Charging alarm method and device based on intelligent charging cabinet, charging cabinet, equipment and medium

Abstract

The invention discloses a charging alarm method and device based on an intelligent charging cabinet, the charging cabinet, equipment and a medium, and belongs to the field of charging monitoring, and the method comprises the steps: obtaining real-time charging parameters of an electric power tool when the electric power tool is placed in the intelligent charging cabinet for charging, the real-time charging parameters comprise charging power, charging voltage, charging current and real-time temperature data; if it is determined that the charging state of the electric power tool is not fully charged based on the charging power, the charging voltage, the charging current and the real-time temperature data are adopted for detection processing, and a detection result is obtained; and if the detection result of the charging voltage is abnormal, the detection result of the charging current is abnormal or the detection result of the real-time temperature data is abnormal, triggering alarm processing and carrying out power-off processing. According to the invention, each charged tool is monitored in real time, so that the condition of over-charging or continuous charging can be avoided, the safety risk of spontaneous combustion of the tool in the charging process can be reduced, and the charging safety is improved.

Description

Technical Field

[0001] This invention relates to the technical field of charging monitoring, and in particular to a charging alarm method, device, charging cabinet, equipment, and medium based on an intelligent charging cabinet. Background Technology

[0002] With the development of technology, more and more power generation tools are equipped with batteries, such as testers, hydraulic torque wrenches, torque wrenches, and electric wrenches. Power generation tools play a crucial role in power construction and live-line work, not only ensuring construction safety but also improving construction efficiency.

[0003] During use, the battery may run out of power. To ensure that the equipment can be used normally during construction, one common method is to collect the power generation tools of the construction workers after each use and then charge them using a household power strip for subsequent construction use.

[0004] However, the above method has the following technical problems: Many power production tools now use lithium batteries, which are subject to impacts, high temperatures and rain during long-term use, which may lead to safety risks such as spontaneous combustion during charging; moreover, there may be overcharging or continuous charging during the charging process, which may cause the equipment to heat up and further increase the charging risk. Summary of the Invention

[0005] This invention provides a charging alarm method, device, charging cabinet, equipment, and medium based on an intelligent charging cabinet, which can solve the technical problem of safety risks in charging power production tools in the prior art.

[0006] A first aspect of this invention provides a charging alarm method based on a smart charging cabinet, the method comprising: When power tools are placed in a smart charging cabinet for charging, real-time charging parameters of the power tools are acquired, including: charging power, charging voltage, charging current and real-time temperature data. If the charging status of the power tool is determined to be not fully charged based on the charging power, the charging voltage, the charging current, and the real-time temperature data are used for detection processing to obtain the detection result. If the detection result of the charging voltage is abnormal, the detection result of the charging current is abnormal, or the detection result of the real-time temperature data is abnormal, an alarm is triggered and the power is cut off.

[0007] This invention, by real-time monitoring of each charging tool, can not only avoid overcharging or continuous charging, but also reduce the safety risk of spontaneous combustion of tools during the charging process, thereby improving charging safety.

[0008] In conjunction with the first aspect, in one implementation, the real-time temperature data is a two-dimensional raw temperature matrix obtained by detecting the entire field of view using an infrared dual-light camera. The real-time temperature data is used for detection and processing to obtain detection results, including: The real-time temperature data is preprocessed to obtain a processed temperature matrix. The preprocessing includes: non-uniformity correction, bad pixel replacement, temperature calibration, and noise reduction filtering. A thermal image is generated based on the temperature matrix. When it is determined that there is any abnormal pixel in the thermal image, the detection result is determined to be abnormal.

[0009] In conjunction with the first aspect, in one implementation, the step of generating a thermal image based on the processed temperature matrix, and determining the detection result as abnormal when it is determined that any abnormal pixel exists in the thermal image, includes: The temperature matrix is ​​linearly mapped to a preset image grayscale range to obtain a temperature grayscale image. A thermal image is obtained by performing pseudo-color mapping and image enhancement on the grayscale value of each pixel in the temperature grayscale image; The real-time temperature value corresponding to each pixel in the thermal image is determined, and whether the pixel is an abnormal pixel is determined based on the real-time temperature value and a preset temperature threshold. The preset temperature threshold is the maximum or average temperature value in the region of interest of the image preset by the user. If it is determined that there are abnormal pixels in the thermal image, then the detection result is determined to be abnormal.

