Intelligent Switchgear Operation Control System Based on Multi-Feature Information Monitoring

Abstract

The present invention belongs to the technical field of switchgear control, specifically an intelligent switchgear operation control system based on multi-feature information monitoring, including 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; the present invention comprehensively monitors and analyzes the switchgear to identify abnormal states of the switchgear, conducts inspection and regulation of the switchgear after identifying abnormal states of the switchgear, conducts dust cleaning early warning analysis on the switchgear when abnormal states of the switchgear are not identified, avoids potential safety hazards caused by dust accumulation inside the switchgear, analyzes the blockage condition of the heat dissipation openings on the switchgear when generating a non-essential cleaning signal, and inspects and dredges the corresponding heat dissipation openings when generating a blockage alarm signal, reducing the potential safety hazards of the operation of the switchgear and significantly reducing the operation supervision difficulty of the switchgear.

Description

Technical Field

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

[0002] As an indispensable part of the power system, the operation state of the switchgear directly affects the safety and stability of the entire power grid. In the Chinese invention patent with the publication number CN118091486A, a power switchgear state monitoring system is disclosed, which automatically adjusts the impedance according to the magnitude of the leakage current of the switchgear, so that the voltage and current input to the signal receiving and alarming module are appropriate, and the components will not be damaged. And after the signal receiving and alarming module alarms, it controls the leakage signal processing module to stop the leakage detection to avoid damage to the subsequent components due to excessive current after the impedance decreases;

[0003] However, in the actual application process of the above invention technical solution, it is difficult to comprehensively monitor the operation of the switchgear and identify abnormal states, and when the abnormal state is not identified, it is impossible to reasonably analyze the necessity of internal cleaning and the blockage condition of the heat dissipation ports of the switchgear and give early warnings in time, which is not conducive to reducing the operation safety hazards of the switchgear and the operation supervision of the switchgear is difficult. Therefore, a solution is proposed. Summary of the Invention

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

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

[0006] The state multi-dimensional monitoring unit comprehensively monitors the operation state of the switchgear and sends the collected monitoring data to the state diagnosis and output unit; the state diagnosis and output unit uses big data analysis and pattern recognition technologies to analyze the received monitoring data, identify the abnormal state of the switchgear, and send the diagnosis and recognition result to the background terminal;

[0007] After identifying the abnormal state of the switchgear, the background terminal issues a warning; if the abnormal state of the switchgear is not identified, the dust cleaning judgment unit conducts a dust cleaning warning analysis on the switchgear, 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; when generating the cleaning unnecessary signal, the blockage detection and analysis unit analyzes the blockage condition of the heat dissipation openings on the switchgear, generates a blockage alarm signal or a blockage-free signal through analysis, and sends the blockage alarm signal or the blockage-free signal to the background terminal. When the background terminal receives the blockage alarm signal, it issues a warning.

[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. Among them, the temperature monitoring module arranges 12 SAW temperature sensors at key points including the breaker contacts and the bus connection, adopts a non-uniform grid layout, and reconstructs the three-dimensional temperature field through the Delaunay triangulation algorithm.

[0009] The vibration monitoring module extracts time-frequency features through a three-axis MEMS accelerometer, synchronously collects the closing and opening coil currents to realize vibration-current phase coupling analysis; the partial discharge monitoring module conducts joint detection based on ultra-high frequency sensors and high-frequency current transformers, and identifies the discharge type through PRPD spectra and CNN classifiers; the environment monitoring module integrates humidity sensors, SF6 concentration sensors, and dust sensors to monitor the internal environment of the switchgear.

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

[0011] Collect the time of the previous dust cleaning inside the switchgear and mark it as the cleaning time, mark the interval duration between the current time and the cleaning time as the first duration, compare the first duration with the preset first duration threshold. If the first duration exceeds the preset first duration threshold, generate a cleaning alarm signal;

[0012] If the first duration does not exceed the preset first duration threshold, obtain the cleaning alarm coefficient through analysis, compare the cleaning alarm coefficient with the preset cleaning alarm coefficient threshold. If the cleaning alarm coefficient exceeds the preset cleaning alarm coefficient threshold, generate a cleaning alarm signal; if the cleaning alarm coefficient does not exceed the preset cleaning alarm coefficient threshold, generate a cleaning unnecessary signal.

