Switch cabinet intelligent monitoring method and system based on Internet of Things

Abstract

The invention relates to the technical field of electric power, and provides a switch cabinet intelligent monitoring method and system based on the Internet of Things, and the method comprises the steps: receiving a switch cabinet unlocking request sent by a switch cabinet operation robot; in response to the switch cabinet unlocking request, detecting whether the switch cabinet operation robot reaches a preset position or not; if yes, hyperspectral image data of the switch cabinet operation robot at multiple angles are collected through a hyperspectral camera; performing oil contamination detection based on each piece of hyperspectral image data to obtain a detection result corresponding to each piece of hyperspectral image data; and when the detection result is that the oil stain exists, sending unlocking rejection information to the switch cabinet operation robot. The safety problem caused by greasy dirt on the surface of the switch cabinet operation robot can be avoided. The safety when the switch cabinet operation robot operates the switch cabinet can be improved.

Description

Technical Field

[0001] The present application relates to the field of electric power technology, and in particular to an intelligent monitoring method and system for switch cabinets based on the Internet of Things. Background Art

[0002] Switchgear is a commonly used electrical equipment in circuit systems, mainly used for control, protection, measurement and power distribution. Manual operation of switchgear may cause safety accidents such as electric shock due to accidental touch or misoperation. With technological advancements, it may become a reality to use switchgear operating robots to operate switchgear. To use a switchgear operating robot to operate the switchgear, it is first necessary to unlock the switchgear. At present, some scholars have proposed a technical solution to automatically unlock the switchgear using the mechanical arm of the switchgear operating robot. However, the inventors have found that if the switchgear operating robot has oil stains on its surface due to environmental factors or the switchgear operating robot itself, it may cause safety problems when the switchgear operating robot opens the switchgear. Therefore, this problem needs to be solved. Summary of the Invention

[0003] In response to the above technical problems, the purpose of this application is to provide an intelligent monitoring method and system for switch cabinets based on the Internet of Things, which aims to solve the technical problem that if the switch cabinet operating robot has oil stains on its surface due to environmental factors or the switch cabinet operating robot itself, it may cause safety problems when the switch cabinet operating robot opens the switch cabinet.

[0004] In a first aspect, an embodiment of the present application provides an IoT-based intelligent monitoring method for a switch cabinet, wherein a hyperspectral camera is provided on the outer surface of the switch cabinet, and the method comprises:

[0005] receiving a switch cabinet unlocking request sent by a switch cabinet operating robot;

[0006] In response to the switch cabinet unlocking request, detecting whether the switch cabinet operating robot reaches a preset position;

[0007] If so, collecting hyperspectral image data of the switch cabinet operating robot at multiple angles using a hyperspectral camera;

[0008] Performing oil pollution detection based on each of the hyperspectral image data to obtain a detection result corresponding to each of the hyperspectral image data;

[0009] When the detection result shows that oil stains are present, an unlocking rejection message is sent to the switch cabinet operating robot.

[0010] Furthermore, a radio frequency tag is provided on the outer surface of the switch cabinet, a QR code is provided in the unlocking area of the switch cabinet, and a first electromagnet is provided at the preset position. The step of detecting whether the switch cabinet operating robot reaches the preset position includes:

[0011] Acquire unique identification information of the switch cabinet operating robot from the switch cabinet unlocking request;

[0012] Sending a switch cabinet operating robot position detection instruction to the cloud based on the unique identification information;

[0013] receiving a radio frequency identification result, a two-dimensional code recognition result, and a first electromagnet sensing result returned by the cloud in response to the position detection instruction;

[0014] When the first electromagnet sensing result is that the first electromagnet is sensed, the radio frequency identification result matches the radio frequency tag of the switch cabinet, and the two-dimensional code recognition result matches the two-dimensional code of the switch cabinet, it is determined that the switch cabinet operating robot has reached the preset position; otherwise, it has not reached the preset position.

