Low-voltage power distribution cabinet

Abstract

The invention discloses a low-voltage power distribution cabinet, and relates to the technical field of low-voltage power distribution cabinets, the low-voltage power distribution cabinet comprises a cabinet body, a cabinet door hinged to the cabinet body and a plurality of electrical elements installed in the cabinet body, and the cabinet door is provided with a processing module; the detection module is mounted on the inner top surface of the cabinet body; the fire extinguishing module is mounted on the inner top surface of the cabinet body; the alarm module comprises an audible and visual alarm installed on the inner top surface of the cabinet body. Through mutual cooperative use of the processing module, the alarm module, the detection module and the fire extinguishing module, real-time monitoring of conditions in the low-voltage power distribution cabinet is facilitated, fire disasters or other faults in the low-voltage power distribution cabinet are avoided, and use of the low-voltage power distribution cabinet is facilitated; performing weighted calculation on the four danger levels through a processing module to obtain the equipment health degree, dynamically adjusting a weight coefficient in combination with historical fault data, and converting the equipment state into a quantifiable health index; when the JK value is below a threshold value, a replacement alert is generated in advance rather than waiting for the occurrence of a fault.

Description

Technical Field

[0001] The present invention relates to the technical field of low-voltage power distribution cabinets, and in particular to a low-voltage power distribution cabinet. Background Art

[0002] In the power system, low-voltage distribution cabinets, as key equipment for power distribution, are widely used in various scenarios such as industrial, commercial, and residential areas, playing an important role in power distribution, control, and protection. However, due to the dense concentration of electrical components within distribution cabinets, long-term operation can easily lead to safety hazards due to factors such as aging lines, poor contact, and excessive loads. The existing low-voltage distribution cabinet has the following problems when in use: On the one hand, fault detection methods lag behind; most distribution cabinets rely on regular manual inspections to detect anomalies, and are unable to monitor key parameters such as internal temperature and smoke in real time. When electrical components overheat, causing insulation aging or short circuits, it is often difficult to provide timely warnings, resulting in gradual escalation of faults and even fires. Moreover, when parameter monitoring is carried out, warnings are mostly issued when an anomaly occurs, or early warnings are issued. There is no clear understanding of the aging process of equipment during use, which may cause dangerous situations during the use of distribution cabinets due to equipment aging. On the other hand, fire prevention and control capabilities are insufficient; traditional distribution cabinets lack automatic fire extinguishing devices. Once a fire occurs, it can spread rapidly, causing not only equipment damage and power outages, but also potentially endangering personnel safety and resulting in significant economic losses. With the advancement of smart grid construction, higher requirements are placed on the safety, reliability and intelligence level of low-voltage distribution cabinets. How to achieve real-time monitoring of the internal status of the distribution cabinet, early warning of faults and automatic handling has become an urgent problem to be solved in the industry. Therefore, the development of a low-voltage distribution cabinet with real-time detection, intelligent alarm and automatic fire extinguishing functions is of great practical significance for improving the operational stability of the power system, reducing operation and maintenance costs, and ensuring the safety of personnel and equipment. Summary of the Invention

[0003] The present invention proposes a low-voltage power distribution cabinet in order to solve the problems in the background technology.

[0004] In order to achieve the above object, the present invention adopts the following technical solutions: A low-voltage power distribution cabinet comprises a cabinet body, a cabinet door hinged to the cabinet body, and a plurality of electrical components installed in the cabinet body, wherein the cabinet door is provided with a processing module; The processing module receives the data transmitted by the detection module, analyzes the transmitted image data, estimates the number of changes required to reach the outbreak point at the abnormal location, and compares it with the change number threshold to derive the corresponding danger level; analyzes the grayscale value change of the grayscale processed image to derive the corresponding danger level again; analyzes the transmitted temperature data and gas concentration data, determines the time required to reach the corresponding threshold based on the rate of change of temperature and gas concentration, and calculates the corresponding danger level; and derives the equipment health of the cabinet through weighted calculation of the four danger levels. If the equipment health is less than the corresponding threshold, a replacement warning signal is generated and transmitted to the alarm module; Detection module: The detection module is installed on the top surface of the cabinet; Fire extinguishing module: The fire extinguishing module is installed on the top surface of the cabinet; Alarm module: The alarm module includes an audible and visual alarm installed on the top surface of the cabinet.