[0013] Furthermore, the method for analyzing and obtaining the cleaning alarm coefficient is specifically as follows:

[0014] The dust concentrations at several detection points inside the switchgear cabinet are collected. The average value of all the dust concentrations at the corresponding detection points within the first time period is calculated to obtain the point dust value. The average value of the point dust values of all the detection points is calculated to obtain the dust detection value, and the point dust value with the largest numerical value is marked as the dust amplitude value. The cleaning alarm coefficient is obtained through numerical calculation of the first time period, the dust detection value, and the dust amplitude value.

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

[0016] All the heat dissipation openings on the switchgear cabinet are obtained, and the corresponding heat dissipation opening is marked as i, where i is a natural number greater than 1. The wind speed outside the heat dissipation opening i is collected and marked as the air outlet speed, and the rotation speed of the heat dissipation fan in the switchgear cabinet is collected and marked as the air supply speed. The ratio of the air outlet speed to the air supply speed is marked as the speed ratio coefficient. 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 opening i is in a state of poor air outlet.

[0017] The total duration of the heat dissipation opening i being in a state of poor air outlet within a unit time is obtained and marked as the air outlet non - smooth value. When it is determined that the heat dissipation opening i is in a state of poor air outlet, the difference between the speed ratio coefficient and the corresponding preset speed ratio coefficient threshold is marked as the speed analysis value. The average value of all the speed analysis values corresponding to the heat dissipation opening i within a unit time is calculated to obtain the air outlet speed measurement value, and the speed analysis value with the largest numerical value corresponding to the heat dissipation opening i within a unit time is marked as the air outlet speed amplitude value.

[0018] The heat dissipation opening blockage value is obtained through numerical calculation of the air outlet non - smooth value, the air outlet speed measurement value, and the air outlet speed amplitude value. The heat dissipation opening blockage value is numerically compared with the preset heat dissipation opening blockage threshold. If the heat dissipation opening blockage value exceeds the preset heat dissipation opening blockage threshold, the heat dissipation opening i is marked as a blocked opening. If there is a blocked opening on the switchgear cabinet, a blockage alarm signal is generated. If there is no blocked opening on the switchgear cabinet, a blockage normal signal is generated.

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

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

[0021] When the switchgear is identified with abnormal status, after the operation and maintenance personnel confirm that there is no corresponding abnormal status, assign the non-precise identification symbol LP-1 to the switchgear; set the detection period, classify all the abnormal statuses identified during the detection period, calculate the ratio of the number of times the non-precise identification symbol LP-1 corresponding to the corresponding abnormal status is assigned to the total number of identifications of the abnormal status of the corresponding type to obtain the class identification evaluation value, compare the class identification evaluation value with the corresponding preset class identification evaluation threshold. If the class identification evaluation value exceeds the preset class identification evaluation threshold, mark the corresponding type of abnormality as a non-precise identification object;

[0022] If there is a non-precise identification object during the detection period, generate a non-precise identification signal; if there is no non-precise identification object during the detection period, mark the ratio of the class identification evaluation value of the corresponding type of abnormal status to the corresponding preset class identification value as the class identification occupancy value, calculate the average value of the class identification occupancy values of all types of abnormal statuses to obtain the precise obstacle value, compare the precise obstacle value with the preset precise obstacle threshold. If the precise obstacle value exceeds the preset precise obstacle threshold, generate a non-precise identification signal.

[0023] Further, if the precise obstacle value does not exceed the preset precise obstacle threshold, set several detection time periods within the detection period, mark the total number of identifications of the abnormal status in the corresponding detection time period as the abnormal status identification value, compare the abnormal status identification value with the preset abnormal status identification threshold. If the abnormal status identification value exceeds the preset abnormal status identification threshold, mark the corresponding detection time period as a dangerous time period;

[0024] Obtain the number of dangerous time periods during the detection period and mark it as the dangerous number situation value, and calculate the sum of the abnormal status identification values of all detection time periods during the detection period to obtain the abnormal status identification situation value. Compare the dangerous number situation value and the abnormal status identification situation value with the preset dangerous number situation threshold and the preset abnormal status identification situation threshold respectively. If the dangerous number situation value or the abnormal status identification situation value exceeds the corresponding preset threshold, generate a control high-risk signal.