[0015] Furthermore, the step of performing oil pollution detection based on hyperspectral image data includes:

[0016] Constructing an oil pollution reference spectrum based on the CH bond spectral characteristics and the hyperspectral image data;

[0017] Based on the difference in reflection characteristics between the switchgear operating robot shell and the oil stain, the band with the largest difference between the switchgear operating robot shell and the oil stain is selected;

[0018] Using the data within the wavelength band with the largest difference to segment the switch cabinet operating robot housing pixels to obtain switch cabinet operating robot housing background data;

[0019] Based on the background data of the switch cabinet operating robot shell, the oil stain reference spectrum and the hyperspectral image data, an adaptive matched filtering method is used to determine whether there is oil stain on the surface of the switch cabinet operating robot.

[0020] Furthermore, after the step of sending an unlocking rejection message to the switch cabinet operating robot when the detection result shows that oil stains are present, the method further includes:

[0021] When the detection result shows that there is no oil contamination, reading the voltage value of the voltmeter configured in the switch cabinet;

[0022] If the voltage value of the voltmeter is equal to 0, then obtaining the time length for which the voltage value of the voltmeter remains at 0;

[0023] If the time length is greater than a preset time length threshold, an unlocking consent message is sent to the switch cabinet operating robot.

[0024] Furthermore, a visible light camera is provided inside the switch cabinet, and the power supply of the visible light camera is independent of the switch cabinet. After the step of sending the unlocking consent information to the switch cabinet operating robot, the method further includes:

[0025] The visible light camera is switched from an off state to an on state to monitor the interior of the switch cabinet, and the monitoring video is sent to a monitoring background.

[0026] Furthermore, the switch cabinet operating robot includes an end execution module, and the end execution module includes a second hyperspectral camera. The second hyperspectral camera is used to collect hyperspectral image data within its visual range when the switch cabinet operating robot operates the internal equipment of the switch cabinet for use in identifying whether there is oil pollution on the internal equipment of the switch cabinet. The switch cabinet operating robot is also used to send a warning message to the monitoring display screen when it detects the presence of oil pollution on the internal equipment of the switch cabinet.

[0027] In a second aspect, an embodiment of the present application provides an IoT-based intelligent monitoring system for a switch cabinet, wherein a hyperspectral camera is provided on the outer surface of the switch cabinet, and the system includes:

[0028] A receiving module, configured to receive a switch cabinet unlocking request sent by the switch cabinet operating robot;

[0029] a detection module, configured to detect whether the switch cabinet operating robot has reached a preset position in response to the switch cabinet unlocking request;

[0030] An acquisition module, configured to acquire hyperspectral image data of the switch cabinet operating robot at multiple angles through a hyperspectral camera;

[0031] An oil pollution detection module is used to perform oil pollution detection based on each of the hyperspectral image data and obtain a detection result corresponding to each of the hyperspectral image data;

[0032] The first sending module is used to send unlocking rejection information to the switch cabinet operating robot when the detection result shows that oil stains are present.

[0033] In one embodiment, a radio frequency tag is provided on the outer surface of the switch cabinet, a QR code is provided in the unlocking area of the switch cabinet, a first electromagnet is provided at the preset position, and the detection module includes:

[0034] an acquiring unit, configured to acquire unique identification information of the switch cabinet operating robot from the switch cabinet unlocking request;

[0035] A sending unit, configured to send a position detection instruction of a switch cabinet operating robot to the cloud based on the unique identification information;

[0036] a receiving unit, configured to receive a radio frequency identification result, a QR code recognition result, and a first electromagnet sensing result returned by the cloud in response to the position detection instruction;

[0037] The judgment unit is configured to determine that the switch cabinet operating robot has reached a preset position when the first electromagnet sensing result indicates that the first electromagnet is sensed, the radio frequency identification result matches the radio frequency tag of the switch cabinet, and the two-dimensional code recognition result matches the two-dimensional code of the switch cabinet; otherwise, the switch cabinet operating robot has not reached the preset position.

[0038] In one embodiment, the oil pollution detection module includes:

[0039] A construction unit, configured to construct an oil pollution reference spectrum based on the CH bond spectral characteristics and the hyperspectral image data;

[0040] A selection unit is used to select a band where the difference between the switch cabinet operating robot shell and the oil stain is the largest based on the difference in reflection characteristics between the switch cabinet operating robot shell and the oil stain;

[0041] a segmentation unit, configured to segment the switchgear operating robot housing pixels using the data within the wavelength band with the largest difference to obtain switchgear operating robot housing background data;

[0042] A judgment unit is used to judge whether there is oil stain on the surface of the switch cabinet operating robot through an adaptive matched filtering method based on the background data of the switch cabinet operating robot shell, the oil stain reference spectrum and the hyperspectral image data.

