Switch cabinet partial discharge and temperature abnormity real-time monitoring method and system

Abstract

The invention relates to the technical field of power system monitoring, in particular to a switch cabinet partial discharge and temperature anomaly real-time monitoring method and system, and the method comprises the following steps: setting a periodic dormancy mechanism according to the historical monitoring data of a power system, and adjusting an intelligent monitoring device through the periodic dormancy mechanism; obtaining real-time monitoring information of the switch cabinet through the adjusted intelligent monitoring device, wherein the real-time monitoring information comprises an electric signal and temperature monitoring information of the switch cabinet; establishing a monitoring data processing model, processing the electric signal monitoring information and the temperature monitoring information by using the monitoring data processing model, and obtaining target detection data of the switch cabinet; and according to the target detection data, the discharge condition and the temperature change condition of the switch cabinet are analyzed, and real-time monitoring of the power system switch cabinet is realized. A periodic dormancy mechanism is set based on the power system, the intelligent monitoring device is adjusted, real-time monitoring of the switch cabinet is achieved, and then the monitoring efficiency and the intelligent level of the system are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power system monitoring, and in particular to a method and system for real-time monitoring of partial discharge and temperature anomaly of a switch cabinet. Background Art

[0002] Real-time monitoring and diagnosis of switch cabinet faults is a complex and comprehensive process, in which heating and partial discharge are the main manifestations of faults. Therefore, monitoring of equipment temperature and discharge site has become the focus of monitoring work. However, in actual operation, it is not comprehensive to judge equipment defects based solely on temperature data or discharge phenomena. Although some equipment has discharge phenomena, the temperature has not yet become abnormal; although some equipment has abnormal temperature, there is no discharge phenomenon. The existing single parameter monitoring method has limitations, which will lead to omissions and incomplete monitoring results.

[0003] Online monitoring of partial discharge and overheating defects in switchgear is an important means to improve the stability and safety of the power system. Real-time monitoring of the temperature and discharge phenomena inside the equipment can help to promptly discover and deal with potential faults, thereby ensuring the normal operation of the high-voltage switchgear and providing a solid guarantee for the stable operation of the power system. In order to improve the efficiency of existing abnormal monitoring methods and systems, it is particularly important to synchronously monitor the temperature and discharge phenomena in the switchgear. Synchronous monitoring technology can not only capture abnormal conditions inside the equipment in a timely manner, but also effectively predict device defects, providing strong support for the prevention of power accidents. Compared with traditional manual inspection methods or single monitoring technologies, online real-time monitoring technology can significantly reduce labor costs while improving the accuracy and timeliness of monitoring results. Summary of the invention

[0004] In view of the shortcomings of the existing methods and the needs of practical applications, in order to achieve accurate prediction of potential faults of switch cabinet equipment, the partial discharge and overheating of the switch cabinet are monitored online in real time, and the monitoring data is optimized and processed at the same time, and the potential faults of the high-voltage switch cabinet are effectively predicted and warned by the processed data, thereby ensuring the safe and stable operation of the switch cabinet of the power system. On the one hand, the present invention provides a method for real-time monitoring of partial discharge and temperature anomaly of the switch cabinet, and the method includes the following steps: setting a periodic sleep mechanism according to the historical monitoring data of the power system, adjusting the intelligent monitoring device through the periodic sleep mechanism, and obtaining the adjusted intelligent monitoring device; obtaining the real-time monitoring information of the switch cabinet through the adjusted intelligent monitoring device, and the real-time monitoring information includes the electrical signal monitoring information and the temperature monitoring information of the switch cabinet; establishing a monitoring data processing model, using the monitoring data processing model to process the electrical signal monitoring information and the temperature monitoring information, and obtaining the target detection data of the switch cabinet; analyzing the discharge condition and temperature change of the switch cabinet according to the target detection data, so as to achieve real-time monitoring of the switch cabinet of the power system. The present invention sets a periodic sleep mechanism according to historical monitoring data, and realizes real-time monitoring of the switch cabinet through the adjusted intelligent monitoring device, which can improve the monitoring efficiency and accuracy of the system, optimize data processing and analysis, and enhance the stability and safety of the power system.

[0005] Optionally, the setting of a periodic sleep mechanism according to the historical monitoring data of the power system includes: analyzing the dynamic power consumption status of the real-time monitoring system according to the historical monitoring data of the power system; and setting a periodic sleep mechanism according to the dynamic power consumption status; The periodic sleep mechanism satisfies the following relationship:

[0006] in, Indicates the sleep time of the real-time monitoring system. Indicates the data sampling period of the real-time monitoring system. Indicates the influence weight of the sampling data change rate, Indicates the rate of change of sampled data. The periodic sleep mechanism provided by the present invention enables the system to enter a sleep state during non-essential working periods, thereby reducing overall energy consumption, helping to reduce unnecessary energy consumption, and improving the utilization efficiency of system energy.

[0007] Optionally, the step of adjusting the intelligent monitoring device through the periodic sleep mechanism and obtaining the adjusted intelligent monitoring device includes: setting the sleep time of the intelligent monitoring device in the real-time monitoring system by using the periodic sleep mechanism; adjusting the intelligent monitoring device based on the sleep time and obtaining the adjusted intelligent monitoring device. The present invention can allocate system resources more reasonably through the periodic sleep mechanism, avoid idleness and waste of resources, and help improve the overall performance and response speed of the system.

[0008] Optionally, the establishment of the monitoring data processing model includes: establishing a monitoring data processing model based on the real-time monitoring information of the switch cabinet, and the monitoring data processing model includes a detection processing model for the partial discharge data of the switch cabinet and an optimization processing model for the temperature data of the switch cabinet. The monitoring data processing model of the present invention can analyze the partial discharge and temperature data of the switch cabinet in real time, so as to discover potential fault signs in advance, help to take timely measures to intervene, prevent the fault from expanding, and reduce economic losses.