[0025] Further, if both the dangerous number situation value and the abnormal status identification situation value do not exceed the corresponding preset thresholds, mark the identification time of the corresponding abnormal status as the decision time, mark the time when the operation and maintenance personnel make a treatment as the target time, and mark the interval duration between the target time and the decision time as the second duration;

[0026] Numerically compare the second duration with a preset second duration threshold. If the second duration exceeds the preset second duration threshold, mark the corresponding second duration as the selected duration; obtain the number of selected durations during the detection period and calculate the ratio with the total number of second durations to obtain a different selection detection value, and calculate the average value of all second durations during the detection period to obtain an operation and maintenance detection value. Numerically calculate the switch cabinet management table value by using the dangerous situation value, the abnormal situation recognition value, the different selection detection value, and the operation and maintenance detection value. Numerically compare the switch cabinet management table value with a preset switch cabinet management table threshold. If the switch cabinet management table value exceeds the preset switch cabinet management table threshold, generate a control high-risk signal.

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

[0028] Step 1: Comprehensively monitor the operation state of the switch cabinet;

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

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

[0031] Step 4: Conduct dust cleaning warning analysis on the switch cabinet when no abnormal state of the switch cabinet is identified;

[0032] Step 5: Analyze the blockage condition of the heat dissipation ports on the switch cabinet when a cleaning non-essential signal is generated.

[0033] Compared with the prior art, the beneficial effects of the present invention are:

[0034] 1. In the present invention, by comprehensively monitoring and analyzing the switch cabinet to identify abnormal states of the switch cabinet, conducting inspection and regulation of the switch cabinet after identifying abnormal states of the switch cabinet, conducting dust cleaning warning analysis on the switch cabinet when no abnormal state of the switch cabinet is identified, avoiding potential safety hazards caused by dust accumulation inside the switch cabinet, and analyzing the blockage condition of the heat dissipation ports on the switch cabinet when a cleaning non-essential signal is generated, and inspecting and dredging the corresponding heat dissipation ports when a blockage alarm signal is generated, reducing the operation safety hazards of the switch cabinet and significantly reducing the operation supervision difficulty of the switch cabinet;

[0035] 2. In the present invention, by storing all diagnosis and recognition results through the switch cabinet control analysis unit, and analyzing and judging whether to generate an inaccurate recognition signal or a control high-risk signal, reminding the background management personnel to optimize the recognition of abnormal states of the switch cabinet when an inaccurate recognition signal or a control high-risk signal is generated, and strengthening the operation supervision of the switch cabinet subsequently, further ensuring the safe and stable operation of the switch cabinet. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] For the convenience of those skilled in the art to understand, the present invention will be further described below in conjunction with the accompanying drawings;

[0037] Figure 1 It is the system block diagram of the first embodiment in the present invention;

[0038] Figure 2 It is the system block diagram of the second embodiment in the present invention;

[0039] Figure 3 It is the method flowchart of the third embodiment in the present invention. Specific Embodiments

[0040] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a 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 those of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

[0041] Embodiment 1: As Figure 1 shown, the intelligent switchgear operation control system based on multi-feature information monitoring proposed by 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 state multi-dimensional monitoring unit comprehensively monitors the operation state of the switchgear (including key indicators such as the temperature, humidity, electrical parameters, and mechanical vibration of the switchgear), and sends the collected monitoring data to the state diagnosis output unit;

[0043] Specifically, 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. Among them, the temperature monitoring module arranges 12 SAW temperature sensors at key points including the breaker contact and the bus connection, 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 extracts time-frequency features through a three-axis MEMS accelerometer (bandwidth 10 kHz), and synchronously collects the closing and opening coil currents to achieve vibration-current phase coupling analysis; the partial discharge monitoring module is based on a combination of a UHF sensor (300 MHz - 1.5 GHz) and a high-frequency current transformer (HFCT) for joint detection, and identifies the discharge type through a PRPD pattern and a CNN classifier; the environment monitoring module integrates a humidity sensor (±2%RH), an SF6 concentration sensor (10 ppm resolution), and a dust sensor (PM2.5 / PM10) to monitor the internal environment of the switchgear.