[0043] In one embodiment, the system further comprises:

[0044] a reading module, configured to read a voltage value of a voltmeter configured in the switch cabinet when the detection result shows that no oil contamination exists;

[0045] an acquisition module, configured to acquire, if the voltage value of the voltmeter is equal to 0, a time length for which the voltage value of the voltmeter remains at 0;

[0046] The second sending module is configured to send unlocking consent information to the switch cabinet operating robot if the duration is greater than a preset duration threshold.

[0047] An embodiment of the present application provides an IoT-based intelligent monitoring method for switch cabinets, wherein a hyperspectral camera is provided on the outer surface of the switch cabinet. The method comprises: receiving a switch cabinet unlocking request sent by a switch cabinet operating robot; in response to the switch cabinet unlocking request, detecting whether the switch cabinet operating robot has reached a preset position; if so, collecting hyperspectral image data of the switch cabinet operating robot from multiple angles using a hyperspectral camera; performing oil contamination detection based on each hyperspectral image data to obtain a detection result corresponding to each hyperspectral image data; and when the detection result indicates the presence of oil contamination, sending an unlocking rejection message to the switch cabinet operating robot. This application can avoid safety issues caused by oil contamination on the surface of the switch cabinet operating robot and improve the safety of the switch cabinet operating robot when operating the switch cabinet. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solution of the present application, the following is a brief introduction to the drawings required for use in the implementation. Obviously, the drawings described below are only some implementation methods of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0049] Figure 1 This is a flow chart of a method for intelligent monitoring of switch cabinets based on the Internet of Things provided by one embodiment of the present application;

[0050] Figure 2 This is a structural diagram of an IoT-based intelligent monitoring system for switch cabinets provided in one embodiment of the present application. DETAILED DESCRIPTION

[0051] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0052] Those skilled in the art will understand that, unless expressly stated otherwise, the singular forms "a", "an", "above", and "the" used herein may also include plural forms. It should be further understood that the term "comprising" used in the specification of this application refers to the presence of features, integers, steps, operations, elements, modules, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, modules, components, and / or groups thereof. It should be understood that when we refer to an element as being "connected" or "coupled" to another element, it may be directly connected or coupled to the other element, or there may be intermediate elements. In addition, "connected" or "coupled" as used herein may include wireless connections or wireless couplings. The term "and / or" used herein includes all or any module and all combinations of one or more associated listed items.

[0053] Those skilled in the art will understand that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs. It should also be understood that terms such as those defined in common dictionaries should be understood to have meanings consistent with their meanings in the context of the prior art and, unless specifically defined as such, will not be interpreted in an idealized or overly formal sense.

[0054] See also Figure 1 The present application provides an IoT-based intelligent monitoring method for a switch cabinet, wherein a hyperspectral camera is provided on the outer surface of the switch cabinet. The method includes:

[0055] S1. Receive a switch cabinet unlocking request sent by a switch cabinet operating robot;

[0056] S2. In response to the switch cabinet unlocking request, detecting whether the switch cabinet operating robot reaches a preset position;

[0057] S3. If yes, collect hyperspectral image data of the switch cabinet operating robot from multiple angles using a hyperspectral camera;

[0058] S4. Performing oil pollution detection based on each of the hyperspectral image data to obtain a detection result corresponding to each of the hyperspectral image data;

[0059] S5. When the detection result shows that oil stains are present, an unlocking rejection message is sent to the switch cabinet operating robot.