[0009] Optionally, the monitoring data processing model is established based on the real-time monitoring information of the switch cabinet, and the monitoring data processing model includes a detection and processing model for the partial discharge data of the switch cabinet and an optimization processing model for the temperature data of the switch cabinet, including: setting the constraint conditions of the operating power of the switch cabinet equipment according to the real-time monitoring information of the switch cabinet; analyzing the distribution of the switch cabinet monitoring signal according to the real-time monitoring information of the switch cabinet; and establishing the detection and processing model of the partial discharge data of the switch cabinet based on the constraint conditions and the distribution conditions. The present invention sets the constraint conditions of the operating power of the switch cabinet equipment, thereby ensuring that the monitoring data fluctuates within a reasonable range and avoiding data anomalies or distortions.

[0010] Optionally, the constraint condition satisfies the following conditions:

[0011] in, Represents the constraints on the operating power of the switchgear equipment, Indicates the partial discharge signal frequency, Indicates the total signal capacity, Indicates the harmonics generated by the operating signal transmission of the switchgear equipment; The distribution meets the following conditions:

[0012] in, Represents the distribution index coefficient of the switch cabinet monitoring signal, represents the signal disturbance compensation value, Represents the stable value of the signal's time domain frequency, express The semaphore of time samples, Indicates the total signal capacity, Indicates the passive amplitude of the monitoring signal.

[0013] The present invention sets constraint conditions and analyzes the distribution of monitoring signals, which can improve the precision and accuracy of monitoring data, enhance the fault warning and diagnosis capabilities of the system, and facilitate efficient management and intelligent monitoring of the power system.

[0014] Optionally, the detection and processing model for the switch cabinet partial discharge data satisfies the following conditions:

[0015] in, The signal output results indicative of partial discharge information, Represents the distribution index coefficient of the monitoring signal in the switch cabinet, represents the reliability coefficient of the distribution index, represents the fuzziness of the output signal, Indicates the constraints of the operating power of the switch cabinet equipment. The detection and processing model of the present invention comprehensively considers multiple factors and improves the accuracy of the partial discharge detection results. At the same time, the model also enhances the fault warning and diagnosis capabilities of the system, which helps to improve the overall performance and reliability of the power system.

[0016] Optionally, the monitoring data processing model is established based on the real-time monitoring information of the switch cabinet, and the monitoring data processing model includes a detection processing model for partial discharge data of the switch cabinet and an optimization processing model for temperature data of the switch cabinet, including: introducing a wavelet analysis method, and establishing an optimization processing model for temperature data of the switch cabinet based on the real-time monitoring information of the switch cabinet and the wavelet analysis method; The optimization processing model of the switch cabinet temperature data satisfies the following conditions: , in, Represents the wavelet coefficients corresponding to the temperature monitoring data, represents the scale factor, express The corresponding temperature monitoring data information within the time period, represents the wavelet analysis function, Represents the time shift factor.

[0017] The present invention introduces a wavelet analysis method and establishes an optimization processing model for switch cabinet temperature data, which can improve the accuracy of temperature monitoring data, help improve the overall performance of the power system, and reduce operation and maintenance costs.

[0018] Optionally, the use of the monitoring data processing model to process the electrical signal monitoring information and the temperature monitoring information and obtain the target detection data of the switch cabinet includes: processing the electrical signal monitoring information through the detection and processing model of the switch cabinet partial discharge data and obtaining the processed electrical signal monitoring information; using the optimization processing model of the switch cabinet temperature data to process the temperature monitoring information and obtain the processed temperature monitoring information; combining the processed electrical signal monitoring information and the processed temperature monitoring information to obtain the target detection data of the switch cabinet. The present invention can quickly locate the fault point based on the target detection data, reduce unnecessary inspections and maintenance work, and thus ensure the safe operation of the power system equipment.

[0019] In the second aspect, in order to efficiently execute a switch cabinet partial discharge and temperature anomaly real-time monitoring method provided by the present invention, the present invention also provides a switch cabinet partial discharge and temperature anomaly real-time monitoring system, the above system includes a processor, an input device, an output device and a memory, the processor, the input device, the output device and the memory are interconnected, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions to execute the switch cabinet partial discharge and temperature anomaly real-time monitoring method as described in the first aspect of the present invention. The switch cabinet partial discharge and temperature anomaly real-time monitoring system of the present invention has a compact structure and stable performance, and can stably execute the switch cabinet partial discharge and temperature anomaly real-time monitoring method provided by the present invention, thereby improving the overall applicability and practical application capability of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a flow chart of the method for real-time monitoring of partial discharge and temperature anomaly of a switch cabinet of the present invention; Figure 2 It is a structural diagram of the switch cabinet partial discharge and temperature anomaly real-time monitoring system of the present invention. DETAILED DESCRIPTION

[0021] The specific embodiments of the present invention will be described in detail below. It should be noted that the embodiments described herein are only for illustration and are not intended to limit the present invention. In the following description, a large number of specific details are set forth in order to provide a thorough understanding of the present invention. However, it is obvious to those of ordinary skill in the art that these specific details do not need to be adopted to implement the present invention. In other examples, in order to avoid confusing the present invention, known circuits, software or methods are not specifically described.

[0022] Throughout the specification, references to "one embodiment," "an embodiment," "an example," or "an example" mean that a particular feature, structure, or characteristic described in conjunction with the embodiment or example is included in at least one embodiment of the present invention. Therefore, the phrases "in one embodiment," "in an embodiment," "an example," or "an example" appearing in various places throughout the specification do not necessarily all refer to the same embodiment or example. In addition, particular features, structures, or characteristics may be combined in one or more embodiments or examples in any suitable combination and / or subcombination. In addition, it should be understood by those of ordinary skill in the art that the figures provided herein are for illustrative purposes and that the figures are not necessarily drawn to scale.

