Intelligent switch cabinet operation control system based on multi-feature information monitoring

Abstract

The invention belongs to the technical field of switch cabinet control, and particularly relates to an intelligent switch cabinet operation control system based on multi-feature information monitoring, which comprises a state multi-dimensional monitoring unit, a state diagnosis output unit, a dust cleaning judgment unit, a blockage detection analysis unit and a background terminal, according to the method, the switch cabinet is comprehensively monitored and analyzed to identify the state abnormity of the switch cabinet, the switch cabinet is checked and regulated after the state abnormity of the switch cabinet is identified, and dust cleaning early warning analysis is performed on the switch cabinet when the state abnormity of the switch cabinet is not identified, so that potential safety hazards caused by dust accumulation in the switch cabinet are avoided; and when the cleaning unnecessary signal is generated, the blockage condition of the heat dissipation opening in the switch cabinet is analyzed, and when the blockage alarm signal is generated, the corresponding heat dissipation opening is checked and dredged, so that the operation potential safety hazard of the switch cabinet is reduced, and the operation supervision difficulty of the switch cabinet is remarkably reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of switch cabinet control, and in particular to an intelligent switch cabinet operation control system based on multi-feature information monitoring. Background Art

[0002] As an indispensable part of the power system, the operating status of the switch cabinet directly affects the safety and stability of the entire power grid. A power switch cabinet status monitoring system is disclosed in the Chinese invention patent with publication number CN118091486A. The system automatically adjusts the impedance based on the leakage current of the switch cabinet, so that the voltage and current input to the signal receiving alarm module are appropriate and will not damage the components. After the signal receiving alarm module alarms, the leakage signal processing module is controlled to stop leakage detection to avoid excessive current after the impedance is reduced and damage to subsequent components.

[0003] However, in actual application of the technical solution of the above invention, it is difficult to comprehensively monitor the operation of the switch cabinet and identify abnormal status. When the abnormal status is not identified, it is impossible to reasonably analyze the necessity of internal cleaning of the switch cabinet and the blockage condition of the heat dissipation port and issue a timely warning, which is not conducive to reducing the safety hazards of the operation of the switch cabinet. The operation supervision of the switch cabinet is difficult, and a solution is proposed for this purpose. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent switch cabinet operation control system based on multi-feature information monitoring to solve the technical defects proposed by the background technology.

[0005] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: an intelligent switch cabinet operation control system based on multi-feature information monitoring, comprising a state multi-dimensional monitoring unit, a state diagnosis output unit, a dust cleaning judgment unit, a blockage detection and analysis unit and a background terminal;

[0006] The multi-dimensional monitoring unit comprehensively monitors the operating status of the switch cabinet and sends the collected monitoring data to the status diagnosis output unit; the status diagnosis output unit uses big data analysis and pattern recognition technology to analyze the received monitoring data, identify abnormal status of the switch cabinet, and send the diagnosis and recognition results to the background terminal;

[0007] After identifying that the state of the switch cabinet is abnormal, the background terminal issues an early warning; if the state of the switch cabinet is not abnormal, the dust cleaning judgment module performs dust cleaning early warning analysis on the switch cabinet, and generates a cleaning alarm signal or a cleaning non-essential signal through analysis, and sends the cleaning alarm signal or the cleaning non-essential signal to the background terminal. The background terminal issues an early warning when receiving the cleaning alarm signal; when generating the cleaning non-essential signal, the blockage condition of the heat dissipation port on the switch cabinet is analyzed through the blockage detection and analysis module, and generates a blockage alarm signal or a blockage normal signal through analysis, and sends the blockage alarm signal or the blockage normal signal to the background terminal. The background terminal issues an early warning when receiving the blockage alarm signal.

[0008] Furthermore, the state multi-dimensional monitoring unit includes a temperature monitoring module, a vibration monitoring module, a partial discharge monitoring module and an environment monitoring module, wherein the temperature monitoring module arranges 12 SAW temperature sensors at key points including the circuit breaker contacts and the busbar connection, adopts a non-uniform grid layout, and reconstructs the three-dimensional temperature field through the Delaunay triangulation algorithm;

[0009] The vibration monitoring module uses a three-axis MEMS accelerometer and the EMD-HHT algorithm to extract time-frequency features and synchronously collect the closing and opening coil currents to achieve vibration-current phase coupling analysis. The partial discharge monitoring module performs joint detection based on UHF sensors and high-frequency current transformers, and identifies the discharge type through PRPD maps and CNN classifiers. The environmental monitoring module integrates humidity sensors, SF6 concentration sensors and dust sensors to monitor the internal environment of the switch cabinet.

