Intelligent switch cabinet fault signal alarm device and alarm method based on pattern recognition

Abstract

The invention relates to the field of pattern recognition signal alarm devices, in particular to an intelligent switch cabinet fault signal alarm device and method based on pattern recognition, and the device comprises a temperature detection array which is used for continuously detecting and obtaining the temperature data of a plurality of regions in a switch cabinet; the infrared scanning module is used for starting infrared scanning to confirm a temperature abnormal area when the temperature data is abnormal, and obtaining coordinates of the temperature abnormal area; the photographing module is used for moving to the temperature abnormal area for photographing based on the temperature abnormal area coordinates to obtain an abnormal image; and the alarm module is used for identifying the fault type in the abnormal image to obtain alarm data and uploading the alarm data to the upper computer to give an alarm. According to the invention, the type of the fault of the switch cabinet can be quickly found and positioned by identifying the graph in the switch cabinet, so that maintenance personnel can timely feed back and process the fault, and the working efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of graphic recognition signal alarm devices, and particularly to an intelligent switchgear fault signal alarm device and an alarm method based on graphic recognition. Background Art

[0002] A switchgear is an electrical device used for power distribution, control, and protection in a power system. It includes components such as circuit breakers, disconnectors, fuses, instrument transformers, and surge arresters, which are used to cut off or connect circuits and quickly isolate the faulty part in case of a fault to ensure the safe operation of the power grid. According to the voltage level, switchgears can be divided into high-voltage switchgears and low-voltage switchgears.

[0003] Due to the aging, moisture absorption, damage of insulating materials, or the influence of the external environment, it may cause a short circuit between the internal live parts and the ground or between different phases, resulting in equipment damage or even fire.

[0004] There is a prior high and low voltage switchgear fault alarm device. A smoke sensor, a temperature sensor, and a voltage sensor are installed on the inner top of the upper installation chamber by screws, and the temperature sensor is located between the smoke sensor and the voltage sensor. One end of the voltage sensor is provided with a single-chip microcomputer and a wireless transceiver module through a fixing member. A cold air chamber is arranged at the bottom of the upper installation chamber, and air inlets are arranged on both sides of the outer housing, so that the situation inside the switchgear can be comprehensively detected by these sensors, and cooling can be carried out through the cold air chamber in case of an emergency.

[0005] In the above way, various sensors are fixed on one side of the switchgear, and only the overall situation inside the switchgear can be detected and alarmed. It is impossible to determine which switch has a problem, so the alarm issued is not convenient for maintenance personnel to quickly confirm and solve the problem, reducing the problem handling efficiency. Summary of the Invention

[0006] The purpose of the present invention is to provide an intelligent switchgear fault signal alarm device and an alarm method based on graphic recognition, aiming to quickly discover and locate the type of switchgear fault by recognizing the graphics inside the switchgear, so that it is convenient for maintenance personnel to give timely feedback and handle it, improving the work efficiency.

[0007] To achieve the above purpose, in the first aspect, the present invention provides an intelligent switchgear fault signal alarm device based on graphic recognition, including a switchgear body and a cabinet door. The cabinet door is arranged on one side of the switchgear body, and further includes a temperature detection array, an infrared scanning module, a photographing module, and an alarm module;

[0008] The temperature detection array is used to continuously detect and obtain the temperature data of multiple areas inside the switchgear;

[0009] The infrared scanning module is used to start infrared scanning to confirm the temperature abnormal area when the temperature data is abnormal, and obtain the coordinates of the temperature abnormal area;

[0010] The photographing module is used to move to the temperature abnormal area based on the coordinates of the temperature abnormal area for photographing, and obtain abnormal images;

[0011] The alarm module is used to identify the fault category in the abnormal image to obtain alarm data, and upload the alarm data to the host computer to issue an alarm.

[0012] Wherein, the photographing module is further used to start the smoke exhaust component to exhaust the thick smoke in the cabinet and then take a photograph to obtain an abnormal image if smoke is detected in the abnormal image.

[0013] Wherein, the temperature detection array includes a sensor unit, an initialization unit and a data acquisition unit;

[0014] The sensor unit is used to obtain temperature data;

[0015] The initialization unit is used to initialize and calibrate the sensor unit during use;

[0016] The data acquisition unit is used to obtain temperature data from multiple sensor units to obtain temperature data of multiple regions.