[0023] See also Figure 1 In order to accurately monitor the temperature and discharge phenomenon in the switch cabinet, timely capture the abnormal situation inside the system, effectively predict and monitor the system equipment, and provide technical support for the safe operation of the power system. The present invention provides a real-time monitoring method for partial discharge and temperature anomaly of a switch cabinet. The above-mentioned real-time monitoring method for partial discharge and temperature anomaly of a switch cabinet comprises the following steps: S1. A periodic dormancy mechanism is set according to the historical monitoring data of the power system, and the intelligent monitoring device is adjusted through the periodic dormancy mechanism to obtain the adjusted intelligent monitoring device. The specific steps and implementation contents are as follows: Firstly, the dynamic power consumption status of the real-time monitoring system is analyzed based on the historical monitoring data of the power system; and a periodic sleep mechanism is set according to the above dynamic power consumption status.

[0024] In this embodiment, the historical monitoring data of the power system is analyzed to grasp the power consumption dynamics of the real-time monitoring system. The embodiment conducts a detailed and in-depth analysis of the historical monitoring data of the power system, aiming to fully grasp the power consumption dynamic characteristics of the real-time monitoring system, based on which key information such as the system power consumption change trend, peak and valley periods can be obtained, providing an information basis for the subsequent formulation and optimization of the periodic sleep mechanism.

[0025] Analyzing and mining historical data can help identify the power consumption characteristics of the system under different operating conditions and the factors that may cause abnormal power consumption. The above information not only helps to more accurately understand the power consumption dynamics of the monitoring system, but also provides strong data support for the subsequent implementation of periodic sleep and wake-up mechanisms, adjustment of data collection frequency and other strategies, further ensuring stable system operation, reducing energy consumption and improving efficiency.

[0026] A periodic sleep mechanism is set up based on the results of historical data analysis to optimize the actual performance of the intelligent monitoring device. The core of the above mechanism is to enable sensors, wireless communication modules and other devices to intelligently adjust the data acquisition frequency according to environmental changes. In an optional embodiment, when the ambient temperature remains stable or changes slowly, the system devices and modules will enter a sleep period to reduce system power consumption. On the contrary, when the ambient temperature changes significantly, the system devices and modules will be awakened immediately and the data acquisition frequency will be increased to ensure the accuracy and timeliness of the monitoring data and related signals.

[0027] Based on the historical data analysis results, the key parameter information of the real-time monitoring system, such as the data sampling period, influencing factors, and data change trends, is analyzed, and a periodic sleep mechanism is established. The setting of the sleep time needs to meet the following relationship:

[0028] in, Indicates the sleep time of the real-time monitoring system. Indicates the data sampling period of the real-time monitoring system. Indicates the influence weight of the sampling data change rate, Indicates the rate of change of sampled data.

[0029] The sleep time of the real-time monitoring system refers to the period of time when the system equipment temporarily stops the monitoring function under certain conditions. During the sleep period, the system will not collect monitoring data at a high frequency, based on which the power consumption of the system equipment can be reduced, the service life of the equipment can be extended, or the occupation of monitoring resources can be reduced during a specific period of time, so that the system can better adapt to various complex application scenarios, intelligently balance power consumption and data collection requirements, and help achieve efficient and energy-saving operation of the power system.

[0030] The data sampling period of a real-time monitoring system refers to the time interval between two adjacent measurements during the periodic measurement of data. Reasonable setting of the sampling period can ensure that the system captures changes in process variables, thereby reflecting the real-time status of the system, and achieving more efficient and stable system monitoring and detection effects.

[0031] In this embodiment, the sampling data mainly includes electrical signal monitoring information and temperature monitoring information. The influence weight of the sampling data change rate refers to the change rate of different sampling data during the processing or analysis process, that is, the speed at which different sampling data changes over time, which can be used to describe the dynamic change characteristics of different monitoring signals.

[0032] The rate of change of different sampled data refers to the speed at which the monitored information, such as electrical signals and temperature, changes over time. Electrical signals can change rapidly due to a variety of factors such as equipment operating status, load changes, power grid fluctuations, etc. In an optional embodiment, the electrical signal changes very quickly, and a high sampling rate is required to capture the relevant change data; in another optional embodiment, the electrical signal is relatively stable and changes slowly, and the sampling rate can be appropriately reduced to reduce data storage and processing requirements.

[0033] Temperature is a relatively slow-changing physical quantity that does not fluctuate as quickly as an electrical signal. However, temperature can also change under certain circumstances. Therefore, for temperature monitoring information, the sampling rate should be adjusted according to the actual situation to ensure that temperature change information is captured while avoiding unnecessary data redundancy.

[0034] Then, the sleep time of the intelligent monitoring device in the real-time monitoring system is set by using the periodic sleep mechanism; and the intelligent monitoring device is adjusted based on the sleep time to obtain the adjusted intelligent monitoring device.

[0035] Next, the sleep periods of different information monitoring devices and data acquisition devices in the real-time monitoring system are planned according to the set periodic sleep mechanism, based on which the sleep and wake-up cycles of the system devices can be set, thereby optimizing the energy consumption performance of the power system. In an optional embodiment, the sleep time is set for each intelligent monitoring device in the system according to the change rate of different sampled data, as well as the real-time performance and power consumption requirements of the system.

