal equivalent model.

[0134] Obtain the winding heat dissipation path and insulation material data;

[0135] In this embodiment, the winding heat dissipation path is usually provided by the design engineer according to the equipment model and structure diagram. By consulting the technical documents of the equipment, the specific parameters of the winding heat dissipation path are obtained, including the heat dissipation area, heat dissipation medium (such as air or oil), and heat dissipation coefficient. The data of the insulation material also comes from the equipment design document, usually including the thermal conductivity, specific heat capacity, dielectric constant, etc. of the material. The type and thickness of the insulation material will be selected according to different equipment models and rated powers, and these data are clearly specified in the document. By sorting and summarizing these data, it provides necessary information support for the subsequent winding thermal equivalent model.

[0136] Construct a winding thermal equivalent model based on the winding heat dissipation path and insulation material data;

[0137] In this embodiment, the construction of the thermal equivalent model of the winding first requires considering the heat source data of the winding, the heat dissipation path, and the thermal properties of the insulating material. Using the heat transfer models of heat conduction, convection, and radiation, the thermal parameters of the heat dissipation path and the insulating material (such as thermal conductivity, specific heat capacity) are input into the numerical calculation to construct the heat transfer equation. The heat transfer process is simulated by the finite element analysis (FEA) method to obtain the thermal equivalent model of the winding. The specific process involves establishing mathematical models for factors such as the winding structure, insulating material, and heat dissipation path, and solving them by numerical methods to obtain the distribution of the winding temperature field. This process requires the use of dedicated thermal analysis software, such as ANSYS or Comsol, etc., and boundary conditions are set, such as parameters such as ambient temperature and fluid flow rate.

[0138] Input the winding heat source data into the thermal equivalent model of the winding and generate the winding temperature field;

[0139] In this embodiment, the winding heat source data is input as a heat source term into the thermal equivalent model for analysis. The input data includes the heat source intensity, position coordinates of each winding, and the working state of the equipment (such as load rate and operating time). Based on these input data, the temperature field distribution of the winding under different working conditions is solved by numerical methods. At this time, the generation of the temperature field will reflect the temperature distribution of each winding during actual operation and can indicate which parts have too high temperature and are at risk of overheating.

[0140] Conduct winding insulation aging assessment based on the winding temperature field to obtain winding insulation aging data;

[0141] In this embodiment, by analyzing the temperature field, the temperature rise of each part of the winding is evaluated. According to the known insulation material aging model, combined with the temperature data, the aging degree of the winding insulation is deduced. Specifically, thermal aging models such as the Arrhenius equation are used to correlate the highest working temperature of the winding with the aging time of the material. The influence of different temperatures on the insulating material is considered during the assessment. For every 10°C increase in temperature, the insulation life is approximately reduced by 50%. The obtained insulation aging data will provide the aging degree, life prediction, and fault risk of each winding.

[0142] Diagnose the short - circuit fault based on the winding insulation aging data to obtain the winding turn - to - turn short - circuit data.

[0143] In this embodiment, the winding insulation aging data is obtained through analysis. If the aging degree reaches a set threshold (for example, the aging degree exceeds 80%), it is considered that the insulation performance of the winding has significantly decreased and there is a risk of inter-turn short circuit. At this time, according to the correlation between the degree of insulation aging and the current density, combined with the current sensing data and temperature field data of the winding, the possibility of short circuit is further analyzed. Finally, the system algorithm determines whether there is an inter-turn short circuit fault in the winding, records the fault data, and generates a short circuit fault report for subsequent processing.

[0144] Preferably, determining the degree of winding insulation deterioration in step S2 includes:

[0145] Calculating the short-circuit impedance based on the inter-turn short-circuit data of the winding to obtain short-circuit impedance data;

[0146] In this embodiment, the current and voltage data of the inter-turn short circuit of the winding are obtained, and the short-circuit impedance is calculated by measuring the changes in the short-circuit current and voltage. The specific method is to calculate through Ohm's law Z = V / I, where V is the voltage during short circuit and I is the short-circuit current flowing through the winding. The voltage signal is obtained through a voltage sensor, and the current signal is collected through a current sensor. The sampling frequencies of the voltage sensor and the current sensor are set to 200 times per second, and the measurement accuracies are ±0.5% and ±1% respectively. The calculated short-circuit impedance data is the impedance value of the winding under short-circuit conditions. All voltage and current signals will be sent to the data processing unit after analog-to-digital conversion for real-time calculation and data storage.

[0147] Performing impedance change analysis based on the preset standard impedance data and the short-circuit impedance data to obtain impedance change data;

[0148] In this embodiment, the preset standard impedance data of each winding is obtained. These data are usually based on the design parameters of the device or historical test data. These standard impedance data include the resistance and impedance values of each winding under normal operating conditions. Then, the standard impedance data is compared with the short-circuit impedance data calculated in step S1, and the impedance change rate formula ΔZ = (Z_actual - Z_standard) / Z_standard is used for calculation, where Z_actual is the actually measured short-circuit impedance value and Z_standard is the standard impedance value. According to this calculation result, the impedance change rate of each winding is obtained. If the change rate exceeds the set threshold (for example, the change rate exceeds 5%), it is determined that the impedance change is abnormal, and the corresponding impedance change data is generated.