[0017] Wherein, the infrared scanning module includes a data abnormality judgment unit, an infrared scanner, an abnormal area extraction unit and a coordinate acquisition unit;

[0018] The data abnormality judgment unit is used to judge whether there is an abnormality based on the temperature data of multiple regions and a set threshold, and when an abnormality is detected, send a start command to the infrared scanner

[0019] The infrared scanner is used to perform a panoramic scan of the interior of the switch cabinet along a preset path after receiving the command

[0020] The abnormal area extraction unit is used to identify the high-temperature area in the image by using the temperature gradient algorithm

[0021] The coordinate acquisition unit is used to calculate the exact position coordinates of each identified temperature abnormal area in the scan view through image processing technology.

[0022] Wherein, the abnormal area extraction unit includes a noise removal subunit, a temperature calculation subunit, and a threshold judgment subunit;

[0023] The noise removal subunit is used to remove random noise in the image;

[0024] The temperature calculation subunit is configured to generate a corresponding temperature image according to temperature information, where the value of each pixel represents the actual temperature at that position;

[0025] The threshold judgment subunit is configured to distinguish a normal temperature area and a potential high-temperature area based on a set temperature gradient threshold.

[0026] Among them, the coordinate acquisition unit includes a boundary recognition subunit, a contour extraction subunit, a contour screening subunit, a center calculation subunit, and a mapping subunit;

[0027] The boundary recognition subunit is configured to obtain boundary data of the temperature anomaly area by applying the Canny edge detection operator;

[0028] The contour extraction subunit is configured to find all closed contour data in the boundary data;

[0029] The contour screening subunit is configured to screen the contour data based on the area to retain the temperature anomaly area;

[0030] The center calculation subunit is configured to calculate the geometric center for each screened temperature anomaly area;

[0031] The mapping subunit is configured to convert the calculated geometric center to the actual physical coordinate system to obtain the position coordinates.

[0032] Among them, the photographing module includes a coordinate acquisition unit, a path planning unit, a moving unit, and a photographing unit;

[0033] The coordinate acquisition unit is configured to acquire position coordinates;

[0034] The path planning unit is configured to plan a path from the current position to the target position according to the received coordinate information;

[0035] The moving unit is configured to control the photographing unit to move along the path to the specified temperature anomaly area;

[0036] The photographing unit is configured to send an instruction to trigger the camera to take a photo when the device arrives at and stabilizes at the predetermined position.

[0037] Among them, the photographing module further includes a smoke feature recognition unit, a power-off unit, a smoke exhaust unit, and a monitoring unit;

[0038] The smoke feature recognition unit is configured to identify smoke features by using image processing technology through the captured image;

[0039] The power-off unit is configured to cut off the relevant circuit after identifying smoke;

[0040] The exhaust unit is used to start the exhaust component to turn on the exhaust fan and the ventilation opening, accelerating air circulation;

[0041] The monitoring unit is used to continuously monitor the smoke concentration. When the smoke concentration drops below the preset value, it controls the camera to take pictures again.

[0042] In a second aspect, the present invention also provides an intelligent switch cabinet fault alarm method, including:

[0043] Continuously detect and obtain the temperature data of multiple areas inside the switch cabinet;

[0044] When the temperature data is abnormal, start infrared scanning to confirm the temperature abnormal area and obtain the coordinates of the temperature abnormal area;

[0045] Move to the temperature abnormal area based on the coordinates of the temperature abnormal area to take pictures and obtain abnormal images;

[0046] Identify the fault category in the abnormal image to obtain alarm data, and upload the alarm data to the host computer to issue an alarm.

[0047] An intelligent switchgear fault signal alarm device and alarm method based on pattern recognition according to the present invention, wherein a temperature detection array continuously monitors the temperature of different areas inside the switchgear. The array consists of multiple high-precision temperature sensors, which can real-time obtain the temperature change of each part inside the switchgear and transmit this data to the central control system. When the temperature detection array identifies that the temperature data of a certain area exceeds the preset safety range, the infrared scanning module will be automatically activated. This module is equipped with advanced infrared thermal imaging technology, which can quickly and accurately scan the entire inside of the switchgear without being affected by ambient light, and precisely locate the specific position of the temperature anomaly. The photographing module will accurately move to the designated position according to the received abnormal area coordinate information. This module is equipped with a high-definition camera, which can take pictures of the temperature anomaly area at close range, capturing clearer and more detailed abnormal images. These images not only record the appearance characteristics of the abnormal situation, but may also contain key details helpful for further analyzing the cause of the fault, such as the aging degree of components, signs of loose connection or short circuit, etc. The alarm module uses machine learning algorithms and a pre-stored fault mode database to automatically identify and classify the captured abnormal images. By comparing the features in the images with the known fault modes, the alarm module can determine the specific type of the fault, such as whether it is a poor electrical connection, insulation material damage or other types of hardware faults. After completing the identification of the fault category, the alarm module will generate corresponding alarm data, including information such as the fault type, severity and recommended measures, and upload this data to the host computer system. After receiving and processing these alarm data, the host computer will immediately issue an alarm to notify relevant personnel, so as to quickly discover and locate the type of switchgear fault, so that maintenance personnel can give timely feedback and handle it, improving work efficiency. Brief Description of the Drawings