[0036] When setting the sleep time, it is necessary to fully consider the characteristics and change rates of different monitoring data such as electrical signals and temperature to ensure that the monitoring capabilities of key information are not reduced while reducing power consumption. Since electrical signal information changes frequently, a shorter sleep time needs to be set to ensure that the system can respond quickly to any abnormal changes; for temperature data that changes more slowly, the sleep time can be appropriately extended to further reduce the system's energy consumption.

[0037] Based on this, the intelligent monitoring device is adjusted accordingly, including but not limited to adjusting its data collection frequency, communication strategy, and wake-up mechanism, so as to obtain an intelligent monitoring device that not only meets the real-time monitoring needs but also can be energy-efficient. The above-mentioned adjusted device can not only better adapt to the actual operating conditions of the power system, but also achieve green and sustainable operation of the system under the premise of ensuring data security and accuracy.

[0038] Furthermore, the adjustment method of the intelligent monitoring device in the embodiment is only an optional condition of the present invention. In one or some other embodiments, the adjustment method of the intelligent monitoring device can be replaced according to the actual operation of the monitoring system and the data collection requirements, which helps to optimize the system performance and find an optimal adjustment strategy, thereby minimizing the system energy consumption and improving the overall performance while meeting the monitoring requirements.

[0039] S2. The real-time monitoring information of the switch cabinet is obtained through the adjusted intelligent monitoring device. The real-time monitoring information mainly includes the electrical signal monitoring information and temperature monitoring information of the switch cabinet. The specific steps and implementation contents are as follows: Through the adjusted intelligent monitoring device, the real-time monitoring information of the switch cabinet can be fully and accurately obtained. In the embodiment, the above information mainly includes the electrical signal monitoring information and temperature monitoring information of the switch cabinet. The relevant information helps to ensure the stable operation of the power system. The specific contents of the adjusted intelligent monitoring device are as follows: 1. Structure and function of intelligent monitoring device.

[0040] Guide rails and monitoring devices: The intelligent monitoring device is designed and installed on the guide rails of the switch cabinet bottom plate. The above structural design enables the monitoring device to move smoothly along the guide rails, thereby realizing comprehensive monitoring of information in various areas inside the switch cabinet.

[0041] Core components: Multiple key devices and modules are integrated in the shell of the monitoring device, including but not limited to ultraviolet detection equipment, temperature detection equipment, infrared imaging equipment and main control module. The relevant equipment and modules work together to complete the real-time monitoring of switch cabinet information.

[0042] The UV detection equipment uses a highly sensitive UV detector to capture the UV discharge signal inside the switch cabinet. The above signal is related to the partial discharge phenomenon and is an important indicator for evaluating the insulation status of the switch cabinet.

[0043] Temperature detection equipment needs to be high-precision and high-stability temperature detection equipment, including but not limited to infrared thermometers, fiber optic thermometers, wireless temperature sensors, etc., which measure information based on the infrared radiation energy of the object being measured and can provide real-time feedback on the temperature distribution inside the switch cabinet.

[0044] Infrared imaging equipment uses infrared array detectors to generate infrared images inside the switch cabinet. The above images can intuitively reflect the temperature distribution of the equipment, thus helping to detect potential equipment overheating problems.

[0045] As the core part of the monitoring device, the main control module is mainly responsible for coordinating the working conditions of various devices, including but not limited to image processing and motor control functions. It can be used to process and analyze data from ultraviolet detection equipment, temperature detection equipment, and infrared imaging equipment, and control the movement of the monitoring device on the guide rail.

[0046] Mobile monitoring equipment, the motor drives the monitoring device to move 3mm on the guide rail each time, from the left side of the guide rail to the right side, completing a cycle of movement. During the above process, the main control module will receive and process the ultraviolet discharge signal, temperature data and infrared image within the field of view of the monitoring device in real time, and superimpose the relevant information. When the monitoring device completes a cycle of movement, some real-time monitoring information of the switch cabinet can be obtained.

[0047] 2. Data acquisition and processing equipment Each set of switchgear is equipped with a collection host for real-time collection of partial discharge and temperature data. Each collection host can monitor up to multiple switchgears, which can improve monitoring efficiency and pre-process the collected data such as filtering and noise reduction, which helps to ensure the accuracy and reliability of the data. In the noise reduction process, advanced filtering technology such as Savitzky-Golay filter is used, and the parameters of the filter are determined by the K-fold cross-validation method, so as to obtain the best noise reduction effect.

[0048] In summary, real-time monitoring of the internal environment of the switch cabinet through the adjusted intelligent monitoring device and sensor technology can help to promptly discover and solve potential fault problems in the switch cabinet, thereby providing guarantee for the stable operation of the power system.

[0049] Furthermore, the method for acquiring real-time monitoring information of the switch cabinet in the present embodiment is only an optional condition of the present embodiment. In one or some other embodiments, different information acquisition methods may be required according to data collection requirements and the structural conditions of the monitoring device. Different switch cabinet structures, operating environments and monitoring requirements may require different information acquisition methods. Adjusting the method for acquiring monitoring information in the embodiment can ensure that the monitoring system can flexibly adapt to various application scenarios and improve the practicality and applicability of the system.

[0050] S3. Establish a monitoring data processing model, use the monitoring data processing model to process the electrical signal monitoring information and temperature monitoring information, and obtain the target detection data of the switch cabinet. The specific steps and implementation contents are as follows: In this embodiment, a monitoring data processing model is established based on the real-time monitoring information of the switch cabinet. The monitoring data processing model mainly includes a detection processing model for partial discharge data of the switch cabinet and an optimization processing model for temperature data of the switch cabinet.

[0051] In an optional embodiment, first, the constraints on the operating power of the switch cabinet equipment are set according to the real-time monitoring information of the switch cabinet; then, the distribution of the switch cabinet monitoring signal is analyzed according to the real-time monitoring information of the switch cabinet; and then, a detection and processing model for the partial discharge data of the switch cabinet is established based on the constraints and the distribution.