[0149] Performing high-frequency pulse current simulation based on the inter-turn short-circuit data of the winding to obtain pulse current data;

[0150] In this embodiment, specific parameters of the inter-turn short circuit of the winding are obtained, such as the short-circuit current value and the short-circuit duration. Based on these parameters, a high-frequency pulsed current generated during the inter-turn short circuit of the winding is simulated by a simulation tool (such as Matlab / Simulink). The instantaneous current model is used during the simulation, the frequency of the current pulse is set to 100 kHz, and the pulse duration is set to 100 μs. Waveform data of the pulsed current, including the current amplitude and frequency, is output by the simulation tool. After the pulsed current data is filtered and denoised, the final pulsed current waveform is obtained. The influence of different frequencies on the winding is considered during the simulation process. Through the simulation of the high-frequency pulsed current, the current change of the winding under short-circuit conditions can be predicted more accurately.

[0151] Calculate the pulse amplitude according to the pulsed current data; calculate the single partial discharge amount according to the pulse amplitude; perform time integration based on the single partial discharge amount to obtain the total discharge amount;

[0152] In this embodiment, the pulse amplitude refers to the maximum amplitude of the current in the pulsed current waveform. In this step, by analyzing the simulated pulsed current data, a peak detection algorithm is used to identify the maximum current value in the waveform and calculate the amplitude of the pulsed current. This calculation method first discretizes the pulsed current waveform, and then calculates the current value at each sampling point to identify the highest point in the current waveform and obtain the maximum current value of the pulse. During the calculation process, a high-precision numerical integration method is used to ensure the accuracy and reliability of the measured pulse amplitude. The obtained pulse amplitude will be used as the basis for calculating the subsequent partial discharge amount. The calculation of the partial discharge amount is based on the amplitude and discharge time of the pulsed current. Through a known discharge model (such as the Peukert formula or the discharge exponent formula), combined with the pulse amplitude and discharge time, the charge generated by each pulse discharge is calculated. The discharge time is determined according to the duration of the current waveform. For example, if the duration of the current waveform is 100 μs, the single partial discharge amount is the product of the pulse amplitude and the discharge time. The unit of the single partial discharge amount is Coulomb (C), and each discharge needs to be filtered and denoised to reduce the interference of noise on the result. According to the single partial discharge amount calculated for each pulse discharge, time integration is performed to obtain the total discharge amount. The specific method is to perform integration according to the working time and partial discharge frequency of the device. Assuming that the device generates one pulse discharge per second within a certain time period (such as 24 hours), the total discharge amount can be obtained by performing time integration on the single partial discharge amount to obtain the total discharge amount per unit time. The formula for calculating the total discharge amount is Q_total = ΣQ_single × T, where Q_single is the single partial discharge amount and T is the length of the discharge time period. The calculated total discharge amount is in units of Coulomb (C), and the discharge amount for each time period needs to be dynamically updated according to the change of the current.

[0153] Evaluate the discharge severity based on the impedance change data and the total discharge amount;

[0154] In this embodiment, the discharge severity of the winding is evaluated by combining the impedance change data and the total discharge amount. The specific method is to perform weighted analysis on the impedance change rate and the total discharge amount to obtain a comprehensive discharge severity index. The evaluation formula for the discharge severity is Severity = w1ΔZ + w2*Q_total, where w1 and w2 are weight coefficients, ΔZ is the impedance change rate, and Q_total is the total discharge amount. The weight coefficients can be set through historical data or engineering experience. Usually, the values of w1 and w2 are 0.7 and 0.3 respectively. The greater the calculated discharge severity, the higher the risk of internal discharge in the winding, which will lead to further insulation damage.

[0155] Statistically analyze the winding heat based on the discharge severity;

[0156] In this embodiment, according to the evaluation result of the discharge severity, the heat generated by the winding due to discharge is statistically analyzed. By combining with the heat source model, the heat generated by each winding due to partial discharge within a certain time is calculated. The heat calculation formula is Q = P×t, where P is the power generated per unit time (obtained by correlating the discharge severity with the current amplitude), and t is the time. This process takes into account the thermal effect of the discharge on the winding, and the thermal conductivity characteristics of the winding and the specific heat capacity of the material need to be considered during the calculation. Through the statistical analysis of the heat of different windings, the total heat generated by the winding due to discharge is finally obtained.

[0157] Determine the degree of winding insulation deterioration based on the winding heat;

[0158] In this embodiment, according to the winding heat data and in combination with a known thermal aging model (such as the Arrhenius model), the degree of deterioration of the winding insulation can be deduced. This model calculates the aging degree of the insulating material at a specific temperature through the temperature-time correlation. Assuming the winding temperature is 70°C, combined with the calculated heat data, the insulation aging time and life are predicted using the formula. Through comprehensive analysis, the degree of insulation deterioration of the winding is obtained, and in combination with other monitoring data, it is determined whether maintenance or replacement is required.

[0159] Preferably, the impulse withstand voltage test described in step S2 includes:

[0160] Determine the windings with insulation deterioration based on the degree of winding insulation deterioration, and measure the impulse current of the windings with insulation deterioration using a high-frequency current probe to obtain impulse current data;

[0161] In this embodiment, through the previous analysis of the winding temperature field and aging assessment, the windings with insulation deterioration are determined. These windings are monitored for current through current sensors, and a high-frequency current probe is used to measure specific windings, with a frequency range of 100 kHz to 1 MHz and a sampling accuracy of ±0.5%. The measurement of the impulse current uses a short-time pulse current excitation signal, and a high-frequency current probe is used to capture the instantaneous impulse current signal of the winding. The obtained impulse current signal will be processed by a signal conditioning system. After removing the noise, the impulse current data will be stored in a data recorder for subsequent analysis.