[0045] The status diagnosis output unit analyzes the received monitoring data by using big data analysis and pattern recognition technologies, identifies abnormal states of the switchgear, and sends the diagnosis and recognition results to the background terminal; after identifying the abnormal state of the switchgear, the background terminal issues a warning so as to timely check and control the switchgear, ensure the safe and stable operation of the switchgear, and significantly reduce the operation supervision difficulty of the switchgear.

[0046] If the abnormal state of the switchgear is not identified, the dust cleaning judgment unit conducts dust cleaning warning analysis on the switchgear, generates a cleaning alarm signal or a cleaning non-necessary signal through analysis, and sends the cleaning alarm signal or the cleaning non-necessary 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 timely clean the inside of the switchgear to avoid potential safety hazards caused by dust accumulation inside the switchgear; the specific analysis process of the dust cleaning warning analysis is as follows:

[0047] Collect the time of the last dust cleaning inside the switchgear and mark it as the cleaning time, mark the interval duration between the current time and the cleaning time as the first duration, compare the first duration with a preset first duration threshold. If the first duration exceeds the preset first duration threshold, it indicates that the inside of the switchgear needs to be cleaned currently to avoid potential safety hazards caused by dust accumulation inside the switchgear, and a cleaning alarm signal is generated;

[0048] If the first duration does not exceed the preset first duration threshold, collect the dust concentrations at several detection points inside the switchgear, calculate the average value of all the dust concentrations at the corresponding detection points within the first duration to obtain the point dust value, calculate the average value of the point dust values of all the detection points to obtain the dust inspection value, and mark the point dust value with the largest numerical value as the dust amplitude value;

[0049] Perform numerical calculation on the first duration YS, the dust inspection value GW, and the dust amplitude value WX through the formula ZP = t1×YS+(t2×GW + t3×WX) / 2 to obtain the cleaning alarm coefficient ZP; where, t1, t2, and t3 are preset proportionality coefficients greater than zero, and the larger the numerical value of the cleaning alarm coefficient ZP, the more serious the comprehensive dust accumulation condition inside the switchgear and the greater the potential safety risk;

[0050] Compare the cleaning alarm coefficient ZP with a preset cleaning alarm coefficient threshold. If the cleaning alarm coefficient ZP exceeds the preset cleaning alarm coefficient threshold, it indicates that the comprehensive dust accumulation condition inside the switchgear is relatively serious and the potential safety risk is relatively large, and the inside of the switchgear 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 comprehensive dust accumulation condition inside the switchgear is relatively serious and the potential safety risk is relatively small, and a cleaning non-necessary signal is generated.

[0051] When generating a signal for cleaning unnecessary signals, the blockage detection and analysis unit analyzes the blockage condition of the heat dissipation openings on the switch cabinet. Through the analysis, a blockage alarm signal or a signal indicating no blockage is generated, and the blockage alarm signal or the signal indicating no blockage is sent to the background terminal. When the background terminal receives the blockage alarm signal, it issues a warning to remind the background management personnel to check and dredge the corresponding heat dissipation openings in time, ensuring the heat dissipation performance of the switch cabinet and reducing the potential safety hazards during the operation of the switch cabinet. The specific operation process of the blockage detection and analysis unit is as follows:

[0052] All the heat dissipation openings on the switch cabinet are obtained, and the corresponding heat dissipation opening is marked as i, where i is a natural number greater than 1. The wind speed outside the heat dissipation opening i is collected and marked as the outlet wind speed, and the rotation speed of the heat dissipation fan in the switch cabinet is collected and marked as the generated wind speed. The ratio of the outlet wind speed to the generated wind speed is marked as the speed ratio coefficient. 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 opening i is in a state of poor air outlet.