[0010] In conjunction with the first aspect, in one implementation, determining whether a pixel is an abnormal pixel based on the real-time temperature value and a preset temperature threshold includes: If the difference between the real-time temperature value and the preset temperature threshold is greater than the preset temperature difference, then the pixel is determined to be an abnormal pixel. or; If the real-time temperature value is greater than the preset temperature threshold, the pixel is determined to be an abnormal pixel. or; The temperature rise rate is calculated using the real-time temperature value and a preset temperature threshold. If the temperature rise rate is greater than the preset rate threshold, the pixel is determined to be an abnormal pixel.

[0011] In conjunction with the first aspect, in one implementation, after the step of generating a thermal image based on the processed temperature matrix, and determining that the detection result is abnormal when it is determined that any abnormal pixel exists in the thermal image, the method further includes: The abnormal pixel and its adjacent pixels are binarized to obtain a binarized point. Anomaly labels are assigned to the binarized points, and the pixels of the labels are clustered to obtain clustered image regions. The clustered image regions are filtered to obtain thermal patch images, which are then visualized.

[0012] A second aspect of this invention provides a charging alarm device based on a smart charging cabinet, the device comprising: The acquisition module is used to acquire real-time charging parameters of the power tools when they are placed in the smart charging cabinet for charging. The real-time charging parameters include: charging power, charging voltage, charging current and real-time temperature data. The detection module is used to perform detection processing using the charging voltage, the charging current, and the real-time temperature data respectively, when the charging status of the power tool is determined to be not fully charged based on the charging power, to obtain the detection result. An alarm module is used to trigger an alarm and cut off power if the detection result of the charging voltage is abnormal, the detection result of the charging current is abnormal, or the detection result of the real-time temperature data is abnormal.

[0013] A third aspect of this invention provides an intelligent charging cabinet, which is applicable to the charging alarm method based on the intelligent charging cabinet as described above. The intelligent charging cabinet is provided with several layers of charging platforms, and each layer of the charging platform is provided with an infrared dual-light camera and several charging sockets. The smart charging cabinet has a display screen and a movable door on its side.

[0014] Compared to existing technologies, the present invention provides a charging alarm method, device, charging cabinet, equipment, and medium based on an intelligent charging cabinet. Its advantages lie in the following: When power tools are placed in the intelligent charging cabinet for charging, the invention can acquire charging power, charging voltage, charging current, and real-time temperature data of the power tools. If the charging power determines that the power tool is not fully charged, the charging voltage, charging current, and real-time temperature data are used for detection processing to obtain the detection results. If any detection result is abnormal, an alarm is triggered and power is cut off. By monitoring each charging tool in real time, the present invention can not only avoid overcharging or continuous charging but also reduce the safety risk of spontaneous combustion of tools during charging, thus improving charging safety. Attached Figure Description

[0015] Figure 1 This is a flowchart illustrating a charging alarm method based on an intelligent charging cabinet according to an embodiment of the present invention. Figure 2 This is a schematic diagram of a detection process based on a temperature data matrix provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of a process for determining abnormal pixels based on real-time temperature values ​​and preset temperature thresholds, provided by an embodiment of the present invention. Figure 4 This is an operation flowchart of a charging alarm method based on an intelligent charging cabinet provided in an embodiment of the present invention; Figure 5 This is a schematic diagram of the structure of a charging alarm device based on an intelligent charging cabinet according to an embodiment of the present invention; Figure 6 This is a front view of an intelligent charging cabinet provided in an embodiment of the present invention; Figure 7 This is a rear view of an intelligent charging cabinet provided in an embodiment of the present invention; Figure 8 This is a side view of an intelligent charging cabinet provided in an embodiment of the present invention. Detailed Implementation

[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] With the development of technology, more and more power generation tools are equipped with batteries, such as testers, hydraulic torque wrenches, torque wrenches, and electric wrenches. Power generation tools play a crucial role in power construction and live-line work, not only ensuring construction safety but also improving construction efficiency.

