Multi-mode fusion monitoring system for intelligent switch cabinet

Abstract

The invention relates to the technical field of intelligent switch cabinet monitoring, and particularly discloses a multi-mode fusion monitoring system for an intelligent switch cabinet. The system is provided with a use environment data analysis module, a monitoring error item matching module, a first monitoring signal analysis module, a second monitoring signal analysis module, a fusion monitoring factor acquisition module and a fusion monitoring result output module. The problems that a traditional single-mode monitoring method is difficult to comprehensively and accurately evaluate the overall state of the intelligent switch cabinet, information islands exist in the single-mode monitoring method, and relevance among various monitoring information cannot be fully utilized are solved. By monitoring electrical parameters, vibration characteristics and the like and combining and fusing monitoring error terms, the errors can be quantized and compensated, the system can evaluate the state of the switch cabinet more comprehensively, the limitation of single-factor evaluation is avoided, and association among different modes can be mined.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent switch cabinet monitoring, and in particular to a multi-modal fusion monitoring system for an intelligent switch cabinet. Background Art

[0002] In modern power systems, as a key device for power distribution and control, the reliable operation of intelligent switchgear is crucial to ensuring the stability of the entire power network. As industrial production and social life become increasingly dependent on power supply, power outages may cause huge economic losses and social impacts. Therefore, a high-precision monitoring system is needed to ensure the normal operation of intelligent switchgear, detect potential faults in time and take measures.

[0003] Smart switchgear integrates numerous electrical, mechanical and automation components. These components interact with each other, and their operating status is affected by many factors. The aging of electrical components will affect their electrical performance, and environmental factors such as temperature, humidity and dust will also cause corrosion and short circuit risks to the internal components of the switchgear.

[0004] Nowadays, there are still some shortcomings in the research on multimodal fusion monitoring of intelligent switch cabinets. Specifically, the traditional single-modal monitoring method is difficult to comprehensively and accurately evaluate the overall status of the intelligent switch cabinet. Therefore, a multimodal fusion monitoring system is needed to comprehensively consider various factors. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a multimodal fusion monitoring system for an intelligent switch cabinet, which can effectively solve the problems involved in the above-mentioned background technology.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a multimodal fusion monitoring system for an intelligent switch cabinet, comprising an environment data analysis module, a monitoring error item matching module, a first monitoring signal analysis module, a second monitoring signal analysis module, a fusion monitoring factor acquisition module and a fusion monitoring result output module, wherein: the environment data analysis module is used to analyze the use environment of the intelligent switch cabinet to obtain the use environment data of the intelligent switch cabinet; the monitoring error item matching module is used to construct an intelligent switch cabinet use environment monitoring model based on the use environment data of the intelligent switch cabinet, output the intelligent switch cabinet use environment monitoring factor, and match the intelligent switch cabinet fusion monitoring error item; The first monitoring signal analysis module is used to obtain the electrical parameters of the intelligent switch cabinet, and obtain the first monitoring signal of the intelligent switch cabinet based on the obtained electrical parameters of the intelligent switch cabinet; the second monitoring signal analysis module is used to construct a vibration characteristic model of the intelligent switch cabinet and output the second monitoring signal of the intelligent switch cabinet; the fusion monitoring factor acquisition module is used to analyze the usage status characteristics of the intelligent switch cabinet to obtain the third monitoring signal of the intelligent switch cabinet, and combine the first monitoring signal of the intelligent switch cabinet and the second monitoring signal of the intelligent switch cabinet to obtain the fusion monitoring factor of the intelligent switch cabinet; the fusion monitoring result output module is used to obtain the multimodal fusion monitoring result of the intelligent switch cabinet based on the trained linear regression model, combined with the fusion monitoring error term of the intelligent switch cabinet and the fusion monitoring factor of the intelligent switch cabinet.

[0007] As a further solution, the use environment of the intelligent switch cabinet is analyzed to obtain the use environment data of the intelligent switch cabinet. The specific analysis process includes: obtaining the use environment temperature of the intelligent switch cabinet ; Get the relative humidity of the environment where the intelligent switch cabinet is used ; Calculate the dew point temperature of the intelligent switch cabinet operating environment : ; Monitor sulfur dioxide concentration in the surrounding environment of intelligent switch cabinet , Nitrogen oxide concentration in the environment around the intelligent switch cabinet ; Detect dust particle concentration in the environment where the intelligent switch cabinet is used The operating environment temperature of the intelligent switch cabinet, the relative humidity of the operating environment of the intelligent switch cabinet, the dew point temperature of the operating environment of the intelligent switch cabinet, the sulfur dioxide concentration in the environment around the intelligent switch cabinet, the nitrogen oxide concentration in the environment around the intelligent switch cabinet and the dust particle concentration in the environment around the intelligent switch cabinet are recorded as the operating environment data of the intelligent switch cabinet.