[0048] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained according to these drawings.

[0049] Figure 1 It is a structural diagram of an intelligent switchgear fault signal alarm device based on pattern recognition according to the present invention.

[0050] Figure 2 It is a right-side structural diagram of an intelligent switchgear fault signal alarm device based on pattern recognition according to the present invention.

[0051] Figure 3 It is a structural diagram of the temperature detection array according to the present invention.

[0052] Figure 4 It is the structural diagram of the infrared scanning module of the present invention.

[0053] Figure 5 It is the structural diagram of the abnormal area extraction unit of the present invention.

[0054] Figure 6 It is the structural diagram of the coordinate acquisition unit of the present invention.

[0055] Figure 7 It is the structural diagram of the photographing module of the present invention.

[0056] Figure 8 It is the flowchart of a fault alarm method for an intelligent switch cabinet of the present invention.

[0057] Switch cabinet body 101, cabinet door 102, temperature detection array 103, infrared scanning module 104, photographing module 105, alarm module 106, sensor unit 107, initialization unit 108, data acquisition unit 109, data anomaly judgment unit 110, infrared scanner 111, abnormal area extraction unit 112, first coordinate acquisition unit 113, noise removal sub-unit 114, temperature calculation sub-unit 115, threshold judgment sub-unit 116, boundary recognition sub-unit 117, contour extraction unit 118, contour screening sub-unit 119, center calculation sub-unit 120, mapping sub-unit 121, second coordinate acquisition unit 122, path planning unit 123, moving unit 124, photographing unit 125, smoke feature recognition unit 126, power-off unit 127, smoke exhaust unit 128, monitoring unit 129. Specific implementation manners

[0058] The embodiments of the present invention will be described in detail below. The examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the accompanying drawings are exemplary and are intended to explain the present invention and should not be construed as limiting the present invention.

[0059] The first embodiment

[0060] Please refer to Figures 1 to 7, the present invention provides an intelligent switchgear fault signal alarm device based on graphic recognition, including a switchgear body 101 and a cabinet door 102. The cabinet door 102 is arranged on one side of the switchgear body 101, and further includes a temperature detection array 103, an infrared scanning module 104, a photographing module 105, and an alarm module 106. The temperature detection array 103 is used to continuously detect and obtain temperature data of multiple areas inside the switchgear. The infrared scanning module 104 is used to start infrared scanning to confirm the temperature abnormal area when the temperature data is abnormal, and obtain the coordinates of the temperature abnormal area. The photographing module 105 is used to move to the temperature abnormal area based on the coordinates of the temperature abnormal area to take pictures and obtain abnormal images. The alarm module 106 is used to identify the fault category in the abnormal image to obtain alarm data, and upload the alarm data to the upper computer to issue an alarm.

[0061] In this embodiment, the switchgear body 101 serves as the physical carrier of the entire system, providing an installation space and a protection structure for electrical equipment. The cabinet door 102 is arranged on one side of the switchgear body 101, which is not only used to enclose and protect internal components, but also equipped with an observation window or a display for the operator to view status information.

[0062] The temperature detection array 103 is composed of multiple high-precision temperature sensors, which are evenly distributed at different key positions inside the entire switchgear. These sensors can continuously collect temperature data of each area, providing basic information for subsequent analysis.

[0063] When any sensor in the temperature detection array 103 detects an abnormally high temperature, this infrared scanning module 104 will be activated. It uses infrared thermal imaging technology to comprehensively scan the inside of the switchgear, accurately locate the specific part with too high temperature, and generate corresponding coordinate data.

[0064] Once the infrared scanning module 104 locks the temperature abnormal area, the photographing module 105 will move to the target position according to the provided coordinates and use a high-definition camera to take a picture of this area.