[0060] In an embodiment of the present application, a wireless communication module is provided on the switch cabinet, and the wireless communication module can be a Bluetooth, WiFi, LoRa module, etc. The power supply of the wireless communication module is independent of the switch cabinet. The switch cabinet operating robot is also equipped with a wireless communication module, and it is also equipped with an end operation module, which can realize the opening / closing operation of the mechanical lock of the switch cabinet. The end operation module is an existing module, and the embodiment of the present invention will not be described in detail here. The user can send an unlocking task to the switch cabinet operating robot through the remote control platform. After the switch cabinet operating robot receives the unlocking task, the switch cabinet operating robot goes to the target switch cabinet according to the switch cabinet number in the task information. When the switch cabinet operating robot detects that it has arrived at the target switch cabinet, it establishes a communication connection with the target switch cabinet through the communication module and sends an unlocking request to the target switch cabinet. To obtain a close-up image of the switchgear operating robot, thereby maximizing the proportion of the switchgear operating robot in the captured image and improving the accuracy and recognition rate of oil stain detection, a position is preset for the switchgear operating robot to reach. Upon receiving an unlock request from the switchgear operating robot, the robot is detected to determine whether it has reached the preset position. The specific detection method will be described later and will not be elaborated on here. After detecting that the switchgear operating robot has reached the preset position, a hyperspectral camera is used to capture hyperspectral image data from multiple angles of the switchgear operating robot. Specifically, the switchgear sends a multi-angle image capture command to the switchgear operating robot. Upon receiving the command, the switchgear operating robot adjusts its position and components according to a preset program so that the hyperspectral camera can capture multi-angle hyperspectral image data of the switchgear operating robot. Complete hyperspectral image data of the switchgear operating robot is obtained, thereby detecting whether there is oil stain on the outer surface of the switchgear operating robot. If oil stain is detected, an unlock rejection message is sent to the switchgear operating robot, thereby avoiding safety issues caused by oil stains on the switchgear operating robot's surface. This embodiment of the present invention can improve the safety of the switchgear operating robot when operating a switchgear.

[0061] In one embodiment, a radio frequency tag is provided on the outer surface of the switch cabinet, a QR code is provided in the unlocking area of the switch cabinet, and a first electromagnet is provided at the preset position. The step of detecting whether the switch cabinet operating robot reaches the preset position includes:

[0062] Acquire unique identification information of the switch cabinet operating robot from the switch cabinet unlocking request;

[0063] Sending a switch cabinet operating robot position detection instruction to the cloud based on the unique identification information;

[0064] receiving a radio frequency identification result, a two-dimensional code recognition result, and a first electromagnet sensing result returned by the cloud in response to the position detection instruction;

[0065] When the first electromagnet sensing result is that the first electromagnet is sensed, the radio frequency identification result matches the radio frequency tag of the switch cabinet, and the two-dimensional code recognition result matches the two-dimensional code of the switch cabinet, it is determined that the switch cabinet operating robot has reached the preset position; otherwise, it has not reached the preset position.

[0066] In an embodiment of the present application, to obtain a close-up image of the switchgear operating robot, thereby maximizing the proportion of the switchgear operating robot in the captured image and improving the accuracy and recognition rate of oil contamination detection, a preset position is set for the switchgear operating robot. Specifically, a first electromagnet is positioned at the preset position. Without interfering with the robot's unlocking, the preset position is determined based on the hyperspectral camera's capture range and the proportion of the switchgear operating robot within the hyperspectral camera. It should be noted that the proportion of the switchgear operating robot within the hyperspectral camera should be as large as possible. Furthermore, a magnetic sensing module is positioned at the bottom of the switchgear operating robot, comprising a second electromagnet. In one embodiment, the second electromagnet is extendably mounted (e.g., via a spring) at the bottom of the switchgear operating robot. When the second electromagnet of the magnetic sensing module attracts the first electromagnet, the magnetic sensing module generates a sensing result indicating the first electromagnet. To detect whether the first electromagnet is the target switchgear, a radio frequency tag is placed on the target switchgear. The tag carries the target switchgear serial number, allowing the identification of the first electromagnet. Furthermore, to enable the switchgear handling robot to face the switchgear in a predetermined direction for better positioning and unlocking, a QR code is placed in the unlocking area. The terminal operation module of the switchgear handling robot is also equipped with a camera to scan the QR code.

[0067] In one embodiment, the step of performing oil pollution detection based on hyperspectral image data includes:

[0068] Constructing an oil pollution reference spectrum based on the CH bond spectral characteristics and the hyperspectral image data;

[0069] Based on the difference in reflection characteristics between the switchgear operating robot shell and the oil stain, the band with the largest difference between the switchgear operating robot shell and the oil stain is selected;

[0070] Using the data within the wavelength band with the largest difference to segment the switch cabinet operating robot housing pixels to obtain switch cabinet operating robot housing background data;

[0071] Based on the background data of the switch cabinet operating robot shell, the oil stain reference spectrum and the hyperspectral image data, an adaptive matched filtering method is used to determine whether there is oil stain on the surface of the switch cabinet operating robot.

