A data center inspection method, device, equipment and storage medium

Abstract

The application discloses a data center inspection method, device, equipment and storage medium. The inspection task instruction includes at least one to-be-inspected cabinet, position information of the at least one to-be-inspected cabinet and a to-be-collected data type corresponding to the at least one to-be-inspected cabinet; first positioning is performed according to a preset driving map and the position information of the at least one to-be-inspected cabinet; when a reference position information of the first positioning is reached according to a first positioning corresponding inspection route movement, reference image information of the at least one to-be-inspected cabinet is collected; the relative positions of an inspection robot and each sub-equipment in the at least one to-be-inspected cabinet are determined according to the reference image information of the at least one to-be-inspected cabinet; target parameters corresponding to the to-be-collected data type of each sub-equipment are detected according to the relative positions of the inspection robot and each sub-equipment in the at least one to-be-inspected cabinet; and the target parameters are processed to obtain an inspection result.

Description

Technical Field

[0001] This application relates to the field of data center operation and maintenance, and in particular to a data center inspection method, device, equipment and storage medium. Background Technology

[0002] With the rapid development of technologies such as the Internet of Things, big data, and cloud computing, and the continuous advancement of digital transformation in various industries in China, the data center industry is developing rapidly, and my country has now become one of the fastest-growing regions for data center business in the world.

[0003] As data centers continue to expand in scale, inspection tasks become more numerous and complex, placing higher demands on data center operation and maintenance management. Traditional manual inspections struggle to accurately obtain the data required for these tasks, failing to meet actual needs. Therefore, there is an urgent need for a data center inspection method to improve the accuracy of data detection and better perform intelligent data center inspections. Summary of the Invention

[0004] This application provides a data center inspection method, apparatus, device, and storage medium to solve the problem in the prior art that it is difficult to accurately obtain the data required for inspection tasks and to meet the actual needs of inspection tasks.

[0005] In a first aspect, embodiments of this application provide a data center inspection method, the method comprising:

[0006] Receive inspection task instructions; the inspection task instructions include at least one cabinet to be inspected, the location information of the at least one cabinet to be inspected, and the data type to be collected corresponding to the at least one cabinet to be inspected;

[0007] Based on the preset driving map and the location information of the at least one cabinet to be inspected, determine at least one reference location information for the inspection robot;

[0008] Based on the at least one reference location information and the current location of the inspection robot, a first inspection route is determined in the preset driving map;

[0009] When the inspection robot moves to the at least one reference position information according to the first inspection route, it collects reference image information of the at least one cabinet to be inspected; and determines the relative position of the inspection robot and each sub-device in the at least one cabinet to be inspected based on the reference image information of the at least one cabinet to be inspected.

[0010] Based on the relative position of the inspection robot and each sub-device in the at least one cabinet to be inspected, the target parameters corresponding to the data type to be collected of each sub-device are detected.

[0011] The target parameters corresponding to the data types to be collected from each of the sub-devices are processed to obtain the inspection results.

[0012] The above method uses two positioning operations to accurately locate the cabinet to be inspected and each sub-device within it. Based on this precise positioning, target parameters are detected, enabling unmanned automatic inspection of the data center. This effectively avoids the impact and errors caused by human factors during manual inspection. By adopting this data center inspection method, inspection costs can be effectively reduced, inspection efficiency and the accuracy of data detection required for inspection tasks can be improved, achieving refined management of data center operation and maintenance and meeting the actual needs of inspection tasks.

[0013] In one possible implementation, determining at least one reference position information for the inspection robot based on a preset driving map and the location information of the at least one cabinet to be inspected includes:

[0014] Based on the correspondence between the location information of magnetic nails and the location information of cabinets in the preset driving map, determine the location information of at least one target magnetic nail corresponding to the location information of at least one cabinet to be inspected;

[0015] The position information of the at least one target magnetic nail is used as at least one reference position information of the inspection robot.

[0016] In the above method, positioning magnetic nails are set on the inspection route on the preset driving map. Then, the cabinet to be inspected is located according to the correspondence between the positioning magnetic nails and the cabinet's position information, thereby obtaining the parameter information of the cabinet to be inspected and completing the initial navigation and positioning movement of the inspection robot.

[0017] In one possible implementation, determining the relative position of the inspection robot to each sub-device in the at least one cabinet to be inspected, based on reference image information of the at least one cabinet to be inspected, includes:

[0018] Based on the reference image information of the at least one cabinet to be inspected, determine the three-dimensional spatial information of the at least one cabinet to be inspected;

[0019] Based on the three-dimensional spatial information, the relative positions of the inspection robot and each sub-device in the at least one cabinet to be inspected are determined.

[0020] In the above method, after the inspection robot completes a positioning using the positioning magnetic nail, it then takes a picture to collect reference image information of the cabinet to be inspected, and accurately positions each sub-device in the cabinet. This allows for precise positioning of the relative positions between the cabinet to be inspected, each sub-device, and the inspection robot.

[0021] In one possible implementation, processing the target parameters corresponding to the data types to be collected from each of the sub-devices includes:

[0022] Repair any abnormal data in the target parameters corresponding to the data types to be collected from each of the sub-devices.

[0023] The above method analyzes and processes the target parameters of each sub-device in the cabinet to be inspected, thereby repairing abnormal data in the target parameters, completing the inspection work, realizing refined management of data center operation and maintenance, and meeting the actual needs of inspection tasks.

[0024] In one possible implementation, abnormal data in the target parameters corresponding to the data type to be collected by each sub-device is repaired, including:

[0025] The target parameters corresponding to the data types to be collected in each of the sub-devices are compared with the stored preset parameters to obtain abnormal parameters;

[0026] In response to the user's repair operation, the abnormal parameter is replaced with the preset parameter.

[0027] The above method uses accurate preset parameters to replace the target parameters of each sub-device in the rack to be inspected, repairs the relevant faults of the rack to be inspected, completes the inspection work, realizes refined management of data center operation and maintenance, and meets the actual needs of inspection tasks.

[0028] In one possible implementation, the abnormal data in the target parameters corresponding to the data type to be collected by each of the sub-devices is repaired, including:

[0029] The reference image information of the at least one cabinet to be inspected is compared with the stored standard image information of the at least one cabinet to be inspected to obtain a comparison result; the comparison result represents the difference between at least one cabinet to be inspected in the reference image information and at least one cabinet to be inspected in the standard image information.

[0030] Based on the relative positions of each sub-device in the at least one cabinet to be inspected and the inspection robot, fault recovery is performed on the sub-devices with abnormal parameters in the comparison results.

[0031] The above method uses reference image information of the cabinet and its sub-devices to be inspected, obtained by taking photos, to compare with the standard image information in the background. It then determines the relevant faults of the cabinet and its sub-devices and repairs the relevant faults based on the relative positions of the sub-devices in at least one cabinet and the inspection robot. This completes the inspection work, realizes refined management of data center operation and maintenance, and meets the actual needs of inspection tasks.

[0032] In one possible implementation, receiving the inspection task instruction includes:

[0033] Receive the inspection task instruction corresponding to the current period's inspection task from the stored archive; or,

[0034] In response to the user's operation of setting inspection tasks on the touch screen of the inspection robot, the robot receives the corresponding inspection task instructions.