[0010] Furthermore, the specific analysis process of dust cleaning early warning analysis is as follows:

[0011] The time when the dust inside the switch cabinet was cleaned is collected and marked as the cleaning time, the interval between the current time and the cleaning time is marked as the first time, and the first time is compared with the preset first time threshold. If the first time exceeds the preset first time threshold, a cleaning alarm signal is generated;

[0012] If the first duration does not exceed the preset first duration threshold, the cleaning alarm coefficient is obtained through analysis, and the cleaning alarm coefficient is numerically compared with the preset cleaning alarm coefficient threshold. If the cleaning alarm coefficient exceeds the preset cleaning alarm coefficient threshold, a cleaning alarm signal is generated; if the cleaning alarm coefficient does not exceed the preset cleaning alarm coefficient threshold, a cleaning unnecessary signal is generated.

[0013] Furthermore, the analysis and acquisition method of the cleaning alarm coefficient is as follows:

[0014] The dust concentration of several detection points inside the switch cabinet is collected, and the point gray value is obtained by averaging all the dust concentrations of the corresponding detection points within the first time period, and the gray detection value is obtained by averaging the point gray values ​​of all the detection points, and the gray value with the largest value is marked as the gray amplitude value; the cleaning alarm coefficient is obtained by numerically calculating the first time period, the gray detection value and the gray amplitude value.

[0015] Furthermore, the specific operation process of the blockage detection and analysis unit includes:

[0016] All heat dissipation ports on the switch cabinet are obtained, and the corresponding heat dissipation port is marked as i, where i is a natural number greater than 1; the wind speed outside the heat dissipation port i is collected and marked as the air outlet speed, and the speed of the cooling fan in the switch cabinet is collected and marked as the wind speed, and the ratio of the air outlet speed to the wind speed is marked as the speed ratio coefficient, and the speed ratio coefficient is numerically compared with the corresponding preset speed ratio coefficient threshold. If the speed ratio coefficient does not exceed the corresponding preset speed ratio coefficient threshold, it is determined that the heat dissipation port i is in a state of poor air outlet;

[0017] The total time length during which the heat dissipation port i is in a poor air outlet state within a unit time is obtained and marked as a non-smooth air outlet value, and when it is determined that the heat dissipation port i is in a poor air outlet state, the difference between the speed ratio coefficient and the corresponding preset speed ratio coefficient threshold is marked as a quick analysis value, all quick analysis values ​​corresponding to the heat dissipation port i within a unit time are averaged to obtain the outlet wind speed measurement value, and the quick analysis value with the largest value corresponding to the heat dissipation port i within a unit time is marked as the outlet wind speed amplitude;

[0018] The heat dissipation outlet blockage value is obtained by numerically calculating the air outlet non-smoothness value, the outlet wind speed measurement value and the outlet wind speed amplitude. The heat dissipation outlet blockage value is numerically compared with the preset heat dissipation outlet blockage threshold. If the heat dissipation outlet blockage value exceeds the preset heat dissipation outlet blockage threshold, the heat dissipation outlet i is marked as a blocked outlet; if there is a blocked outlet on the switch cabinet, a blockage alarm signal is generated; if there is no blocked outlet on the switch cabinet, a blockage normal signal is generated.

[0019] Furthermore, the status diagnosis output unit is communicatively connected to the switch cabinet control and analysis unit, and the status diagnosis output unit sends the diagnosis and identification result of the switch cabinet to the switch cabinet control and analysis unit. The switch cabinet control and analysis unit stores all the diagnosis and identification results, and determines through analysis whether to generate an inaccurate identification signal or a high-risk control signal. When the inaccurate identification signal or the high-risk control signal is generated, it is sent to the background terminal, and the background terminal issues a warning when receiving the inaccurate identification signal or the high-risk control signal.