[0052] During the actual operation of the switch cabinet, due to the interference of environmental factors, the collected operation signal contains a large amount of mixed frequency signals and noise. The above factors have a significant impact on the electrical signal monitoring information of partial discharge of the switch cabinet. Therefore, this application proposes an electrical signal monitoring information processing method, which aims to remove the mixed frequency signal from the original signal.

[0053] First, the constraints of the equipment operating power are analyzed based on the coupling process parameters of the switchgear partial discharge and the load fluctuation. The above constraints meet the following conditions:

[0054] in, Represents the constraints on the operating power of the switchgear equipment, Indicates the partial discharge signal frequency, Indicates the total signal capacity, Indicates the harmonics generated by the operating signal transmission of the switchgear equipment; The operating power constraint condition means that in order to make the switch cabinet and its internal equipment work under safe, stable and efficient conditions, it is necessary to set limit conditions on the operating power to ensure that the input power and output power of each device in the switch cabinet are balanced, thereby ensuring the stable operation of the entire system.

[0055] The frequency of partial discharge signals refers to the frequency range of electromagnetic pulse signals in partial discharge phenomena. Partial discharge refers to a local, unstable, transient discharge phenomenon. When partial discharge occurs, an environment with high electric field strength and high energy density will be generated inside the equipment, causing damage and degradation of equipment materials, thereby reducing the reliability and service life of the equipment. In severe cases, fire or explosion accidents may occur.

[0056] The total signal capacity is related to the channel capacity in the system, which refers to the maximum amount of information that the system can transmit under specific conditions. In communication theory, the total signal capacity satisfies the following relationship:

[0057] in, Indicates the total signal capacity, represents the signal bandwidth, Represents the signal-to-noise ratio.

[0058] The above signal-to-noise ratio is the ratio of signal power to noise power, indicating that under given bandwidth and signal-to-noise ratio, the maximum information rate that can be transmitted by the analysis system can be analyzed.

[0059] Harmonics generated by the transmission of switchgear equipment operating signals refer to electrical quantities with frequencies that are integer multiples of the fundamental wave generated during the operation of the switchgear and its internal equipment due to the non-sinusoidal waveform changes of current and voltage. The above harmonics are generated by the operation of power electronic equipment, arc and electric light source equipment, and nonlinear electrical equipment.

[0060] Then, the distribution of monitoring signals is analyzed based on the real-time monitoring information of the switch cabinet, and the following conditions are met:

[0061] in, Represents the distribution index coefficient of the switch cabinet monitoring signal, represents the signal disturbance compensation value, Represents the stable value of the signal's time domain frequency, express The semaphore of time samples, Indicates the total signal capacity, Indicates the passive amplitude of the monitoring signal.

[0062] In the power system, the monitoring of the operating status of the switchgear is of great significance to the stability and safety of the power system. During the monitoring process, a large amount of signal data will be collected. The relevant data reflects the operating status of the switchgear and its internal equipment. The distribution index coefficient of the switchgear monitoring signal is a parameter that describes the distribution characteristics of the relevant monitoring signal. Based on this, it can be analyzed whether the distribution of the monitoring signal in different positions or different time periods of the switchgear is uniform. Uniform distribution means that the system operating status is stable, while uneven distribution indicates that there are potential problems or abnormalities in the system.

[0063] The signal disturbance compensation value refers to a compensation amount introduced into the system in order to eliminate or reduce the signal deviation caused by external or internal disturbances. The above compensation amount is conducive to the relevant information maintaining or approaching the value or law required by the input signal, thereby improving the feasibility of the monitoring method and system.

[0064] The signal time domain frequency stability value refers to the degree of deviation of the signal frequency relative to its reference frequency or expected frequency over a period of time, and the above deviation degree further reflects the stability and consistency of the signal frequency in the time domain.

[0065] In this embodiment, the signal time domain frequency stability is further analyzed, and the specific contents are as follows: Frequency stability can reflect the long-term stability and short-term stability of the signal, that is, the changing trend and fluctuation of the signal frequency over time, and is an important basis for evaluating the stability of the signal frequency. In the embodiment, the noise is identified by analyzing the changes of the signal in different time domains, and the intensity coefficients of various noises are calculated, based on which the fluctuation of the signal frequency can be intuitively reflected.

[0066] In this embodiment, the monitoring time interval is divided into n time samples, and the frequency deviation between adjacent time samples is calculated to evaluate the stability of the signal frequency. The monitoring time interval T is divided into n equally spaced time samples, satisfying the following relationship: ,The above method can effectively reflect the fluctuation of the signal frequency in different ,time periods, and is an important indicator for evaluating the performance of ,frequency standards.

[0067] The time domain frequency stability value of the above signal satisfies the following relationship:

[0068] in, Indicates the stable value of the signal frequency in the time domain, Indicates the number of time samples in the monitoring time interval, represents the average monitoring time of different time samples, express The phase measurement of the time samples, express The phase measurement of the time samples, express The phase measurement of the time samples, express The phase measurement of the time samples, express Phase measurement of the time samples.

[0069] The signal quantities of different time samples refer to the values ​​or states of the signal quantities observed at different time points or time periods, which further reflects the data collection situation or synchronization state of the system at different times.

[0070] The passive amplitude of a monitoring signal usually refers to the signal amplitude obtained by passive reception and measurement without active interference or excitation of the signal source. It reflects the strength or size of the signal at a certain moment or in a certain period of time. During the data monitoring process, the monitoring system can receive the signal from the signal source, process and analyze it, and thus obtain the amplitude information of the monitoring signal.