[0035] The above method involves receiving inspection instructions in two ways.

[0036] In one possible implementation, the method further includes:

[0037] Monitor the status of the inspection robot;

[0038] When the inspection robot is idle or powered off, charge the inspection robot.

[0039] In the above method, by monitoring the status of the inspection robot, the robot can be charged when it is idle or powered off, ensuring that the robot is always powered and ready to perform inspection tasks at any time.

[0040] Secondly, embodiments of this application provide a data center inspection device, the device comprising:

[0041] The receiving module is used to receive inspection task instructions; the inspection task instructions include at least one cabinet to be inspected, the location information of the at least one cabinet to be inspected, and the data type to be collected corresponding to the at least one cabinet to be inspected.

[0042] The first positioning module is used to determine at least one reference position information of the inspection robot based on the preset driving map and the position information of the at least one cabinet to be inspected.

[0043] The first route determination module is used to determine a first inspection route in the preset driving map based on the at least one reference position information and the current position of the inspection robot.

[0044] The second positioning module is used to collect reference image information of the at least one cabinet to be inspected when the inspection robot moves to the at least one reference position information according to the first inspection route; and to determine the relative position of the inspection robot and each sub-device in the at least one cabinet to be inspected according to the reference image information of the at least one cabinet to be inspected.

[0045] The parameter detection module is used to detect the target parameters corresponding to the data type to be collected of each sub-device based on the relative position of the inspection robot and each sub-device in the at least one cabinet to be inspected.

[0046] The parameter processing module is used to process the target parameters corresponding to the data types to be collected from each of the sub-devices to obtain the inspection results.

[0047] In one possible implementation, the first positioning module is specifically used for:

[0048] Based on the correspondence between the location information of magnetic nails and the location information of cabinets in the preset driving map, determine the location information of at least one target magnetic nail corresponding to the location information of at least one cabinet to be inspected;

[0049] The position information of the at least one target magnetic nail is used as at least one reference position information of the inspection robot.

[0050] In one possible implementation, the second positioning module is specifically used for:

[0051] Based on the reference image information of the at least one cabinet to be inspected, determine the three-dimensional spatial information of the at least one cabinet to be inspected;

[0052] Based on the three-dimensional spatial information, the relative positions of the inspection robot and each sub-device in the at least one cabinet to be inspected are determined.

[0053] In one possible implementation, the parameter processing module is specifically used for:

[0054] The target parameters corresponding to the data types to be collected in each of the sub-devices are repaired.

[0055] In one possible implementation, the parameter processing module is specifically used for:

[0056] The target parameters corresponding to the data types to be collected in each of the sub-devices are compared with the stored preset parameters to obtain abnormal parameters;

[0057] In response to the user's repair operation, the abnormal parameter is replaced with the preset parameter.

[0058] In one possible implementation, the parameter processing module is specifically used for:

[0059] The reference image information of the at least one cabinet to be inspected is compared with the stored standard image information of the at least one cabinet to be inspected to obtain a comparison result; the comparison result represents the difference between at least one cabinet to be inspected in the reference image information and at least one cabinet to be inspected in the standard image information.

[0060] Based on the relative positions of each sub-device in the at least one cabinet to be inspected and the inspection robot, fault recovery is performed on the sub-devices with abnormal parameters in the comparison results.

[0061] In one possible implementation, the receiving module is specifically used for:

[0062] Receive the inspection task instruction corresponding to the current period's inspection task from the stored archive; or,

[0063] In response to the user's operation of setting inspection tasks on the touch screen of the inspection robot, the robot receives the corresponding inspection task instructions.

[0064] In one possible implementation, the device further includes a charging module for:

[0065] Monitor the status of the inspection robot;

[0066] When the inspection robot is idle or powered off, charge the inspection robot.

[0067] Thirdly, embodiments of this application provide a data center inspection system, the system comprising an inspection robot, a navigation and positioning device, a photo positioning device, a detection device, a robotic arm device, and a control center; the navigation and positioning device, the photo positioning device, the robotic arm device, and the detection device are mounted on the inspection robot; wherein:

[0068] The inspection robot is used to receive inspection task instructions; the inspection task instructions include at least one cabinet to be inspected, the location information of the at least one cabinet to be inspected, and the data type to be collected corresponding to the at least one cabinet to be inspected.

[0069] The navigation and positioning device is used to determine at least one reference position information of the inspection robot based on a preset driving map and the position information of the at least one cabinet to be inspected; and to determine a first inspection route in the preset driving map based on the at least one reference position information and the current position of the inspection robot.

[0070] The inspection robot is used to move according to the first inspection route;

[0071] The image positioning device is used to collect reference image information of the at least one cabinet to be inspected when the inspection robot moves to the at least one reference position information according to the first inspection route; and to determine the relative position of the inspection robot and each sub-device in the at least one cabinet to be inspected based on the reference image information of the at least one cabinet to be inspected.

[0072] The robotic arm device is used to move the detection device from its initial position to each of the sub-devices in the inspection robot according to the relative position of the inspection robot and each of the sub-devices in the at least one cabinet to be inspected;

[0073] The detection device is used to detect the target parameters corresponding to the data types to be collected in each of the sub-devices and send them to the control center;

[0074] The control center is used to process the target parameters corresponding to the data types to be collected from each of the sub-devices to obtain the inspection results.

[0075] In one possible implementation, the navigation and positioning device is specifically used for:

[0076] Based on the correspondence between the location information of magnetic nails and the location information of cabinets in the preset driving map, determine the location information of at least one target magnetic nail corresponding to the location information of at least one cabinet to be inspected;

[0077] The position information of the at least one target magnetic nail is used as at least one reference position information of the inspection robot.

[0078] In one possible implementation, the image positioning device is specifically used for:

[0079] Based on the reference image information of the at least one cabinet to be inspected, determine the three-dimensional spatial information of the at least one cabinet to be inspected;

[0080] Based on the three-dimensional spatial information, the relative positions of the inspection robot and each sub-device in the at least one cabinet to be inspected are determined.

[0081] In one possible implementation, the robotic arm device is further used for:

[0082] After detecting the target parameters corresponding to the data types to be collected in each of the sub-devices, the detection device is moved to the initial position.

[0083] In one possible implementation, the control center is specifically used for:

[0084] Repair any abnormal data in the target parameters corresponding to the data types to be collected from each of the sub-devices.

[0085] In one possible implementation, the control center is specifically used for:

[0086] The target parameters corresponding to the data types to be collected in each of the sub-devices are compared with the stored preset parameters to obtain abnormal parameters;

[0087] In response to the user's repair operation, the abnormal parameter is replaced with the preset parameter.

[0088] In one possible implementation, the control center is specifically configured to: compare the reference image information of the at least one cabinet to be inspected with the stored standard image information of the at least one cabinet to be inspected, and obtain a comparison result; the comparison result characterizes the difference between the at least one cabinet to be inspected in the reference image information and the at least one cabinet to be inspected in the standard image information; and send the comparison result and the relative positions of each sub-device in the at least one cabinet to be inspected and the inspection robot to the robotic arm device;

[0089] The robotic arm device is used to receive the comparison results sent by the control center, and to perform fault recovery on the sub-devices with abnormal parameters in the comparison results according to the relative positions of each sub-device in the at least one cabinet to be inspected and the inspection robot.