[0020] Furthermore, the specific analysis process of the switch cabinet control and analysis unit is as follows:

[0021] When the switch cabinet is identified as abnormal, after confirmation by the operation and maintenance personnel, if it is determined that there is no corresponding abnormal state, the switch cabinet is assigned an inaccurate identification symbol LP-1; a detection period is set, and all state abnormalities identified during the detection period are classified. The number of times the inaccurate identification symbol LP-1 corresponding to the corresponding state abnormality is assigned is calculated by ratio with the total number of identifications of the corresponding type of state abnormality to obtain a class identification evaluation value, and the class identification evaluation value is numerically compared with the corresponding preset class identification evaluation threshold. If the class identification evaluation value exceeds the preset class identification evaluation threshold, the corresponding type of abnormality is marked as an inaccurate identification object;

[0022] If there is an inaccurate object to be identified during the detection period, an inaccurate identification signal is generated; if there is no inaccurate object to be identified during the detection period, the ratio of the class recognition evaluation value of the corresponding type of state abnormality to the corresponding preset class recognition evaluation value is marked as the class recognition occupation value, the class recognition occupation values ​​of all types of state abnormalities are averaged to obtain the precise obstruction value, the precise obstruction value is numerically compared with the preset precise obstruction threshold, and if the precise obstruction value exceeds the preset precise obstruction threshold, an inaccurate identification signal is generated.

[0023] Furthermore, if the precise obstruction value does not exceed the preset precise obstruction threshold, a number of detection periods are set within the detection period, the total number of recognitions of abnormal state in the corresponding detection period is marked as an abnormal state recognition value, the abnormal state recognition value is numerically compared with the preset abnormal state recognition threshold, and if the abnormal state recognition value exceeds the preset abnormal state recognition threshold, the corresponding detection period is marked as a dangerous period;

[0024] The number of dangerous time periods within the detection period is obtained and marked as dangerous condition values, and the abnormal condition recognition values ​​of all detection periods within the detection period are summed up to obtain the abnormal condition recognition value, and the dangerous condition value and the abnormal condition recognition value are numerically compared with the preset dangerous condition threshold and the preset abnormal condition recognition threshold respectively. If the dangerous condition value or the abnormal condition recognition value exceeds the corresponding preset threshold, a high-risk control signal is generated.

[0025] Furthermore, if both the dangerous condition value and the abnormal condition value do not exceed the corresponding preset threshold value, the recognition time of the corresponding abnormal state is marked as the decision time, the time when the operation and maintenance personnel take action is marked as the target time, and the interval between the target time and the decision time is marked as the second time.

[0026] The second time duration is numerically compared with the preset second time duration threshold. If the second time duration exceeds the preset second time duration threshold, the corresponding second time duration is marked as the selected time duration; the number of selected time durations in the detection period is obtained and the ratio thereof is calculated with the total number of second time durations to obtain the abnormal selection detection value, and the average of all second time durations in the detection period is calculated to obtain the operation and maintenance detection value, and the switch cabinet pipe meter value is obtained by numerically calculating the dangerous condition value, the abnormal condition recognition value, the abnormal selection detection value and the operation and maintenance detection value, and the switch cabinet pipe meter value is numerically compared with the preset switch cabinet pipe meter threshold. If the switch cabinet pipe meter value exceeds the preset switch cabinet pipe meter threshold, a high-risk signal for management and control is generated.

[0027] The present invention also proposes an intelligent switch cabinet operation control method based on multi-feature information monitoring, comprising the following steps:

[0028] Step 1: Comprehensively monitor the operating status of the switch cabinet;

[0029] Step 2: Collect various monitoring data of the switch cabinet;

[0030] Step 3: Analyze various monitoring data to identify abnormal status of the switch cabinet;

[0031] Step 4: When the abnormal state of the switch cabinet is not identified, a dust cleaning early warning analysis is performed on the switch cabinet;

[0032] Step 5: When generating a signal to clear unnecessary signals, analyze the blockage condition of the heat dissipation vents on the switch cabinet.

