CN116597536A - Intelligent safety inspection method and system for engineering construction of data center - Google Patents
Intelligent safety inspection method and system for engineering construction of data center Download PDFInfo
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- G—PHYSICS
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- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C1/00—Registering, indicating or recording the time of events or elapsed time, e.g. time-recorders for work people
- G07C1/20—Checking timed patrols, e.g. of watchman
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Abstract
The application provides an intelligent safety inspection method and system for data center engineering construction, which are characterized in that an inspection code is arranged at each inspection point, a safety management center determines the inspection point identity information according to the inspection code information of an acquired inspection image with safety problems, so that the inspection point position information with safety problems can be rapidly determined.
Description
Technical Field
The application relates to the technical field of intelligent safety inspection, in particular to an intelligent safety inspection method and system for engineering construction of a data center.
Background
At present, when a data center is used for site construction, a safety officer needs to carry out safety inspection on a fixed line every day, mainly checks whether a site constructor wears a safety helmet or not, whether a safety net meets the standards or not, whether safety protection is carried out on a stair opening, an elevator opening, a passage opening, a reserved hole or not and the like is judged, the safety protection is repeated, the efficiency is low, the safety protection is low, in order to improve the efficiency, an intelligent safety inspection technology can be adopted for carrying out automatic inspection so as to improve the efficiency and the accuracy of site safety management, for example, an inspection robot replaces a manual inspection according to a preset inspection route to send an inspection image shot on the inspection route to a safety management center, but the safety management center finds an image with a safety problem from a massive inspection image, and then positions the inspection point position information with the safety problem according to the inspection image with the safety problem, time and labor are consumed, and the efficiency is low.
Disclosure of Invention
The application provides an intelligent safety inspection method and system for engineering construction of a data center, which are used for solving the technical problem that the efficiency is low when a safety management center finds images with safety problems from a large number of inspection images and then positions inspection point position information with the safety problems according to the images with the safety problems.
In order to solve the technical problems, the application adopts the following technical scheme:
in a first aspect, the application provides an intelligent security inspection method for engineering construction of a data center, which comprises the following steps:
the inspection robot performs inspection according to a preset inspection route, wherein the preset inspection route comprises a plurality of inspection points, and each inspection point is provided with a corresponding inspection code for storing the identity information of the inspection point and storing the identity information of the inspection point;
collecting inspection code images at each inspection point inspection robot, and dividing the inspection code images into different image blocks according to the positions of the locators;
extracting a locator image in each image block, determining a convolution kernel of the locator image, taking the convolution kernel of the locator image as the convolution kernel of the image block where the locator image is located, and carrying out deconvolution on the image block according to the convolution kernel of each image block to obtain an image-enhanced inspection code image;
decoding the image enhanced inspection code image to obtain inspection point identity verification information, carrying out identity verification on the inspection point according to the inspection point identity verification information, and acquiring the inspection image of the inspection point if the identity verification is passed;
the inspection robot sends the collected inspection images to a security management center and generates an inspection security report according to the inspection images.
In some embodiments, the extracting the locator image in each image block may specifically include:
denoising and smoothing each image block;
performing edge detection on each image block subjected to denoising and smoothing treatment to determine contour information of a locator image;
carrying out corner information of the locator image in corner detection on each image block subjected to denoising and smoothing treatment;
and extracting a corresponding locator image from each image block according to the determined contour information and the determined corner information.
In some embodiments, the number of the positioners is 4, and the positioners are distributed in the upper left, the lower left, the upper right and the lower right of the inspection code image, and the inspection code image is divided into different image blocks according to the positions of the positioners, namely, an upper left image block, a lower left image block, an upper right image block and a lower right image block.
In some embodiments, the deconvoluting the image blocks according to the convolution of the image blocks to obtain the image-enhanced inspection code image may specifically include:
the convolution kernels of the image blocks are subjected to transposition to obtain deconvolution kernels corresponding to the image blocks;
dividing each image block into divided image blocks with the same size as the convolution kernel;
and performing edge filling on the segmented image blocks, and then performing convolution operation on the filled segmented image blocks and the deconvolution kernel to obtain an image-enhanced inspection code image.
In some embodiments, the predetermined inspection route includes a slide rail through which the inspection robot moves on the inspection route.
In some embodiments, the tour route includes an indoor tour route and an outdoor tour route.
In some embodiments, the inspection robot is provided with a camera for acquiring inspection code images and inspection images of various inspection points.