[0018] During use, the battery may run out of power. To ensure that the equipment can be used normally during construction, one common method is to collect the power generation tools of the construction workers after each use and then charge them using a household power strip for subsequent construction use.

[0019] However, the above method has the following technical problems: Many power production tools now use lithium batteries, which are subject to impacts, high temperatures and rain during long-term use, which may lead to safety risks such as spontaneous combustion during charging; moreover, there may be overcharging or continuous charging during the charging process, which may cause the equipment to heat up and further increase the charging risk.

[0020] To address the aforementioned issues, the following detailed embodiments will be used to illustrate and explain a charging alarm method, device, charging cabinet, equipment, and medium based on an intelligent charging cabinet, as provided in this application.

[0021] To address the safety risks associated with charging electrical power generation equipment using existing technologies, and with reference to... Figure 1 The diagram shows a flowchart of a charging alarm method based on an intelligent charging cabinet according to an embodiment of the present invention.

[0022] The charging alarm method based on the intelligent charging cabinet is applicable to intelligent charging cabinets. Users can place various tools in the intelligent charging cabinet for charging. The intelligent charging cabinet monitors the charging tools in real time and triggers an alarm when there is a safety risk or abnormality, thereby reducing the safety risk of tools spontaneously combusting during the charging process; it can also reduce the risk of equipment overheating due to overcharging or continuous charging.

[0023] As an example, the charging alarm method based on the smart charging cabinet may include: S11. When the power tool is placed in the smart charging cabinet for charging, the real-time charging parameters of the power tool are obtained, wherein the real-time charging parameters include: charging power, charging voltage, charging current and real-time temperature data.

[0024] Users can place various tools in the smart charging cabinet for charging. When the power tools are charging in the smart charging cabinet, the real-time charging parameters of the power tools are obtained. The real-time charging parameters include: charging power, charging voltage, charging current and real-time temperature data.

[0025] Specifically, the smart charging cabinet adopts an integrated, aesthetically pleasing, and user-friendly design. The smart charging cabinet has several shelves, each with multiple charging ports, allowing for convenient placement, arrangement, and charging of various sizes and models of tools, batteries, power banks, etc.

[0026] Each charging port can detect the charging power, charging voltage, and charging current during the charging process and display them on the working screen. When the battery is fully charged, the plug will automatically disconnect the power to avoid prolonged charging and reduce safety risks.

[0027] It can also obtain the tool's real-time temperature, providing real-time temperature data. Based on the temperature, it can determine whether there is a risk of spontaneous combustion or high temperature.

[0028] S12. If the charging status of the power tool is determined to be not fully charged based on the charging power, the charging voltage, the charging current, and the real-time temperature data are used for detection processing to obtain the detection result.

[0029] In one operating mode, when the socket is idle or fully charged, if the socket power is >3W, the socket status is changed to charging, the power tool's charging status is determined to be not fully charged, and the socket's last charging time is updated. If the socket power is <3W, the socket status is determined to be idle or fully charged.

[0030] If a socket has no output power and the last charging time is within two minutes, it is considered to be in a fully charged state; if the last charging time exceeds two minutes, the socket is considered to be in an idle state.

[0031] The normal voltage range of the charging socket is between 110V and 250V, and the current is within 10A.

[0032] When the charging socket is charging, if the charging voltage is detected to be outside the normal range, it can be determined that the charging voltage detection and processing is abnormal. Similarly, if the charging current is detected to be outside the normal range, it can be determined that the charging voltage detection and processing is abnormal.

[0033] It should be noted that the normal current range of each device is determined by its own power, and the power of each device is not fixed, so the range of the single current of the device is an unknown range.

[0034] If the real-time temperature data is outside the preset temperature range when the charging socket is charging, it can be determined that the charging voltage detection and processing is abnormal.