[0005] Preferably, the detection module includes a camera, a temperature sensor and a smoke sensor.

[0006] Preferably, the fire extinguishing module comprises a fire extinguisher.

[0007] Preferably, the processing module includes a processor and a controller, and the processor is electrically connected to the camera, the temperature sensor and the smoke sensor, and the controller is electrically connected to the sound and light alarm and the fire extinguisher.

[0008] Preferably, an intelligent detection component is provided inside the cabinet, and the intelligent detection component includes a detection module, a processing module and an alarm module; The detection module detects the image data, temperature data and gas concentration data inside the distribution cabinet and transmits the detected data to the processing module; The alarm module receives the replacement warning signal transmitted by the processing module, then controls the warning light to emit an audible and visual alarm, and sends information to the staff through the transmission function of the module to remind the staff to replace the distribution cabinet.

[0009] Preferably, the processing module performs the following steps for image data analysis: S1: Determine a preset grayscale contrast image corresponding to the camera shooting position according to the rotation angle between the camera and the set initial direction; S2: grayscale processing is performed on the image data at the corresponding time point according to the set time interval, and the grayscale processed image data is divided according to the size of the pixel block, the grayscale value of the grayscale image block after the division is calculated, and the grayscale value data of the grayscale image block obtained by calculation is converted into grayscale value data. Compare the grayscale value data at the corresponding position on the corresponding preset grayscale comparison chart Comparing the two images, if the absolute value of the grayscale value difference between the two exceeds the preset difference threshold of the grayscale comparison image, the corresponding position of the grayscale image block is determined to be an abnormal position; S3: If the adjacent pixel blocks at the abnormal position are also at abnormal positions, they are determined to be at the same abnormal position, and the area of ​​the abnormal position is is the number of grayscale image blocks at the abnormal position multiplied by the area of ​​a single grayscale image block, if , then the abnormal position is analyzed and marked for the number of changes. is the preset abnormal area threshold; if , then the total number of abnormal locations in the detected image data Perform statistics, if , then the abnormal position is analyzed and marked for the number of changes. is the preset scale factor, Summarize the total number of grayscale image blocks for the detection image data; S4: Retrieve historical data, and compare the grayscale image block at the abnormal position with the normal grayscale value data. , and the gray value data corresponding to the critical point of dangerous outbreak Acquire; the gray value change of the gray image block at the corresponding normal position within the adjacent acquisition time period Record and calculate the change threshold based on the gray value change ; Compare the grayscale value data of the grayscale image block at the change number analysis mark position with the grayscale value data at the corresponding position on the corresponding preset grayscale comparison map Compare and get the expected number of changes corresponding to the detected grayscale image block ,like , then it is determined that there is danger at the detection location, and the danger level , is the preset proportional coefficient; S5: The change in grayscale value of adjacent detection time points at the detection position To obtain, if the preset gray value at the corresponding position changes the threshold , then it is also determined that there is danger at the detection location, and the danger level .

[0010] Preferably, the processing module performs the following steps to analyze the temperature and gas concentration data: K1: Establish a binary coordinate system using temperature data / gas concentration data and acquisition time. Draw corresponding coordinate points within the coordinate system, connect adjacent coordinate points, calculate the slope of the connecting lines, and compare the slopes of the temperature and gas concentration lines with the preset change thresholds of the corresponding items. K2: If the slope of the corresponding line is greater than the preset change threshold of the corresponding item, it is determined that there is danger, and the danger level is and Equal to the slope value of the corresponding item minus the preset change threshold of the corresponding item, divided by the preset change threshold of the corresponding item; K3: If the slope of the corresponding line is less than the preset change threshold of the corresponding item, the detection data of the current corresponding item is recorded, and the detection data before this time point is substituted into the formula ,get and The specific value of is the detection data of the corresponding item, is the detection time; then the formula can be used to determine the elapsed time After that, the detection data of the corresponding item will reach the preset warning threshold. If the preset response time , then it is determined that there is danger, the danger level and Equal to the time of the corresponding item Subtract the preset reaction time of the corresponding item , and divided by the preset reaction time of the corresponding item .