[0008] As a further solution, based on the use environment data of the smart switch cabinet, a smart switch cabinet use environment monitoring model is constructed to output the smart switch cabinet use environment monitoring factors. The specific analysis process is as follows: Based on the use environment data of the smart switch cabinet, a smart switch cabinet use environment monitoring model is constructed: ; In the formula, The environmental monitoring factor used for the intelligent switch cabinet, e is a natural constant.

[0009] As a further solution, the intelligent switch cabinet fusion monitoring error items are matched. The specific analysis process is: obtain the intelligent switch cabinet usage environment monitoring factor-intelligent switch cabinet fusion monitoring error item mapping table pre-stored in the database, and find the matching intelligent switch cabinet fusion monitoring error item according to the intelligent switch cabinet usage environment monitoring factor by searching the mapping table.

[0010] As a further solution, the electrical parameters of the intelligent switch cabinet are obtained, and based on the obtained electrical parameters of the intelligent switch cabinet, the first monitoring signal of the intelligent switch cabinet is obtained. The specific analysis process is: calculating the voltage fluctuation signal of the intelligent switch cabinet: ; In the formula, It is the voltage fluctuation signal of the intelligent switch cabinet. is the maximum value of the voltage of the intelligent switch cabinet during the monitoring period. is the minimum value of the voltage of the intelligent switch cabinet during the monitoring period. is the rated voltage of the intelligent switch cabinet, and e is a natural constant; During the monitoring period, the current sensor is used to measure the maximum current of the intelligent switch cabinet. ; Calculate the power factor of the intelligent switch cabinet: ; In the formula, is the power factor of the intelligent switch cabinet, P is the active power of the intelligent switch cabinet, and S is the apparent power of the intelligent switch cabinet; The voltage fluctuation signal of the intelligent switch cabinet, the maximum current of the intelligent switch cabinet and the power factor of the intelligent switch cabinet are comprehensively analyzed based on the electrical parameters of the intelligent switch cabinet to obtain the first monitoring signal of the intelligent switch cabinet. The first monitoring signal of the intelligent switch cabinet is used as the analysis basis for obtaining the fusion monitoring factor of the intelligent switch cabinet and is recorded as the electrical parameter of the intelligent switch cabinet.

[0011] As a further solution, the first monitoring signal of the intelligent switch cabinet, the specific analysis process is: ; In the formula, It is the first monitoring signal of the intelligent switch cabinet. is the rated current of the intelligent switch cabinet, For setting The compensation factor, For setting The compensation factor, For setting compensation factor.

[0012] As a further solution, a vibration characteristic model of the intelligent switch cabinet is constructed to output the second monitoring signal of the intelligent switch cabinet. The specific analysis process is: obtaining the vibration characteristic data of the intelligent switch cabinet, which specifically includes the vibration acceleration amplitude of the intelligent switch cabinet , Intelligent switch cabinet vibration displacement amplitude , Average vibration frequency of intelligent switch cabinet ; Based on the acquired intelligent switch cabinet vibration characteristic data, the intelligent switch cabinet vibration characteristic model is constructed: ; In the formula, It is the second monitoring signal of the intelligent switch cabinet. For setting The compensation factor, For setting The compensation factor, For setting The compensation factor of , e is a natural constant.

[0013] As a further solution, the usage status characteristics of the intelligent switch cabinet are analyzed to obtain the third monitoring signal of the intelligent switch cabinet. The specific analysis process is: obtaining the insulation resistance of the intelligent switch cabinet ; Calculate the temperature rise signal of the intelligent switch cabinet contact: ; In the formula, It is the temperature rise signal of the contact of the intelligent switch cabinet. is the contact temperature of the intelligent switch cabinet, is the ambient temperature of the intelligent switch cabinet, and e is a natural constant; Obtaining the travel deviation signal of the operating mechanism of the circuit breaker of the intelligent switch cabinet; ; In the formula, It is the travel deviation signal of the operating mechanism of the circuit breaker of the intelligent switch cabinet. is the actual travel of the circuit breaker operating mechanism of the intelligent switch cabinet, It is the reference stroke of the operating mechanism of the circuit breaker of the intelligent switch cabinet; Get the service life of the smart switch cabinet Based on the insulation resistance of the intelligent switch cabinet, the temperature rise signal of the contact of the intelligent switch cabinet, the travel deviation signal of the circuit breaker operating mechanism of the intelligent switch cabinet and the service life of the intelligent switch cabinet, a comprehensive analysis is performed to obtain the third monitoring signal of the intelligent switch cabinet. The third monitoring signal of the intelligent switch cabinet is used as the analysis basis for obtaining the fusion monitoring factor of the intelligent switch cabinet. ; In the formula, It is the third monitoring signal of the intelligent switch cabinet. For setting The compensation factor, For setting The compensation factor, For setting The compensation factor, For setting compensation factor.