[0072] This application constructs an oil pollution reference spectrum based on the hyperspectral image data collected in real time, and selects the band with the largest difference between the switch cabinet operating robot shell and the oil pollution to calculate the background data. Compared with constructing the oil pollution reference spectrum in the laboratory and using the entire image to calculate the background parameters, the oil pollution detection is more accurate.

[0073] In the embodiment of the present application, the main component of the oil pollution is hydrocarbons, in which the CH bond has obvious absorption band characteristics within a certain number of (m) bands. Therefore, these absorption band characteristics of the CH bond can be used to extract the reference spectrum of the oil pollution. Specifically, the above m independent bands are selected and the reflectivity ratio of each band is calculated. The calculation formula of the reflectivity ratio of each band is: :where i,j represents the pixel position, k=1,2,...,m, 、 The value of is the average value of the spectral reflectance in three adjacent bands. For example, for the absorption band of 1.73μm, the average value of the reflectance in three adjacent bands within 1.72–1.74μm is taken as , take the average reflectivity of the three bands 1.65–1.67 μm on the left side (or right side) of the absorption band as Then, these m reflectivity ratios are combined to construct a comprehensive feature. The constructed comprehensive feature is: Finally, in order to detect oil pollution more accurately, the first segmentation threshold is set to . yes The mean of yes The segmentation result of the reference spectrum is:

[0074] ;

[0075] The constructed oil pollution reference spectrum is:

[0076] ;

[0077] in, represents the number of pixels of the reference spectrum obtained by segmentation, represents hyperspectral image data, specifically, a reflectance spectrum. The data within the wavelength band with the largest difference is used to segment the switchgear operating robot housing pixels to calculate the switchgear operating robot housing background parameters (which can be understood as the switchgear operating robot housing being the background). Specifically, the average spectral reflectance of all pixels within the wavelength band is calculated. The switchgear operating robot housing background is obtained by segmentation based on a second segmentation threshold. Specifically, the switchgear operating robot housing background is obtained by segmentation according to the following formula:

[0078] ;

[0079] in, is the second segmentation threshold, is the average value of the spectral reflectance of pixel (i, j).

[0080] Based on the background data of the switch cabinet operating robot shell, the oil stain reference spectrum, and the hyperspectral image data, an adaptive matched filtering method is used to determine whether there is oil stain on the surface of the switch cabinet operating robot. Specifically, the following formula is used to determine whether there is oil stain on the surface of the switch cabinet operating robot:

[0081] ;

[0082] Where x is the hyperspectral image data, , n is the number of pixels in the hyperspectral image, is the mean vector of the shell background, is the covariance matrix, which is calculated by segmenting the shell background pixels, that is, ;in, It represents the number of background pixels of the shell switch cabinet operating robot obtained by segmentation, and T is the transpose. If the value is greater than the set threshold, it proves that there is oil pollution.

[0083] In one embodiment, the power supply of the hyperspectral camera may be independent of the switch cabinet, or may be powered by the power supply of the switch cabinet, which is not limited in this embodiment of the present invention.

[0084] In one embodiment, after the step of sending an unlocking rejection message to the switch cabinet operating robot when the detection result indicates the presence of oil stains, the method further includes:

[0085] When the detection result shows that there is no oil contamination, reading the voltage value of the voltmeter configured in the switch cabinet;

[0086] If the voltage value of the voltmeter is equal to 0, then obtaining the time length for which the voltage value of the voltmeter remains at 0;

[0087] If the time length is greater than a preset time length threshold, an unlocking consent message is sent to the switch cabinet operating robot.

[0088] In an embodiment of the present application, the voltmeter can be installed on the power incoming side. If the voltmeter indicates that there is no voltage on the incoming side, that is, the voltage value of the voltmeter is 0, it can be ensured that the switch cabinet as a whole is in a power-off state. If the switch cabinet is a sectionalized switch cabinet, a voltmeter can be installed at the outlet of the circuit breaker, and the value of the voltmeter can be used to determine whether the switch cabinet is in a power-off state. When the voltage value of the voltmeter is 0V, the switch cabinet is in a power-off state. Only when it is detected that the switch cabinet is in a power-off state and the duration is greater than the preset time threshold will the unlocking consent information be sent to the switch cabinet operating robot, which can avoid the safety risks caused by the robot working in the energized state of the switch cabinet and can avoid the safety risks caused by electric arcs. It should be understood that the capacitance of the cables and equipment in the switch cabinet may have residual charge, causing the voltage to drop slowly. The time verification can ensure that the charge is completely released.