[0033] Compared with the prior art, the present invention has the following beneficial effects:

[0034] 1. In the present invention, the switch cabinet is comprehensively monitored and analyzed to identify the abnormal state of the switch cabinet, and the switch cabinet is inspected and regulated after the abnormal state of the switch cabinet is identified. When the abnormal state of the switch cabinet is not identified, the switch cabinet is subjected to dust cleaning early warning analysis to avoid dust accumulation inside the switch cabinet and bring safety hazards. When the unnecessary cleaning signal is generated, the blockage condition of the heat dissipation port on the switch cabinet is analyzed, and when the blockage alarm signal is generated, the corresponding heat dissipation port is inspected and unblocked, thereby reducing the safety hazards of the operation of the switch cabinet and significantly reducing the difficulty of operation supervision of the switch cabinet;

[0035] 2. In the present invention, all diagnostic identification results are stored by the switch cabinet management and analysis unit, and it is determined by analysis whether an inaccurate identification signal or a high-risk control signal is generated. When an inaccurate identification signal or a high-risk control signal is generated, the background management personnel are reminded to optimize the identification of abnormal switch cabinet status, and subsequently strengthen the operation supervision of the switch cabinet to further ensure the safe and stable operation of the switch cabinet. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings;

[0037] Figure 1 This is a system block diagram of Embodiment 1 of the present invention;

[0038] Figure 2 This is a system block diagram of Embodiment 2 of the present invention;

[0039] Figure 3 This is a flow chart of the method of Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0040] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] Embodiment 1: Figure 1 As shown, the intelligent switch cabinet operation control system based on multi-feature information monitoring proposed in the present invention includes a state multi-dimensional monitoring unit, a state diagnosis output unit, a dust cleaning judgment unit, a blockage detection and analysis unit and a background terminal;

[0042] The multi-dimensional monitoring unit comprehensively monitors the operating status of the switch cabinet (including key indicators such as temperature, humidity, electrical parameters, mechanical vibration, etc. of the switch cabinet), and sends the collected monitoring data to the status diagnosis output unit;

[0043] Specifically, the multi-dimensional state monitoring unit includes a temperature monitoring module, a vibration monitoring module, a partial discharge monitoring module and an environmental monitoring module. The temperature monitoring module arranges 12 SAW temperature sensors at key points including the circuit breaker contacts and busbar connections, adopts a non-uniform grid layout (spacing ≤ 50 mm), and reconstructs the three-dimensional temperature field through the Delaunay triangulation algorithm;

[0044] The vibration monitoring module uses a three-axis MEMS accelerometer (bandwidth 10kHz) and an improved EMD-HHT algorithm to extract time-frequency features and synchronously collect the closing and opening coil currents to achieve vibration-current phase coupling analysis. The partial discharge monitoring module performs joint detection based on a UHF sensor (300MHz-1.5GHz) and a high-frequency current transformer (HFCT), and identifies the discharge type through a PRPD spectrum and a CNN classifier. The environmental monitoring module integrates a humidity sensor (±2%RH), an SF6 concentration sensor (10ppm resolution) and a dust sensor (PM2.5 / PM10) to monitor the internal environment of the switch cabinet.

[0045] The status diagnosis output unit uses big data analysis and pattern recognition technology to analyze the received monitoring data, identify abnormal status of the switch cabinet, and send the diagnosis identification results to the background terminal; after identifying the abnormal status of the switch cabinet, the background terminal issues an early warning so that the switch cabinet can be inspected and adjusted in time to ensure the safe and stable operation of the switch cabinet, significantly reducing the difficulty of operation supervision of the switch cabinet.

[0046] If the switch cabinet is not identified as abnormal, the dust cleaning judgment module performs dust cleaning warning analysis on the switch cabinet, generates a cleaning alarm signal or a cleaning unnecessary signal through analysis, and sends the cleaning alarm signal or the cleaning unnecessary signal to the background terminal. When the background terminal receives the cleaning alarm signal, it issues a warning to remind the background management personnel to clean the inside of the switch cabinet in time to avoid the accumulation of dust inside the switch cabinet and bring safety hazards. The specific analysis process of dust cleaning warning analysis is as follows:

[0047] The time when the dust inside the switch cabinet was cleaned is collected and marked as the cleaning time, the interval between the current time and the cleaning time is marked as the first time, and the first time is compared with the preset first time threshold. If the first time exceeds the preset first time threshold, it indicates that the dust inside the switch cabinet needs to be cleaned to avoid internal dust accumulation threatening the safe and stable operation of the switch cabinet, and a cleaning alarm signal is generated;

[0048] If the first time duration does not exceed the preset first time duration threshold, the dust concentrations of several detection points inside the switch cabinet are collected, and the average of all dust concentrations of the corresponding detection points within the first time duration is calculated to obtain the point gray value, and the average of the point gray values ​​of all detection points is calculated to obtain the gray inspection value, and the point gray value with the largest value is marked as the gray amplitude value;