[0014] As a further solution, the first monitoring signal of the smart switch cabinet and the second monitoring signal of the smart switch cabinet are combined to obtain the fusion monitoring factor of the smart switch cabinet. The specific analysis process is: the first monitoring signal of the smart switch cabinet, the second monitoring signal of the smart switch cabinet and the third monitoring signal of the smart switch cabinet are accumulated and processed to obtain the fusion monitoring factor of the smart switch cabinet. The fusion monitoring factor of the smart switch cabinet is used as the analysis basis for outputting the multimodal fusion monitoring results of the smart switch cabinet.

[0015] As a further solution, based on the trained linear regression model, combined with the intelligent switch cabinet fusion monitoring error term and the intelligent switch cabinet fusion monitoring factor, the multimodal fusion monitoring result of the intelligent switch cabinet is obtained. The specific analysis process is: the intelligent switch cabinet fusion monitoring error term and the intelligent switch cabinet fusion monitoring factor are input into the trained linear regression model; the trained linear regression model is expressed as: ; In the formula, It is the multi-modal fusion monitoring result indicator of the intelligent switch cabinet. is the intercept, is the slope, Integrate monitoring factors into smart switch cabinets. Integrate monitoring error terms for smart switchgear; Output the multimodal fusion monitoring result indicators of the intelligent switch cabinet; obtain the multimodal fusion monitoring result indicator-intelligent switch cabinet multimodal fusion monitoring result mapping table pre-stored in the database, and find the matching multimodal fusion monitoring result of the intelligent switch cabinet according to the multimodal fusion monitoring result indicator of the intelligent switch cabinet by searching the mapping table.

[0016] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: (1) The present invention provides a multi-modal fusion monitoring system for an intelligent switch cabinet. By using an environmental data analysis module, the system can take into account the environmental factors of the intelligent switch cabinet. By taking into account the monitoring error, the system can correct the monitoring results, making the output fusion monitoring results more accurate and reliable.

[0017] (2) By combining the monitoring of electrical parameters, vibration characteristics and other aspects, the system can more comprehensively evaluate the status of the switch cabinet, avoiding the limitation of single factor evaluation. The system integrates the first monitoring signal (electrical parameters), the second monitoring signal (vibration characteristics) and the third monitoring signal (usage status characteristics), and can mine the correlation between different modes.

[0018] (3) The present invention obtains the multimodal fusion monitoring result of the intelligent switch cabinet by combining the intelligent switch cabinet fusion monitoring error term and the intelligent switch cabinet fusion monitoring factor based on the trained linear regression model. In the actual monitoring process, the monitoring data of the intelligent switch cabinet will be interfered by various factors, thereby generating errors. By combining the fusion monitoring error term, these errors can be quantified and compensated.

[0019] (4) The present invention can predict the future state change trend of the intelligent switch cabinet by using historical data and current fusion monitoring factors based on the trained linear regression model. When the fusion monitoring result approaches or exceeds the set fault threshold, the system can issue a warning signal in time, effectively avoiding the impact of the fault on the normal operation of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0021] Figure 1 It is a schematic diagram of system module connection of the present invention; Figure 2 This is a flow chart of the steps of analyzing the use environment of the intelligent switch cabinet according to the present invention. DETAILED DESCRIPTION

[0022] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0023] See also Figure 1 An embodiment of the present invention provides a multimodal fusion monitoring technology solution for an intelligent switch cabinet: a multimodal fusion monitoring system for an intelligent switch cabinet, including an environment data analysis module, a monitoring error term matching module, a first monitoring signal analysis module, a second monitoring signal analysis module, a fusion monitoring factor acquisition module and a fusion monitoring result output module.

[0024] The usage environment data analysis module is used to analyze the usage environment of the intelligent switch cabinet and obtain the usage environment data of the intelligent switch cabinet.

[0025] like Figure 2 As shown, the specific analysis process includes: obtaining the ambient temperature of the intelligent switch cabinet ; Get the relative humidity of the environment where the intelligent switch cabinet is used ; Calculate the dew point temperature of the intelligent switch cabinet operating environment : ; Monitor sulfur dioxide concentration in the surrounding environment of intelligent switch cabinet , Nitrogen oxide concentration in the environment around the intelligent switch cabinet ; Detect dust particle concentration in the environment where the intelligent switch cabinet is used The operating environment data of the smart switch cabinet specifically include the operating environment temperature of the smart switch cabinet, the relative humidity of the operating environment of the smart switch cabinet, the dew point temperature of the operating environment of the smart switch cabinet, the sulfur dioxide concentration in the environment around the smart switch cabinet, the nitrogen oxide concentration in the environment around the smart switch cabinet, and the dust particle concentration in the environment around the smart switch cabinet.

[0026] Obtaining the ambient temperature of the intelligent switch cabinet can ensure that the equipment works within the appropriate temperature range. Too high or too low temperature will affect the performance and life of the electrical components in the switch cabinet. Obtaining relative humidity and calculating the dew point temperature can help prevent problems caused by excessive humidity. High humidity environment can easily cause moisture inside the switch cabinet, resulting in electrical short circuits, corrosion of metal parts and other faults. By monitoring humidity and dew point temperature, measures such as dehumidification can be taken to keep the inside of the switch cabinet dry and reduce the risk of equipment failure.