[0089] In one embodiment, a visible light camera is provided inside the switch cabinet, and the visible light camera is powered independently of the switch cabinet. After the step of sending the unlocking consent information to the switch cabinet operating robot, the method further includes:

[0090] The visible light camera is switched from an off state to an on state to monitor the interior of the switch cabinet, and the monitoring video is sent to a monitoring background.

[0091] In the embodiment of the present application, a second power source is provided to power the visible light camera, making the power supply of the visible light camera independent of the switch cabinet. This allows the visible light camera to be turned on to monitor the operation of the robot and the interior of the switch cabinet even when the switch cabinet is powered off, and to transmit the data to the monitoring backend via the wireless communication module for monitoring. It should be understood that the power supply of the wireless communication module is also independent of the switch cabinet.

[0092] In one embodiment, the switch cabinet operating robot includes an end execution module, and the end execution module includes a second hyperspectral camera. The second hyperspectral camera is used to collect hyperspectral image data within its visual range when the switch cabinet operating robot operates the internal equipment of the switch cabinet for use in identifying whether the internal equipment of the switch cabinet is oily. The switch cabinet operating robot is also used to send a warning message to a monitoring display screen when detecting the presence of oily equipment in the internal equipment of the switch cabinet.

[0093] In the embodiment of the present application, the method for identifying whether the internal equipment of the switchgear is contaminated with oil is similar in principle to the above-described embodiment and is not further described herein. Furthermore, the embodiment of the present invention identifies whether the internal equipment of the switchgear is contaminated with oil and, when oil contamination is detected, sends a warning message to a monitoring display screen, enabling timely implementation of appropriate measures to mitigate safety issues caused by the oil contamination. The warning message includes the switchgear number and an image corresponding to the detected oil contamination.

[0094] like Figure 2 As shown, an embodiment of the present application further provides an IoT-based intelligent monitoring system for a switch cabinet, wherein a hyperspectral camera is provided on the outer surface of the switch cabinet, and the system comprises:

[0095] Receiving module 1, used to receive a switch cabinet unlocking request sent by the switch cabinet operating robot;

[0096] Detection module 2, configured to detect whether the switch cabinet operating robot reaches a preset position in response to the switch cabinet unlocking request;

[0097] If yes, the acquisition module 3 is used to acquire hyperspectral image data of the switch cabinet operating robot at multiple angles through a hyperspectral camera;

[0098] An oil pollution detection module 4 is configured to perform oil pollution detection based on each of the hyperspectral image data and obtain a detection result corresponding to each of the hyperspectral image data;

[0099] The first sending module 5 is configured to send an unlocking rejection message to the switch cabinet operating robot when the detection result shows that oil stains are present.

[0100] In one embodiment, a radio frequency tag is provided on the outer surface of the switch cabinet, a QR code is provided in the unlocking area of the switch cabinet, a first electromagnet is provided at the preset position, and the detection module includes:

[0101] an acquiring unit, configured to acquire unique identification information of the switch cabinet operating robot from the switch cabinet unlocking request;

[0102] A sending unit, configured to send a position detection instruction of a switch cabinet operating robot to the cloud based on the unique identification information;

[0103] a receiving unit, configured to receive a radio frequency identification result, a QR code recognition result, and a first electromagnet sensing result returned by the cloud in response to the position detection instruction;

[0104] The judgment unit is configured to determine that the switch cabinet operating robot has reached a preset position when the first electromagnet sensing result indicates that the first electromagnet is sensed, the radio frequency identification result matches the radio frequency tag of the switch cabinet, and the two-dimensional code recognition result matches the two-dimensional code of the switch cabinet; otherwise, the switch cabinet operating robot has not reached the preset position.