[0049] The first time length YS, the gray detection value GW and the gray amplitude value WX are numerically calculated by the formula ZP=t1×YS+(t2×GW+t3×WX) / 2 to obtain the cleaning alarm coefficient ZP; wherein t1, t2, and t3 are preset proportional coefficients with values ​​greater than zero, and the larger the value of the cleaning alarm coefficient ZP, the more serious the dust accumulation condition in the switch cabinet is in general, and the greater the safety risk it brings;

[0050] The cleaning alarm coefficient ZP is numerically compared with the preset cleaning alarm coefficient threshold. If the cleaning alarm coefficient ZP exceeds the preset cleaning alarm coefficient threshold, it indicates that the dust accumulation condition in the switch cabinet is generally serious and the safety risk is relatively large. The switch cabinet needs to be cleaned in time, and a cleaning alarm signal is generated; if the cleaning alarm coefficient ZP does not exceed the preset cleaning alarm coefficient threshold, it indicates that the dust accumulation condition in the switch cabinet is generally serious and the safety risk is relatively small, and a cleaning unnecessary signal is generated.

[0051] When generating a signal for clearing unnecessary signals, the blockage status of the heat dissipation ports on the switch cabinet is analyzed through the blockage detection and analysis module, and a blockage alarm signal or a blockage-free signal is generated through analysis, and the blockage alarm signal or the blockage-free signal is sent to the background terminal. When the background terminal receives the blockage alarm signal, it issues an early warning to remind the background management personnel to check and clear the corresponding heat dissipation ports in time to ensure the heat dissipation performance of the switch cabinet and reduce the safety hazards of the switch cabinet operation; the specific operation process of the blockage detection and analysis unit is as follows:

[0052] All heat dissipation ports on the switch cabinet are obtained, and the corresponding heat dissipation port is marked as i, where i is a natural number greater than 1; the wind speed outside the heat dissipation port i is collected and marked as the air outlet speed, and the speed of the cooling fan in the switch cabinet is collected and marked as the wind speed, and the ratio of the air outlet speed to the wind speed is marked as the speed ratio coefficient, and the speed ratio coefficient is numerically compared with the corresponding preset speed ratio coefficient threshold. If the speed ratio coefficient does not exceed the corresponding preset speed ratio coefficient threshold, it is determined that the heat dissipation port i is in a state of poor air outlet;

[0053] The total time length during which the heat dissipation port i is in a poor air outlet state within a unit time is obtained and marked as a non-smooth air outlet value, and when it is determined that the heat dissipation port i is in a poor air outlet state, the difference between the speed ratio coefficient and the corresponding preset speed ratio coefficient threshold is marked as a quick analysis value, all quick analysis values ​​corresponding to the heat dissipation port i within a unit time are averaged to obtain the outlet wind speed measurement value, and the quick analysis value with the largest value corresponding to the heat dissipation port i within a unit time is marked as the outlet wind speed amplitude;

[0054] The heat dissipation outlet blocking value TXi is obtained by numerically calculating the air outlet non-smoothness value QFi, the outlet wind speed measurement value YLi and the outlet wind speed amplitude value HPi through the formula TXi=uy×QFi+(re×YLi+sq×HPi) / 2; wherein uy, re, sq are preset proportional coefficients with values ​​greater than zero, and the larger the value of the heat dissipation outlet blocking value TXi, the greater the possibility that the heat dissipation outlet i is blocked;

[0055] The heat dissipation port blockage value TXi is numerically compared with the preset heat dissipation port blockage threshold. If the heat dissipation port blockage value TXi exceeds the preset heat dissipation port blockage threshold, it indicates that there is a high possibility of blockage in heat dissipation port i, and heat dissipation port i is marked as a blocked port; if there is a blocked port on the switch cabinet, it indicates that the heat dissipation risk of the switch cabinet is high, and a blockage alarm signal is generated; if there is no blocked port on the switch cabinet, it indicates that the heat dissipation risk of the switch cabinet is low, and a blockage normal signal is generated.