[0011] Preferably, the processing module performs the following steps to analyze the health of the device: M1: Quantify the health of the equipment of the distribution cabinet according to the risk level. , 、 、 、 and are weight coefficients of the corresponding items respectively; when the health of the device is less than the preset health threshold, it is determined that the safety hazard of continuing to use the device is large, and a replacement warning signal is generated and transmitted to the alarm module; M2: retrieve historical fault information, count the number of occurrences of the three types of abnormalities in the historical fault information, and then divide the number of occurrences of the three types of abnormalities by the total number of occurrences of the three types of abnormalities to obtain the corresponding weight coefficients 、 and ; M3: Obtain the accuracy of abnormal judgment by the two analysis methods of change number and gray value change. The accuracy of the corresponding analysis method is divided by the sum of the accuracies of the two analysis methods to obtain the corresponding weight coefficient. and .

[0012] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: 1. Through the coordinated use of the processing module, alarm module, detection module and fire extinguishing module, it is convenient to monitor the situation inside the low-voltage distribution cabinet in real time, avoid fire or other faults in the low-voltage distribution cabinet, and thus facilitate the use of the low-voltage distribution cabinet; 2. The processing module calculates the weighted value of the four hazard levels to determine the equipment health. The weight coefficient is dynamically adjusted based on historical fault data to convert the equipment status into a quantifiable health indicator. When the JK value falls below the threshold, a replacement warning is generated in advance rather than waiting for a fault to occur. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 It shows a schematic structural diagram of a front view provided by an embodiment of the present invention; Figure 2 A schematic structural diagram of a cabinet provided in an embodiment of the present invention is shown; Figure 3 A system flow chart provided according to an embodiment of the present invention is shown.

[0014] Legend: 1. Cabinet body; 2. Electrical components; 3. Processing module; 4. Cabinet door; 5. Fire extinguishing module; 6. Detection module; 7. Alarm module. DETAILED DESCRIPTION

[0015] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0016] See also Figure 1-Figure 3 , the present invention provides a technical solution: A low-voltage power distribution cabinet comprises a cabinet body 1, a cabinet door 4 hinged to the cabinet body 1, and a plurality of electrical components 2 installed in the cabinet body 1, wherein a processing module 3 is provided on the cabinet door 4; A detection module 6 is installed in the middle of the top surface of the cabinet 1. The detection module 6 includes a camera, a temperature sensor and a smoke sensor, which is used to collect information inside the low-voltage distribution cabinet and determine whether the low-voltage distribution cabinet has a fault through processing by the processing module 3, thereby facilitating timely handling of the fault of the low-voltage distribution cabinet; A fire extinguishing module 5 is installed on the top surface of the cabinet 1, and the fire extinguishing module 5 includes a fire extinguisher, which is convenient for extinguishing fire in the low-voltage distribution cabinet to avoid the occurrence of fire and thus reduce losses.

[0017] The alarm module 7 includes an audible and visual alarm installed on the top surface of the cabinet 1, which is used to remind the staff that there is a fault in the low-voltage distribution cabinet, so that the staff can deal with the fault of the low-voltage distribution cabinet in time and avoid the occurrence of fire, which is beneficial to the use of the low-voltage distribution cabinet.

[0018] In the present invention, the processing module 3 includes a processor and a controller, and the processor is electrically connected to the camera, temperature sensor and smoke sensor, and the controller is electrically connected to the sound and light alarm and fire extinguisher; through the mutual coordination of the processing module 3, the alarm module 7, the detection module 6 and the fire extinguishing module 5, it is convenient to monitor the situation inside the low-voltage distribution cabinet in real time, avoid fire or other faults in the low-voltage distribution cabinet, and thus facilitate the use of the low-voltage distribution cabinet.