The application provides a data center engineering construction intelligent safety inspection system, which comprises an inspection robot and a safety management center, wherein the inspection robot performs inspection according to a preset inspection route, the preset inspection route comprises a plurality of inspection points, and each inspection point is provided with a corresponding inspection code for storing the identity information of the inspection point;
the inspection robot comprises an inspection control unit, wherein the inspection control unit comprises the following components in detail:
the inspection code acquisition module is used for acquiring inspection code images at each inspection point inspection robot and dividing the inspection code images into different image blocks according to the positions of the locators;
the inspection code image enhancement module is used for extracting a locator image in each image block, determining a convolution kernel of the locator image, taking the convolution kernel of the locator image as the convolution kernel of the image block where the locator image is located, and carrying out deconvolution on the image block according to the convolution kernel of each image block to obtain an image enhanced inspection code image;
the identity verification module is used for decoding the image-enhanced inspection code image to obtain inspection point identity verification information, carrying out identity verification on the inspection point according to the inspection point identity verification information, and acquiring an inspection image of the inspection point if the identity verification is passed;
and the inspection image processing module is used for sending the collected inspection image to the security management center and generating an inspection security report according to the inspection image.
In a third aspect, the present application provides a computer device comprising a memory and a processor; the memory stores codes, and the processor is configured to acquire the codes and execute the intelligent security inspection method for the engineering construction of the data center.
In a fourth aspect, the present application provides a computer readable storage medium, where a computer program is stored, where the computer program when executed by a processor implements the above-mentioned intelligent security inspection method for engineering construction of a data center.
The technical scheme provided by the embodiment of the application has the following beneficial effects:
in the intelligent safety inspection method and system for the engineering construction of the data center, firstly, an inspection robot performs inspection according to a preset inspection route, wherein the preset inspection route comprises a plurality of inspection points, and each inspection point is provided with a corresponding inspection code; collecting inspection code images at each inspection point inspection robot, and dividing the inspection code images into different image blocks according to the positions of the locators; extracting a locator image in each image block, determining a convolution kernel of the locator image, taking the convolution kernel of the locator image as the convolution kernel of the image block where the locator image is located, and carrying out deconvolution on the image block according to the convolution kernel of each image block to obtain an image-enhanced inspection code image; decoding the image enhanced inspection code image to obtain inspection point identity verification information, carrying out identity verification on the inspection point according to the inspection point identity verification information, and acquiring the inspection image of the inspection point if the identity verification is passed; the inspection robot sends the collected inspection images to a security management center and generates an inspection security report according to the inspection images, the security management center sets the inspection codes on each inspection point, the security management center determines the identity information of the inspection points according to the inspection code information of the inspection images with the security problems, and further can rapidly determine the position information of the inspection points with the security problems.
Drawings
FIG. 1 is an exemplary flow chart of a data center engineering intelligent security inspection method according to some embodiments of the application;
FIG. 2 is a schematic diagram of exemplary hardware and/or software of a patrol control unit, shown according to some embodiments of the application;
fig. 3 is a schematic structural diagram of a computer device for an intelligent security inspection method for data center engineering construction according to an embodiment of the present application.
Detailed Description
In order to better understand the above technical solutions, the following detailed description will refer to the accompanying drawings and specific embodiments. Referring to fig. 1, which is an exemplary flowchart of a data center engineering intelligent security inspection method according to some embodiments of the present application, the data center engineering intelligent security inspection method 100 mainly includes the following steps:
in step S101, the inspection robot performs inspection according to a preset inspection route, where the preset inspection route includes a plurality of inspection points, and each inspection point is provided with a corresponding inspection code for storing the identity information of the inspection point.
In specific implementation, the preset inspection route in the application comprises a slide rail, the inspection robot can move on the inspection route through the slide rail, and the inspection robot is provided with a camera or other image acquisition equipment for acquiring inspection code images and inspection images of various inspection points, which are not described herein.
In addition, the routing inspection route in the application can comprise an indoor routing inspection route and an outdoor routing inspection route, wherein the indoor routing inspection route comprises a channel entrance, a building entrance, an elevator entrance, a reserved hole and a routing inspection route of a channel exit, and the outdoor routing inspection route comprises a construction platform, a construction downstairs, a construction building a surface and a construction building b surface, and the routing inspection route can be actually set by detecting routing inspection points according to the needs without being particularly limited.
In addition, it should be noted that the inspection code in the present application may store the inspection point identity information in the form of a two-dimensional code, where 4 locator images are generally distributed at four positions of the upper left, the lower left, the upper right and the lower right in the two-dimensional code image, and will not be described herein.
In step S102, a patrol robot collects patrol code images at each patrol point, and divides the patrol code images into different image blocks according to locator positions.