[0071] In order to more accurately identify and process the partial discharge phenomenon inside the switch cabinet, a fuzzy parameter identification method is introduced in the embodiment. The above method uses fuzzy mathematics theory to effectively process the uncertainty and ambiguity in the discharge data, thereby improving the accuracy and reliability of partial discharge information.

[0072] Taking into account the distribution characteristics, constraints and fuzzy parameter identification methods of the monitoring signals, a detection and processing model for partial discharge data of switchgear was established. Based on this, the electrical signal monitoring information was comprehensively analyzed and processed, and the characteristic information of the electrical signal can be effectively extracted.

[0073] The detection and processing model of the above switchgear partial discharge data meets the following conditions:

[0074] in, The signal output results indicative of partial discharge information, Represents the distribution index coefficient of the monitoring signal in the switch cabinet, represents the reliability coefficient of the distribution index, represents the fuzziness of the output signal, Represents the constraints on the operating power of the switchgear equipment.

[0075] The signal output result of partial discharge information refers to the signal data or information obtained after processing and analysis of the partial discharge phenomenon monitored in the switch cabinet. The above signal output result contains relevant characteristics about partial discharge and is an important basis for evaluating the insulation status of power equipment, predicting potential faults and taking corresponding maintenance measures.

[0076] The reliability coefficient of the distribution index can describe the stability and reliability of the distribution characteristics of electrical signals under specific conditions.

[0077] Fuzzy control method is a control method based on fuzzy logic and fuzzy set theory. Its core is to realize intelligent control of the system through fuzzification, fuzzy reasoning and defuzzification. In the above process, both the input and output signals of the system need to be fuzzified in order to better adapt to fuzzy logic operations and obtain the fuzzy quantity of the output signal of the monitoring system.

[0078] In another optional embodiment, a wavelet analysis method is introduced, and an optimization processing model for the switch cabinet temperature data is established based on the real-time monitoring information of the switch cabinet and the wavelet analysis method.

[0079] The data acquisition and processing device in the embodiment is the core component of temperature monitoring. It receives sensor data from the wireless communication module and parses, calculates, stores and displays the temperature monitoring information. In order to ensure the effective acquisition and storage of temperature monitoring information, the embodiment uses an industrial computer as the hardware basis to ensure the efficiency and smoothness of the data processing and storage process.

[0080] At the software level, based on Python data processing program, wavelet analysis method is used to achieve filtering, normalization and anomaly detection of temperature monitoring information. In order to further explore the potential characteristics and relationship between temperature monitoring information and detection time, the temperature monitoring signal is mapped to the scale time plane using wavelet analysis method, so as to obtain the wavelet coefficients corresponding to the temperature monitoring data.

[0081] The above switch cabinet temperature data optimization processing model meets the following conditions:

[0082] in, Represents the wavelet coefficients corresponding to the temperature monitoring data, represents the scale factor, express The corresponding temperature monitoring data information within the time period, represents the wavelet analysis function, Represents the time shift factor.

[0083] In wavelet analysis, the scale factor can also be called the expansion factor, which is the compression or stretching factor of the wavelet function in the time direction, and can be used to adjust the width of the wavelet function to better adapt to the signal characteristics of different scales. That is to say, the scale factor determines the waveform characteristics of the wavelet function in different time domains. By changing the scale factor, wavelet functions of different scales and positions can be obtained, thereby realizing multi-scale analysis of the signal.

[0084] The temperature monitoring data information corresponding to different time periods refers to the data set obtained by regular or real-time measurement and recording of the temperature of different areas or equipment in a continuous time series. The above data includes the temperature values ​​​​at different time points, as well as other related information, such as temperature change trends, abnormal temperature values ​​​​and their occurrence time.

[0085] The wavelet analysis function matches the input signal by scaling and translating. The wavelet analysis function can analyze the signal at different times and scales according to the different frequency characteristics of the signal, thereby effectively capturing the local characteristics of the signal.

[0086] In wavelet analysis, the time translation factor can also be called the displacement factor or translation parameter, which refers to the parallel movement of the wavelet function on the time axis during the wavelet transform process. The above time translation factor determines the starting position of the wavelet function on the time axis. By changing the time translation factor, the wavelet function at different time points can be obtained, thereby realizing a detailed analysis of the signal in the time dimension.

[0087] Finally, in this embodiment, the electrical signal monitoring information is processed by the detection and processing model of the partial discharge data of the switch cabinet, and the processed electrical signal monitoring information is obtained; the temperature monitoring information is processed by the optimization processing model of the temperature data of the switch cabinet, and the processed temperature monitoring information is obtained; the processed electrical signal monitoring information and the processed temperature monitoring information are combined to obtain the target detection data of the switch cabinet.

[0088] In this embodiment, a comprehensive data processing process is implemented to effectively process the electrical signal monitoring information and temperature monitoring information, which is conducive to the subsequent comprehensive evaluation of the operating status of the switch cabinet. The switch cabinet partial discharge data detection and processing model is used to analyze the electrical signal monitoring information collected inside the switch cabinet, which can accurately identify and extract the characteristic information related to partial discharge in the electrical signal, thereby generating processed electrical signal monitoring information, which in turn provides important clues about the electrical insulation status inside the switch cabinet.

[0089] At the same time, the temperature monitoring information is processed through the optimization processing model of the switch cabinet temperature data. Based on various factors such as wavelet analysis functions, environmental monitoring data, and signal processing parameters, the original temperature monitoring information is corrected and optimized. Based on the above process, more accurate and reliable temperature monitoring information can be obtained, which helps to timely detect problems such as switch cabinet overheating.

[0090] After obtaining the processed electrical signal monitoring information and temperature monitoring information, the relevant monitoring data is further integrated and correlated. By comparing and analyzing the correlation between the two data sets, the operating status and safety risks of the switchgear can be more deeply understood. Finally, the target detection data of the switchgear is generated by combining the above information, which further provides the basis for evaluating the overall operating status of the switchgear.