[0053] The total duration of the heat dissipation opening i being in a state of poor air outlet within a unit time is obtained and marked as the air outlet non - smooth value. When it is determined that the heat dissipation opening i is in a state of poor air outlet, the difference between the speed ratio coefficient and the corresponding preset speed ratio coefficient threshold is marked as the speed analysis value. The average value of all the speed analysis values corresponding to the heat dissipation opening i within a unit time is calculated to obtain the air outlet speed measurement value, and the numerically largest speed analysis value corresponding to the heat dissipation opening i within a unit time is marked as the air outlet speed amplitude.

[0054] The air outlet non - smooth value QFi, the air outlet speed measurement value YLi, and the air outlet speed amplitude HPi are numerically calculated through the formula TXi = uy×QFi+(re×YLi + sq×HPi) / 2 to obtain the heat dissipation opening blockage condition value TXi. Where uy, re, and sq are preset proportionality coefficients greater than zero. Moreover, the larger the numerical value of the heat dissipation opening blockage condition value TXi, the greater the possibility that the heat dissipation opening i is blocked.

[0055] The heat dissipation opening blockage condition value TXi is numerically compared with the preset heat dissipation opening blockage threshold. If the heat dissipation opening blockage condition value TXi exceeds the preset heat dissipation opening blockage threshold, indicating that the heat dissipation opening i has a greater possibility of being blocked, then the heat dissipation opening i is marked as a blocked opening. If there are blocked openings on the switch cabinet, indicating that the heat dissipation risk of the switch cabinet is relatively high, a blockage alarm signal is generated. If there are no blocked openings on the switch cabinet, indicating that the heat dissipation risk of the switch cabinet is relatively low, a signal indicating no blockage is generated.

[0056] Embodiment 2: As Figure 2As shown in the figure, the difference between this embodiment and the first embodiment is that the status diagnosis output unit is communicatively connected to the switchgear control and analysis unit. The status diagnosis output unit sends the diagnosis and identification results of the switchgear to the switchgear control and analysis unit. The switchgear control and analysis unit stores all the diagnosis and identification results, and determines whether to generate an inaccurate identification signal or a high-risk control signal through analysis. When an inaccurate identification signal or a high-risk control signal is generated, it is sent to the background terminal;

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

[0058] When the switchgear is identified as having an abnormal status, and after the maintenance personnel confirm that there is no corresponding abnormal status, an inaccurate identification symbol LP-1 is assigned to the switchgear; set the detection period. Preferably, the detection period is twenty days; classify all the abnormal statuses identified during the detection period, and calculate the ratio of the number of times the inaccurate identification symbol LP-1 corresponding to the corresponding abnormal status is assigned to the total number of identifications of the corresponding type of abnormal status to obtain a class identification evaluation value;

[0059] Compare the class identification evaluation value with the corresponding preset class identification evaluation threshold. If the class identification evaluation value exceeds the preset class identification evaluation threshold, it indicates that the error rate of identifying the corresponding type of abnormal status is relatively high and it is difficult to accurately identify the corresponding type of abnormal status. Then, mark the corresponding type of abnormality as an inaccurate identification object; if there is an inaccurate identification object during the detection period, it indicates that the identification of the corresponding type of abnormal status needs to be optimized in a timely manner, and an inaccurate identification signal is generated;

[0060] If there is no inaccurate identification object during the detection period, then mark the ratio of the class identification evaluation value of the corresponding type of abnormal status to the corresponding preset class identification value as the class identification measurement value. Calculate the average value of the class identification measurement values of all types of abnormal statuses to obtain a precision hindrance value. Compare the precision hindrance value with the preset precision hindrance threshold. If the precision hindrance value exceeds the preset precision hindrance threshold, it indicates that the overall accuracy of identifying the abnormal status of the switchgear is relatively poor, and an inaccurate identification signal is generated.