[0090] In one possible implementation, the inspection robot is specifically used for:

[0091] Receive the inspection task instruction corresponding to the current period's inspection task from the stored archive; or,

[0092] In response to the user's operation of setting inspection tasks on the touch screen of the inspection robot, the robot receives the corresponding inspection task instructions.

[0093] In one possible implementation, the system further includes a cabinet information acquisition device;

[0094] The cabinet information acquisition device is used to: acquire target parameters corresponding to the data type to be acquired for the at least one cabinet to be inspected.

[0095] In one possible implementation, the system further includes a charging device for:

[0096] Monitor the status of the inspection robot;

[0097] When the inspection robot is idle or powered off, charge the inspection robot.

[0098] Fourthly, an electronic device is provided, comprising a processor and a memory, wherein the memory stores program code that, when executed by the processor, causes the processor to perform the steps of the data center inspection method described in the first aspect.

[0099] Fifthly, a computer-readable storage medium is provided, comprising program code that, when executed on an electronic device, causes the electronic device to perform the steps of the data center inspection method described in the first aspect.

[0100] Other features and advantages of this application will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the application. The objectives and other advantages of this application may be realized and obtained by means of the structures particularly pointed out in the written description, claims, and drawings. Attached Figure Description

[0101] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments of this application and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0102] Figure 1 A structural block diagram of a data center inspection system provided in this application embodiment;

[0103] Figure 2 A flowchart illustrating a data center inspection method provided in this application embodiment;

[0104] Figure 3 A schematic diagram of a data center inspection system provided in an embodiment of this application;

[0105] Figure 4 A structural block diagram of a data center inspection system provided in this application embodiment;

[0106] Figure 5 A flowchart illustrating a data center inspection method provided in this application embodiment;

[0107] Figure 6 This application provides a schematic flowchart for determining reference position information in an embodiment of the present application.

[0108] Figure 7 This application provides a schematic diagram of a process for determining target location information in an embodiment of the present application.

[0109] Figure 8 This is a schematic diagram illustrating a process for repairing abnormal data, provided as an embodiment of this application.

[0110] Figure 9 This is a schematic diagram illustrating a process for repairing abnormal data, provided as an embodiment of this application.

[0111] Figure 10 A schematic diagram illustrating a process for charging an inspection robot, provided as an embodiment of this application;

[0112] Figure 11 This is a schematic diagram of the structure of a data center inspection device provided in an embodiment of this application;

[0113] Figure 12 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0114] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. The described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0115] Furthermore, in the description of the embodiments of this application, unless otherwise stated, " / " means "or". For example, A / B can mean A or B. The "and / or" in the text is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist simultaneously, and B exists alone. In addition, in the description of the embodiments of this application, "multiple" means two or more.

[0116] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined with "first" and "second" may explicitly or implicitly include one or more of that feature, and in the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more.

[0117] With the rapid development of technologies such as the Internet of Things, big data, and cloud computing, and the continuous advancement of digital transformation in various industries in China, the data center industry is developing rapidly, and my country has now become one of the fastest-growing regions for data center business in the world.

[0118] As data centers continue to expand in scale, inspection tasks become more numerous and complex, placing higher demands on data center operation and maintenance management. Traditional manual inspections struggle to accurately obtain the data required for these tasks, failing to meet actual needs. Therefore, there is an urgent need for a data center inspection method to improve the accuracy of data detection and better perform intelligent data center inspections.

[0119] In view of this, embodiments of this application provide a data center inspection method, apparatus, device, and storage medium to solve the problem in the prior art that it is difficult to accurately obtain the data required for inspection tasks and to meet the actual needs of inspection tasks.

[0120] The inventive concept of this application can be summarized as follows: By receiving an inspection task instruction including at least one cabinet to be inspected, the location information of at least one cabinet to be inspected, and the data type to be collected corresponding to at least one cabinet to be inspected; performing initial positioning based on a preset driving map and the location information of at least one cabinet to be inspected; when moving to the reference position information of the initial positioning according to the inspection route corresponding to the initial positioning, collecting reference image information of at least one cabinet to be inspected; determining the relative position of the inspection robot and each sub-device in the at least one cabinet to be inspected based on the reference image information of the at least one cabinet to be inspected; detecting the target parameters corresponding to the data type to be collected of each sub-device based on the relative position of the inspection robot and each sub-device in the at least one cabinet to be inspected; and processing the target parameters to obtain the inspection results, the inspection efficiency and accuracy can be improved.

[0121] After introducing the main inventive concepts of the embodiments of this application, the data center inspection system corresponding to the data center inspection method provided in the embodiments of this application will be described below with reference to the accompanying drawings. For example... Figure 1 The diagram shown is a structural block diagram of the data center inspection system provided in an embodiment of this application.

[0122] Among them, such as Figure 1 As shown, the data center inspection system of this application embodiment includes an inspection robot, a navigation and positioning device, a photo positioning device, a detection device, a robotic arm device, and a control center; the navigation and positioning device, the photo positioning device, the robotic arm device, and the detection device are mounted on the inspection robot; wherein:

[0123] The inspection robot is used to receive inspection task instructions. The inspection task instructions include at least one cabinet to be inspected, the location information of at least one cabinet to be inspected, and the data type to be collected corresponding to at least one cabinet to be inspected.

[0124] The navigation and positioning device is used to determine at least one reference position information of the inspection robot based on a preset driving map and the position information of at least one cabinet to be inspected; and to determine a first inspection route in the preset driving map based on at least one reference position information and the current position of the inspection robot.

[0125] The inspection robot is used to move according to the first inspection route;

[0126] The image positioning device is used to collect reference image information of at least one cabinet to be inspected when the inspection robot moves to at least one reference position information according to the first inspection route; and to determine the relative position of the inspection robot and each sub-device in the at least one cabinet to be inspected based on the reference image information of the at least one cabinet to be inspected.

[0127] A robotic arm device is used to move the inspection device from its initial position to each sub-device based on the relative position of the inspection robot and each sub-device in at least one cabinet to be inspected.

[0128] The detection device is used to detect the target parameters corresponding to the data types to be collected from each sub-device and send them to the control center;

[0129] The control center processes the target parameters corresponding to the data types to be collected from each sub-device to obtain the inspection results.

[0130] In one possible implementation, Figure 1 The inspection robot shown can receive inspection task instructions in the following two ways:

[0131] Method 1: Receive the inspection task instruction corresponding to the current cycle's inspection task from the stored data.

[0132] Method 2: Responding to the user's operation of setting inspection tasks on the touch screen of the inspection robot, receiving the corresponding inspection task instructions.

[0133] Figure 1 The inspection robot shown interacts with other devices through communication technology and is the main part of the data center inspection system. It can automatically walk according to the inspection route and stop moving at the location information of the specific cabinet to be inspected, perform relevant data detection, and complete the inspection task.

[0134] In this embodiment, the inspection robot can be equipped with a touch screen, allowing users to operate on the touch screen to set relevant parameters of the data center inspection system, issue inspection task instructions, and monitor relevant parameter information of the inspection task.

[0135] The inspection task instruction includes at least one cabinet to be inspected, the location information of at least one cabinet to be inspected, and the data type to be collected corresponding to at least one cabinet to be inspected.