[0105] In one embodiment, the oil pollution detection module includes:

[0106] A construction unit, configured to construct an oil pollution reference spectrum based on the CH bond spectral characteristics and the hyperspectral image data;

[0107] A selection unit is used to select a band where the difference between the switch cabinet operating robot shell and the oil stain is the largest based on the difference in reflection characteristics between the switch cabinet operating robot shell and the oil stain;

[0108] a segmentation unit, configured to segment the switchgear operating robot housing pixels using the data within the wavelength band with the largest difference to obtain switchgear operating robot housing background data;

[0109] A judgment unit is used to judge whether there is oil stain on the surface of the switch cabinet operating robot through an adaptive matched filtering method based on the background data of the switch cabinet operating robot shell, the oil stain reference spectrum and the hyperspectral image data.

[0110] In one embodiment, the system further comprises:

[0111] a reading module, configured to read a voltage value of a voltmeter configured in the switch cabinet when the detection result shows that no oil contamination exists;

[0112] an acquisition module, configured to acquire, if the voltage value of the voltmeter is equal to 0, a time length for which the voltage value of the voltmeter remains at 0;

[0113] The second sending module is configured to send unlocking consent information to the switch cabinet operating robot if the duration is greater than a preset duration threshold.

[0114] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media provided in this application and used in the embodiments may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct RAM bus dynamic RAM (DRDRAM), and RAM bus dynamic RAM (RDRAM).

[0115] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, apparatus, article, or method comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, apparatus, article, or method. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, apparatus, article, or method comprising the element.

[0116] The above description is only a preferred embodiment of the present application and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A switch cabinet intelligent monitoring method based on the Internet of Things, characterized in that: A hyperspectral camera is provided on the outer surface of the switch cabinet, and the method includes: receiving a switch cabinet unlocking request sent by a switch cabinet operating robot; In response to the switch cabinet unlocking request, detecting whether the switch cabinet operating robot reaches a preset position; If so, collecting hyperspectral image data of the switch cabinet operating robot at multiple angles using a hyperspectral camera; Performing oil pollution detection based on each of the hyperspectral image data to obtain a detection result corresponding to each of the hyperspectral image data; When the detection result shows that oil stains are present, an unlocking rejection message is sent to the switch cabinet operating robot.

2. The switch cabinet intelligent monitoring method based on the Internet of Things according to claim 1 is characterized in that: The outer surface of the switch cabinet is provided with a radio frequency tag, the unlocking area of the switch cabinet is provided with a QR code, and the preset position is provided with a first electromagnet. The step of detecting whether the switch cabinet operating robot reaches the preset position includes: Acquire unique identification information of the switch cabinet operating robot from the switch cabinet unlocking request; Sending a switch cabinet operating robot position detection instruction to the cloud based on the unique identification information; receiving a radio frequency identification result, a two-dimensional code recognition result, and a first electromagnet sensing result returned by the cloud in response to the position detection instruction; When the first electromagnet sensing result is that the first electromagnet is sensed, the radio frequency identification result matches the radio frequency tag of the switch cabinet, and the two-dimensional code recognition result matches the two-dimensional code of the switch cabinet, it is determined that the switch cabinet operating robot has reached the preset position; otherwise, it has not reached the preset position.

3. The switch cabinet intelligent monitoring method based on the Internet of Things according to claim 2 is characterized in that: The steps of performing oil pollution detection based on hyperspectral image data include: Constructing an oil pollution reference spectrum based on the CH bond spectral characteristics and the hyperspectral image data; Based on the difference in reflection characteristics between the switchgear operating robot shell and the oil stain, the band with the largest difference between the switchgear operating robot shell and the oil stain is selected; Using the data within the wavelength band with the largest difference to segment the switch cabinet operating robot housing pixels to obtain switch cabinet operating robot housing background data; Based on the background data of the switch cabinet operating robot shell, the oil stain reference spectrum and the hyperspectral image data, an adaptive matched filtering method is used to determine whether there is oil stain on the surface of the switch cabinet operating robot.

4. The switch cabinet intelligent monitoring method based on the Internet of Things according to claim 1 is characterized in that: After the step of sending unlocking rejection information to the switch cabinet operating robot when the detection result shows that oil stains are present, the method further includes: When the detection result shows that there is no oil contamination, reading the voltage value of the voltmeter configured in the switch cabinet; If the voltage value of the voltmeter is equal to 0, then obtaining the time length for which the voltage value of the voltmeter remains at 0; If the time length is greater than a preset time length threshold, an unlocking consent message is sent to the switch cabinet operating robot.