[0061] Moreover, if the precision hindrance value does not exceed the preset precision hindrance threshold, then set several detection time periods during the detection period, mark the total number of identifications of abnormal statuses in the corresponding detection time periods as the abnormal status identification value, and compare the abnormal status identification value with the preset abnormal status identification threshold. If the abnormal status identification value exceeds the preset abnormal status identification threshold, it indicates that the operating stability of the switchgear in the corresponding detection time period is relatively poor and its operating risk is relatively high. Then, mark the corresponding detection time period as a dangerous time period;

[0062] Obtain the number of dangerous time periods during the detection period and mark it as the dangerous situation value, and calculate the sum of the state anomaly identification values of all detection time periods during the detection period to obtain the state anomaly situation value. Numerically compare the dangerous situation value and the state anomaly situation value with the preset dangerous situation threshold and the preset state anomaly situation threshold respectively. If the dangerous situation value or the state anomaly situation value exceeds the corresponding preset threshold, it indicates that the operation and control of the switch cabinet during the detection period is difficult, and a high-risk control signal is generated.

[0063] Furthermore, if both the dangerous situation value and the state anomaly situation value do not exceed the corresponding preset thresholds, mark the recognition time of the corresponding state anomaly as the decision time, mark the time when the operation and maintenance personnel make a handling as the target time, and mark the time interval between the target time and the decision time as the second time length;

[0064] Numerically compare the second time length with the preset second time length threshold. If the second time length exceeds the preset second time length threshold, mark the corresponding second time length as the selected time length; obtain the number of selected time lengths during the detection period and calculate the ratio with the total number of second time lengths to obtain the abnormal selection detection value, and calculate the average value of all second time lengths during the detection period to obtain the operation and maintenance detection value;

[0065] Numerically calculate the dangerous situation value SY, the state anomaly situation value PX, the abnormal selection detection value ZW, and the operation and maintenance detection value NS through the formula GL = b1×SY + b2×PX + b3×ZW + b4×NS to obtain the switch cabinet management table value GL, where b1, b2, b3, and b4 are preset proportionality coefficients greater than zero. Moreover, the larger the numerical value of the switch cabinet management table value GL, the higher the comprehensive control risk of the switch cabinet during the detection period;

[0066] Numerically compare the switch cabinet management table value GL with the preset switch cabinet management table threshold. If the switch cabinet management table value GL exceeds the preset switch cabinet management table threshold, it indicates that the comprehensive control risk of the switch cabinet during the detection period is relatively high, and it is necessary to strengthen the supervision of the switch cabinet in the follow-up, and a high-risk control signal is generated.

[0067] Embodiment 3: As Figure 3 shown, the difference between this embodiment and Embodiment 1 and Embodiment 2 is that the intelligent switch cabinet operation control method based on multi-feature information monitoring proposed by the present invention includes the following steps:

[0068] Step 1: Comprehensively monitor the operation state of the switch cabinet;

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

[0070] Step 3: Analyze based on various monitoring data to identify the state anomalies of the switch cabinet;

[0071] Step 4: Conduct dust cleaning warning analysis on the switchgear when no abnormal state of the switchgear is identified;

[0072] Step 5: Analyze the blockage condition of the heat dissipation openings on the switchgear when a cleaning non-necessary signal is generated.

[0073] The working principle of the present invention: When in use, the state multi-dimensional monitoring unit comprehensively monitors the operating state of the switchgear, and the state diagnosis output unit analyzes each monitoring data to identify the abnormal state of the switchgear. After identifying the abnormal state of the switchgear, the switchgear is inspected and regulated to ensure the safe and stable operation of the switchgear. When no abnormal state of the switchgear is identified, the dust cleaning judgment unit conducts dust cleaning warning analysis on the switchgear. When a cleaning alarm signal is generated, the background management personnel are reminded to clean the inside of the switchgear in time to avoid potential safety hazards caused by the accumulation of dust inside the switchgear. When a cleaning non-necessary signal is generated, the blockage detection and analysis unit analyzes the blockage condition of the heat dissipation openings on the switchgear. When a blockage alarm signal is generated, the background management personnel are reminded to check and dredge the corresponding heat dissipation openings in time to ensure the heat dissipation performance of the switchgear, reduce the potential safety hazards during the operation of the switchgear, and significantly reduce the operation supervision difficulty of the switchgear.