[0136] Relevant parameters of the data center inspection system include, but are not limited to, the travel speed of the inspection robot and the frequency of parameter collection.

[0137] In one possible implementation, Figure 1 When the navigation and positioning device shown determines at least one reference position information for the inspection robot based on a preset driving map and the location information of at least one cabinet to be inspected, it specifically performs the following actions:

[0138] Based on the correspondence between the location information of magnetic nails and the location information of cabinets in the preset driving map, determine the location information of at least one target magnetic nail corresponding to the location information of at least one cabinet to be inspected;

[0139] The position information of at least one target magnetic nail is used as at least one reference position information for the inspection robot.

[0140] Specifically, the implementation is as follows: Figure 1 The navigation and positioning device shown includes positioning magnetic nails set on all inspection routes of the preset driving map and magnetic nail sensing devices on the bottom of the inspection robot. Based on the correspondence between the position information of the magnetic nails and the position information of the cabinets, the position information of at least one target magnetic nail corresponding to the position information of at least one cabinet to be inspected can be determined, thereby determining the reference position information.

[0141] Figure 1 When the navigation and positioning device shown determines the first inspection route in a preset driving map based on at least one reference position information and the current position of the inspection robot, it can calculate the route with the shortest distance from the current position to at least one reference position information in the preset driving map, and take the route with the shortest distance as the first inspection route. Then, the inspection robot detects each positioning magnetic nail on the first inspection route through the magnetic nail sensing device, and moves according to the position information of the sensing positioning magnetic nail, thus completing the navigation of the inspection robot and realizing the positioning movement of the inspection robot on the first inspection route.

[0142] like Figure 2 As shown in the figure, this is a data center inspection method provided in an embodiment of this application. This method only performs one location check and mainly includes the following: Figure 2 The steps shown are as follows:

[0143] In step 201, an inspection task instruction is received; the inspection task instruction includes at least one cabinet to be inspected, the location information of at least one cabinet to be inspected, and the data type to be collected corresponding to at least one cabinet to be inspected.

[0144] In step 202, at least one reference position information of the inspection robot is determined based on the preset driving map and the position information of at least one cabinet to be inspected;

[0145] In step 203, a first inspection route is determined in a preset driving map based on at least one reference position information and the current position of the inspection robot; and the robot moves according to the first inspection route.

[0146] In step 204, when the object moves to at least one target location, the target parameter corresponding to the data type to be collected is detected.

[0147] The data types to be collected include temperature, humidity, pressure, and asset information.

[0148] In step 205, the target parameters corresponding to the data type to be collected are processed to obtain the inspection results.

[0149] Specifically, this can be implemented by comparing the target parameters corresponding to the detected data type to be collected with the preset parameters stored in the background, detecting abnormal parameters and issuing alarm prompts, and simultaneously repairing the abnormal parameters; and automatically completing various tasks based on the target parameters corresponding to the detected data type to be collected, such as drawing temperature cloud maps and asset inventory.

[0150] In step 206, the inspection robot completes the inspection task and returns to the standby position or directly begins to execute the next inspection task.

[0151] In order to more accurately locate and inspect the server racks, Figure 1 The data center inspection system shown includes a photo positioning device. This device is used to acquire reference image information of at least one rack to be inspected when the inspection robot moves to at least one reference location according to a first inspection route; and to determine the relative position of the inspection robot to each sub-device within the rack based on the reference image information of the at least one rack.

[0152] in, Figure 1 When the image-based positioning device shown determines the relative position of the inspection robot and each sub-device in at least one cabinet to be inspected based on reference image information, it can be implemented as follows:

[0153] Based on reference image information of at least one cabinet to be inspected, determine the three-dimensional spatial information of at least one cabinet to be inspected.

[0154] Based on three-dimensional spatial information, the relative positions of the inspection robot and each sub-device in at least one cabinet to be inspected are determined.

[0155] In practice, Figure 1The image positioning device shown can be set up Figure 1 The inspection robot shown undergoes an initial positioning process via its navigation and positioning device. It then uses visual imaging to acquire reference image information of at least one cabinet to be inspected. Based on this reference image information, three-dimensional spatial information of the cabinet can be obtained. Finally, based on this three-dimensional spatial information, the relative positions of the inspection robot and each sub-device within the cabinet are determined.

[0156] For example, the relative positions of the inspection robot and each sub-device in at least one cabinet to be inspected can be calculated using the relative distances along the X, Y, and Z axes in three-dimensional space. This allows for precise positioning of the relative positions between the cabinet to be inspected, its sub-devices, and the inspection robot, providing accurate position coordinates for subsequent inspection tasks such as detecting target parameters and troubleshooting.

[0157] In one possible implementation, in order to detect the target parameters corresponding to the data types to be collected from each sub-device, after determining the relative positions of the inspection robot and each sub-device in at least one cabinet to be inspected... Figure 1 The robotic arm shown moves the detection device from its initial position to each sub-device based on the relative position of the inspection robot and each sub-device in at least one cabinet to be inspected. Then, the detection device detects the target parameters corresponding to the data types to be collected from each sub-device.

[0158] Furthermore, in one possible implementation, Figure 1 The robotic arm device shown is also used to move the detection device to the initial position after detecting the target parameters corresponding to the data types to be collected from each sub-device.

[0159] Among them, the robotic arm device is a multi-joint, multi-degree-of-freedom robotic arm device. After the inspection robot performs secondary positioning, it obtains the precise position coordinates of the cabinet to be inspected and each sub-device (IT equipment), and completes the relevant inspection work through the robotic arm device.

[0160] For example, based on the relative position of the inspection robot and each sub-device (IT device), the wireless detection device can be precisely placed on each sub-device (IT device) to complete the accurate measurement of the relevant detection parameters of each sub-device (IT device), complete the establishment of relevant models, accurately judge the data center operation status, and after the measurement is completed, the wireless detection device can be returned to its original position.

[0161] like Figure 3As shown, cabinet A1 includes multiple sub-devices: sub-device a1, sub-device a2, sub-device a3, and sub-device a4. After the inspection robot performs secondary positioning, the relative position between the inspection robot and sub-device a1 is obtained. The robotic arm places the detection device in the detection device on sub-device a1, completes the accurate measurement of the relevant detection parameters of sub-device a1, completes the establishment of the relevant model, accurately judges the data center operation status, and puts the wireless detection device back to its original position after the measurement is completed.

[0162] To detect the target parameters corresponding to the data types to be collected from each sub-device and the target parameters of at least one rack to be inspected, the data center inspection system in this embodiment includes... Figure 1 The detection device shown is used to detect the target parameters corresponding to the data types to be collected of each sub-device based on the relative position of the inspection robot and each sub-device in at least one cabinet to be inspected, and send them to the control center.

[0163] in, Figure 1 The detection device shown includes various wired and / or wireless detection equipment. During measurement, the device position can automatically change according to the task, such as particle measuring instruments, temperature sensors, humidity sensors, pressure sensors, wind speed sensors, noise sensors, vibration sensors, and RFID readers. The detection device acquires target parameters corresponding to the data type to be collected for at least one cabinet to be inspected through various detection devices, and transmits them to the inspection robot. The inspection robot then transmits them to the control center, where these target parameters are stored, analyzed, and diagnosed.