[0027] By monitoring the concentration of sulfur dioxide, nitrogen oxides and dust particles in the surrounding environment, we can understand the degree of pollution in the environment where the switch cabinet is located. These pollutants will adhere to the surface of the switch cabinet or enter the interior, affecting the heat dissipation, insulation and other performance of the equipment. According to the monitoring data, targeted protective measures can be taken, such as strengthening sealing, regular cleaning, etc., to improve the adaptability of the equipment to the environment. At the same time, it also helps to optimize the maintenance plan, prevent equipment damage caused by environmental factors in advance, and reduce maintenance costs.

[0028] The monitoring error term matching module is used to build an intelligent switch cabinet usage environment monitoring model based on the intelligent switch cabinet usage environment data, output the intelligent switch cabinet usage environment monitoring factor, and match the intelligent switch cabinet fusion monitoring error term.

[0029] The specific analysis process is as follows: Based on the usage environment data of the smart switch cabinet, a monitoring model for the usage environment of the smart switch cabinet is constructed: ; In the formula, The environmental monitoring factor used for the intelligent switch cabinet, e is a natural constant.

[0030] Obtain a mapping table of intelligent switch cabinet usage environment monitoring factors and intelligent switch cabinet fusion monitoring error items pre-stored in the database, and find matching intelligent switch cabinet fusion monitoring error items according to the intelligent switch cabinet usage environment monitoring factors by searching the mapping table.

[0031] Taking into account multiple environmental factors such as ambient temperature, dew point temperature, sulfur dioxide concentration, nitrogen oxide concentration, dust particle concentration and relative humidity, an environmental monitoring factor is used to quantify the impact of the overall environment on the intelligent switch cabinet. This allows a more comprehensive and intuitive understanding of the comprehensive effect of environmental conditions on the equipment, rather than looking at each environmental parameter in isolation.

[0032] By building models and calculating environmental monitoring factors, the environmental status of the smart switch cabinet can be monitored more accurately. Compared with monitoring each environmental parameter separately, environmental monitoring factors can provide a comprehensive indicator, which is more convenient for evaluating and comparing environmental quality and timely discovering the impact of subtle changes in the environment on the equipment.

[0033] Obtain the intelligent switch cabinet use environment monitoring factor-intelligent switch cabinet fusion monitoring error term mapping table pre-stored in the database, and find the matching fusion monitoring error term according to the calculated environmental monitoring factor. This helps to accurately analyze the impact of environmental factors on the accuracy of switch cabinet monitoring data, so as to correct and compensate for existing errors in subsequent data processing and equipment status evaluation, improve the reliability and accuracy of monitoring results, and optimize equipment management and maintenance.

[0034] The first monitoring signal analysis module is used to obtain electrical parameters of the intelligent switch cabinet, and obtain a first monitoring signal of the intelligent switch cabinet based on the obtained electrical parameters of the intelligent switch cabinet.

[0035] The specific analysis process is: Calculate the voltage fluctuation signal of the intelligent switch cabinet: ; In the formula, It is the voltage fluctuation signal of the intelligent switch cabinet. is the maximum value of the voltage of the intelligent switch cabinet during the monitoring period. is the minimum value of the voltage of the intelligent switch cabinet during the monitoring period. is the rated voltage of the intelligent switch cabinet, and e is a natural constant; During the monitoring period, the current sensor is used to measure the maximum current of the intelligent switch cabinet. ; Calculate the power factor of the intelligent switch cabinet: ; In the formula, is the power factor of the intelligent switch cabinet, P is the active power of the intelligent switch cabinet, and S is the apparent power of the intelligent switch cabinet; The electrical parameters of the intelligent switch cabinet specifically include the voltage fluctuation signal of the intelligent switch cabinet, the maximum current of the intelligent switch cabinet and the power factor of the intelligent switch cabinet. Based on the electrical parameters of the intelligent switch cabinet, a comprehensive analysis is performed to obtain the first monitoring signal of the intelligent switch cabinet. The first monitoring signal of the intelligent switch cabinet is used as the analysis basis for obtaining the fusion monitoring factor of the intelligent switch cabinet.

[0036] The first monitoring signal of the intelligent switch cabinet, the specific analysis process is: ; In the formula, It is the first monitoring signal of the intelligent switch cabinet. is the rated current of the intelligent switch cabinet, For setting The compensation factor, For setting The compensation factor, For setting compensation factor.

[0037] Calculate the voltage fluctuation signal of the intelligent switch cabinet, which involves the maximum, minimum and rated voltage of the voltage during the monitoring period. This allows real-time understanding of the voltage stability. Excessive voltage fluctuations can affect the normal operation of electrical equipment in the switch cabinet, such as causing equipment malfunctions and reducing equipment life. Timely monitoring of voltage fluctuations helps to take measures in advance, such as adjusting the power supply system, checking the lines, etc., to ensure the quality of power supply and safe operation of equipment.