[0056] Embodiment 2: Figure 2As shown, the difference between this embodiment and the first embodiment is that the state diagnosis output unit is communicatively connected to the switch cabinet management and analysis unit, and the state diagnosis output unit sends the diagnosis and identification result of the switch cabinet to the switch cabinet management and analysis unit, and the switch cabinet management and analysis unit stores all the diagnosis and identification results, and determines through analysis whether to generate an inaccurate identification signal or a high-risk control signal, and sends the inaccurate identification signal or the high-risk control signal to the background terminal when it is generated;

[0057] When the back-end terminal receives an inaccurate identification signal or a high-risk control signal, it issues an early warning to remind back-end management personnel to identify and optimize the abnormal status of the switch cabinet, and subsequently strengthen the operation supervision of the switch cabinet to further ensure the safe and stable operation of the switch cabinet with a high level of intelligence. The specific analysis process of the switch cabinet control and analysis unit is as follows:

[0058] When the switch cabinet is identified as abnormal, after confirmation by the operation and maintenance personnel, if it is determined that there is no corresponding abnormal state, the switch cabinet is assigned an inaccurate identification symbol LP-1; a detection period is set, preferably, the detection period is twenty days; all state abnormalities identified during the detection period are classified, and the number of times the inaccurate identification symbol LP-1 corresponding to the corresponding state abnormality is assigned is calculated by ratio to the total number of identifications of the corresponding type of state abnormality to obtain a classification evaluation value;

[0059] The class recognition evaluation value is numerically compared with the corresponding preset class recognition evaluation threshold. If the class recognition evaluation value exceeds the preset class recognition evaluation threshold, it indicates that the recognition error rate of the corresponding type of state abnormality is high and it is difficult to accurately recognize the corresponding type of state abnormality, and the corresponding type of abnormality is marked as an inaccurate object for recognition; if an inaccurate object for recognition exists during the detection period, it indicates that the recognition optimization of the corresponding type of state abnormality needs to be carried out in a timely manner, and an inaccurate signal for recognition is generated;

[0060] If there is no inaccurate identification object during the detection period, the ratio of the class identification evaluation value of the corresponding type of state abnormality to the corresponding preset class identification evaluation value will be marked as the class identification measurement value, and the class identification measurement values ​​of all types of state abnormalities will be averaged to obtain the precise obstruction value, and the precise obstruction value will be numerically compared with the preset precise obstruction threshold. If the precise obstruction value exceeds the preset precise obstruction threshold, it indicates that the overall identification accuracy of the switch cabinet state abnormality is poor, and an inaccurate identification signal is generated.

[0061] Furthermore, if the precise blocking value does not exceed the preset precise blocking threshold, several detection periods are set within the detection period, the total number of recognitions of abnormal state in the corresponding detection period is marked as the abnormal state recognition value, the abnormal state recognition value is numerically compared with the preset abnormal state recognition threshold, and if the abnormal state recognition value exceeds the preset abnormal state recognition threshold, it indicates that the operation stability of the switch cabinet in the corresponding detection period is poor and its operation risk is high, and the corresponding detection period is marked as a dangerous period;

[0062] The number of dangerous time periods in the detection period is obtained and marked as dangerous condition values, and the abnormal condition recognition values ​​of all detection periods in the detection period are summed up to obtain the abnormal condition recognition value, and the dangerous condition value and the abnormal condition recognition value are numerically compared with the preset dangerous condition threshold and the preset abnormal condition recognition threshold respectively. If the dangerous condition value or the abnormal condition recognition value exceeds the corresponding preset threshold, it indicates that the operation control of the switchgear during the detection period is difficult, and a high-risk control signal is generated.

[0063] Furthermore, if the dangerous condition value and the abnormal condition value do not exceed the corresponding preset threshold, the recognition time of the corresponding abnormal state is marked as the decision time, the time when the operation and maintenance personnel take action is marked as the target time, and the interval between the target time and the decision time is marked as the second time.

[0064] The second duration is numerically compared with a preset second duration threshold. If the second duration exceeds the preset second duration threshold, the corresponding second duration is marked as a selected duration. The number of selected durations in the detection period is obtained and the ratio is calculated with the total number of second durations to obtain a different selection detection value, and the average of all second durations in the detection period is calculated to obtain an operation and maintenance detection value.