[0164] The detection device is located on the inspection equipment placement platform of the inspection robot, and the platform can charge the detection device at the same time.

[0165] In one possible implementation, after the detected target parameters are sent to the control center, the control center stores, analyzes, and diagnoses the target parameters. The control center can also repair abnormal data in the target parameters corresponding to the data types to be collected from each sub-device.

[0166] In one possible implementation, when the control center repairs abnormal data in the target parameters corresponding to the data types to be collected from each sub-device, the specific execution is as follows:

[0167] The target parameters corresponding to the data types to be collected from each sub-device are compared with the stored preset parameters to obtain abnormal parameters; in response to the user's repair operation, the abnormal parameters are replaced with preset parameters.

[0168] In one possible implementation, when the control center repairs abnormal data in the target parameters corresponding to the data type to be collected, the specific execution is as follows: the reference image information of at least one cabinet to be inspected is compared with the standard image information of at least one cabinet to be inspected stored, and a comparison result is obtained; the comparison result represents the difference between at least one cabinet to be inspected in the reference image information and at least one cabinet to be inspected in the standard image information; and the comparison result and the relative positions of each sub-device in at least one cabinet to be inspected and the inspection robot are sent to the robotic arm device.

[0169] Then, the robotic arm receives the comparison results sent by the control center and, based on the relative positions of each sub-device in at least one cabinet to be inspected and the inspection robot, performs fault recovery on the sub-devices with abnormal parameters in the comparison results.

[0170] In practice, Figure 1 The control center shown includes a server, monitor, and communication network, enabling communication and information monitoring between inspection robots, navigation and positioning devices, photo positioning devices, detection devices, cabinet information acquisition devices, robotic arms, and charging devices. It can also plan automatic inspection routes, store and issue inspection task instructions corresponding to the current cycle's inspection tasks, store, analyze, and diagnose target parameters, and display the position and working status of the inspection robot on the inspection route, as well as the relevant settings of the entire data center inspection system for management personnel.

[0171] Among them, the robotic arm device is a multi-joint, multi-degree-of-freedom robotic arm device. After the inspection robot is positioned twice, it obtains the precise position coordinates of the cabinet to be inspected and each sub-device (IT device). By using the relative position of the inspection robot and each sub-device (IT device), it can complete the operation and maintenance of the cabinet to be inspected and each sub-device (IT device).

[0172] For example, the control center compares the reference image information of at least one cabinet to be inspected with the standard image information of at least one cabinet to be inspected stored, obtains the comparison result and sends it to the robotic arm device. The robotic arm device can then perform fault recovery on the sub-devices with abnormal parameters in the comparison result based on the relative position of the inspection robot and each sub-device (IT device). For example, by obtaining the reference network cable insertion image of a cabinet through the photo positioning device, and comparing it with the standard network cable insertion image in the background, the comparison result is that the network cable of the cabinet is loose. Then, by obtaining the relative position of the inspection robot and each sub-device (IT device) after secondary positioning, the network cable is tightened.

[0173] In one possible implementation, Figure 1The system shown also includes a cabinet information acquisition device, which is used to acquire target parameters corresponding to the data type to be acquired for at least one cabinet to be inspected.

[0174] In this embodiment of the application, a cabinet information acquisition device is set on each cabinet or several adjacent cabinets, including a controller and various sensors, which are set at the corresponding positions of the cabinet to acquire relevant information of the cabinet.

[0175] For example, each sub-device (IT device) is equipped with a cabinet RFID tag. The inspection robot can use the RFID reader in the detection device to detect the cabinet RFID tag and the RFID tag of each sub-device (IT device) in the corresponding cabinet information collection device, and complete the collection of asset information in the target parameters of the cabinet and each sub-device (IT device).

[0176] In one possible implementation, Figure 1 The rack information acquisition device shown can also collect the physical information of all racks in real time and send it directly to the corresponding devices. For example, rack detection sensors (such as photoelectric switches, mechanical switches, etc.), rack door position sensors, PDUs (Power Distribution Units), and hot and cold aisle door controllers are set on each sub-device (IT equipment). Then, the rack occupancy rate is obtained through the rack detection sensors and sent to the control center; the rack door position sensors are used to determine whether the rack is open or closed and are sent to the inspection robot and robotic arm so that the inspection robot and robotic arm can perform parameter detection on the rack to be inspected; the power consumption of the IT equipment is obtained through the PDU; after the rack information acquisition device receives the parameter detection information of the rack to be processed by the inspection robot and robotic arm, and controls the hot and cold aisle door to open and the detection is completed, the hot and cold aisle door controller controls the hot and cold aisle door to close.

[0177] In one possible implementation, to ensure the inspection robot is always powered and ready to perform inspection tasks at any time, such as... Figure 1 As shown, the data center inspection system in this application embodiment also includes a charging device for: monitoring the status of the inspection robot; and charging the inspection robot when it is in an idle state or a powered-off state.

[0178] To facilitate the data center inspection system in this application embodiment, the following is combined with... Figure 4 The structural block diagram is used to illustrate this.

[0179] like Figure 4As shown, the data center inspection system includes an inspection robot S1, a navigation and positioning device S2, a photo positioning device S3, a detection device S4, a cabinet information acquisition device S5, a robotic arm device S6, a control center S7, and a charging device S8.

[0180] The navigation and positioning device S2, the photo positioning device S3, the detection device S4, and the robotic arm device S6 are mounted on the inspection robot S1; the charging device S8 is located in the standby position of the inspection robot; and the cabinet information collection device S5 is mounted on each cabinet or several adjacent cabinets. The control center S7 can be a server or a terminal device.

[0181] The server room includes racks A1, A2, A3, A4, B1, B2, B3, B4, C1, C2, C3, C4, D1, D2, D3, and D4. The racks to be inspected are some or all of racks A1, A2, A3, A4, B1, B2, B3, B4, C1, C2, C3, C4, D1, D2, D3, and D4. Multiple positioning magnetic nails are set near the racks. All the positioning magnetic nails are connected to obtain the inspection route in the preset driving map. The inspection robot moves on the inspection route in the preset driving map to execute the inspection task according to the inspection task instructions.

[0182] Based on the same inventive concept, this application also provides a data center inspection method, which performs two positioning operations, mainly including as follows: Figure 5 The steps shown are as follows:

[0183] In step 501, an inspection task instruction is received; the inspection task instruction includes at least one cabinet to be inspected, the location information of at least one cabinet to be inspected, and the data type to be collected corresponding to at least one cabinet to be inspected.

[0184] In one possible implementation, the inspection task instruction can be received in the following manner in this embodiment of the application:

[0185] Receive the inspection task instruction corresponding to the current period's inspection task from the stored archive; or,

[0186] In response to the user's operation of setting inspection tasks on the touch screen of the inspection robot, the robot receives the corresponding inspection task instructions.

[0187] In step 502, at least one reference position information of the inspection robot is determined based on the preset driving map and the position information of at least one cabinet to be inspected.