[0035] In an optional embodiment, the real-time temperature data is a two-dimensional raw temperature matrix obtained by detecting the entire field of view using an infrared dual-light camera.

[0036] Reference Figure 2 The diagram illustrates a flow chart of a detection process based on a temperature data matrix, according to an embodiment of the present invention.

[0037] As an example, the detection and processing of the real-time temperature data to obtain the detection result may include the following sub-steps: S21. The real-time temperature data is preprocessed to obtain a processed temperature matrix. The preprocessing includes: non-uniformity correction, bad pixel replacement, temperature calibration, and noise reduction filtering.

[0038] S22. Generate a thermal image based on the processed temperature matrix. When it is determined that there is any abnormal pixel in the thermal image, the detection result is determined to be abnormal.

[0039] In one embodiment, the raw data output by the infrared camera is a two-dimensional temperature data matrix (or "radiation data"). Each point in the matrix corresponds to a detector element on the sensor, and its value represents the apparent temperature of the object (charging tool) corresponding to that point in the field of view.

[0040] In one embodiment, the real-time temperature data can be preprocessed to obtain a processed temperature matrix. The preprocessing includes: non-uniformity correction, bad pixel replacement, temperature calibration, and noise reduction filtering.

[0041] Non-uniformity correction can eliminate response differences between individual detectors. Defect replacement can repair data from faulty pixels. Temperature calibration converts voltage signals into temperature values. Noise reduction filtering can suppress noise through time-domain or spatial-domain filtering.

[0042] Next, a thermal image can be generated using the temperature matrix. Then, the temperature of the tool within the thermal image is used for detection to determine if any abnormal pixel exists. If any abnormal pixel is found in the thermal image, the detection result is determined to be abnormal.

[0043] As an example, the step of generating a thermal image based on the processed temperature matrix, and determining the detection result as abnormal when any abnormal pixel is found in the thermal image, may include the following sub-steps: S221. Linearly map the processed temperature matrix to a preset image grayscale range to obtain a temperature grayscale image.

[0044] S222. Perform pseudo-color mapping and image enhancement on each pixel of the temperature grayscale image to obtain a thermal image.

[0045] S223. Determine the real-time temperature value corresponding to each pixel in the thermal image, and determine whether the pixel is an abnormal pixel based on the real-time temperature value and a preset temperature threshold, wherein the preset temperature threshold is the maximum or average temperature value within the region of interest in the image preset by the user.

[0046] S224. If it is determined that there are abnormal pixels in the thermal image, then the detection result is determined to be abnormal.

[0047] The process of generating a thermal image involves linearly mapping the temperature matrix to a preset image grayscale range to obtain a temperature grayscale image. Specifically, the temperature matrix can be linearly mapped to an image grayscale range (e.g., 0-255) to obtain a temperature grayscale image.

[0048] Pseudo-color mapping is performed on the grayscale value of each pixel in the temperature grayscale image. This pseudo-color mapping uses a pseudo-color table to look up the grayscale values ​​and assigns different colors. Image enhancement can then be performed to obtain the thermal image. Image enhancement can include contrast stretching, sharpening, and other methods to optimize visual effects.

[0049] Each pixel in the constructed thermal image corresponds to a temperature, and each pixel represents a temperature value. The temperature value of each pixel within the thermal image can be determined, yielding the real-time temperature value of each pixel. Then, based on a preset temperature threshold and the real-time temperature value of each pixel, it can be determined whether the pixel is an abnormal pixel.

[0050] If the pixel is determined to be an abnormal pixel, it can be determined that there is at least one abnormal pixel in the thermal image, and the detection result of the real-time temperature data is determined to be abnormal.

[0051] The preset temperature threshold is the maximum or average temperature within the region of interest in the image, preset by the user.

[0052] Specifically, a calibrated M*N temperature matrix is ​​obtained (each pixel represents a temperature value).