[0162] Perform envelope detection on the impulse current data to generate an envelope signal;

[0163] In this embodiment, envelope detection processing is performed on the measured impulse current signal. The envelope detection process uses the Hilbert transform algorithm. By performing time-domain analysis on the original impulse current signal, the envelope of the signal is calculated. The specific method is to first perform a complex transformation on the impulse current signal to obtain the analytical expression of the signal, and then calculate the absolute value of the envelope signal. The frequency range of the envelope signal is 0 to 100 kHz, the sampling rate is 10 kHz, and the signal amplitude is related to the amplitude change of the impulse current waveform. The generated envelope signal will be used as the basis for further signal analysis.

[0164] Identify the decaying envelope signal based on the envelope signal;

[0165] In this embodiment, based on the envelope signal, an algorithm for identifying the decaying envelope is applied to identify the gradually decreasing part of the signal. The identification of the decaying envelope signal uses the fast Fourier transform (FFT) technology. Through frequency-domain analysis, the decay characteristics of the envelope signal are extracted. The decaying part of the signal usually shows that the amplitude of the envelope signal gradually decreases over time. Specifically, when implementing, a threshold is set to determine when to start the identification of decay. The threshold is set to 30% of the relative maximum amplitude of the envelope signal. The obtained decaying envelope signal will provide key parameters for evaluating the insulation withstand capacity of the winding.

[0166] Calculate the envelope decay rate of the decaying envelope signal;

[0167] In this embodiment, it is necessary to analyze the variation of the amplitude of the attenuation envelope signal with time. The specific operation is to select two different time points t1 and t2, and the envelope signal amplitude between these two time points will be extracted. Then, by calculating the change rate of the envelope signal amplitude between these two time points, the attenuation rate can be obtained. Generally, the attenuation rate will reflect the speed at which the envelope signal intensity decreases, thereby being able to characterize the degradation of the winding insulation material. In practical applications, the calculation of the attenuation rate usually depends on the change of the signal amplitude in different time periods. A larger attenuation rate indicates a faster degradation rate of the insulation material. The data acquisition system used in this process must have sufficient time resolution to ensure the accuracy of the selected time points. Finally, the unit of the attenuation rate is dB / s, which is used to measure the change speed of the insulation material under the action of the impulse current.

[0168] Evaluate the insulation withstand capacity of the insulation deteriorated winding according to the envelope attenuation rate to obtain the winding insulation withstand data;

[0169] In this embodiment, the calculated attenuation rate is compared with the preset insulation withstand standard. If the attenuation rate exceeds the set threshold (for example, the attenuation rate exceeds -5 dB / s), it indicates that the insulation withstand capacity of the winding has decreased. The evaluation standard of the insulation withstand capacity is the ability of the insulation material to continuously work under a specific voltage. The evaluation result is quantified by the difference from the standard value to obtain the winding insulation withstand data. This data will provide a decision basis on whether the winding insulation needs to be repaired or replaced.

[0170] Based on the winding insulation withstand data, perform impulse withstand voltage determination to obtain impulse withstand voltage data.

[0171] In this embodiment, the impulse withstand voltage test simulates the voltage applied to the winding to detect its insulation performance. During the specific operation, the winding insulation withstand data is compared with the set impulse withstand voltage threshold. If the withstand capacity is lower than the threshold, it is determined that the winding cannot withstand the impulse withstand voltage. In the impulse withstand voltage test, the amplitude of the impulse voltage is set to 1.5 times the normal operating voltage of the winding, and the duration is 2 seconds. During the test process, the current change of the winding is monitored in real time. If there is an excessive current change or short - circuit phenomenon, it is determined that the winding insulation fails, and the impulse withstand voltage data is generated and output as a fault alarm.

[0172] Preferably, step S3 is specifically as follows:

[0173] Step S31: Extract the overload contact structure data based on the overload load structure data;

[0174] In this embodiment, based on the overload load structure data of the substation, the data acquisition system is used to obtain the contact load information during the operation of the overload load. By analyzing the load data, the contact-related structure information when the overload current is applied is extracted. This information includes the geometry of the contact, the contact area, the current-carrying capacity, the electrical characteristics (such as resistance) of the connection point, etc. The structured data analysis method will be used to identify the key contact structures under the overload load condition from the collected electrical parameters to ensure that the overload current can be effectively applied to these contacts. During the analysis process, the load data is processed by the power system simulation software to clearly identify the impact of the overload load condition on the contacts.

[0175] Step S32: Perform a simulation of applying the overload current according to the contact structure data to obtain the overload current contact data; calculate the temperature rise value of the contact of the overload current contact data; calculate the voltage drop value of the contact of the overload current contact data;

[0176] In this embodiment, a current simulation tool is used to perform a numerical simulation of the impact of applying the overload current on the contacts. The input of the overload current simulation is usually set to 100%-200% of the standard rated current, and the overload duration, the operating temperature of the contacts, and the current density, etc. will be set in the simulation. The calculation of the temperature rise value is based on the heat conduction equation and is calculated through data such as the thermal conductivity of the known contact material, the contact area, and the current density. The temperature rise value and the contact resistance value are combined to further calculate the voltage drop value under the applied current. The calculation process uses Ohm's law U = I×R, where I is the overload current and R is the contact resistance of the contact, and the obtained voltage drop value helps to further evaluate the health status of the contact.