[0019] An intelligent detection component is provided inside the cabinet 1, and the intelligent detection component includes a detection module 6, a processing module 3 and an alarm module 7; Detection module 6 detects image data, temperature data and gas concentration data inside the power distribution cabinet and transmits the detected data to processing module 3; Processing module 3 receives the data transmitted by detection module 6, analyzes the transmitted image data, estimates the number of changes required to reach the outbreak point at the abnormal location, and compares it with the change number threshold to derive the corresponding danger level; analyzes the grayscale value change of the grayscale processed image to derive the corresponding danger level again; analyzes the transmitted temperature data and gas concentration data, determines the time required to reach the corresponding threshold based on the rate of change of temperature and gas concentration, and calculates the corresponding danger level; and derives the equipment health of cabinet 1 through weighted calculation of the four danger levels. If the equipment health is less than the corresponding threshold, a replacement warning signal is generated and transmitted to alarm module 7; The appearance image data of each device inside the distribution cabinet is monitored by the camera, and the preset grayscale comparison map corresponding to the camera shooting position is determined according to the rotation angle between the camera and the set initial direction; the image data of the corresponding time point is grayscale processed according to the set time interval, and the grayscale processed image data is segmented according to the size of the pixel block, the grayscale value of the segmented grayscale image block is calculated, and the grayscale value data of the calculated grayscale image block is converted into grayscale value data. Compare the grayscale value data at the corresponding position on the corresponding preset grayscale comparison chart Comparing the two images, if the absolute value of the grayscale value difference between the two exceeds the preset difference threshold of the grayscale comparison image, the corresponding position of the grayscale image block is determined to be an abnormal position; The matching mechanism between the camera rotation angle and the preset grayscale comparison map is based on the principle of spatial mapping. Specifically, the system pre-processes the grayscale of the normal cabinet 1 interior images taken at different camera rotation angles (such as 0°, 30°, and 60°) to generate a standard grayscale map corresponding to each angle. During actual detection, the system obtains the current angle of the camera through the encoder and automatically calls the grayscale comparison map of the corresponding angle. Grayscale processing usually adopts the weighted average method (such as the RGB to grayscale formula: Gray=0.299R+0.587G+0.114B) to convert the color image into an 8-bit grayscale image (0-255 levels), and then divides it into 16×16 pixel blocks to facilitate the calculation of the average grayscale value of each block. The setting of the preset difference threshold needs to be combined with the material characteristics of the component. For example, the normal grayscale value of the copper busbar is 180-200, and the grayscale value drops below 150 after oxidation, so the threshold can be set to 30 (i.e. ≥30 is considered abnormal); If the adjacent pixel blocks at the abnormal position are also at abnormal positions, they are determined to be at the same abnormal position, and the area of ​​the abnormal position is is the number of grayscale image blocks at the abnormal position multiplied by the area of ​​a single grayscale image block, if , then the abnormal position is analyzed and marked for the number of changes. is the preset abnormal area threshold; if , then the total number of abnormal locations in the detected image data Perform statistics, if , then the abnormal position is analyzed and marked for the number of changes. is the preset scale factor, Summarize the total number of grayscale image blocks for the detection image data; Abnormal area threshold The setting of the component size must be considered. For example, if the abnormal area of ​​the contact of a small relay exceeds 100mm², it may affect the contact performance. Set to 100mm²; when the abnormal area is small (such as <100mm²), if the number of abnormal points exceeds 5% of the total number of pixel blocks ( ), it indicates that there is a risk of multi-point aging and needs to be marked for analysis; Retrieve historical data, the grayscale image block at the corresponding abnormal position is in the normal grayscale value data , and the gray value data corresponding to the critical point of dangerous outbreak Acquire; the gray value change of the gray image block at the corresponding normal position within the adjacent acquisition time period Record and calculate the change threshold based on the gray value change ; Compare the grayscale value data of the grayscale image block at the change number analysis mark position with the grayscale value data at the corresponding position on the corresponding preset grayscale comparison map Compare and get the expected number of changes corresponding to the detected grayscale image block ,like , then it is determined that there is danger at the detection location, and the danger level , is the preset proportional coefficient; Gray value of critical point of dangerous outbreak Through accelerated aging experiments, it is determined that, for example, when a circuit breaker contact is continuously overloaded, sparks appear when the grayscale value drops from the normal 180 to 120. ; is the average grayscale value during normal operation (such as 180); the grayscale change between adjacent acquisition time periods Usually take the average value of changes within 1 hour. Grayscale unit, then (120-180) / 5=-12 times (the negative sign indicates a decreasing trend in grayscale); when a certain area is detected 160, 180, then (160-180) / 5=-4 times, if ,but -6 times, because -4>-6, it is determined that there is danger, (-4-(-6)) / (-6)=0.33 (normalized hazard level); The change in gray value of adjacent detection time points at the detection position To obtain, if the preset gray value at the corresponding position changes the threshold , then it is also determined that there is danger at the detection location, and the danger level .