[0053] It can acquire user-preset regions of interest (ROIs) to limit the analysis scope. Temperature statistics (such as calculating maximum / average temperature) can be performed within the ROI. The calculated maximum / average temperature within the ROI can be used to dynamically adjust thresholds (referencing the average temperature of the reference area when setting relative thresholds).

[0054] Reference Figure 3 The diagram illustrates a flowchart of a process for determining abnormal pixels based on real-time temperature values ​​and preset temperature thresholds, according to an embodiment of the present invention.

[0055] As an example, determining whether a pixel is an abnormal pixel based on the real-time temperature value and a preset temperature threshold may include the following sub-steps: S2231. If the difference between the real-time temperature value and the preset temperature threshold is greater than the preset temperature difference, then the pixel is determined to be an abnormal pixel.

[0056] or; S2232. If the real-time temperature value is greater than the preset temperature threshold, then the pixel is determined to be an abnormal pixel.

[0057] or; S2233. Calculate the temperature rise rate using the real-time temperature value and the preset temperature threshold. If the temperature rise rate is greater than the preset rate threshold, then determine the pixel as an abnormal pixel.

[0058] In one embodiment, threshold rules (absolute threshold, relative temperature difference, temperature rise rate) can be applied to identify abnormal pixels.

[0059] Specifically, if the difference between the real-time temperature value and the preset temperature threshold is greater than the preset temperature difference, the pixel is determined to be an abnormal pixel. Alternatively, if the real-time temperature value is greater than the preset temperature threshold, the pixel is determined to be an abnormal pixel. Alternatively, the temperature rise rate is calculated using the real-time temperature value and the preset temperature threshold, and if the temperature rise rate is greater than a preset rate threshold, the pixel is determined to be an abnormal pixel.

[0060] Specifically, multiple independent judgments can be used, and any rule triggered will be marked as an abnormal pixel (logical "OR" relationship) to improve sensitivity.

[0061] To facilitate users in viewing temperature anomalies, after the step of generating a thermal image based on the processed temperature matrix and determining that the detection result is abnormal when any abnormal pixel is found in the thermal image, the method may further include the following sub-steps: S23. Perform binarization processing on the abnormal pixel and the adjacent pixels of the abnormal pixel to obtain a binarized point.

[0062] S24. Assign abnormal labels to the binarized points and cluster the pixels of the labels to obtain clustered image regions.

[0063] S25. Perform region filtering on the clustered image region to obtain a hot patch image, and visualize the hot patch image.

[0064] Specifically, abnormal pixels and their adjacent pixels are binarized to obtain binarized points. Binarization marks abnormal pixels and their adjacent pixels as 1, and all others as 0.

[0065] Next, anomaly labels are assigned to the binarized points, and the pixels of the labels are clustered to obtain clustered image regions. Specifically, the binary matrix can be traversed, and the same label can be assigned to each binarized point.

[0066] Finally, region filtering can be performed on the clustered image regions to obtain hot patch images, which can then be visualized. Region filtering can remove isolated small regions caused by noise based on factors such as area and shape.

[0067] By using connected component analysis, discrete anomalous pixels are aggregated into "hot spots" to obtain hot spot images.

[0068] Finally, the thermal patch image can be visualized and an alarm can be output, specifically a visual selection and an alarm signal.

[0069] Generating thermal patch images can avoid false alarms (such as a single anomaly point being noise), and by aggregating them, the actual range and location of the abnormal area can be determined, providing a spatial basis for the selection alarm, which meets the actual engineering needs.

[0070] S13. If the detection result of the charging voltage is abnormal, the detection result of the charging current is abnormal, or the detection result of the real-time temperature data is abnormal, an alarm is triggered and a power-off is performed.

[0071] If the charging voltage detection result is abnormal, the charging current detection result is abnormal, or the real-time temperature data detection result is abnormal, an alarm will be triggered and the power will be cut off.

[0072] Based on this, if the charging voltage detection result is abnormal or the charging current detection result is abnormal, the charging socket will perform power-off protection.

[0073] The charging power, voltage, and current of each charging port can be displayed on the working screen. When the battery is fully charged, the plug will automatically disconnect the power to avoid long-term charging and reduce safety risks.