[0177] Step S33: Based on the contact temperature rise value and the contact voltage drop value, perform a welding judgment to obtain the welding data;

[0178] In this embodiment, based on the calculated temperature rise value and voltage drop value, a certain welding judgment criterion is adopted to judge the occurrence of welding. The conventional welding judgment criterion is set that the temperature rise value exceeds the set threshold (such as 80°C), and at the same time the voltage drop value is greater than 200 μΩ. Through the welding judgment algorithm, the temperature rise and voltage drop values are brought into the formula for comprehensive judgment. If the temperature rise value and the voltage drop value reach the set standard within a certain time, it is determined that there is a welding risk for the contact. This standard is determined through the accumulation of experimental data and the analysis of the operating conditions of power equipment.

[0179] Step S34: Calculate the welding energy of the contact based on the welding data; perform an abnormal welding judgment on the welding energy of the contact according to the preset standard welding energy of the contact to obtain the abnormal welding data of the contact;

[0180] In this embodiment, when the contact is determined to be welded, the energy during the welding process is calculated. This calculation is based on the principles of thermodynamics, assuming that the heat in the contact area is generated by current and resistance losses. According to the current density, resistance, and the duration of the contact operation, the heat generated in the contact area is calculated. The welding energy is usually obtained by cumulative calculation and is in joules (J). In addition, the calculated welding energy is compared with a preset standard welding energy (set according to the contact design and material characteristics, such as the design standard welding energy is 1.2 J). If the welding energy exceeds the preset standard, it is determined as abnormal welding.

[0181] Step S35: Identify the abnormal welding area of the contact based on the abnormal welding data of the contact;

[0182] In this embodiment, the abnormal temperature area of the contact is identified by an infrared thermal imager or current distribution simulation. In this area, further through the change of contact resistance and using microscopic current flow simulation, the specific position of the welding is accurately calibrated. There will be abnormal color change or deformation on the contact surface, which is observed by a high-resolution microscope or scanning electron microscope to extract the spatial characteristics of the welding area. Through image processing algorithms, the abnormal welding area of the contact is located and marked, providing basic data for subsequent damage analysis.

[0183] Step S36: Irradiate the abnormal welding area of the contact with X-rays to generate an X-ray energy spectrum; Detect the surface oxide of the contact based on the X-ray energy spectrum;

[0184] In this embodiment, in the abnormal welding area of the contact, X-ray imaging technology is used for scanning to generate an X-ray energy spectrum diagram. The X-ray energy spectrum diagram can reveal the surface composition change of the contact material, especially the presence of the oxide layer. The X-ray energy spectrometer can clearly identify the types and their distribution of oxides by analyzing the energy distribution, providing detailed data on the surface chemical composition change. The presence and distribution of the surface oxide of the contact are important bases in damage assessment, and the oxide has a further degradation effect on the contact performance.

[0185] Step S37: Apply a simulation of metallographic etchant to the abnormal welding area of the contact to obtain the surface corrosion area of the contact; Identify the molten recrystallization area based on the surface corrosion area of the contact;

[0186] In this embodiment, in the fusion welding area, surface treatment is carried out using a metallographic etchant to simulate the microscopic changes after the surface corrosion of the contact. The metallographic etchant selectively corrodes the contact surface, exposing the structural features of different regions, especially the difference between the recrystallization zone and the melting zone. A high-power microscope is used to observe the corroded surface and analyze the microstructural changes generated after corrosion. Using this information, the molten recrystallization region is further identified. Through an image recognition algorithm, the boundary of the melting zone is judged and compared with the non-melting zone to quantify the damage degree of the contact.

[0187] Step S38: Integrate the damage of the contact material based on the oxide on the contact surface and the molten recrystallization region to obtain the contact material damage data;

[0188] In this embodiment, based on the analysis results of the oxide on the contact surface and the molten recrystallization region, combined with the degradation of the mechanical properties of the metal, the integrated analysis of the contact material damage data is carried out. The microstructure of the contact is analyzed in detail by a scanning electron microscope (SEM) to extract data such as the thickness of the oxide layer and the crack distribution, and combined with the mechanical properties of the contact material, such as yield strength and hardness, to evaluate the overall damage degree of the contact. These data provide a reliable basis for subsequent evaluation and can accurately judge whether the contact material can still withstand the normal working load.

[0189] Step S39: Measure the dielectric loss angle based on the contact material damage data and evaluate the degree of contact contamination according to the dielectric loss angle.

[0190] In this embodiment, based on the contact material damage data, an LCR tester is used to measure the electrical performance of the contact, especially the measurement of the dielectric loss angle. The LCR tester measures the phase difference between the current and the voltage by applying an AC voltage signal of 50 Hz or 1 kHz, and then calculates the dielectric loss angle. The dielectric loss angle is an important parameter reflecting the degradation of the electrical performance of the contact material. Usually, a threshold value (for example, 0.05) is set. When the measured loss angle exceeds this value, it indicates that the degree of contact contamination or damage is relatively serious and replacement or maintenance is required.