[0065] The alarm module 106 receives data from the temperature detection array 103, the infrared scanning module 104, and the photographing module 105. It can analyze details in the photo, such as features like electric arcs, sparks, and smoke, to determine the specific fault type. After classification, the alarm module 106 will form a detailed alarm report, including but not limited to fault description, recommended measures, etc., and upload this information to the upper computer or cloud platform through a network interface to trigger an immediate alarm to notify relevant personnel.

[0066] The intelligent switchgear fault alarm device of the present invention realizes the comprehensive perception and intelligent management of the operation state of the switchgear by combining multi-sensing technology, image processing technology, and automation control technology. Compared with the traditional manual inspection method, it greatly improves the timeliness and accuracy of fault early warning and reduces the risks caused by misjudgment. At the same time, all operations are autonomously completed by the system, reducing the input of labor costs and improving work efficiency. It is applicable to various industrial facilities, data centers, substations and other fields and is an important tool to ensure the safe and stable operation of the power system.

[0067] The photographing module 105 is further configured to, if smoke is detected in the abnormal image, start the smoke exhaust component to exhaust the thick smoke in the cabinet and then take a photograph to obtain an abnormal image.

[0068] Once the photographing module 105 identifies the presence of smoke in the image, it will first suspend the current photographing task and send an emergency signal to the control system. After receiving this signal, the control system will quickly evaluate the situation and start the smoke exhaust component (Exhaust System) according to the preset safety protocol. The smoke exhaust component usually includes highly efficient ventilation fans, smoke filters, and possible emergency exhaust ports, etc., which work together to quickly reduce the smoke concentration in the cabinet. Only then will it instruct the photographing module 105 to resume the photographing task and obtain a clear and smokeless abnormal image. This process ensures the quality of the obtained image and provides reliable visual evidence for subsequent fault analysis.

[0069] The temperature detection array 103 includes a sensor unit 107, an initialization unit 108, and a data acquisition unit 109; the sensor unit 107 is configured to acquire temperature data; the initialization unit 108 is configured to initialize and calibrate the sensor unit 107 during use; the data acquisition unit 109 is configured to acquire temperature data from multiple sensor units 107 to obtain temperature data of multiple regions.

[0070] The sensor unit 107 is the basic component of the temperature detection array 103 and is composed of multiple high-precision temperature sensors distributed throughout the switchgear. Each sensor is responsible for monitoring the temperature at its location and can sample at a very high frequency to ensure that any slight temperature fluctuation can be captured in a timely manner.

[0071] The initialization unit 108 plays a crucial role every time the temperature detection array 103 is started or reconfigured. It is responsible for comprehensively checking all sensor units 107, setting parameters, and performing calibration procedures to ensure the measurement accuracy and reliability of the entire system.

[0072] After the system is powered on, the initialization unit 108 will automatically run a series of tests to verify whether the working status of each sensor is normal. According to the preset standards or user-defined parameters, adjust the working modes, sampling frequencies and other attributes of each sensor. Through the built-in reference source or external standard device, accurately calibrate the sensor to eliminate the drift error that may be brought by long-term use.

[0073] As the information center of the temperature detection array 103, the data acquisition unit 109 is responsible for collecting data from each sensor unit 107, and performing preliminary processing and integration on it to form a complete temperature distribution map. This enables the operator to intuitively understand the temperature conditions in different areas of the switchgear cabinet.

[0074] Through the above-expanded description, we can see that the temperature detection array 103 is not just a simple temperature measurement tool, but an intelligent system integrating advanced sensing technology, automatic control and data analysis capabilities. It can not only provide accurate and real-time temperature monitoring services, but also maintain the best performance through self-maintenance and optimization, thus providing a solid guarantee for the safe and stable operation of the power system. In addition, this modular design also facilitates future upgrades and technology expansions to adapt to the changing application requirements.

[0075] The infrared scanning module 104 includes a data anomaly judgment unit 110, an infrared scanner 111, an anomaly area extraction unit 112 and a coordinate acquisition unit; the data anomaly judgment unit 110 is used to judge whether there is an anomaly based on the temperature data of multiple areas and the set threshold, and when an anomaly is detected, send a start command to the infrared scanner 111;

[0076] The infrared scanner 111 is used to perform a panoramic scan of the interior of the switchgear cabinet according to a preset path after receiving the command. The anomaly area extraction unit 112 is used to identify the high-temperature areas in the image by using the temperature gradient algorithm;

[0077] The coordinate acquisition unit is used to calculate the accurate position coordinates of each identified temperature anomaly area in the scan view through image processing technology.