[0074] When the real-time temperature data shows an abnormality, the smart charging cabinet can cut off the power to the corresponding charging port, display alarm information on the control screen, and send alarms via voice and SMS.

[0075] Reference Figure 4 The diagram shows an operation flowchart of a charging alarm method based on an intelligent charging cabinet according to an embodiment of the present invention.

[0076] Specifically, the operation of the charging alarm method based on the smart charging cabinet may include the following steps: The first step is to acquire charging power, charging voltage, charging current, and real-time temperature data when the tool is placed in the smart charging cabinet for charging.

[0077] The second step is to determine whether the tool is fully charged based on the charging power.

[0078] The third step is to automatically power off the battery when it is fully charged and notify the user via screen, voice, or SMS that it is fully charged.

[0079] The fourth step is to determine if there is any abnormality based on the charging voltage, charging current, and real-time temperature data if the battery is not fully charged.

[0080] Fifth, if an abnormality is detected, the system will automatically cut off the power and issue an alarm via screen, voice, and SMS.

[0081] In this embodiment, the present invention provides a charging alarm method based on a smart charging cabinet. Its advantages are as follows: When power tools are placed in the smart charging cabinet for charging, the invention can acquire charging power, charging voltage, charging current, and real-time temperature data of the power tools. If the charging power determines that the power tool is not fully charged, the charging voltage, charging current, and real-time temperature data are used for detection processing to obtain the detection results. If any detection result is abnormal, an alarm is triggered and power is cut off. By monitoring each charging tool in real time, the present invention can not only avoid overcharging or continuous charging, but also reduce the safety risk of spontaneous combustion of tools during charging, thus improving charging safety.

[0082] This invention also provides a charging alarm device based on a smart charging cabinet, see [link / reference]. Figure 5 The diagram shows a schematic representation of a charging alarm device based on an intelligent charging cabinet according to an embodiment of the present invention.

[0083] As an example, the charging alarm device based on the smart charging cabinet may include: The acquisition module 201 is used to acquire real-time charging parameters of the power tool when it is placed in the smart charging cabinet for charging. The real-time charging parameters include: charging power, charging voltage, charging current and real-time temperature data. The detection module 202 is used to perform detection processing using the charging voltage, the charging current and the real-time temperature data respectively, when the charging state of the power tool is determined to be not fully charged based on the charging power, to obtain the detection result; The alarm module 203 is used to trigger an alarm and cut off power if the detection result of the charging voltage is abnormal, the detection result of the charging current is abnormal, or the detection result of the real-time temperature data is abnormal.

[0084] Optionally, the real-time temperature data is a two-dimensional raw temperature matrix obtained by detecting the entire field of view using an infrared dual-light camera; The real-time temperature data is used for detection and processing to obtain detection results, including: The real-time temperature data is preprocessed to obtain a processed temperature matrix. The preprocessing includes: non-uniformity correction, bad pixel replacement, temperature calibration, and noise reduction filtering. A thermal image is generated based on the temperature matrix. When it is determined that there is any abnormal pixel in the thermal image, the detection result is determined to be abnormal.

[0085] Optionally, the step of generating a thermal image based on the processed temperature matrix, and determining the detection result as abnormal when it is determined that any abnormal pixel exists in the thermal image, includes: The temperature matrix is ​​linearly mapped to a preset image grayscale range to obtain a temperature grayscale image. A thermal image is obtained by performing pseudo-color mapping and image enhancement on the grayscale value of each pixel in the temperature grayscale image; The real-time temperature value corresponding to each pixel in the thermal image is determined, and whether the pixel is an abnormal pixel is determined based on the real-time temperature value and a preset temperature threshold. The preset temperature threshold is the maximum or average temperature value in the region of interest of the image preset by the user. If it is determined that there are abnormal pixels in the thermal image, then the detection result is determined to be abnormal.