[0188] In one possible implementation, this application determines at least one reference position information for the inspection robot based on a preset driving map and the position information of at least one cabinet to be inspected, which can be executed as follows: Figure 6The steps shown are as follows:

[0189] In step 601, based on the correspondence between the location information of the magnetic nails and the location information of the cabinets in the preset driving map, the location information of at least one target magnetic nail corresponding to the location information of at least one cabinet to be inspected is determined.

[0190] In step 602, the position information of at least one target magnetic nail is used as at least one reference position information of the inspection robot.

[0191] Therefore, by setting positioning magnetic nails on the inspection route on the preset driving map, the cabinet to be inspected is located according to the correspondence between the positioning magnetic nails and the cabinet's position information, thereby obtaining the parameter information of the cabinet to be inspected and completing the initial navigation and positioning movement of the inspection robot.

[0192] In step 503, a first inspection route is determined in a preset driving map based on at least one reference position information and the current position of the inspection robot.

[0193] In step 504, when the inspection robot moves to at least one reference position information according to the first inspection route, it collects reference image information of at least one cabinet to be inspected; and based on the reference image information of at least one cabinet to be inspected, it determines the relative position of the inspection robot and each sub-device in at least one cabinet to be inspected.

[0194] In one possible implementation, this application determines the relative position of the inspection robot to each sub-device in at least one cabinet based on reference image information of at least one cabinet to be inspected, which can be executed as follows: Figure 7 The steps shown are as follows:

[0195] In step 701, the three-dimensional spatial information of at least one cabinet to be inspected is determined based on the reference image information of at least one cabinet to be inspected.

[0196] In step 702, based on three-dimensional spatial information, the relative positions of the inspection robot and each sub-device in at least one cabinet to be inspected are determined.

[0197] Therefore, after the inspection robot completes one positioning using the positioning magnetic nail, it can then take a picture to collect reference image information of the cabinet to be inspected and reposition each sub-device in the cabinet. This allows for precise positioning of the relative position between the inspection robot and each sub-device in the cabinet, making the position information obtained by the inspection robot more accurate, enabling it to collect more accurate data, and improving the efficiency of the inspection task.

[0198] In step 505, the target parameters corresponding to the data types to be collected for each sub-device are detected based on the relative positions of the inspection robot and each sub-device in at least one cabinet to be inspected.

[0199] In step 506, the target parameters corresponding to the data types to be collected from each sub-device are processed to obtain the inspection results.

[0200] In one possible implementation, the processing of the target parameters corresponding to the data type to be collected in this application can be performed as follows: repairing abnormal data in the target parameters corresponding to the data type to be collected of each sub-device.

[0201] Therefore, the target parameters of each sub-device in the inspection cabinet are analyzed and processed to repair abnormal data in the target parameters, complete the inspection work, realize refined management of data center operation and maintenance, and meet the actual needs of inspection tasks.

[0202] In one possible implementation, the repair of abnormal data in the target parameters corresponding to the data types to be collected by each sub-device can be performed as follows: Figure 8 The steps shown are as follows:

[0203] In step 801, the target parameters corresponding to the data types to be collected from each sub-device are compared with the stored preset parameters to obtain abnormal parameters;

[0204] In step 802, in response to the user's repair operation, the abnormal parameters are replaced with preset parameters.

[0205] For example, based on the precise location coordinates of the racks and various sub-devices (IT devices) to be inspected, the testing equipment is precisely placed on the racks and various sub-devices (IT devices) to be inspected, and the relevant testing parameters of the racks and various sub-devices (IT devices) to be inspected are measured to complete the establishment of relevant models and accurately determine the operating status of the data center.

[0206] Therefore, by using accurate preset parameters to replace the target parameters of each sub-device in the rack to be inspected, the relevant faults of the rack to be inspected are repaired, the inspection work is completed, the data center operation and maintenance is refined, and the actual needs of the inspection task are met.

[0207] In one possible implementation, the repair of abnormal data in the target parameters corresponding to the data types to be collected by each sub-device can be performed as follows: Figure 9 The steps shown are as follows:

[0208] In step 901, the reference image information of at least one cabinet to be inspected is compared with the standard image information of at least one cabinet to be inspected stored to obtain a comparison result; the comparison result characterizes the difference between at least one cabinet to be inspected in the reference image information and at least one cabinet to be inspected in the standard image information.

[0209] In step 902, based on the relative positions of each sub-device in at least one cabinet to be inspected and the inspection robot, fault recovery is performed on the sub-devices with abnormal parameters in the comparison results.

[0210] For example, the reference image information of at least one cabinet to be inspected is compared with the standard image information of at least one cabinet to be inspected stored. After the comparison result is sent to the robotic arm device, the robotic arm device can perform fault recovery on the sub-devices with abnormal parameters in the comparison result according to the precise position coordinates of the cabinet to be inspected and each sub-device (IT device). For example, the reference network cable plug image of a cabinet is obtained by the photo positioning device. By comparing it with the standard network cable plug image in the background, the comparison result is that the network cable plug of the cabinet is loose. After a second precise positioning, the position information of the second positioning of the robotic arm device completes the clamping operation of the network cable.

[0211] Therefore, by using reference image information of the racks and sub-devices to be inspected obtained by taking photos, and comparing it with the standard image information in the background, the relevant faults of the racks and sub-devices to be inspected can be determined. Then, based on the relative position of each sub-device in at least one rack to be inspected and the inspection robot, the relevant faults can be repaired, the inspection work can be completed, and the refined management of data center operation and maintenance can be realized to meet the actual needs of inspection tasks.

[0212] In step 507, the inspection robot completes the inspection task and returns to the standby position or directly begins to execute the next inspection task.

[0213] In one possible implementation, to ensure that the inspection robot can perform inspection tasks, it is also necessary to... Figure 10 The steps shown are as follows:

[0214] In step 1001, the status of the inspection robot is monitored;

[0215] In step 1002, when the inspection robot is in an idle state or a powered-off state, the inspection robot is charged.

[0216] Therefore, by monitoring the status of the inspection robot, it can be charged to ensure that the inspection robot is always powered and ready to perform inspection tasks at any time.

[0217] Based on the preceding description, the system receives an inspection task instruction including at least one cabinet to be inspected, the location information of at least one cabinet to be inspected, and the data type to be collected corresponding to at least one cabinet to be inspected; performs initial positioning based on a preset driving map and the location information of at least one cabinet to be inspected; when the robot moves to the reference position information of the initial positioning according to the inspection route corresponding to the initial positioning, it collects reference image information of at least one cabinet to be inspected; determines the relative position of the inspection robot to each sub-device in at least one cabinet to be inspected based on the reference image information of at least one cabinet to be inspected; detects the target parameters corresponding to the data type to be collected of each sub-device based on the relative position of the inspection robot to each sub-device in at least one cabinet to be inspected; and processes the target parameters to obtain the inspection results.

[0218] Therefore, by performing two positioning operations, the cabinet to be inspected and each sub-device within the cabinet can be accurately located. Based on this precise positioning, target parameters can be detected, enabling unmanned automatic inspection of the data center. This effectively avoids the impact and errors caused by human factors during manual inspection. By adopting this data center inspection method, inspection costs can be effectively reduced, inspection efficiency and the accuracy of data detection required for inspection tasks can be improved, achieving refined management of data center operation and maintenance and meeting the actual needs of inspection tasks.