[0038] Power factor is an important indicator to measure the efficiency of power system. Low power factor will lead to problems such as increased power loss and reduced utilization of power supply equipment. By calculating the power factor, the power utilization efficiency of the switchgear can be evaluated, and then measures can be taken to optimize reactive power compensation, etc., to improve the economy and reliability of the power system.

[0039] The voltage fluctuation signal, maximum current, power factor and other electrical parameters are combined to obtain the first monitoring signal of the intelligent switch cabinet, which is used as the analysis basis for the integrated monitoring factor. This comprehensive analysis can more comprehensively reflect the operating status of the switch cabinet. The change of a single parameter is not enough to accurately judge the health status of the equipment, and the comprehensive consideration of multiple parameters can provide richer information and help to timely discover potential fault hazards. Abnormal voltage fluctuations are usually accompanied by changes in power factor. Through comprehensive analysis, the problem can be more accurately located, early warning can be given, and the occurrence or expansion of faults can be avoided.

[0040] Intelligent switchgear is an important part of the power system. Accurate monitoring and analysis of its electrical parameters can ensure the stable operation of the switchgear itself, and thus guarantee the power supply quality of the entire power system. Stable voltage, reasonable power factor, etc. can help reduce the impact on other power equipment and improve the overall stability and reliability of the power system.

[0041] The second monitoring signal analysis module is used to construct a vibration characteristic model of the intelligent switch cabinet and output a second monitoring signal of the intelligent switch cabinet.

[0042] The specific analysis process is: obtain the vibration characteristic data of the intelligent switch cabinet, which specifically includes the vibration acceleration amplitude of the intelligent switch cabinet , Intelligent switch cabinet vibration displacement amplitude , Average vibration frequency of intelligent switch cabinet ; Based on the acquired intelligent switch cabinet vibration characteristic data, the intelligent switch cabinet vibration characteristic model is constructed: ; In the formula, It is the second monitoring signal of the intelligent switch cabinet. For setting The compensation factor, For setting The compensation factor, For setting The compensation factor of , e is a natural constant.

[0043] By acquiring vibration characteristic data such as vibration acceleration amplitude, vibration displacement amplitude, and average vibration frequency of the intelligent switch cabinet, we can fully understand the vibration of the switch cabinet during operation. These parameters can reflect the operating status of the mechanical components inside the switch cabinet. Abnormal vibration acceleration amplitude indicates that some components are loose, worn, or unbalanced; changes in vibration displacement amplitude are related to the connection status or structural stability of the components; abnormal average vibration frequency indicates abnormal speed of rotating components or resonance risk.

[0044] The intelligent switch cabinet vibration characteristic model built based on these vibration characteristic data can integrate multiple vibration parameters to obtain a second monitoring signal that can better reflect the overall vibration status of the equipment. When this monitoring signal shows abnormal changes, it can warn of equipment failures in advance, avoid further deterioration of the failure, and reduce downtime and maintenance costs caused by sudden failures.

[0045] Switchgear plays an important role in power distribution and control in the power system, and its safe and stable operation is crucial. Through real-time monitoring and analysis of vibration characteristics, factors that affect the safe operation of equipment, such as fatigue of mechanical components and deformation of structures, can be discovered in time, and corresponding measures can be taken to solve them, avoiding power accidents caused by equipment failures and ensuring the safe operation of the power system.

[0046] The fusion monitoring factor acquisition module is used to analyze the usage status characteristics of the intelligent switch cabinet, obtain the third monitoring signal of the intelligent switch cabinet, and combine the first monitoring signal of the intelligent switch cabinet and the second monitoring signal of the intelligent switch cabinet to obtain the fusion monitoring factor of the intelligent switch cabinet.

[0047] The specific analysis process is: Get the insulation resistance of the intelligent switch cabinet ; Calculate the temperature rise signal of the contact of the intelligent switch cabinet: ; In the formula, It is the temperature rise signal of the contact of the intelligent switch cabinet. is the contact temperature of the intelligent switch cabinet, is the ambient temperature of the intelligent switch cabinet, and e is a natural constant; Obtaining the travel deviation signal of the operating mechanism of the circuit breaker of the intelligent switch cabinet; ; In the formula, It is the travel deviation signal of the operating mechanism of the circuit breaker of the intelligent switch cabinet. is the actual travel of the circuit breaker operating mechanism of the intelligent switch cabinet, It is the reference stroke of the operating mechanism of the circuit breaker of the intelligent switch cabinet; Get the service life of the smart switch cabinet Based on the insulation resistance of the intelligent switch cabinet, the temperature rise signal of the contact of the intelligent switch cabinet, the travel deviation signal of the circuit breaker operating mechanism of the intelligent switch cabinet and the service life of the intelligent switch cabinet, a comprehensive analysis is performed to obtain the third monitoring signal of the intelligent switch cabinet. The third monitoring signal of the intelligent switch cabinet is used as the analysis basis for obtaining the fusion monitoring factor of the intelligent switch cabinet. ; In the formula, It is the third monitoring signal of the intelligent switch cabinet. For setting The compensation factor, For setting The compensation factor, For setting The compensation factor, For setting compensation factor.