[0086] Optionally, determining whether a pixel is an abnormal pixel based on the real-time temperature value and a preset temperature threshold includes: If the difference between the real-time temperature value and the preset temperature threshold is greater than the preset temperature difference, then the pixel is determined to be an abnormal pixel. or; If the real-time temperature value is greater than the preset temperature threshold, the pixel is determined to be an abnormal pixel. or; The temperature rise rate is calculated using the real-time temperature value and a preset temperature threshold. If the temperature rise rate is greater than the preset rate threshold, the pixel is determined to be an abnormal pixel.

[0087] Optionally, the device further includes: The binarization module is used to perform binarization processing on the abnormal pixel and the adjacent pixels of the abnormal pixel to obtain a binarized point after determining that the detection result is abnormal when the thermal image is generated based on the processing temperature matrix and when it is determined that any abnormal pixel exists in the thermal image. The clustering module is used to assign abnormal labels to the binarized points and cluster the pixels of the labels to obtain clustered image regions. The visualization module is used to perform region filtering on the clustered image region to obtain a hot patch image and visualize the hot patch image.

[0088] This invention also provides an intelligent charging cabinet, see [link to relevant documentation]. Figure 6-8 The figures show a front view, a rear view, and a side view of a smart charging cabinet provided in one embodiment of the present invention.

[0089] The intelligent charging cabinet is applicable to the charging alarm method based on the intelligent charging cabinet as described in the above embodiments. As an example, the intelligent charging cabinet is provided with several layers of charging platforms 1, and each layer of the charging platform is provided with an infrared dual-light camera 2 and several charging sockets 3. The smart charging cabinet is equipped with a display screen 4 and a movable door 5 on its side.

[0090] Specifically, the charging cabinet adopts an integrated, aesthetically pleasing, and user-friendly design. It features an open three-layer design, forming a three-layer charging platform 1. Each layer has 10 charging ports 3, and each charging port 3 can detect the charging power, voltage, and current during the charging process. Each layer also has two infrared dual-light cameras 2, which can monitor the temperature of the entire layer.

[0091] Optionally, each layer of the charging platform 1 is provided with multiple reinforcing ribs, and the reinforcing ribs are fixed inside the layer of the charging platform 1 by means of upper and lower sealing plates.

[0092] Those skilled in the art will understand that, for ease of description and brevity, the specific working process of the device described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0093] Furthermore, this application also provides an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the charging alarm method based on the intelligent charging cabinet as described in the above embodiments.

[0094] Furthermore, embodiments of this application also provide a computer-readable storage medium storing a computer-executable program, the computer-executable program being used to cause a computer to execute the charging alarm method based on a smart charging cabinet as described in the above embodiments.

[0095] In the description of the embodiments of the present invention, it should be noted that the terms "above," "below," etc., indicating the orientation or positional relationship are based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing the embodiments of the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention. When an element such as a layer, region, or substrate is referred to as being "above" or "on top of" another element, it may be directly on the other element, or there may be an intermediate element. Conversely, when an element is referred to as being "directly on" or "above" another element, there is no intermediate element. It should also be understood that when an element is referred to as being "below" or "under" another element, it may be directly below or under the other element, or there may be an intermediate element. Conversely, when an element is referred to as being "directly below" or "under" another element, there is no intermediate element. Unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections or electrical connections; they can refer to direct connections or indirect connections through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0096] Those skilled in the art will understand that embodiments of this application may also include computer program products. Therefore, this application may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application may take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0097] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), devices, and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0098] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0099] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0100] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A charging alarm method based on an intelligent charging cabinet, characterized in that, The method includes: When power tools are placed in a smart charging cabinet for charging, real-time charging parameters of the power tools are acquired, including: charging power, charging voltage, charging current and real-time temperature data. If the charging status of the power tool is determined to be not fully charged based on the charging power, the charging voltage, the charging current, and the real-time temperature data are used for detection processing to obtain the detection result. If the detection result of the charging voltage is abnormal, the detection result of the charging current is abnormal, or the detection result of the real-time temperature data is abnormal, an alarm is triggered and the power is cut off.