[0219] Based on the same inventive concept, embodiments of this application also provide a data center inspection device. For example... Figure 11 As shown, the device includes:

[0220] The receiving module 1101 is used to receive inspection task instructions; the inspection task instructions include at least one cabinet to be inspected, the location information of the at least one cabinet to be inspected, and the data type to be collected corresponding to the at least one cabinet to be inspected.

[0221] The first positioning module 1102 is used to determine at least one reference position information of the inspection robot based on the preset driving map and the position information of the at least one cabinet to be inspected.

[0222] The first route determination module 1103 is used to determine a first inspection route in the preset driving map based on the at least one reference position information and the current position of the inspection robot.

[0223] The second positioning module 1104 is used to collect reference image information of the at least one cabinet to be inspected when the inspection robot moves to the at least one reference position information according to the first inspection route; and to determine the relative position of the inspection robot and each sub-device in the at least one cabinet to be inspected according to the reference image information of the at least one cabinet to be inspected.

[0224] The parameter detection module 1105 is used to detect the target parameters corresponding to the data type to be collected of each sub-device based on the relative position of the inspection robot and each sub-device in the at least one cabinet to be inspected.

[0225] The parameter processing module 1106 is used to process the target parameters corresponding to the data types to be collected by each sub-device to obtain the inspection results.

[0226] In one possible implementation, the first positioning module 1102 is specifically used for:

[0227] Based on the correspondence between the location information of magnetic nails and the location information of cabinets in the preset driving map, determine the location information of at least one target magnetic nail corresponding to the location information of at least one cabinet to be inspected;

[0228] The position information of the at least one target magnetic nail is used as at least one reference position information of the inspection robot.

[0229] In one possible implementation, the second positioning module 1104 is specifically used for:

[0230] Based on the reference image information of the at least one cabinet to be inspected, determine the three-dimensional spatial information of the at least one cabinet to be inspected;

[0231] Based on the three-dimensional spatial information, the relative positions of the inspection robot and each sub-device in the at least one cabinet to be inspected are determined.

[0232] In one possible implementation, the parameter processing module 1106 is specifically used for:

[0233] Repair any abnormal data in the target parameters corresponding to the data types to be collected from each of the sub-devices.

[0234] In one possible implementation, the parameter processing module 1106 is specifically used for:

[0235] The target parameters corresponding to the data types to be collected in each of the sub-devices are compared with the stored preset parameters to obtain abnormal parameters;

[0236] In response to the user's repair operation, the abnormal parameter is replaced with the preset parameter.

[0237] In one possible implementation, the parameter processing module 1106 is specifically used for:

[0238] The reference image information of the at least one cabinet to be inspected is compared with the stored standard image information of the at least one cabinet to be inspected to obtain a comparison result; the comparison result represents the difference between at least one cabinet to be inspected in the reference image information and at least one cabinet to be inspected in the standard image information.

[0239] Based on the relative positions of each sub-device in the at least one cabinet to be inspected and the inspection robot, fault recovery is performed on the sub-devices with abnormal parameters in the comparison results.

[0240] In one possible implementation, the receiving module 1101 is specifically used for:

[0241] Receive the inspection task instruction corresponding to the current period's inspection task from the stored archive; or,

[0242] In response to the user's operation of setting inspection tasks on the touch screen of the inspection robot, the robot receives the corresponding inspection task instructions.

[0243] In one possible implementation, the device further includes a charging module 1107, used for:

[0244] Monitor the status of the inspection robot;

[0245] When the inspection robot is idle or powered off, charge the inspection robot.

[0246] Based on the same inventive concept, this application also provides an electronic device 1200, referring to... Figure 12 As shown, the electronic device 1200 is used to implement the methods described in the above-described method embodiments, such as the data center inspection method shown above. The electronic device 1200 may include a memory 1201, a processor 1202, an input unit 1203, and a display panel 1204.

[0247] The memory 1201 stores computer programs executed by the processor 1202. The memory 1201 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, applications required for at least one function, etc.; the data storage area may store data created based on the use of the electronic device 1200, etc. The processor 1202 may be a central processing unit (CPU) or a digital processing unit, etc. The input unit 1203 may be used to acquire user input commands. The display panel 1204 is used to display information input by the user or information provided to the user. In this embodiment, the display panel 1204 is mainly used to display the display interfaces of various applications in the electronic device and the control entities displayed in each display interface. Optionally, the display panel 1204 may be configured as a liquid crystal display (LCD) or an OLED (organic light-emitting diode), etc.

[0248] This application embodiment does not limit the specific connection medium between the memory 1201, processor 1202, input unit 1203, and display panel 1204. This application embodiment... Figure 12 The memory 1201, processor 1202, input unit 1203, and display panel 1204 are connected via a bus 1205, and the bus 1205 is in... Figure 12 The connections between other components are shown in thick lines only and are not intended to be limiting. The 1205 bus can be divided into address bus, data bus, control bus, etc. For ease of illustration, Figure 12 It is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0249] Memory 1201 may be volatile memory, such as random-access memory (RAM); memory 1201 may also be non-volatile memory, such as read-only memory, flash memory, hard disk drive (HDD), or solid-state drive (SSD); or memory 1201 may be any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but is not limited thereto. Memory 1201 may be a combination of the above-described memories.

[0250] The processor 1202 is used to call the computer program stored in the memory 1201 to execute the data center inspection method as described above.

[0251] This application also provides a computer-readable storage medium including program code that, when run on an electronic device, causes the electronic device to perform the steps of the data center inspection method described in the first aspect above.

[0252] In some possible implementations, various aspects of the data center inspection method provided in this application can also be implemented as a program product, including program code. When the program product is run on an electronic device, the program code causes the electronic device to perform the steps of a data center inspection method according to various exemplary embodiments of this application described above. For example, the electronic device can perform the data center inspection method as shown above.

[0253] The program product may employ any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of readable storage media include: electrical connections having one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0254] The implementation of this application for a data center inspection program product can employ a portable compact disc read-only memory (CD-ROM) and include program code, and can run on a computing device. However, the program product of this application is not limited thereto. In this document, the readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0255] A readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying readable program code. This propagated data signal may take many forms, including—but not limited to—electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium, capable of sending, propagating, or transmitting a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0256] The program code contained on the readable medium may be transmitted using any suitable medium, including—but not limited to—wireless, wired, optical fiber, RF, or any suitable combination thereof.

[0257] Program code for performing the operations of this application can be written in any combination of one or more programming languages, including entity-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0258] It should be noted that although several units or sub-units of the device have been mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to embodiments of this application, the features and functions of two or more units described above can be embodied in one unit. Conversely, the features and functions of one unit described above can be further divided and embodied by multiple units.

[0259] Furthermore, although the operations of the method of this application are described in a specific order in the accompanying drawings, this does not require or imply that these operations must be performed in that specific order, or that all the operations shown must be performed to achieve the desired result. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.

[0260] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can 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.

[0261] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), 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 file processing device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable file processing device, 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.

[0262] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable file 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.

[0263] These computer program instructions can also be loaded onto a computer or other programmable document processing device to cause a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable device 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.