When the method is specifically implemented, if the routing inspection code adopts a two-dimensional code, the routing inspection code image can be divided into different image blocks according to the positions of the locators, and specifically, the routing inspection code image can be divided into an upper left image block, a lower left image block, an upper right image block and a lower right image block, and in practice, the routing inspection code image can be separated according to other distribution conditions of the locators, which is not repeated here.
In step S103, extracting the locator image in each image block, determining the convolution kernel of the locator image, taking the convolution kernel of the locator image as the convolution kernel of the image block where the locator image is located, and deconvoluting the image block according to the convolution kernel of each image block to obtain the image-enhanced inspection code image.
In some embodiments, the extracting the locator image in each image block may be implemented in the following manner:
firstly, denoising and smoothing are carried out on each image block, and as noise interference and the like possibly exist in the acquired inspection code image, the inspection code image is required to be subjected to image preprocessing, namely denoising and smoothing are carried out on each image block so as to reduce the noise interference;
secondly, edge detection is carried out on each image block after denoising and smoothing treatment to determine the outline information of the locator image, the edge detection can be realized through a Canny algorithm when the image block is specifically realized, and the detection and extraction of the edge of the locator image are realized through steps of multiple filtering, non-maximum value suppression, double-threshold detection and the like by adopting the Canny algorithm, and the details are not repeated here;
thirdly, carrying out corner information of the locator image in the corner detection on each image block after denoising and smoothing, wherein a Harris corner detection algorithm can be adopted for the specific implementation of the corner detection, and the corner of the locator image is detected by calculating a second moment matrix of the gray level change of the locator image by adopting the Harris corner detection algorithm, and the details are not repeated;
and finally, extracting a corresponding locator image from each image block according to the determined contour information and the determined corner information.
In specific implementation, for each image block, according to the position of the corner point position locator of the locator image, after the position of the locator image is determined, the size and shape of the locator are obtained according to the contour information, the center of the locator image is taken as a center point, and according to the determined size and shape, the corresponding locator image is intercepted in the original image, which is not described herein again.
In addition, the convolution kernel of the locator image may be determined in various manners, for example, in the present application, the image blur may occur in the inspection code image, and as a preferred embodiment, the convolution kernel may enhance the inspection code image based on the form of the blur kernel, for example, in the locator image of the present application, a gaussian kernel, a mean kernel, etc. may be used to process the locator image to obtain a blurred locator image, then the error between each blurred locator image and the original locator image is calculated, and finally, the blur kernel with the smallest error is selected as the final blur kernel of the locator image, which is not described herein again.
It should be noted that, no matter how the graphics of other parts change, the locator image is unchanged, so in the application, the convolution kernel of the locator image is used as the convolution kernel of the image block where the locator is located, and then the image block is subjected to deconvolution according to the convolution check of the image block to obtain the inspection code image, which is effectively enhanced, has better image quality and is more beneficial to identity verification, and is not repeated here.
In addition, in some embodiments, the deconvolution of the image blocks according to the convolution of the image blocks to obtain the image-enhanced inspection code image may be implemented in the following manner, that is:
the convolution kernels of the image blocks are subjected to transposition to obtain deconvolution kernels corresponding to the image blocks;
dividing each image block into divided image blocks with the same size as the convolution kernel;
and performing edge filling on the segmented image blocks, and then performing deconvolution operation on the filled segmented image blocks and the deconvolution core to obtain an image-enhanced inspection code image.
In step S104, the image-enhanced inspection code image is decoded to obtain inspection point identity verification information, the inspection point is authenticated according to the inspection point identity verification information, and if the identity verification is passed, the inspection image of the inspection point is collected.
In specific implementation, the inspection robot needs to be equipped with corresponding decoding equipment or a decoding processing module to decode the inspection code image, the inspection point identity verification information obtained after decoding is compared with the inspection point identity information stored in the system to judge whether the identity of the inspection point is legal, if the identity verification is passed, the inspection robot can acquire the inspection image of the inspection point, and a camera or a camera can be used for acquiring the acquired image, so that specific limitation is not made here.
In step S105, the inspection robot transmits the collected inspection image to the security management center and generates an inspection security report from the inspection image.
In specific implementation, for example, the inspection robot transmits the collected inspection image to the security management center through the network, the security management center processes the received inspection image, the processing includes operations such as image denoising, image enhancement, image registration and the like, so as to improve the image quality, an inspection report can be generated according to the collected inspection image and the identity verification result, the report content can include information such as the state, abnormal condition, inspection time and the like of the inspection point, and suggested maintenance measures and the like, and the report generation period can be daily or weekly, and is not repeated here.