2. The charging alarm method based on an intelligent charging cabinet according to claim 1, characterized in that, The real-time temperature data is a two-dimensional raw temperature matrix obtained by detecting the entire field of view using an infrared dual-light camera. The real-time temperature data is used for detection and processing to obtain detection results, including: The real-time temperature data is preprocessed to obtain a processed temperature matrix. The preprocessing includes: non-uniformity correction, bad pixel replacement, temperature calibration, and noise reduction filtering. A thermal image is generated based on the temperature matrix. When it is determined that there is any abnormal pixel in the thermal image, the detection result is determined to be abnormal.

3. The charging alarm method based on an intelligent charging cabinet according to claim 2, characterized in that, The process of generating a thermal image based on the processed temperature matrix, and determining the detection result as abnormal when any abnormal pixel is found in the thermal image, includes: The temperature matrix is ​​linearly mapped to a preset image grayscale range to obtain a temperature grayscale image. A thermal image is obtained by performing pseudo-color mapping and image enhancement on the grayscale value of each pixel in the temperature grayscale image; The real-time temperature value corresponding to each pixel in the thermal image is determined, and whether the pixel is an abnormal pixel is determined based on the real-time temperature value and a preset temperature threshold. The preset temperature threshold is the maximum or average temperature value in the region of interest of the image preset by the user. If it is determined that there are abnormal pixels in the thermal image, then the detection result is determined to be abnormal.

4. The charging alarm method based on an intelligent charging cabinet according to claim 3, characterized in that, The step of determining whether a pixel is an abnormal pixel based on the real-time temperature value and a preset temperature threshold includes: If the difference between the real-time temperature value and the preset temperature threshold is greater than the preset temperature difference, then the pixel is determined to be an abnormal pixel. or; If the real-time temperature value is greater than the preset temperature threshold, the pixel is determined to be an abnormal pixel. or; The temperature rise rate is calculated using the real-time temperature value and a preset temperature threshold. If the temperature rise rate is greater than the preset rate threshold, the pixel is determined to be an abnormal pixel.

5. The charging alarm method based on an intelligent charging cabinet according to claim 2, characterized in that, After the step of generating a thermal image based on the processed temperature matrix, and determining that the detection result is abnormal when any abnormal pixel is found in the thermal image, the method further includes: The abnormal pixel and its adjacent pixels are binarized to obtain a binarized point. Anomaly labels are assigned to the binarized points, and the pixels of the labels are clustered to obtain clustered image regions. The clustered image regions are filtered to obtain thermal patch images, which are then visualized.

6. A charging alarm device based on an intelligent charging cabinet, characterized in that, The device includes: The acquisition module is used to acquire real-time charging parameters of the power tools when they are placed in the smart charging cabinet for charging. The real-time charging parameters include: charging power, charging voltage, charging current and real-time temperature data. The detection module is used to perform detection processing using the charging voltage, the charging current, and the real-time temperature data respectively, when the charging status of the power tool is determined to be not fully charged based on the charging power, to obtain the detection result. An alarm module is used to trigger an alarm and cut off power if the detection result of the charging voltage is abnormal, the detection result of the charging current is abnormal, or the detection result of the real-time temperature data is abnormal.

7. A smart charging cabinet, characterized in that, The intelligent charging cabinet is applicable to the charging alarm method based on the intelligent charging cabinet as described in any one of claims 1-5. The intelligent charging cabinet is provided with several layers of charging platforms, and each layer of the charging platform is provided with an infrared dual-light camera and several charging sockets. The smart charging cabinet has a display screen and a movable door on its side.

8. The intelligent charging cabinet according to claim 7, characterized in that, Each layer of the charging platform has multiple reinforcing ribs, and the reinforcing ribs are fixed inside the layer of the charging platform by upper and lower sealing plates.

9. An electronic device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, when the processor executes the program, it implements the charging alarm method based on an intelligent charging cabinet as described in any one of claims 1-5.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which are used to cause a computer to perform the charging alarm method based on a smart charging cabinet as described in any one of claims 1-5.

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