[0065] The dangerous condition value SY, abnormal condition value PX, abnormal selection detection value ZW and operation and maintenance detection value NS are numerically calculated by the formula GL=b1×SY+b2×PX+b3×ZW+b4×NS to obtain the switch cabinet tube table value GL, where b1, b2, b3 and b4 are preset proportional coefficients with values ​​greater than zero, and the larger the value of the switch cabinet tube table value GL is, the higher the overall control risk of the switch cabinet during the detection period is;

[0066] The switch cabinet tube meter value GL is numerically compared with the preset switch cabinet tube meter threshold. If the switch cabinet tube meter value GL exceeds the preset switch cabinet tube meter threshold, it indicates that the overall control risk of the switch cabinet during the detection period is high, and it is necessary to strengthen the supervision of the switch cabinet in the future, and a high-risk control signal is generated.

[0067] Embodiment 3: Figure 3 As shown, the difference between this embodiment and the first and second embodiments is that the intelligent switch cabinet operation control method based on multi-feature information monitoring proposed in the present invention includes the following steps:

[0068] Step 1: Comprehensively monitor the operating status of the switch cabinet;

[0069] Step 2: Collect various monitoring data of the switch cabinet;

[0070] Step 3: Analyze various monitoring data to identify abnormal status of the switch cabinet;

[0071] Step 4: When the abnormal state of the switch cabinet is not identified, a dust cleaning early warning analysis is performed on the switch cabinet;

[0072] Step 5: When generating a signal to clear unnecessary signals, analyze the blockage condition of the heat dissipation vents on the switch cabinet.

[0073] The working principle of the present invention is as follows: when in use, the operating status of the switch cabinet is comprehensively monitored through a multi-dimensional monitoring unit, and the monitoring data of the status diagnosis output unit are analyzed to identify the abnormal status of the switch cabinet. After the abnormal status of the switch cabinet is identified, the switch cabinet is inspected and regulated to ensure the safe and stable operation of the switch cabinet, and when the abnormal status of the switch cabinet is not identified, the dust cleaning judgment module is used to perform dust cleaning early warning analysis on the switch cabinet, and when a cleaning alarm signal is generated, the background management personnel are reminded to clean the inside of the switch cabinet in time to avoid dust accumulation inside the switch cabinet and cause safety hazards, and when a non-essential cleaning signal is generated, the blockage status of the heat dissipation port on the switch cabinet is analyzed through the blockage detection and analysis module, and when a blockage alarm signal is generated, the background management personnel are reminded to check and clear the corresponding heat dissipation port in time to ensure the heat dissipation performance of the switch cabinet, reduce the operating safety hazards of the switch cabinet, and significantly reduce the difficulty of operating supervision of the switch cabinet.

[0074] The above formulas are all dimensionless and numerical calculations. The formula is a formula obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formula are set by technicians in this field according to actual conditions. The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the contents of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that technicians in the relevant technical field can understand and use the present invention well. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. Intelligent switch cabinet operation control system based on multi-feature information monitoring, characterized in that: It includes a multi-dimensional status monitoring unit, a status diagnosis output unit, a dust cleaning judgment unit, a blockage detection and analysis unit and a background terminal; The multi-dimensional monitoring unit comprehensively monitors the operating status of the switch cabinet, and the status diagnosis output unit analyzes various monitoring data to identify abnormal status of the switch cabinet. After identifying the abnormal status of the switch cabinet, the background terminal issues an early warning; If the abnormal state of the switch cabinet is not identified, the dust cleaning judgment module will perform dust cleaning warning analysis on the switch cabinet, and a cleaning alarm signal or a cleaning non-essential signal will be generated through analysis, and the cleaning alarm signal or the cleaning non-essential signal will be sent to the background terminal; when the cleaning non-essential signal is generated, the blockage condition of the heat dissipation port on the switch cabinet will be analyzed through the blockage detection and analysis module, and a blockage alarm signal or a blockage normal signal will be generated through analysis, and the background terminal will issue a warning when receiving the blockage alarm signal.

2. The intelligent switch cabinet operation control system based on multi-feature information monitoring according to claim 1 is characterized in that: The multi-dimensional state monitoring unit includes a temperature monitoring module, a vibration monitoring module, a partial discharge monitoring module and an environment monitoring module.