[0020] The data detected by the temperature sensor and the smoke sensor are acquired, and a binary coordinate system is established with the temperature data / gas concentration data and the acquisition time. The corresponding coordinate points are drawn in the coordinate system, and the adjacent coordinate points are connected. The slope of the connection line is calculated, and the slope of the temperature connection line and the gas concentration connection line are compared with the preset change threshold of the corresponding item. If the slope of the corresponding connection line is greater than the preset change threshold of the corresponding item, it is determined that there is danger and the danger level is and Equal to the slope value of the corresponding item minus the preset change threshold of the corresponding item, divided by the preset change threshold of the corresponding item; If the slope of the corresponding line is less than the preset change threshold of the corresponding item, the detection data of the current corresponding item is recorded, and the detection data before this time point is substituted into the formula ,get and The specific value of is the detection data of the corresponding item, is the detection time; then the formula can be used to determine the elapsed time After that, the detection data of the corresponding item will reach the preset warning threshold. If the preset response time , then it is determined that there is danger, the danger level and Equal to the time of the corresponding item Subtract the preset reaction time of the corresponding item , and divided by the preset reaction time of the corresponding item ; The temperature data collection interval is usually 5 minutes to draw the temperature-time curve; the slope is calculated using the two-point difference method, such as Temperature at all times =25℃, Minutes 26℃, slope (26-25) / 5=0.2℃ / minute; The preset change threshold is set according to the component temperature rise limit. For example, the contactor allows a temperature rise rate of 0.5℃ / minute, so the threshold is set to 0.5; when When 0.6>0.5, (0.6-0.5) / 0.5=0.2, which means the danger level is 20%; When the slope When the value is less than the threshold, linear regression is used to fit historical data (such as the past 10 time points). For example, the temperature data of a certain area is fitted as 0.1t+20, the preset warning threshold is 40℃, then the threshold time is (40-20) / 0.1=200 minutes; if the preset reaction time 120 minutes, because 200≤120 is not established, it is judged that there is no danger; if after fitting 100 minutes ≤ 120 minutes, then (100-120) / 120=-0.17 (negative value means insufficient time remaining, danger level 17%); Quantify the health of the equipment of the distribution cabinet according to the risk level. , 、 、 、 and are weight coefficients of the corresponding items respectively; when the health of the device is less than the preset health threshold of the device, it is determined that the safety hazard of continuing to use the device is large, and a replacement warning signal is generated and transmitted to the alarm module 7; Health formula The weight coefficient needs to be set according to the operating characteristics of the equipment. Taking industrial distribution cabinets as an example, historical data shows that 60% of faults are caused by abnormal component appearance (such as oxidation, cracks), 30% are caused by abnormal temperature, and 10% are caused by abnormal smoke concentration. 0.6, 0.3, 0.1; and They correspond to the accuracy weights of "number of changes" and "grayscale value changes" in image analysis. If the test shows that the accuracy of the number of changes method is 85% and the grayscale change method is 75%, then 85 / (85+75)=0.53, 0.47; Hazard Level Need to be normalized to the [0,1] interval, for example 0.33 (previous example), 0.2 (when 30, 25:00, (30-25) / 25=0.2), 0.2, 0 (no abnormality in gas concentration), then 0.221; if the preset health threshold is 0.6, a replacement warning is generated because 0.221 < 0.6; Retrieve historical fault information, count the number of occurrences of the three types of anomalies in the historical fault information, and then divide the number of occurrences of the three types of anomalies by the total number of occurrences of the three types of anomalies to obtain the corresponding weight coefficients. 、 and ; Obtain the accuracy of abnormal judgment by the two analysis methods of change number and gray value change, and divide the accuracy of the corresponding analysis method by the sum of the accuracies of the two analysis methods to obtain the corresponding weight coefficient and ; If a distribution cabinet has 10 faults within one year of operation, 6 of which are due to temperature anomalies, 3 to image anomalies, and 1 to smoke anomaly, then 3 / 10=0.3, 6 / 10=0.6, 1 / 10=0.1, that is, increase the weight of the temperature parameter; regularly verify the accuracy of the two image analysis methods, for example, select 100 known fault samples, the change number method correctly identifies 85 times, and the grayscale change method correctly identifies 75 times, so 85 / (85+75)=0.53, 0.47. When the aging of the equipment causes the appearance of the components to change more significantly, the Improve analytical accuracy; The alarm module 7 receives the replacement warning signal transmitted by the processing module 3, then controls the warning light to emit an audible and visual alarm, and sends information to the staff through the transmission function of the module to remind the staff to replace the distribution cabinet.