[0078] The data anomaly judgment unit 110 serves as the first line of defense in the entire infrared scanning process. The data anomaly judgment unit 110 is responsible for analyzing the temperature data of multiple regions from the temperature detection array 103 and conducting a preliminary screening for abnormal situations based on preset thresholds. It continuously receives and processes the real-time temperature data stream provided by the temperature detection array 103 to ensure that any potential anomalies are captured without omission. It compares the actual temperature of each region with the set upper and lower safety limits to identify situations beyond the normal range. Once a temperature anomaly is detected, it immediately triggers the alarm mechanism and sends a start command to the infrared scanner 111 to prepare for further detailed inspection.

[0079] The infrared scanner 111 is the core execution component of the infrared scanning module 104. After receiving the start command, it conducts a comprehensive panoramic scan of the interior of the switchgear according to the preset path to generate a detailed thermal imaging map. Specifically, advanced infrared detectors can be used to provide high-resolution thermal images that can clearly show the smallest temperature differences.

[0080] When the infrared scanner 111 completes the scan and generates the thermal imaging map, the abnormal area extraction unit 112 effectively distinguishes normal areas and abnormal hotspots based on the distribution characteristics of the temperature field by applying the temperature gradient algorithm to improve the recognition accuracy.

[0081] For each temperature abnormal area confirmed by the abnormal area extraction unit 112, the coordinate acquisition unit is responsible for calculating its precise position coordinates in the scan view to provide key reference information for subsequent operations.

[0082] The abnormal area extraction unit 112 includes a noise removal subunit 114, a temperature calculation subunit 115, and a threshold judgment subunit 116; the noise removal subunit 114 is used to remove random noise in the image; the temperature calculation subunit 115 is used to generate a corresponding temperature image based on temperature information, where the value of each pixel represents the actual temperature at that position; the threshold judgment subunit 116 is used to distinguish normal temperature areas and potential high-temperature areas based on the set temperature gradient threshold.

[0083] The noise removal subunit 114 is the first step in image preprocessing, aiming to eliminate or reduce random noise in the thermal imaging map, thereby improving the accuracy of subsequent analysis. Specifically, various digital filtering techniques, such as Gaussian filtering and median filtering, can be used to effectively remove high-frequency noise while maintaining the clarity of the image edges.

[0084] The temperature calculation subunit 115 is responsible for converting the original temperature information collected by the infrared scanner 111 into an intuitive temperature image, where the gray value of each pixel represents the actual temperature at the corresponding position.

[0085] Correct the measurement errors caused by environmental factors (such as atmospheric absorption, reflection, etc.) to ensure the accuracy of temperature readings. Convert the non-linear infrared signal into a linear temperature value and establish an accurate mapping relationship between temperature and pixel grayscale. Use a built-in or external standard blackbody source for temperature calibration to ensure the long-term stability of the system. Finally, generate a temperature distribution map where the color or grayscale of each pixel reflects the temperature at its corresponding position, facilitating visual analysis.

[0086] The threshold judgment sub-unit 116 divides the regions in the temperature image into a normal temperature region and a potential high-temperature region based on the set temperature gradient threshold for further analysis and processing. The threshold range can be dynamically adjusted according to historical data and real-time conditions to ensure that abnormal changes under different working conditions can be captured. Apply the temperature gradient algorithm to identify regions with sharp temperature changes, which are often the hotspots where faults occur.

[0087] The coordinate acquisition unit includes a boundary recognition sub-unit 117, a contour extraction unit 118, a contour screening sub-unit 119, a center calculation sub-unit 120, and a mapping sub-unit 121; the boundary recognition sub-unit 117 is used to obtain the boundary data of the temperature anomaly region by applying the Canny edge detection operator; the contour extraction unit 118 is used to find all closed contour data in the boundary data; the contour screening sub-unit 119 is used to screen the contour data based on the area to retain the temperature anomaly region; the center calculation sub-unit 120 is used to calculate the geometric center of each screened temperature anomaly region; the mapping sub-unit 121 is used to convert the calculated geometric center into the actual physical coordinate system to obtain the position coordinates.

[0088] As the first step of image processing, the boundary recognition sub-unit 117 is responsible for applying the Canny edge detection operator to extract the boundary data of the temperature anomaly region. Using the classic Canny algorithm and combining multi-scale gradient information can effectively capture the boundary of the temperature anomaly region while suppressing noise interference. Automatically adjust the high and low thresholds according to the local characteristics of the image to ensure clear boundaries can be obtained under different lighting and background conditions.