[0048] The first monitoring signal of the intelligent switch cabinet, the second monitoring signal of the intelligent switch cabinet and the third monitoring signal of the intelligent switch cabinet are accumulated and processed to obtain the fusion monitoring factor of the intelligent switch cabinet. The fusion monitoring factor of the intelligent switch cabinet is used as the analysis basis for outputting the multimodal fusion monitoring result of the intelligent switch cabinet.

[0049] By acquiring multiple parameters such as the insulation resistance, contact temperature rise signal, circuit breaker operating mechanism travel deviation signal, and years of use of the intelligent switch cabinet, a third monitoring signal was constructed, and combined with the previous first monitoring signal (involving electrical parameters such as voltage fluctuations and power factor) and the second monitoring signal (involving vibration characteristics), the intelligent switch cabinet fusion monitoring factor was obtained. This fusion of multi-dimensional information can comprehensively and systematically reflect the operating status of the switch cabinet, avoiding the limitations of single parameter monitoring. For example, relying solely on electrical parameters cannot timely detect potential problems of mechanical components, and only focusing on vibration characteristics ignores changes in insulation performance. Fusion monitoring can comprehensively evaluate the health of equipment from multiple angles.

[0050] Each parameter related to the intelligent switch cabinet reflects the performance and status of the switch cabinet from different aspects. The insulation resistance is directly related to the insulation performance of the equipment. The decline of insulation performance leads to serious faults such as leakage and short circuit. The contact temperature rise signal can reflect the contact condition and heating degree of the contact. Abnormal temperature rise is a sign of problems such as poor contact or overload of the contact. The stroke deviation signal of the circuit breaker operating mechanism reflects the accuracy and reliability of the circuit breaker operation. Excessive stroke deviation affects the normal opening and closing operation of the circuit breaker. The service life takes into account the aging factor of the equipment. Combining these parameters, the actual status of the switch cabinet under different working conditions can be evaluated more accurately, and potential fault hazards can be discovered in time.

[0051] The fusion monitoring factor accumulates multiple monitoring signals. When any one or more parameters change abnormally, the fusion monitoring factor will change accordingly, so that fault warnings can be issued in advance. The service life of the intelligent switch cabinet can be effectively extended by timely discovering and handling potential fault hazards and performing reasonable maintenance and care according to the actual status of the equipment.

[0052] It should be noted that all the above compensation factors are obtained through a mapping set of historical data and compensation factors established in a database, that is, the corresponding compensation factors are obtained according to the current data.

[0053] The fusion monitoring result output module is used to obtain the multimodal fusion monitoring result of the intelligent switch cabinet based on the trained linear regression model, combined with the intelligent switch cabinet fusion monitoring error term and the intelligent switch cabinet fusion monitoring factor.

[0054] The specific analysis process is: input the intelligent switch cabinet fusion monitoring error term and the intelligent switch cabinet fusion monitoring factor into the trained linear regression model; the trained linear regression model can be expressed as: ; In the formula, It is the multi-modal fusion monitoring result indicator of the intelligent switch cabinet. is the intercept, is the slope, Integrate monitoring factors into smart switch cabinets. Integrate monitoring error terms for smart switchgear; Output the multimodal fusion monitoring result indicators of the intelligent switch cabinet; obtain the multimodal fusion monitoring result indicator-intelligent switch cabinet multimodal fusion monitoring result mapping table pre-stored in the database, and find the matching multimodal fusion monitoring result of the intelligent switch cabinet according to the multimodal fusion monitoring result indicator of the intelligent switch cabinet by searching the mapping table.

[0055] By inputting the intelligent switchgear fusion monitoring error term and fusion monitoring factor into the trained linear regression model, the influence of various environmental data (temperature, humidity, pollutant concentration, etc.), electrical parameters (voltage fluctuation, power factor, etc.), vibration characteristics and other related parameters (insulation resistance, contact temperature rise, circuit breaker travel deviation, years of use, etc.) on the switchgear status can be comprehensively considered. This comprehensive consideration avoids the limitations of isolated analysis of a single factor, making the evaluation of the switchgear status more comprehensive and accurate. For example, some abnormal phenomena cannot be fully explained based on electrical parameters alone, but combined with environmental factors and mechanical vibration information, the true operating status of the equipment can be more clearly understood.

[0056] The multimodal fusion monitoring result indicators of the intelligent switch cabinet and the related models and mapping tables provide a data-driven decision-making basis for operation and maintenance management. Based on the linear regression model and multimodal fusion monitoring result indicators, faults can be located more quickly.