3. The intelligent switch cabinet operation control system based on multi-feature information monitoring according to claim 1 is characterized in that: The specific analysis process of dust cleaning early warning analysis is as follows: The time when the dust inside the switch cabinet was cleaned is collected and marked as the cleaning time, and the interval between the current time and the cleaning time is marked as the first time. If the first time exceeds the preset first time threshold, a cleaning alarm signal is generated; If the first duration does not exceed the preset first duration threshold, the cleaning alarm coefficient is obtained through analysis. If the cleaning alarm coefficient exceeds the preset cleaning alarm coefficient threshold, a cleaning alarm signal is generated; if the cleaning alarm coefficient does not exceed the preset cleaning alarm coefficient threshold, a cleaning unnecessary signal is generated.

4. The intelligent switch cabinet operation control system based on multi-feature information monitoring according to claim 3 is characterized in that: The analysis and acquisition method of the cleaning alarm coefficient is as follows: The dust concentrations at several detection points inside the switch cabinet are collected, and the point gray values ​​are obtained by averaging all the dust concentrations at the corresponding detection points within the first time period, and the point gray values ​​of all the detection points are averaged to obtain the gray detection value, and the point gray value with the largest value is marked as the gray amplitude value; The cleaning alarm coefficient is obtained by numerically calculating the first time length, the gray detection value and the gray amplitude value.

5. The intelligent switch cabinet operation control system based on multi-feature information monitoring according to claim 1 is characterized in that: The specific operation process of the blockage detection and analysis unit includes: All heat dissipation vents on the switch cabinet are obtained, and the corresponding heat dissipation vents are marked as i, where i is a natural number greater than 1; the heat dissipation vent blockage value is obtained by numerically calculating the air outlet non-smoothness value, the outlet wind speed measurement value and the outlet wind speed amplitude; if the heat dissipation vent blockage value exceeds the preset heat dissipation vent blockage threshold, the heat dissipation vent i is marked as a blocked vent; if there is a blocked vent on the switch cabinet, a blockage alarm signal is generated; if there is no blocked vent on the switch cabinet, a blockage normal signal is generated.

6. The intelligent switch cabinet operation control system based on multi-feature information monitoring according to claim 1 is characterized in that: The status diagnosis output unit is communicatively connected to the switch cabinet control and analysis unit. The switch cabinet control and analysis unit determines through analysis whether to generate an inaccurate identification signal or a high-risk control signal, and sends the inaccurate identification signal or the high-risk control signal to the background terminal when it is generated.

7. The intelligent switch cabinet operation control system based on multi-feature information monitoring according to claim 6 is characterized in that: The specific analysis process of the switch cabinet control and analysis unit is as follows: if there is an inaccurate object identified during the detection period, an inaccurate identification signal is generated; if there is no inaccurate object identified during the detection period, the class recognition measurement values ​​of all types of state abnormalities are averaged to obtain the accurate obstruction value. If the accurate obstruction value exceeds the preset accurate obstruction threshold, an inaccurate identification signal is generated.

8. The intelligent switch cabinet operation control system based on multi-feature information monitoring according to claim 7 is characterized in that: If the precise blocking value does not exceed the preset precise blocking threshold, the dangerous condition value and the abnormal condition recognition value will be numerically compared with the preset dangerous condition threshold and the preset abnormal condition recognition threshold respectively. If the dangerous condition value or the abnormal condition recognition value exceeds the corresponding preset threshold, a high-risk control signal will be generated.

9. The intelligent switch cabinet operation control system based on multi-feature information monitoring according to claim 8 is characterized in that: If the dangerous condition value and the abnormal condition identification value do not exceed the corresponding preset threshold value, the switch cabinet pipe meter value is obtained by numerically calculating the dangerous condition value, abnormal condition identification value, abnormal selection detection value and operation and maintenance detection value. If the switch cabinet pipe meter value exceeds the preset switch cabinet pipe meter threshold, a high-risk control signal is generated.

10. An intelligent switch cabinet operation control method based on multi-feature information monitoring, using the intelligent switch cabinet operation control system based on multi-feature information monitoring according to any one of claims 1 to 9, characterized in that: The following steps are involved: Step 1: Comprehensively monitor the operating status of the switch cabinet; Step 2: Collect various monitoring data of the switch cabinet; Step 3: Analyze various monitoring data to identify abnormal status of the switch cabinet; Step 4: When the abnormal state of the switch cabinet is not identified, a dust cleaning early warning analysis is performed on the switch cabinet; Step 5: When generating a signal to clear unnecessary signals, analyze the blockage condition of the heat dissipation vents on the switch cabinet.

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