[0021] The detection module 6 collects data in real time and transmits it to the processing module 3, which calculates the health status every 10 minutes. ;when When it is less than 0.6, the first level warning will be triggered (such as APP push); if If the value is less than 0.4, it is judged as an emergency fault and an audible and visual alarm is activated (such as 80dB buzzer sound + red light flashing), and a text message (including fault location, health value, and recommended processing time) is sent to the operation and maintenance personnel via the 4G module. If the value is 0.35<0.4, the system generates a warning message: "Contactor C1 is not healthy enough, and it is recommended to replace it within 24 hours." At the same time, the system links the camera to focus on the component and provides real-time video for remote diagnosis. In addition to automatically starting when the smoke concentration is greater than 1% obs / m and the temperature is greater than 100°C, the fire extinguishing module 5 is also associated with health: When the value is less than 0.3 and the temperature is greater than 80°C, even if no smoke is detected, it is determined that there is a high-risk fire hazard, and the fire extinguisher is activated in advance to spray dry powder (such as 5kg ABC dry powder, covering an area of ​​5m²) to prevent the fault from escalating. For example, if the temperature of a component in a certain area rises to 85°C due to poor contact, the health 0.28<0.3, the system automatically starts the fire extinguishing module 5 and cuts off the power supply of the circuit at the same time.

[0022] Working principle: When the present invention is in use, when a fire occurs in the low-voltage distribution cabinet, the camera captures the image and transmits the image to the processor, which processes the image and controls the fire extinguisher to start through the controller, and then sprays dry powder. The dry powder covers the fire point, isolates the oxygen and achieves the purpose of extinguishing the fire; and the sound and light alarm will light up and make a sound to remind the staff that there is a fault in the low-voltage distribution cabinet, thereby facilitating timely fault handling of the low-voltage distribution cabinet.

[0023] The above description of the embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A low-voltage distribution cabinet comprising a cabinet body (1), a cabinet door (4) hinged to the cabinet body (1), and a plurality of electrical components (2) installed in the cabinet body (1), characterized in that: The cabinet door (4) is provided with a processing module (3); Alarm module (7): the alarm module (7) comprises an audible and visual alarm mounted on the top surface of the cabinet (1); Detection module (6): the detection module (6) is installed on the top surface of the cabinet (1); The processing module (3) receives the data transmitted by the detection module (6), analyzes the transmitted image data, estimates the number of changes required to reach the outbreak point at the abnormal position, and compares it with the change number threshold to obtain the corresponding danger level; analyzes the gray value change of the grayscale processed image to obtain the corresponding danger level again; analyzes the transmitted temperature data and gas concentration data, determines the time required to reach the corresponding threshold based on the change rate of temperature and gas concentration, and calculates the corresponding danger level; obtains the equipment health of the cabinet (1) through weighted calculation of the four danger levels; if the equipment health is less than the corresponding threshold, generates a replacement warning signal, and transmits the replacement warning signal to the alarm module (7); Fire extinguishing module (5): the fire extinguishing module (5) is installed on the top surface of the cabinet (1).

2. A low-voltage distribution cabinet according to claim 1, characterized in that: The detection module (6) comprises a camera, a temperature sensor and a smoke sensor.

3. A low-voltage distribution cabinet according to claim 2, characterized in that: The fire extinguishing module (5) comprises a fire extinguisher.

4. A low-voltage distribution cabinet according to claim 3, characterized in that: The processing module (3) comprises a processor and a controller, and the processor is electrically connected to the camera, the temperature sensor and the smoke sensor, and the controller is electrically connected to the sound and light alarm and the fire extinguisher.

5. A low-voltage distribution cabinet according to claim 1, characterized in that: An intelligent detection component is provided inside the cabinet (1), and the intelligent detection component includes a detection module (6), a processing module (3) and an alarm module (7); A detection module (6) detects image data, temperature data, and gas concentration data inside the power distribution cabinet, and transmits the detected data to the processing module (3); The alarm module (7) receives the replacement warning signal transmitted by the processing module (3), then controls the warning light to emit an audible and visual alarm, and sends information to the staff through the transmission function of the module to remind the staff to perform the replacement operation of the distribution cabinet.