[0089] The contour extraction unit 118 performs connectivity analysis on the boundary data, combines adjacent boundary points into closed contours, and ensures that each anomaly region is completely depicted. Adopt methods such as chain coding or Freeman chain code to trace along the boundary points to generate a continuous contour path for subsequent processing.

[0090] The contour screening subunit 119 screens all the extracted contour data, retains the contours that truly represent the temperature anomaly regions based on the area size, and excludes non-critical or misjudged contours. A reasonable area threshold range is set according to the actual application scenario, and only the contours with an area exceeding a certain limit are retained, while the tiny pseudo-contours that may be caused by noise are excluded.

[0091] Combined with shape factors (such as circularity, aspect ratio, etc.) for comprehensive evaluation, further screen out the anomaly regions that meet the expected characteristics.

[0092] The center calculation subunit 120 calculates the geometric center for each temperature anomaly region after screening, providing an important reference point for the final position determination. The centroid formula is used to calculate the average value of all pixel coordinates within each contour to obtain the specific position of the geometric center.

[0093] The mapping subunit 121 converts the calculated geometric center into the actual physical coordinate system, thereby obtaining the position coordinates of the temperature anomaly region, providing precise guidance for subsequent operations and maintenance. Geometric transformation techniques such as affine transformation and perspective transformation are applied to convert the two-dimensional image coordinates into three-dimensional space coordinates, considering the posture and position factors of the scanner to ensure the authenticity and accuracy of the coordinates. Then, through preset reference points or markers, the precise matching between the image coordinate system and the actual physical coordinate system is achieved to eliminate systematic errors.

[0094] The photographing module 105 includes a coordinate acquisition unit, a path planning unit 123, a moving unit 124, and a photographing unit 125; the coordinate acquisition unit is used to acquire position coordinates; the path planning unit 123 is used to plan a path from the current position to the target position according to the received coordinate information; the moving unit 124 is used to control the photographing unit 125 to move along the path to the specified temperature anomaly region; the photographing unit 125 is used to send an instruction to trigger the camera to take a photo when the device arrives at and stabilizes at the predetermined position.

[0095] The coordinate acquisition unit receives the position coordinates of the temperature anomaly region from the infrared scanning module 104 and converts them into a format suitable for use by the photographing module 105.

[0096] Based on the received coordinate information, the path planning unit 123 uses an algorithm to plan a safe and efficient path from the current position to the target position. Specifically, a two-dimensional model inside the switchgear is constructed. The A* algorithm is applied to comprehensively consider distance and time factors to select the optimal path.

[0097] The moving unit 124 is responsible for controlling the photographing unit 125 to move smoothly along the path provided by the path planning unit 123 to the specified temperature anomaly region.

[0098] After reaching and stabilizing at the predetermined position, the photographing unit 125 sends an instruction to trigger the camera to take a high-quality photograph, recording the specific situation of the temperature anomaly area. It is equipped with a high-resolution camera to provide clear and detailed image quality for subsequent analysis.

[0099] The photographing module 105 further includes a smoke feature recognition unit 126, a power-off unit 127, a smoke exhaust unit 128, and a monitoring unit 129;

[0100] The smoke feature recognition unit 126 is used to recognize smoke features by using image processing technology on the photographed images; the power-off unit 127 is used to cut off relevant circuits after recognizing smoke; the smoke exhaust unit 128 is used to start the smoke exhaust component to open the exhaust fan and ventilation opening to accelerate air circulation; the monitoring unit 129 is used to continuously monitor the smoke concentration, and when the smoke concentration drops below a preset value, control the camera to take a photograph again.

[0101] The smoke feature recognition unit 126 is responsible for recognizing smoke features by taking images and using advanced image processing technology.

[0102] Combining visible light and infrared imaging to enhance the accuracy of smoke recognition, especially in complex backgrounds, it can effectively distinguish smoke from other objects. Applying deep learning models such as convolutional neural networks (CNNs), after being trained with a large number of samples, it can automatically recognize different types of smoke features, such as color, shape, motion pattern, etc. Optimizing the algorithm structure to ensure rapid processing of each frame of image, achieving real-time smoke detection and reducing latency. Dynamically adjusting recognition parameters according to changes in ambient light to improve the robustness and adaptability of the system.