[0191] Preferably, step S39 is specifically:

[0192] Step S391: Identify the damaged contact material based on the contact material damage data and apply an AC voltage to the damaged contact material to obtain AC voltage data;

[0193] In this embodiment, according to the contact material damage data, the damaged area of the contact is identified by means of scanning electron microscopy (SEM) or X-ray diffraction analysis. Based on the chemical composition, microstructure characteristics and surface oxidation condition of the material, the damage degree of the material is determined. On this basis, a standard AC voltage (for example, with a frequency of 50 Hz or 60 Hz and a voltage amplitude of 10 - 100 V) is applied using a high-frequency signal generator, and this AC voltage is applied to the damaged area of the contact. This operation is achieved through the electrical connection between the voltage source and the contact. This process ensures that the electrical response data of the damaged area of the contact under the action of the AC voltage can be obtained, providing a basis for subsequent current data acquisition and power calculation.

[0194] Step S392: Collect the current data of the damaged contact material based on the AC voltage data; calculate the current phase difference based on the current data of the damaged contact material;

[0195] In this embodiment, after the AC voltage is applied to the damaged contact material, a current detector (such as a Hall effect sensor, a shunt resistor, etc.) is used to collect the current data of the damaged area of the contact in real time. Through the collected current signal, the amplitude and phase information of the current are analyzed. An oscilloscope or a phase analyzer is used to accurately measure the current signal, and the phase difference between the current signal and the AC voltage signal is calculated. This phase difference reflects the changes in the electrical characteristics of the damaged area of the contact, especially the changes related to material loss and electrical performance degradation.

[0196] Step S393: Calculate the active power according to the AC voltage data and the current phase difference; calculate the reactive power according to the AC voltage data and the current phase difference; calculate the dielectric loss angle according to the active power and the reactive power;

[0197] In this embodiment, the active power and the reactive power are calculated. The calculation of the active power takes into account the effective values of the voltage and the current and the phase difference between them, representing the part that can actually do work in the power system. The reactive power is related to the sine function of the phase difference between the voltage and the current, indicating the energy exchange in the power system but not doing actual work. After calculating the active power and the reactive power, the dielectric loss angle is further calculated through the ratio of these two parameters. The size of the loss angle can reflect the changes in the electrical performance of the contact material during the current flow, especially in the case of material aging or surface contamination, the change of the loss angle will be more obvious. Through these calculations, the electrical characteristics of the contact can be evaluated, and then it can be judged whether there is a risk of contamination or performance degradation.

[0198] Step S394: Establish a pollution assessment level model according to the dielectric loss angle;

[0199] In this embodiment, a pollution assessment level model is established based on the calculated dielectric loss angle data. This model can set different pollution levels corresponding to different dielectric loss angles based on empirical data or standardized electrical performance parameters. The pollution assessment level model is based on existing standards. For example, when the loss angle is greater than 0.05, it indicates a relatively high pollution level and obvious degradation of the dielectric performance; when the loss angle is between 0.03 and 0.05, it indicates a medium pollution level and the dielectric performance begins to degrade; when the loss angle is less than 0.03, it indicates a relatively low pollution level of the contact and good material performance. This model is further optimized based on historical data through statistical methods or machine learning techniques to improve the accuracy of the assessment.

[0200] Step S395: Determine the pollution level of the contact material based on the pollution assessment level model for the contact material damage data, and generate the pollution level of the contact.

[0201] In this embodiment, based on the pollution assessment level model and combined with actual test data, the pollution level of the contact material damage data is evaluated. According to the loss angle threshold set in the model, the dielectric loss angle of each damaged contact material is determined. If the calculated dielectric loss angle value is greater than the set maximum standard value, the contact is determined to be severely polluted; if the dielectric loss angle is within the intermediate range, the pollution level is considered to be relatively light; if the loss angle is small, the pollution level is considered to be almost non-existent. Finally, the pollution level of the contact is obtained through these data, and a pollution level report is generated. This report is provided to maintenance personnel as an important reference for the analysis of the power system equipment status.

[0202] Preferably, step S4 is specifically as follows:

[0203] Step S41: Detect the surface topography of the contact according to the pollution level of the contact to obtain the surface topography data of the contact;

[0204] In this embodiment, the surface topography of the contact is detected according to the pollution level of the contact. Usually, a scanning electron microscope (SEM) or a surface profiler is used for the operation. When performing the surface topography detection, first, a high-resolution image of the contact surface is obtained using a scanning electron microscope. The image can show the pollution, oxide layer, corrosion area, etc. on the contact surface. To ensure the accuracy of the surface topography, it is usually necessary to perform multi-angle scanning at different magnifications and collect multiple data points. Next, according to the scanned image, the microscopic morphology of the contact surface is analyzed, including the distribution of surface defects, cracks, oxides or corrosion products. Image processing software is used to extract the surface topography data, including the depth, width, and morphology of the worn area. This data can be further used for the assessment of the pollution level of the contact.

[0205] Step S42: Measure the wear amount of the contact according to the surface topography data of the contact; extract the high-wear area of the contact where the wear amount of the contact is located;

[0206] In this embodiment, after obtaining the surface topography data of the contact, a contact surface roughness measuring instrument or a surface profiler is used to measure the contact surface in detail. This includes selecting a certain area on the contact surface, using a sensor to scan the surface and record the microscopic height changes of the contact within the scanned area. From these data, the wear amount of the contact is calculated, usually by determining the average wear depth within a unit area. Then, the area with the most severe wear is identified, usually by using a threshold method to extract the high-wear area. For example, when the wear amount in a certain area is greater than 50 microns, that area is considered a high-wear area. This operation can accurately locate the key damage areas of the contact and provide a basis for subsequent judgment.