5. The switch cabinet intelligent monitoring method based on the Internet of Things according to claim 4 is characterized in that: A visible light camera is provided inside the switch cabinet, and the visible light camera is powered independently of the switch cabinet. After the step of sending the unlocking consent information to the switch cabinet operating robot, the method further includes: The visible light camera is switched from an off state to an on state to monitor the interior of the switch cabinet, and the monitoring video is sent to a monitoring background.

6. The switch cabinet intelligent monitoring method based on the Internet of Things according to claim 1 is characterized in that: The switch cabinet operating robot includes an end execution module, which includes a second hyperspectral camera. The second hyperspectral camera is used to collect hyperspectral image data within its visual range when the switch cabinet operating robot operates the internal equipment of the switch cabinet for use in identifying whether there is oil pollution on the internal equipment of the switch cabinet. The switch cabinet operating robot is also used to send a warning message to a monitoring display screen when oil pollution is detected on the internal equipment of the switch cabinet.

7. An intelligent monitoring system for switch cabinets based on the Internet of Things, characterized in that: A hyperspectral camera is provided on the outer surface of the switch cabinet, and the system includes: A receiving module, configured to receive a switch cabinet unlocking request sent by the switch cabinet operating robot; a detection module, configured to detect whether the switch cabinet operating robot has reached a preset position in response to the switch cabinet unlocking request; An acquisition module, configured to acquire hyperspectral image data of the switch cabinet operating robot at multiple angles through a hyperspectral camera; An oil pollution detection module is used to perform oil pollution detection based on each of the hyperspectral image data and obtain a detection result corresponding to each of the hyperspectral image data; The first sending module is used to send unlocking rejection information to the switch cabinet operating robot when the detection result shows that oil stains are present.

8. The switch cabinet intelligent monitoring system based on the Internet of Things according to claim 7 is characterized in that: The outer surface of the switch cabinet is provided with a radio frequency tag, the unlocking area of the switch cabinet is provided with a QR code, the preset position is provided with a first electromagnet, and the detection module includes: an acquiring unit, configured to acquire unique identification information of the switch cabinet operating robot from the switch cabinet unlocking request; A sending unit, configured to send a position detection instruction of a switch cabinet operating robot to the cloud based on the unique identification information; a receiving unit, configured to receive a radio frequency identification result, a QR code recognition result, and a first electromagnet sensing result returned by the cloud in response to the position detection instruction; The judgment unit is configured to determine that the switch cabinet operating robot has reached a preset position when the first electromagnet sensing result indicates that the first electromagnet is sensed, the radio frequency identification result matches the radio frequency tag of the switch cabinet, and the two-dimensional code recognition result matches the two-dimensional code of the switch cabinet; otherwise, the switch cabinet operating robot has not reached the preset position.

9. The switch cabinet intelligent monitoring system based on the Internet of Things according to claim 8 is characterized in that: The oil pollution detection module includes: A construction unit, configured to construct an oil pollution reference spectrum based on the CH bond spectral characteristics and the hyperspectral image data; A selection unit is used to select a band where the difference between the switch cabinet operating robot shell and the oil stain is the largest based on the difference in reflection characteristics between the switch cabinet operating robot shell and the oil stain; a segmentation unit, configured to segment the switchgear operating robot housing pixels using the data within the wavelength band with the largest difference to obtain switchgear operating robot housing background data; A judgment unit is used to judge whether there is oil stain on the surface of the switch cabinet operating robot through an adaptive matched filtering method based on the background data of the switch cabinet operating robot shell, the oil stain reference spectrum and the hyperspectral image data.

10. The switch cabinet intelligent monitoring system based on the Internet of Things according to claim 7, characterized in that: The system further comprises: a reading module, configured to read a voltage value of a voltmeter configured in the switch cabinet when the detection result shows that no oil contamination exists; an acquisition module, configured to acquire, if the voltage value of the voltmeter is equal to 0, a time length for which the voltage value of the voltmeter remains at 0; The second sending module is configured to send unlocking consent information to the switch cabinet operating robot if the duration is greater than a preset duration threshold.

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