[0103] When the smoke feature recognition unit 126 confirms the existence of smoke, the power-off unit 127 will immediately cut off relevant circuits to prevent the expansion of faults or the occurrence of more serious accidents. Once smoke features are detected, the power-off unit 127 will cut off the power supply within milliseconds to ensure the elimination of electrical risks in the first place.

[0104] The smoke exhaust unit 128 is responsible for starting the smoke exhaust component, opening the exhaust fan and ventilation opening to accelerate air circulation, and quickly reducing the smoke concentration inside the cabinet.

[0105] The monitoring unit 129 continuously monitors the smoke concentration. When the smoke concentration drops below a preset value, it controls the camera to take a photograph again to ensure clear and smokeless abnormal images are obtained.

[0106] From the above-expanded description, it can be seen that the photographing module 105 is not just a simple image capture tool, but a comprehensive security system integrating advanced smoke recognition, power-off protection, smoke exhaust treatment, and continuous monitoring capabilities. It can not only quickly take measures when detecting emergencies such as smoke to ensure system safety, but also provide high-quality fault image records, greatly improving the efficiency and accuracy of fault troubleshooting.

[0107] Second Embodiment

[0108] Please refer to Figure 8 , the present invention also provides an intelligent switchgear fault alarm method, including:

[0109] S201 Continuously detect and obtain temperature data of multiple areas inside the switchgear;

[0110] The system will continuously monitor and obtain the temperature information of each key area inside the switchgear. This includes but is not limited to the ambient temperature around easily heat-generating components such as circuit breakers, bus connections, and insulators. Through high-precision temperature sensors deployed in these areas, the current thermal state can be timely and accurately reflected, providing basic data support for subsequent anomaly detection.

[0111] S202 When the temperature data is abnormal, start infrared scanning to confirm the temperature abnormal area and obtain the coordinates of the temperature abnormal area;

[0112] Once it is detected that the temperature in a certain or certain areas exceeds the preset safety range, it is considered that a temperature abnormal situation has occurred. At this time, the system will automatically activate the built-in or external infrared thermal imaging device to precisely scan the suspected problem area. Infrared scanning can not only verify the authenticity of the temperature anomaly, but also further determine the specific location of the anomaly and record it in the form of coordinates for subsequent processing.

[0113] S203 Move to the temperature abnormal area based on the coordinates of the temperature abnormal area to take a photo and obtain an abnormal image;

[0114] According to the coordinates of the temperature abnormal area obtained in the previous step, the system will guide one or more small mobile devices with cameras (such as robotic arms or drones) to the designated location. After arriving, these devices will take high-definition photos of the abnormal area, thereby obtaining clear pictures of the abnormal situation. The advantage of this is that it can intuitively display the situation at the fault site and provide important reference for technicians.

[0115] S204 Identify the fault category in the abnormal image to obtain alarm data, and upload the alarm data to the upper computer to issue an alarm.

[0116] The obtained abnormal images will be sent into a fault diagnosis model constructed based on deep learning algorithms for analysis. This model has been trained with a large number of samples and can quickly and accurately identify different types of fault features, such as overheating, arc discharge, mechanical damage, etc., and generate detailed alarm data accordingly. Subsequently, these alarm messages, together with the original images, are uploaded to the host computer system through the network, which is responsible for sending alarm notifications to relevant operation and maintenance personnel to ensure that they can take appropriate measures to solve the problem in a timely manner and avoid the expansion of potential risks.

[0117] The above-disclosed is only a preferred embodiment of the present invention. Of course, it cannot be used to limit the scope of the rights of the present invention. Those of ordinary skill in the art can understand all or part of the processes of implementing the above embodiments, and the equivalent changes made according to the claims of the present invention still fall within the scope covered by the invention.

Claims

1. An intelligent switchgear fault signal alarm device based on graphic recognition, comprising a switchgear body and a cabinet door, the cabinet door being arranged on one side of the switchgear body, characterized in that, it further comprises a temperature detection array, an infrared scanning module, a photographing module and an alarm module; the temperature detection array is used for continuously detecting and obtaining temperature data of multiple areas inside the switchgear; the infrared scanning module is used for starting infrared scanning to confirm the temperature abnormal area when the temperature data is abnormal, and obtaining the coordinates of the temperature abnormal area; the photographing module is used for moving to the temperature abnormal area based on the coordinates of the temperature abnormal area to take pictures and obtain abnormal images; the alarm module is used for identifying the fault category in the abnormal image to obtain alarm data, and uploading the alarm data to the host computer to issue an alarm.