[0091] Furthermore, the method for acquiring target detection data in the present embodiment is merely an optional condition of the present embodiment. In one or some other embodiments, the method for acquiring target detection data may be adjusted according to the real-time monitoring requirements of the switch cabinet and the actual situation of the monitoring data. Setting the method for acquiring target detection data as an adjustable and optimized process may help to better meet actual needs, continuously improve system performance, and provide a more solid guarantee for the safe and stable operation of the switch cabinet.

[0092] S4. Analyze the discharge status and temperature change of the switch cabinet according to the target detection data to realize real-time monitoring of the power system switch cabinet. The specific steps and implementation contents are as follows: By comparing historical data and target detection data, abnormal discharge phenomena and abnormal temperature changes in the switchgear can be discovered in a timely manner, and their impact on the safe operation of the switchgear can be evaluated.

[0093] Based on the target detection data, partial discharge is identified, located and the discharge intensity is quantified. By comparing historical data and real-time monitoring data, abnormal change trends of discharge phenomena can be discovered in time and their impact on switchgear operation can be evaluated.

[0094] In addition to the discharge status, it is also necessary to pay close attention to the temperature changes of the switch cabinet. Through the target detection data, it is possible to timely detect abnormal temperatures or local temperature increases, and determine whether they may cause safety hazards such as equipment failure or fire. At the same time, the temperature data change trend analysis can also be used to predict the temperature changes of the switch cabinet in the future, providing strong support for preventive maintenance.

[0095] A comprehensive analysis is conducted based on the analysis of discharge conditions and temperature changes to comprehensively evaluate the operating status of the switchgear. When a potential fault or abnormal phenomenon is detected, the system can immediately trigger the alarm mechanism and send a clear alarm signal to relevant personnel, which helps to respond quickly and take corresponding measures to prevent the fault from further expanding or causing more serious accidents.

[0096] Finally, the target detection data and analysis results are recorded and a detailed monitoring report is generated, which helps relevant personnel understand the operating status of the switchgear and can also provide a reference for subsequent troubleshooting and preventive maintenance work.

[0097] A method for real-time monitoring of partial discharge and temperature anomaly of a switch cabinet also includes setting corresponding visual monitoring equipment.

[0098] The method of the present invention not only focuses on the optimization and upgrading of the monitoring data processing flow, but also emphasizes the comprehensive configuration and efficient use of monitoring equipment. In the embodiment, a corresponding visual monitoring device is set up, which is composed of two core parts: a monitoring host and monitoring software, which together constitute the core components of real-time monitoring of partial discharge and temperature anomaly of the switch cabinet.

[0099] The monitoring host is the receiving and storage center of the target detection data. It can not only receive the target detection data in real time, but also ensure the safe storage of relevant data, providing a reliable basis for subsequent detection data analysis and troubleshooting. At the same time, the monitoring host runs a special monitoring software, which has a series of powerful functions to meet the diverse needs of real-time monitoring of switch cabinets.

[0100] The functions of the above monitoring software include but are not limited to: real-time display and query of monitoring data, spectrum display, anti-interference processing, real-time alarm and alarm query, etc. Through the real-time display and query function, the software interface can clearly display the real-time data of multiple measurement channels, and can also view relevant historical data to facilitate a comprehensive understanding of the operating status of the switch cabinet; the spectrum display function provides a more intuitive data diagnosis method, which displays the changing trends and characteristics of the data in a graphical way, which helps to quickly discover potential problems.

[0101] In addition, the system monitoring software also has anti-interference capabilities. Through the dual protection of hardware and software filtering, the impact of background noise on monitoring data is reduced, ensuring the accuracy and reliability of target detection data. When partial discharge or temperature abnormality is detected, the monitoring software can immediately trigger the alarm function, issue an alarm signal in time, and remind relevant personnel to take corresponding measures. At the same time, the alarm query function provides a convenient alarm record query service, which helps to trace and analyze the cause and process of the fault.

[0102] On the other hand, the above switch cabinet partial discharge and temperature anomaly real-time monitoring method also fully considers the scalability and compatibility of the corresponding system. The system has the function of docking with other platforms, and can achieve seamless connection with other monitoring systems or management platforms to achieve data sharing and interaction, further improving the overall efficiency and practical value of the system.

[0103] In summary, the real-time monitoring method for partial discharge and temperature anomaly of switchgear configures visual monitoring equipment, optimizes data processing procedures and methods, and provides monitoring software functions, thereby realizing real-time monitoring and efficient management of partial discharge and temperature anomaly of switchgear, and providing a strong guarantee for the safe and stable operation of the switchgear.

[0104] See also Figure 2 In an optional embodiment, in order to efficiently execute the real-time monitoring method for partial discharge and temperature anomaly of a switch cabinet provided by the present invention, the present invention further provides a real-time monitoring system for partial discharge and temperature anomaly of a switch cabinet, the above-mentioned real-time monitoring system for partial discharge and temperature anomaly of a switch cabinet comprises a processor, an input device, an output device and a memory, the processor, the input device, the output device and the memory are interconnected, wherein the memory is used to store a computer program, the computer program comprises program instructions, the processor is configured to call the program instructions, and execute the specific steps of the embodiment related to the real-time monitoring method for partial discharge and temperature anomaly of a switch cabinet provided by the present invention. The real-time monitoring system for partial discharge and temperature anomaly of a switch cabinet of the present invention has a complete structure, is objective and stable, and can efficiently execute the real-time monitoring method for partial discharge and temperature anomaly of a switch cabinet of the present invention, thereby improving the overall applicability and practical application capability of the present invention.

[0105] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and specification of the present invention.