[0057] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. A multi-modal fusion monitoring system for an intelligent switch cabinet, characterized in that: It includes an environment data analysis module, a monitoring error term matching module, a first monitoring signal analysis module, a second monitoring signal analysis module, a fusion monitoring factor acquisition module and a fusion monitoring result output module, wherein: The usage environment data analysis module is used to analyze the usage environment of the intelligent switch cabinet to obtain the usage environment data of the intelligent switch cabinet; The monitoring error term matching module is used to construct an intelligent switch cabinet use environment monitoring model based on the intelligent switch cabinet use environment data, output the intelligent switch cabinet use environment monitoring factor, and match the intelligent switch cabinet fusion monitoring error term; The first monitoring signal analysis module is used to obtain electrical parameters of the intelligent switch cabinet, and obtain a first monitoring signal of the intelligent switch cabinet based on the obtained electrical parameters of the intelligent switch cabinet; The second monitoring signal analysis module is used to construct a vibration characteristic model of the intelligent switch cabinet and output a second monitoring signal of the intelligent switch cabinet; The fusion monitoring factor acquisition module is used to analyze the usage status characteristics of the intelligent switch cabinet to obtain the third monitoring signal of the intelligent switch cabinet, and combine the first monitoring signal of the intelligent switch cabinet and the second monitoring signal of the intelligent switch cabinet to obtain the fusion monitoring factor of the intelligent switch cabinet; The fusion monitoring result output module is used to obtain the multimodal fusion monitoring result of the intelligent switch cabinet based on the trained linear regression model, combined with the intelligent switch cabinet fusion monitoring error term and the intelligent switch cabinet fusion monitoring factor.

2. The multi-modal fusion monitoring system for an intelligent switch cabinet according to claim 1, characterized in that: The intelligent switch cabinet use environment is analyzed to obtain the intelligent switch cabinet use environment data. The specific analysis process includes: Get the ambient temperature of the intelligent switch cabinet ; Get the relative humidity of the environment where the smart switch cabinet is used ; Calculate the dew point temperature of the operating environment of the intelligent switch cabinet : ； Monitor sulfur dioxide concentration in the environment around the intelligent switch cabinet , Nitrogen oxide concentration in the environment around the intelligent switch cabinet ; Detect dust particle concentration in the environment where the smart switch cabinet is used ; The operating environment temperature of the intelligent switch cabinet, the relative humidity of the operating environment of the intelligent switch cabinet, the dew point temperature of the operating environment of the intelligent switch cabinet, the sulfur dioxide concentration in the environment around the intelligent switch cabinet, the nitrogen oxide concentration in the environment around the intelligent switch cabinet and the dust particle concentration in the environment around the intelligent switch cabinet are recorded as the operating environment data of the intelligent switch cabinet.

3. The multi-modal fusion monitoring system for an intelligent switch cabinet according to claim 2, characterized in that: Based on the use environment data of the intelligent switch cabinet, the use environment monitoring model of the intelligent switch cabinet is constructed, and the use environment monitoring factor of the intelligent switch cabinet is output. The specific analysis process is as follows: Based on the usage environment data of the smart switch cabinet, a monitoring model for the usage environment of the smart switch cabinet is constructed: ； In the formula, The environmental monitoring factor used for the intelligent switch cabinet, e is a natural constant.

4. The multi-modal fusion monitoring system for an intelligent switch cabinet according to claim 3 is characterized in that: The matching intelligent switch cabinet integrates the monitoring error term, and the specific analysis process is as follows: Obtain a mapping table of intelligent switch cabinet usage environment monitoring factors and intelligent switch cabinet fusion monitoring error items pre-stored in the database, and find matching intelligent switch cabinet fusion monitoring error items according to the intelligent switch cabinet usage environment monitoring factors by searching the mapping table.

5. The multi-modal fusion monitoring system for an intelligent switch cabinet according to claim 1, characterized in that: The electrical parameters of the intelligent switch cabinet are obtained, and the first monitoring signal of the intelligent switch cabinet is obtained based on the obtained electrical parameters of the intelligent switch cabinet. The specific analysis process is as follows: Calculate the voltage fluctuation signal of the intelligent switch cabinet: ； In the formula, It is the voltage fluctuation signal of the intelligent switch cabinet. is the maximum value of the voltage of the intelligent switch cabinet during the monitoring period. is the minimum value of the voltage of the intelligent switch cabinet during the monitoring period. is the rated voltage of the intelligent switch cabinet, and e is a natural constant; During the monitoring period, the current sensor is used to measure the maximum current of the intelligent switch cabinet. ; Calculate the power factor of the intelligent switch cabinet: ； In the formula, is the power factor of the intelligent switch cabinet, P is the active power of the intelligent switch cabinet, and S is the apparent power of the intelligent switch cabinet; The voltage fluctuation signal of the intelligent switch cabinet, the maximum current of the intelligent switch cabinet and the power factor of the intelligent switch cabinet are comprehensively analyzed based on the electrical parameters of the intelligent switch cabinet to obtain the first monitoring signal of the intelligent switch cabinet. The first monitoring signal of the intelligent switch cabinet is used as the analysis basis for obtaining the fusion monitoring factor of the intelligent switch cabinet and is recorded as the electrical parameter of the intelligent switch cabinet.