[0264] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0265] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A data center inspection system, characterized in that, The system includes an inspection robot, a navigation and positioning device, a photo positioning device, a detection device, a robotic arm device, and a control center; the navigation and positioning device, the photo positioning device, the robotic arm device, and the detection device are mounted on the inspection robot; wherein: The inspection robot is used to receive inspection task instructions; the inspection task instructions include at least one cabinet to be inspected, the location information of the at least one cabinet to be inspected, and the data type to be collected corresponding to the at least one cabinet to be inspected. The navigation and positioning device is used to determine at least one reference position information of the inspection robot based on a preset driving map and the position information of the at least one cabinet to be inspected; and to determine a first inspection route in the preset driving map based on the at least one reference position information and the current position of the inspection robot. The inspection robot is used to move according to the first inspection route; The image positioning device is used to collect reference image information of the at least one cabinet to be inspected when the inspection robot moves to the at least one reference position information according to the first inspection route; and to determine the relative position of the inspection robot and each sub-device in the at least one cabinet to be inspected based on the reference image information of the at least one cabinet to be inspected. The robotic arm device is used to move the detection device from its initial position to each of the sub-devices in the inspection robot according to the relative position of the inspection robot and each of the sub-devices in the at least one cabinet to be inspected; The detection device is used to detect the target parameters corresponding to the data types to be collected in each of the sub-devices and send them to the control center; The control center is used to process the target parameters corresponding to the data types to be collected by each sub-device to obtain the inspection results; The robotic arm device is further configured to move the detection device to the initial position after detecting the target parameter corresponding to the data type to be collected of each of the sub-devices; The control center is specifically used to compare the reference image information of the at least one cabinet to be inspected with the stored standard image information of the at least one cabinet to be inspected, and obtain a comparison result; the comparison result represents the difference between at least one cabinet to be inspected in the reference image information and at least one cabinet to be inspected in the standard image information; and sends the comparison result and the relative positions of each sub-device in the at least one cabinet to be inspected and the inspection robot to the robotic arm device; The robotic arm device is used to receive the comparison results sent by the control center, and to perform fault recovery on the sub-devices with abnormal parameters in the comparison results according to the relative positions of each sub-device in the at least one cabinet to be inspected and the inspection robot.

2. The system according to claim 1, characterized in that, The system also includes a cabinet information acquisition device; The cabinet information acquisition device is used to acquire target parameters corresponding to the data type to be acquired for at least one cabinet to be inspected, and send them to the control center.

3. A data center inspection method, characterized in that, The method is applied to the data center inspection system according to claim 1 or 2, and the method includes: Receive inspection task instructions; the inspection task instructions include at least one cabinet to be inspected, the location information of the at least one cabinet to be inspected, and the data type to be collected corresponding to the at least one cabinet to be inspected; Based on the preset driving map and the location information of the at least one cabinet to be inspected, determine at least one reference location information for the inspection robot; Based on the at least one reference location information and the current location of the inspection robot, a first inspection route is determined in the preset driving map; When the inspection robot moves to the at least one reference position information according to the first inspection route, it collects reference image information of the at least one cabinet to be inspected; and determines the relative position of the inspection robot and each sub-device in the at least one cabinet to be inspected based on the reference image information of the at least one cabinet to be inspected. Based on the relative position of the inspection robot and each sub-device in the at least one cabinet to be inspected, the target parameters corresponding to the data type to be collected of each sub-device are detected. The target parameters corresponding to the data types to be collected from each of the sub-devices are processed to obtain the inspection results.

4. The method according to claim 3, characterized in that, The step of determining at least one reference position information for the inspection robot based on a preset driving map and the location information of at least one cabinet to be inspected includes: Based on the correspondence between the location information of magnetic nails and the location information of cabinets in the preset driving map, determine the location information of at least one target magnetic nail corresponding to the location information of at least one cabinet to be inspected; The position information of the at least one target magnetic nail is used as at least one reference position information of the inspection robot.

5. The method according to claim 3, characterized in that, Determining the relative position of the inspection robot to each sub-device in the at least one cabinet to be inspected, based on the reference image information of the at least one cabinet to be inspected, includes: Based on the reference image information of the at least one cabinet to be inspected, determine the three-dimensional spatial information of the at least one cabinet to be inspected; Based on the three-dimensional spatial information, the relative positions of the inspection robot and each sub-device in the at least one cabinet to be inspected are determined.

6. The method according to claim 3, characterized in that, The processing of the target parameters corresponding to the data types to be collected from each of the sub-devices includes: Repair any abnormal data in the target parameters corresponding to the data types to be collected from each of the sub-devices.

7. The method according to claim 6, characterized in that, The step of repairing abnormal data in the target parameters corresponding to the data types to be collected from each of the sub-devices includes: The target parameters corresponding to the data types to be collected in each of the sub-devices are compared with the stored preset parameters to obtain abnormal parameters; In response to the user's repair operation, the abnormal parameter is replaced with the preset parameter.

8. The method according to claim 6, characterized in that, The step of repairing abnormal data in the target parameters corresponding to the data types to be collected from each of the sub-devices includes: The reference image information of the at least one cabinet to be inspected is compared with the stored standard image information of the at least one cabinet to be inspected to obtain a comparison result; the comparison result represents the difference between at least one cabinet to be inspected in the reference image information and at least one cabinet to be inspected in the standard image information. Based on the relative positions of each sub-device in the at least one cabinet to be inspected and the inspection robot, fault recovery is performed on the sub-devices with abnormal parameters in the comparison results.

9. The method according to claim 3, characterized in that, The receiving of inspection task instructions includes: Receive the inspection task instruction corresponding to the current period's inspection task from the stored archive; or, In response to the user's operation of setting inspection tasks on the touch screen of the inspection robot, the robot receives the corresponding inspection task instructions.

10. The method according to any one of claims 3 to 9, characterized in that, The method further includes: Monitor the status of the inspection robot; When the inspection robot is idle or powered off, charge the inspection robot.

11. A data center inspection device, characterized in that, The device is applied to the data center inspection system according to claim 1 or 2, and the device comprises: The receiving module is used to receive inspection task instructions; the inspection task instructions include at least one cabinet to be inspected, the location information of the at least one cabinet to be inspected, and the data type to be collected corresponding to the at least one cabinet to be inspected. The first positioning module is used to determine at least one reference position information of the inspection robot based on the preset driving map and the position information of the at least one cabinet to be inspected; The first route determination module is used to determine a first inspection route in the preset driving map based on the at least one reference position information and the current position of the inspection robot. The second positioning module is used to collect reference image information of the at least one cabinet to be inspected when the inspection robot moves to the at least one reference position information according to the first inspection route; and to determine the relative position of the inspection robot and each sub-device in the at least one cabinet to be inspected according to the reference image information of the at least one cabinet to be inspected. The parameter detection module is used to detect the target parameters corresponding to the data types to be collected of each sub-device based on the relative position of the inspection robot and each sub-device in the at least one cabinet to be inspected. The parameter processing module is used to process the target parameters corresponding to the data types to be collected from each of the sub-devices to obtain the inspection results.

12. An electronic device, characterized in that, It includes a processor and a memory, wherein the memory stores program code that, when executed by the processor, causes the processor to perform the steps of the data center inspection method of claims 3-10.

13. A computer-readable storage medium, characterized in that, It includes program code that, when run on an electronic device, causes the electronic device to perform the steps of the data center inspection method of claims 3-10.

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