[0207] Step S43: Identify continuous high-value current based on the impulse withstand voltage data;

[0208] In this embodiment, based on the impulse withstand voltage test data, continuous high-value current is identified. Continuous high-value current refers to the situation where the current remains at a relatively high level for a short period during the impulse withstand voltage process. By using a current sensor to monitor the current waveform in real time during the impulse process and record the current values. When the current value continuously exceeds a set threshold (such as 100 A) and remains for more than 50 milliseconds, it is determined as continuous high-value current. The key to this process is the real-time analysis of the current during the application of the impulse voltage to identify and record the current characteristics that cause faults.

[0209] Step S44: Identify instantaneous voltage drop based on the impulse withstand voltage data;

[0210] In this embodiment, based on the impulse withstand voltage test data, instantaneous voltage drop is identified. Instantaneous voltage drop usually refers to the phenomenon where the voltage drops sharply and then quickly recovers when the impulse voltage is applied. A voltage sensor is used to record the voltage waveform in real time, and the time period of the instantaneous voltage drop is detected in the data. The drop amplitude needs to exceed a set threshold (such as a voltage drop of more than 20%), and the duration is less than 10 milliseconds. Through precise analysis of the voltage waveform, the specific moment and duration of the voltage drop can be determined, thereby obtaining the instantaneous voltage drop data.

[0211] Step S45: Perform arc determination based on the continuous high-value current and the instantaneous voltage drop to obtain arc data;

[0212] In this embodiment, in the power supply system, the occurrence of an arc is usually accompanied by abnormal fluctuations in current and voltage, especially in the case of poor contact of the contacts or overload. First, by real-time monitoring of the current and voltage waveform data, thresholds for current and voltage are set. Specifically, when the current exceeds 100 A and the voltage shows a significant drop (such as a drop of more than 20% and a duration of less than 10 milliseconds), it indicates that an arc has occurred. When an arc occurs, the current will show large fluctuations, usually manifested as a sharp increase in current within a short time or maintaining a high value, accompanied by a rapid drop in voltage. Through the synchronous analysis of the current waveform and the voltage waveform, a sudden increase in current and an instantaneous drop in voltage can be accurately detected. In the synchronous analysis, the focus is on the change trends of the current and voltage waveforms. When the current remains at a high value (for example, exceeding 100 A) within a certain time, and the voltage drops by more than the set threshold within a short time, it is confirmed that an arc has occurred. The arc determination does not depend on a single current or voltage data, but through the comparison of the current and voltage waveforms, combined with their phase relationship and change pattern, for comprehensive analysis to ensure that the arc phenomenon is accurately identified. The generated arc data includes key information such as the start and end time points of the arc, the arc duration, and the fluctuation amplitude of the current and voltage. This process requires high-precision sampling and waveform processing technologies to ensure the accuracy of the arc data.

[0213] Step S46: Statistically analyze the arc duration of the arc data;

[0214] In this embodiment, the arc duration refers to the time period from the generation to the extinction of the arc. Using a current waveform analysis tool, monitor the time when the current maintains a high value (such as above 100 A). If the high value of the current is maintained for more than 100 milliseconds and gradually decreases to zero over time, it indicates the end of the arc duration. According to the change of the current waveform, calculate the total arc duration. At this time, through an automated software tool for time calculation, ensure the accurate statistical analysis of the arc duration.

[0215] Step S47: Based on the high wear area of the contacts and the arc duration, determine the open circuit fault, and obtain the open circuit fault data;

[0216] In this embodiment, a comprehensive evaluation is carried out by combining the relationship between the high wear area of the contacts and the arc duration. The high wear area is usually accompanied by the occurrence of an arc, and the arc duration directly affects the damage of the contact material. If the high wear area exceeds the set wear threshold (such as exceeding 50 microns), and the arc duration exceeds 100 milliseconds, it is determined that an open circuit fault has occurred. The generation of the open circuit fault data is based on the combination of the wear depth and the arc duration, and is inferred by combining a preset fault determination model.

[0217] Step S48: Generate a fault alarm based on the open circuit fault data and upload it to the power supply system to execute the fault warning task.

[0218] In this embodiment, based on the aforementioned open - circuit fault data, an alarm threshold is set. For example, when an open - circuit fault occurs, the system needs to generate and push an alarm within 1 second. The generated alarm includes detailed information such as the fault type, occurrence time, specific conditions of contact damage, and relevant electrical parameters. This alarm is uploaded to the monitoring platform of the power supply system through wireless communication or wired communication protocols. The monitoring platform will sort the faults by priority and trigger fault warning tasks, such as shutting down, switching power supplies, or taking other emergency measures, to ensure the safe operation of the power supply system.