6. A low-voltage distribution cabinet according to claim 5, characterized in that: The steps of image data analysis in the processing module (3) are as follows: S1: Determine a preset grayscale contrast image corresponding to the camera shooting position according to the rotation angle between the camera and the set initial direction; S2: grayscale processing is performed on the image data at the corresponding time point according to the set time interval, and the grayscale processed image data is divided according to the size of the pixel block, the grayscale value of the grayscale image block after the division is calculated, and the grayscale value data of the grayscale image block obtained by calculation is converted into grayscale value data. Compare the grayscale value data at the corresponding position on the corresponding preset grayscale comparison chart Comparing the two images, if the absolute value of the grayscale value difference between the two exceeds the preset difference threshold of the grayscale comparison image, the corresponding position of the grayscale image block is determined to be an abnormal position; S3: If the adjacent pixel blocks at the abnormal position are also at abnormal positions, they are determined to be at the same abnormal position, and the area of ​​the abnormal position is is the number of grayscale image blocks at the abnormal position multiplied by the area of ​​a single grayscale image block, if , then the abnormal position is analyzed and marked for the number of changes. is the preset abnormal area threshold; if , then the total number of abnormal locations in the detected image data Perform statistics, if , then the abnormal position is analyzed and marked for the number of changes. is the preset scale factor, Summarize the total number of grayscale image blocks for the detection image data; S4: Retrieve historical data, and compare the grayscale image block at the abnormal position with the normal grayscale value data. , and the gray value data corresponding to the critical point of dangerous outbreak Acquire; the gray value change of the gray image block at the corresponding normal position within the adjacent acquisition time period Record and calculate the change threshold based on the gray value change ; Compare the grayscale value data of the grayscale image block at the change number analysis mark position with the grayscale value data at the corresponding position on the corresponding preset grayscale comparison map Compare and get the expected number of changes corresponding to the detected grayscale image block ,like , then it is determined that there is danger at the detection location, and the danger level , is the preset proportional coefficient; S5: The change in grayscale value of adjacent detection time points at the detection position To obtain, if the preset gray value at the corresponding position changes the threshold , then it is also determined that there is danger at the detection location, and the danger level .

7. A low-voltage distribution cabinet according to claim 6, characterized in that: The steps for analyzing the temperature and gas concentration data in the processing module (3) are as follows: K1: Establish a binary coordinate system using temperature data / gas concentration data and acquisition time. Draw corresponding coordinate points within the coordinate system, connect adjacent coordinate points, calculate the slope of the connecting lines, and compare the slopes of the temperature and gas concentration lines with the preset change thresholds of the corresponding items. K2: If the slope of the corresponding line is greater than the preset change threshold of the corresponding item, it is determined that there is danger, and the danger level is and Equal to the slope value of the corresponding item minus the preset change threshold of the corresponding item, divided by the preset change threshold of the corresponding item; K3: If the slope of the corresponding line is less than the preset change threshold of the corresponding item, the detection data of the current corresponding item is recorded, and the detection data before this time point is substituted into the formula ,get and The specific value of is the detection data of the corresponding item, is the detection time; then the formula can be used to determine the elapsed time After that, the detection data of the corresponding item will reach the preset warning threshold. If the preset response time , then it is determined that there is danger, the danger level and Equal to the time of the corresponding item Subtract the preset reaction time of the corresponding item , and divided by the preset reaction time of the corresponding item .

8. A low-voltage distribution cabinet according to claim 7, characterized in that: The steps for analyzing the equipment health in the processing module (3) are as follows: M1: Quantify the health of the equipment of the distribution cabinet according to the risk level. , 、 、 、 and are weight coefficients of the corresponding items respectively; when the health of the equipment is less than the preset health threshold of the equipment, it is determined that the safety hazard of continuing to use the equipment is large, and a replacement warning signal is generated and transmitted to the alarm module (7); M2: retrieve historical fault information, count the number of occurrences of the three types of abnormalities in the historical fault information, and then divide the number of occurrences of the three types of abnormalities by the total number of occurrences of the three types of abnormalities to obtain the corresponding weight coefficients 、 and ; M3: Obtain the accuracy of abnormal judgment by the two analysis methods of change number and gray value change. The accuracy of the corresponding analysis method is divided by the sum of the accuracies of the two analysis methods to obtain the corresponding weight coefficient. and .

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