Claims

1. A method for real-time monitoring of partial discharge and temperature anomaly of a switch cabinet, characterized in that: The steps include: A periodic dormancy mechanism is set according to historical monitoring data of the power system, and the intelligent monitoring device is adjusted through the periodic dormancy mechanism to obtain an adjusted intelligent monitoring device; The real-time monitoring information of the switch cabinet is obtained by the adjusted intelligent monitoring device, wherein the real-time monitoring information includes the electrical signal monitoring information and the temperature monitoring information of the switch cabinet; Establishing a monitoring data processing model, using the monitoring data processing model to process the electrical signal monitoring information and the temperature monitoring information, and obtaining target detection data of the switch cabinet; The discharge status and temperature change of the switch cabinet are analyzed according to the target detection data to realize real-time monitoring of the power system switch cabinet.

2. The method for real-time monitoring of partial discharge and temperature anomaly of a switch cabinet according to claim 1, characterized in that: The periodic dormancy mechanism is set according to the historical monitoring data of the power system, including: Analyze the dynamic power consumption status of the real-time monitoring system based on the historical monitoring data of the power system; Setting a periodic sleep mechanism according to the dynamic power consumption status; The periodic sleep mechanism satisfies the following relationship: ， in, Indicates the sleep time of the real-time monitoring system. Indicates the data sampling period of the real-time monitoring system. Indicates the influence weight of the sampling data change rate, Indicates the rate of change of sampled data.

3. The method for real-time monitoring of partial discharge and temperature anomaly of a switch cabinet according to claim 2, characterized in that: The intelligent monitoring device is adjusted by the periodic sleep mechanism, and the adjusted intelligent monitoring device includes: Using the periodic sleep mechanism to set the sleep time of the intelligent monitoring device in the real-time monitoring system; The intelligent monitoring device is adjusted based on the sleep time, and an adjusted intelligent monitoring device is obtained.

4. The method for real-time monitoring of partial discharge and temperature anomaly of a switch cabinet according to claim 1, characterized in that: The establishment of the monitoring data processing model comprises: A monitoring data processing model is established based on the real-time monitoring information of the switch cabinet, and the monitoring data processing model includes a detection processing model for partial discharge data of the switch cabinet and an optimization processing model for temperature data of the switch cabinet.

5. The method for real-time monitoring of partial discharge and temperature anomaly of a switch cabinet according to claim 4 is characterized in that: The monitoring data processing model is established based on the real-time monitoring information of the switch cabinet, and the monitoring data processing model includes a detection processing model for the partial discharge data of the switch cabinet and an optimization processing model for the temperature data of the switch cabinet, including: Set the operating power constraints of the switch cabinet equipment according to the real-time monitoring information of the switch cabinet; Analyze the distribution of switch cabinet monitoring signals based on the real-time monitoring information of the switch cabinet; A detection and processing model for switch cabinet partial discharge data is established based on the constraint conditions and the distribution conditions.

6. The method for real-time monitoring of partial discharge and temperature anomaly of a switch cabinet according to claim 5, characterized in that: The constraints satisfy the following conditions: ， in, represents the constraints on the operating power of the switchgear equipment, Indicates the partial discharge signal frequency, Indicates the total signal capacity, Indicates the harmonics generated by the operating signal transmission of the switchgear equipment; The distribution meets the following conditions: ， in, Represents the distribution index coefficient of the switch cabinet monitoring signal, represents the signal disturbance compensation value, Represents the stable value of the signal's time domain frequency, express The semaphore of time samples, Indicates the total signal capacity, Indicates the passive amplitude of the monitoring signal.

7. The method for real-time monitoring of partial discharge and temperature anomaly of a switch cabinet according to claim 5, characterized in that: The switch cabinet partial discharge data detection and processing model meets the following conditions: , in, The signal output results indicative of partial discharge information, Represents the distribution index coefficient of the monitoring signal in the switch cabinet, represents the reliability coefficient of the distribution index, represents the fuzziness of the output signal, Represents the constraints on the operating power of the switchgear equipment.

8. The method for real-time monitoring of partial discharge and temperature anomaly of a switch cabinet according to claim 4, characterized in that: The monitoring data processing model is established based on the real-time monitoring information of the switch cabinet, and the monitoring data processing model includes a detection processing model for the partial discharge data of the switch cabinet and an optimization processing model for the temperature data of the switch cabinet, including: Introducing a wavelet analysis method, and establishing an optimization processing model for switch cabinet temperature data based on the switch cabinet real-time monitoring information and the wavelet analysis method; The optimization processing model of the switch cabinet temperature data satisfies the following conditions: ， in, Represents the wavelet coefficients corresponding to the temperature monitoring data, represents the scale factor, express The corresponding temperature monitoring data information within the time period, represents the wavelet analysis function, Represents the time shift factor.

9. The method for real-time monitoring of partial discharge and temperature anomaly of a switch cabinet according to claim 4, characterized in that: The using the monitoring data processing model to process the electrical signal monitoring information and the temperature monitoring information and obtaining the target detection data of the switch cabinet includes: Processing the electrical signal monitoring information through a detection and processing model of switch cabinet partial discharge data, and obtaining processed electrical signal monitoring information; Processing the temperature monitoring information using an optimization processing model for switch cabinet temperature data, and obtaining processed temperature monitoring information; The target detection data of the switch cabinet is obtained by combining the processed electrical signal monitoring information and the processed temperature monitoring information.

10. A switch cabinet partial discharge and temperature anomaly real-time monitoring system, characterized in that: The system includes a processor, an input device, an output device and a memory, wherein the processor, the input device, the output device and the memory are interconnected, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions to execute the real-time monitoring method for partial discharge and temperature anomaly of a switch cabinet according to any one of claims 1 to 9.

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