[0219] Preferably, this specification also provides a fault analysis system for a power supply system based on state analysis, which is used to execute the fault analysis method for a power supply system based on state analysis as described above. The fault analysis system for a power supply system based on state analysis includes:

[0220] An overload load structure identification module, which is used to obtain substation equipment data; perform load structure analysis based on the substation equipment data to obtain substation load structure data; identify the overload load structure based on the substation load structure data to obtain overload load structure data;

[0221] An impulse withstand voltage test module, which is used to detect inter - turn short - circuit of windings based on the overload load structure data to obtain inter - turn short - circuit data of windings; determine the degree of winding insulation deterioration based on the inter - turn short - circuit data of windings; perform impulse withstand voltage test based on the degree of winding insulation deterioration to generate impulse withstand voltage data;

[0222] A contact contamination degree evaluation module, which is used to detect abnormal contact welding based on the overload load structure data to obtain abnormal contact welding data; perform contact material damage analysis according to the abnormal contact welding data to obtain contact material damage data; measure the dielectric loss angle based on the contact material damage data, and evaluate the contact contamination degree according to the dielectric loss angle;

[0223] A fault alarm generation module, which is used to perform open - circuit fault analysis according to the contact contamination degree and impulse withstand voltage data to obtain open - circuit fault data; generate a fault alarm based on the open - circuit fault data and upload it to the power supply system to execute the fault warning task.

[0224] The fault analysis system for a power supply system based on state analysis of the present invention can implement any fault analysis method for a power supply system based on state analysis of the present invention. It is a medium for coordinating the operations and signal transmissions between various modules. With the fault analysis method for a power supply system based on state analysis, the internal modules of the system cooperate with each other, improving the accuracy of fault detection and the efficiency of warning response of the power supply system.

[0225] Therefore, from any perspective, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the application documents are intended to be encompassed within the present invention.

[0226] The above are only specific embodiments of the present invention, enabling those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be obvious to those skilled in the art. The general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown herein, but rather to the broadest scope consistent with the principles and novel features disclosed herein.

Claims

1. A fault analysis method for a power supply system based on state analysis, characterized in that It includes the following steps: Step S1: Obtain substation equipment data; Based on the substation equipment data, conduct a load structure analysis to obtain substation load structure data; Based on the substation load structure data, identify the overload load structure to obtain overload load structure data; Step S2: Detect the inter-turn short circuit of the winding based on the overload load structure data to obtain inter-turn short circuit data of the winding; Determine the degree of winding insulation deterioration based on the inter-turn short circuit data of the winding; Conduct an impulse withstand voltage test based on the degree of winding insulation deterioration to generate impulse withstand voltage data; Step S3: Detect abnormal fusion welding of contacts based on the overload load structure data to obtain abnormal fusion welding data of contacts; Conduct an analysis of contact material damage based on the abnormal fusion welding data of contacts to obtain contact material damage data; Measure the dielectric loss angle based on the contact material damage data, and evaluate the degree of contact contamination according to the dielectric loss angle; Step S4: Conduct an open circuit fault analysis based on the degree of contact contamination and the impulse withstand voltage data to obtain open circuit fault data; Generate a fault alarm based on the open circuit fault data and upload it to the power supply system to execute the fault warning task.

2. The fault analysis method of the power supply system based on state analysis according to claim 1, characterized in that, Specifically, Step S1 is as follows: Step S11: Obtain substation equipment data; Step S12: Analyze the substation equipment structure based on the substation equipment data; Identify the core power structure according to the substation equipment structure; Identify the auxiliary power structure according to the substation equipment structure; Step S13: Conduct a bus connection analysis based on the core power structure and the auxiliary power structure to obtain bus connection data; Step S14: Construct the substation equipment connection structure based on the core power structure, the auxiliary power structure, and the bus connection data; Step S15: Conduct a load flow simulation based on the substation equipment connection structure to obtain substation load structure data; Step S16: Identify the overload load structure based on the substation load structure data to obtain overload load structure data.

3. The fault analysis method of the power supply system based on state analysis according to claim 2, characterized in that Specifically, Step S16 is as follows: Step S161: Calculate the load factor based on the substation load structure data; Conduct a high load factor structure division on the substation load structure data according to the load factor to obtain high load factor structure data; Step S162: Calculate the load time of the high load factor structure data; Step S163: Calculate the current density of the high load factor structure data; Step S164: Conduct an overload load structure determination on the high load factor structure data according to the load time and the current density to obtain overload load structure data.

4. The fault analysis method of the power supply system based on state analysis according to claim 1, characterized in that The detection of the inter-turn short circuit of the winding in Step S2 includes: Collect the current sensing data of the overload load structure data; Conduct signal conditioning on the current sensing data to obtain conditioned current sensing signal data; Draw a current distribution map according to the conditioned current sensing signal data; Conduct a winding heat source calculation according to the current distribution map to obtain winding heat source data; Obtain the winding heat dissipation path and insulation material data; Construct a winding thermal equivalent model according to the winding heat dissipation path and the insulation material data; Input the winding heat source data into the winding thermal equivalent model and generate a winding temperature field; Conduct a winding insulation aging assessment according to the winding temperature field to obtain winding insulation aging data; Diagnose the short circuit fault based on the winding insulation aging data to obtain inter-turn short circuit data of the winding.

5. The fault analysis method of the power supply system based on state analysis according to claim 1, characterized in that, The determination of the degree of winding insulation deterioration described in step S2 includes: Calculating the short-circuit impedance based on the winding turn-to-turn short-circuit data to obtain short-circuit impedance data; Performing impedance change analysis based on the preset standard impedance data and the short-circuit impedance data to obtain impedance change data; Performing high-frequency pulse current simulation based on the winding turn-to-turn short-circuit data to obtain pulse current data; Calculating the pulse amplitude according to the pulse current data; calculating the single partial discharge quantity according to the pulse amplitude; performing time accumulation based on the single partial discharge quantity to obtain the total discharge quantity; Evaluating the severity of the discharge according to the impedance change data and the total discharge quantity; Statistically calculating the winding heat based on the severity of the discharge; Determining the degree of winding insulation deterioration according to the winding heat.