6. The multi-modal fusion monitoring system for an intelligent switch cabinet according to claim 5, characterized in that: The specific analysis process of the first monitoring signal of the intelligent switch cabinet is as follows: ； In the formula, It is the first monitoring signal of the intelligent switch cabinet. is the rated current of the intelligent switch cabinet, For setting The compensation factor, For setting The compensation factor, For setting compensation factor.

7. The multi-modal fusion monitoring system for an intelligent switch cabinet according to claim 1, characterized in that: The intelligent switch cabinet vibration characteristic model is constructed to output the second monitoring signal of the intelligent switch cabinet. The specific analysis process is as follows: Obtain the vibration characteristic data of the intelligent switch cabinet, which specifically includes the vibration acceleration amplitude of the intelligent switch cabinet , Intelligent switch cabinet vibration displacement amplitude , Average vibration frequency of intelligent switch cabinet ; Based on the acquired intelligent switch cabinet vibration characteristic data, the intelligent switch cabinet vibration characteristic model is constructed: ； In the formula, It is the second monitoring signal of the intelligent switch cabinet. For setting The compensation factor, For setting The compensation factor, For setting The compensation factor of , e is a natural constant.

8. The multi-modal fusion monitoring system for an intelligent switch cabinet according to claim 1, characterized in that: The intelligent switch cabinet usage status characteristics are analyzed to obtain the third monitoring signal of the intelligent switch cabinet. The specific analysis process is as follows: Get the insulation resistance of the intelligent switch cabinet ; Calculate the temperature rise signal of the contact of the intelligent switch cabinet: ； In the formula, It is the temperature rise signal of the contact of the intelligent switch cabinet. is the contact temperature of the intelligent switch cabinet, is the ambient temperature of the intelligent switch cabinet, and e is a natural constant; Obtaining the travel deviation signal of the operating mechanism of the circuit breaker of the intelligent switch cabinet; ； In the formula, It is the travel deviation signal of the operating mechanism of the circuit breaker of the intelligent switch cabinet. is the actual travel of the circuit breaker operating mechanism of the intelligent switch cabinet, It is the reference stroke of the operating mechanism of the circuit breaker of the intelligent switch cabinet; Get the service life of the smart switch cabinet ; Based on the insulation resistance of the intelligent switch cabinet, the temperature rise signal of the contact of the intelligent switch cabinet, the travel deviation signal of the circuit breaker operating mechanism of the intelligent switch cabinet and the service life of the intelligent switch cabinet, a comprehensive analysis is performed to obtain the third monitoring signal of the intelligent switch cabinet. The third monitoring signal of the intelligent switch cabinet is used as the analysis basis for obtaining the fusion monitoring factor of the intelligent switch cabinet. ； In the formula, It is the third monitoring signal of the intelligent switch cabinet. For setting The compensation factor, For setting The compensation factor, For setting The compensation factor, For setting compensation factor.

9. The multi-modal fusion monitoring system for an intelligent switch cabinet according to claim 8, characterized in that: The first monitoring signal of the intelligent switch cabinet and the second monitoring signal of the intelligent switch cabinet are combined to obtain the intelligent switch cabinet fusion monitoring factor. The specific analysis process is: The first monitoring signal of the intelligent switch cabinet, the second monitoring signal of the intelligent switch cabinet and the third monitoring signal of the intelligent switch cabinet are accumulated and processed to obtain the fusion monitoring factor of the intelligent switch cabinet. The fusion monitoring factor of the intelligent switch cabinet is used as the analysis basis for outputting the multimodal fusion monitoring result of the intelligent switch cabinet.

10. The multi-modal fusion monitoring system for an intelligent switch cabinet according to claim 1, characterized in that: Based on the trained linear regression model, combined with the intelligent switch cabinet fusion monitoring error term and the intelligent switch cabinet fusion monitoring factor, the multi-modal fusion monitoring result of the intelligent switch cabinet is obtained. The specific analysis process is as follows: Input the intelligent switch cabinet fusion monitoring error term and the intelligent switch cabinet fusion monitoring factor into the trained linear regression model; The trained linear regression model is expressed as: ； In the formula, It is the multi-modal fusion monitoring result indicator of the intelligent switch cabinet. is the intercept, is the slope, Integrate monitoring factors into smart switch cabinets. Integrate monitoring error terms for smart switchgear; Output the multi-modal fusion monitoring result indicators of intelligent switch cabinet; Obtain the intelligent switch cabinet multimodal fusion monitoring result indicator-intelligent switch cabinet multimodal fusion monitoring result mapping table pre-stored in the database, and find the matching intelligent switch cabinet multimodal fusion monitoring result according to the intelligent switch cabinet multimodal fusion monitoring result indicator by searching the mapping table.

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