[0074] The above formulas are all dimensionless and take their numerical values for calculation. The formulas are obtained by collecting a large amount of data and performing software simulation to get a formula that is closest to the actual situation. The preset parameters in the formulas are set by those skilled in the art according to the actual situation. The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only the specific implementation manners. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments to better explain the principle and practical application of the present invention, so that those skilled in the relevant technical field can understand and utilize the present invention well. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. An intelligent switchgear operation control system based on multi-feature information monitoring, characterized in that, It 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; The state multi-dimensional monitoring unit comprehensively monitors the operating state of the switch cabinet. The state diagnosis output unit analyzes the monitoring data and identifies abnormal states of the switch cabinet. After identifying the abnormal state of the switch cabinet, the background terminal issues a warning; If the abnormal state of the switch cabinet is not identified, the dust cleaning judgment unit conducts a dust cleaning warning analysis on the switch cabinet, generates a cleaning alarm signal or a cleaning non-necessary signal through the analysis, and sends the cleaning alarm signal or the cleaning non-necessary signal to the background terminal; when generating the cleaning non-necessary signal, the blockage detection and analysis unit analyzes the blockage condition of the heat dissipation port on the switch cabinet, generates a blockage alarm signal or a blockage-free signal through the analysis, and the background terminal issues a warning when receiving the blockage alarm signal; The state diagnosis output unit is communicatively connected to the switch cabinet control and analysis unit. The switch cabinet control and analysis unit determines whether to generate an inaccurate recognition signal through analysis, and sends it to the background terminal when generating the inaccurate recognition signal; The specific analysis process of the switch cabinet control and analysis unit is as follows: When the switch cabinet is identified as having an abnormal state and it is determined that there is no corresponding abnormal state after being confirmed by the maintenance personnel, an inaccurate recognition symbol LP-1 is assigned to the switch cabinet; Set the detection period, classify all the abnormal states identified during the detection period, calculate the ratio of the number of times the inaccurate recognition symbol LP-1 corresponding to the corresponding abnormal state is assigned to the total number of identifications of the corresponding type of abnormal state to obtain a class recognition evaluation value, compare the class recognition evaluation value with the corresponding preset class recognition evaluation threshold. If the class recognition evaluation value exceeds the preset class recognition evaluation threshold, the corresponding type of abnormality is marked as an inaccurate recognition object; If there is an inaccurate recognition object during the detection period, an inaccurate recognition signal is generated; if there is no inaccurate recognition object during the detection period, the ratio of the class recognition evaluation value of the corresponding type of abnormal state to the corresponding preset class recognition value is marked as the class recognition measurement value. Calculate the average value of the class recognition measurement values of all types of abnormal states to obtain a precision hindrance value, compare the precision hindrance value with the preset precision hindrance threshold. If the precision hindrance value exceeds the preset precision hindrance threshold, an inaccurate recognition signal is generated.

2. The intelligent switchgear operation control system based on multi-feature information monitoring according to claim 1, wherein The state multi-dimensional monitoring unit includes a temperature monitoring module, a vibration monitoring module, a partial discharge monitoring module, and an environmental monitoring module.

3. The intelligent switchgear operation control system based on multi-feature information monitoring according to claim 1, wherein The specific analysis process of the dust cleaning warning analysis is as follows: Collect the moment of the previous dust cleaning inside the switch cabinet and mark it as the cleaning moment. Mark the time interval between the current moment and the cleaning moment as the first duration. If the first duration exceeds the preset first duration threshold, a cleaning alarm signal is generated; If the first duration does not exceed the preset first duration threshold, a 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 non-necessary signal is generated.

4. The intelligent switchgear operation control system based on multi-feature information monitoring according to claim 3, characterized in that, The method for analyzing and obtaining the cleaning alarm coefficient is specifically as follows: The dust concentrations at several detection points inside the switchgear are collected. The average value of all the dust concentrations at the corresponding detection points within the first period is calculated to obtain the point dust value. The average value of the point dust values of all the detection points is calculated to obtain the dust detection value, and the point dust value with the largest numerical value is marked as the dust amplitude value. The cleaning alarm coefficient is obtained by performing numerical calculations on the first period, the dust detection value, and the dust amplitude value.