6. The fault analysis method of the power supply system based on state analysis according to claim 1, characterized in that, The impulse withstand voltage test described in step S2 includes: Determining the insulation deteriorated winding based on the degree of winding insulation deterioration, and measuring the impulse current of the insulation deteriorated winding using a high-frequency current probe to obtain impulse current data; Performing envelope detection on the impulse current data to generate an envelope signal; Identifying the decaying envelope signal based on the envelope signal; Calculating the envelope decay rate of the decaying envelope signal; Evaluating the insulation withstand capacity of the insulation deteriorated winding according to the envelope decay rate to obtain winding insulation withstand data; Performing impulse withstand voltage determination based on the winding insulation withstand data to obtain impulse withstand voltage data.

7. The fault analysis method of the power supply system based on state analysis according to claim 1, characterized in that, Step S3 is specifically: Step S31: Extracting the overload contact structure data based on the overload load structure data; Step S32: Performing overload current application simulation according to the contact structure data to obtain overload current contact data; calculating the contact temperature rise value of the overload current contact data; Calculating the contact voltage drop value of the overload current contact data; Step S33: Performing welding determination based on the contact temperature rise value and the contact voltage drop value to obtain welding data; Step S34: Calculating the contact welding energy based on the welding data; performing abnormal welding determination on the contact welding energy according to the preset contact standard welding energy to obtain contact abnormal welding data; Step S35: Identifying the contact abnormal welding area based on the contact abnormal welding data; Step S36: Irradiating the contact abnormal welding area with X-rays to generate an X-ray energy spectrum; detecting the contact surface oxide based on the X-ray energy spectrum; Step S37: Performing simulation of applying a metallographic etchant to the contact abnormal welding area to obtain the contact surface corrosion area; Identifying the molten recrystallization area based on the contact surface corrosion area; Step S38: Integrating the contact material damage according to the contact surface oxide and the molten recrystallization area to obtain contact material damage data; Step S39: Measuring the dielectric loss angle based on the contact material damage data, and evaluating the contact contamination degree according to the dielectric loss angle.

8. A fault analysis method for a power supply system based on state analysis according to claim 7, characterized in that Step S39 is specifically: Step S391: Identifying the contact damaged material based on the contact material damage data, and applying an alternating voltage to the contact damaged material to obtain alternating voltage data; Step S392: Collecting the contact damaged material current data based on the alternating voltage data; Calculating the current phase difference based on the contact damaged material current data; Step S393: Calculate the active power based on the AC voltage data and the current phase difference; calculate the reactive power based on the AC voltage data and the current phase difference; calculate the dielectric loss angle based on the active power and the reactive power; Step S394: Establish a pollution assessment level model based on the dielectric loss angle; Step S395: Determine the contact contamination degree of the contact material damage data according to the pollution assessment level model, and generate the contact contamination degree.

9. The fault analysis method of the power supply system based on state analysis according to claim 1, characterized in that, Step S4 is specifically as follows: Step S41: Perform contact surface topography detection according to the contact contamination degree to obtain contact surface topography data; Step S42: Measure the contact wear amount according to the contact surface topography data; extract the high-contact-wear area of the contact wear amount; Step S43: Identify the continuous high-value current according to the impulse withstand voltage data; Step S44: Identify the instantaneous voltage drop according to the impulse withstand voltage data; Step S45: Perform arc determination according to the continuous high-value current and the instantaneous voltage drop to obtain arc data; Step S46: Statistically analyze the arc duration of the arc data; Step S47: Perform open circuit fault determination according to the high-contact-wear area and the arc duration to obtain open circuit fault data; Step S48: Generate a fault alarm based on the open circuit fault data and upload it to the power supply system to execute the fault early warning task.

10. A fault analysis system for a power supply system based on state analysis, characterized in that, A fault analysis system for a power supply system based on state analysis as claimed in claim 1, the fault analysis system for the power supply system based on state analysis comprising: An overload load structure identification module, configured to obtain substation equipment data; perform load structure analysis based on the substation equipment data to obtain substation load structure data; identify an overload load structure based on the substation load structure data to obtain overload load structure data; An impulse withstand voltage test module, configured to detect inter-turn short circuit of the winding based on the overload load structure data to obtain inter-turn short circuit data of the winding; determine the degree of winding insulation deterioration based on the inter-turn short circuit data of the winding; perform an impulse withstand voltage test based on the degree of winding insulation deterioration to generate impulse withstand voltage data; A contact contamination degree evaluation module, configured to detect abnormal contact welding of the contact based on the overload load structure data to obtain abnormal contact welding data of the contact; perform contact material damage analysis according to the abnormal contact welding data of the contact to obtain contact material damage data; measure the dielectric loss angle based on the contact material damage data, and evaluate the contact contamination degree according to the dielectric loss angle; A fault alarm generation module, configured to perform open circuit fault analysis according to the contact contamination degree and the impulse withstand voltage data to obtain open circuit fault data; generate a fault alarm based on the open circuit fault data and upload it to the power supply system to execute the fault early warning task.

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