2. An intelligent switchgear fault signal alarm device based on graphic recognition according to claim 1, characterized in that, the photographing module is further used for if it detects smoke in the abnormal image, starting a smoke exhaust component to exhaust the thick smoke in the cabinet and then taking pictures to obtain abnormal images.

3. An intelligent switchgear fault signal alarm device based on graphic recognition according to claim 2, characterized in that, the temperature detection array comprises a sensor unit, an initialization unit and a data acquisition unit; the sensor unit is used for obtaining temperature data; the initialization unit is used for initializing and calibrating the sensor unit during use; the data acquisition unit is used for obtaining temperature data from multiple sensor units to obtain temperature data of multiple areas.

4. An intelligent switchgear fault signal alarm device based on graphic recognition according to claim 3, characterized in that, the infrared scanning module comprises a data abnormality judgment unit, an infrared scanner, an abnormal area extraction unit and a coordinate acquisition unit; the data abnormality judgment unit is used for judging whether there is an abnormality based on the temperature data of multiple areas and a set threshold, and when an abnormality is detected, sending a start command to the infrared scanner; the infrared scanner is used for panoramically scanning the inside of the switchgear along a preset path after receiving the command; the abnormal area extraction unit is used for identifying the high-temperature area in the image by using a temperature gradient algorithm; the coordinate acquisition unit is used for calculating the precise position coordinates of each identified temperature abnormal area in the scanning view through image processing technology.

5. An intelligent switchgear fault signal alarm device based on graphic recognition according to claim 4, characterized in that, the abnormal area extraction unit comprises a noise removal subunit, a temperature calculation subunit and a threshold judgment subunit; the noise removal subunit is used for removing random noise in the image; the temperature calculation subunit is used for generating a corresponding temperature image according to temperature information, wherein the value of each pixel represents the actual temperature at that position; the threshold judgment subunit is used for distinguishing the normal temperature area and the potential high-temperature area based on a set temperature gradient threshold.

6. An intelligent switchgear fault signal alarm device based on graphic recognition according to claim 5, characterized in that, The coordinate acquisition unit includes a boundary recognition subunit, a contour extraction unit, a contour screening subunit, a center calculation subunit, and a mapping subunit; The boundary recognition subunit is configured to obtain the boundary data of the temperature anomaly region by applying the Canny edge detection operator; The contour extraction unit is configured to find all closed contour data in the boundary data; The contour screening subunit is configured to screen the contour data based on the area to retain the temperature anomaly region; The center calculation subunit is configured to calculate the geometric center of each screened temperature anomaly region; The mapping subunit is configured to convert the calculated geometric center to the actual physical coordinate system to obtain the position coordinates.

7. The intelligent switchgear fault signal alarm device based on graphic recognition according to claim 6, wherein The photographing module includes a coordinate acquisition unit, a path planning unit, a moving unit, and a photographing unit; The coordinate acquisition unit is configured to acquire position coordinates; The path planning unit is configured to plan a path from the current position to the target position according to the received coordinate information; The moving unit is configured to control the photographing unit to move along the path to the specified temperature anomaly region; The photographing unit is configured to send an instruction to trigger the camera to take a picture when the device arrives at and stabilizes at the predetermined position.

8. The intelligent switchgear fault signal alarm device based on graphic recognition according to claim 7, wherein The photographing module further includes a smoke feature recognition unit, a power-off unit, a smoke exhaust unit, and a monitoring unit; The smoke feature recognition unit is configured to recognize the smoke feature by using image processing technology through the captured image; The power-off unit is configured to cut off the relevant circuit after the smoke is recognized; The smoke exhaust unit is configured to start the smoke exhaust component to turn on the exhaust fan and the ventilation opening to accelerate the air circulation; The monitoring unit is configured to continuously monitor the smoke concentration, and when the smoke concentration drops below the preset value, control the camera to take pictures again.

9. A method for fault alarm of an intelligent switchgear cabinet, which uses an intelligent switchgear cabinet fault signal alarm device based on graphic recognition described in any one of claims 1 to 8, is characterized in that, Including: Continuously detect and acquire the temperature data of multiple regions inside the switchgear; When the temperature data is abnormal, start the infrared scan to confirm the temperature anomaly region and obtain the coordinates of the temperature anomaly region; Move to the temperature anomaly region based on the coordinates of the temperature anomaly region to take pictures and obtain abnormal images; Identify the fault category in the abnormal image to obtain alarm data, and upload the alarm data to the upper computer to issue an alarm.

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