5. The intelligent switchgear operation control system based on multi-feature information monitoring according to claim 1, wherein The specific operation process of the blockage detection and analysis unit includes: All the heat dissipation ports on the switchgear 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 rotation speed of the heat dissipation fan in the switchgear is collected and marked as the air supply speed. The ratio of the air outlet speed to the air supply speed is marked as the speed ratio coefficient. 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. The total duration of the heat dissipation port i being in a state of poor air outlet per unit time is obtained and marked as the air outlet non - smooth value. When it is determined that the heat dissipation port i is in a state of poor air outlet, the difference between the speed ratio coefficient and the corresponding preset speed ratio coefficient threshold is marked as the speed analysis value. The average value of all the speed analysis values corresponding to the heat dissipation port i per unit time is calculated to obtain the air outlet speed measurement value, and the speed analysis value with the largest numerical value corresponding to the heat dissipation port i per unit time is marked as the air outlet speed amplitude value. The heat dissipation port blockage condition value is obtained by performing numerical calculations on the air outlet non - smooth value, the air outlet speed measurement value, and the air outlet speed amplitude value. The heat dissipation port blockage condition value is numerically compared with the preset heat dissipation port blockage threshold. If the heat dissipation port blockage condition value exceeds the preset heat dissipation port blockage threshold, the heat dissipation port i is marked as a blocked port. If there is a blocked port on the switchgear, a blockage alarm signal is generated. If there is no blocked port on the switchgear, a blockage normal signal is generated.

6. The intelligent switchgear operation control system based on multi-feature information monitoring according to claim 1, wherein The switchgear control and analysis unit determines whether to generate a control high - risk signal through analysis. When a control high - risk signal is generated, it is sent to the background terminal. The specific analysis process of the switchgear control and analysis unit also includes: If the precise obstruction value does not exceed the preset precise obstruction threshold, several detection periods are set within the detection period. The total number of abnormal state identifications in the corresponding detection periods is marked as the state abnormal identification value. The state abnormal identification value is numerically compared with the preset state abnormal identification threshold. If the state abnormal identification value exceeds the preset state abnormal identification threshold, the corresponding detection period is marked as a dangerous period. The number of dangerous periods within the detection period is obtained and marked as the dangerous number condition value. The sum of the state abnormal identification values of all the detection periods within the detection period is calculated to obtain the state abnormal identification condition value. The dangerous number condition value and the state abnormal identification condition value are numerically compared with the preset dangerous number condition threshold and the preset state abnormal identification condition threshold respectively. If the dangerous number condition value or the state abnormal identification condition value exceeds the corresponding preset threshold, a control high - risk signal is generated.

7. The intelligent switchgear operation control system based on multi-feature information monitoring according to claim 6, wherein If both the dangerous number condition value and the state abnormal identification condition value do not exceed the corresponding preset thresholds, the moment of the abnormal state identification is marked as the decision moment, the moment when the maintenance personnel make a treatment is marked as the target moment, and the time interval between the target moment and the decision moment is marked as the second period. Numerically compare the second duration with a preset second duration threshold. If the second duration exceeds the preset second duration threshold, mark the corresponding second duration as the selected duration; obtain the number of selected durations during the detection period and calculate the ratio with the total number of second durations to obtain the abnormal selection detection value, and calculate the average value of all second durations during the detection period to obtain the operation and maintenance detection value. Numerically calculate the switchgear management table value by performing numerical calculations on the dangerous situation value, abnormal situation recognition value, abnormal selection detection value, and operation and maintenance detection value. Numerically compare the switchgear management table value with a preset switchgear management table threshold. If the switchgear management table value exceeds the preset switchgear management table threshold, generate a control high-risk signal.

8. The intelligent switchgear operation control method based on multi-feature information monitoring uses the intelligent switchgear operation control system based on multi-feature information monitoring as described in any one of claims 1-7, characterized in that, It includes the following steps: Step 1, comprehensively monitor the operating status of the switchgear; Step 2, collect various monitoring data of the switchgear; Step 3, analyze based on various monitoring data to identify abnormal conditions of the switchgear; Step 4, conduct dust cleaning warning analysis on the switchgear when no abnormal conditions of the switchgear are identified; Step 5, analyze the blockage condition of the heat dissipation openings on the switchgear when generating a non-necessary cleaning signal.

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