In addition, in another aspect of the present application, in some embodiments, the present application provides a bone conduction apparatus for a cosmetic instrument, referring to fig. 2, which is a schematic diagram of exemplary hardware and/or software of a patrol control unit 200 in a patrol robot according to some embodiments of the present application, the patrol control unit 200 includes: the inspection code acquisition module 201, the inspection code image enhancement module 202, the identity verification module 203 and the inspection image processing module 204 are respectively described as follows:
the inspection code acquisition module 201 is mainly used for acquiring inspection code images at each inspection point inspection robot, and dividing the inspection code images into different image blocks according to the positions of the locators;
the inspection code image enhancement module 202 is mainly used for extracting a locator image in each image block, determining a convolution kernel of the locator image, taking the convolution kernel of the locator image as a convolution kernel of the image block where the locator image is located, and performing deconvolution on the image block according to the convolution kernel of each image block to obtain an image enhanced inspection code image;
the identity verification module 203 is mainly used for decoding the image-enhanced inspection code image to obtain inspection point identity verification information, carrying out identity verification on the inspection point according to the inspection point identity verification information, and acquiring the inspection image of the inspection point if the identity verification is passed;
the inspection image processing module 204 is mainly used for sending the collected inspection image to the security management center and generating an inspection security report according to the inspection image.
In addition, the application also provides a computer device, which comprises a memory and a processor; the memory stores codes, and the processor is configured to acquire the codes and execute the intelligent security inspection method for the engineering construction of the data center.
In some embodiments, reference is made to fig. 3, which is a schematic structural diagram of a computer device for implementing an intelligent security inspection method for engineering construction of a data center according to an embodiment of the present application. The data center engineering intelligent security inspection method in the above embodiment may be implemented by a computer device shown in fig. 3, where the computer device includes at least one processor 301, a communication bus 302, a memory 303, and at least one communication interface 304.
Processor 301 may be a general purpose central processing unit (central processing unit, CPU), application-specific integrated circuit (ASIC), or one or more of the various methods for controlling the execution of the intelligent security inspection method of the data center engineering of the present application.
Communication bus 302 may include a path to transfer information between the above components.
The Memory 303 may be, but is not limited to, a read-only Memory (ROM) or other type of static storage device that can store static information and instructions, a random access Memory (random access Memory, RAM) or other type of dynamic storage device that can store information and instructions, an electrically erasable programmable read-only Memory (electrically erasable programmable read-only Memory, EEPROM), a compact disc (compact disc read-only Memory) or other optical disk storage, a compact disc storage (including compact disc, laser disc, optical disc, digital versatile disc, blu-ray disc, etc.), a magnetic disk or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and that can be accessed by a computer. The memory 303 may be stand alone and be coupled to the processor 301 via the communication bus 302. Memory 303 may also be integrated with processor 301.
The memory 303 is used for storing program codes for executing the scheme of the present application, and the processor 301 controls the execution. The processor 301 is configured to execute program code stored in the memory 303. One or more software modules may be included in the program code. The determination of the open loop corrector transfer function model in the above embodiments may be implemented by one or more software modules in the processor 301 and in the program code in the memory 303.
Communication interface 304, using any transceiver-like device for communicating with other devices or communication networks, such as ethernet, radio access network (radio access network, RAN), wireless local area network (wireless local areanetworks, WLAN), etc.
In a specific implementation, as an embodiment, a computer device may include a plurality of processors, where each of the processors may be a single-core (single-CPU) processor or may be a multi-core (multi-CPU) processor. A processor herein may refer to one or more devices, circuits, and/or processing cores for processing data (e.g., computer program instructions).
The computer device may be a general purpose computer device or a special purpose computer device. In particular implementations, the computer device may be a desktop, laptop, web server, palmtop (personal digital assistant, PDA), mobile handset, tablet, wireless terminal device, communication device, or embedded device. Embodiments of the application are not limited to the type of computer device.
In addition, the application also provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program realizes the intelligent safety inspection method for the engineering construction of the data center when being executed by a processor.
In summary, in the data center engineering construction intelligent security inspection method and system disclosed by the embodiment of the application, by setting an inspection code at each inspection point, a security management center determines the inspection point identity information according to the inspection code information of the collected inspection images with security problems, so that the inspection point position information with security problems can be rapidly determined.
While preferred embodiments of the present application have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the application.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present application without departing from the spirit or scope of the application. Thus, it is intended that the present application also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (10)
1. The intelligent safety inspection method for the engineering construction of the data center is characterized by comprising the following steps of:
the inspection robot performs inspection according to a preset inspection route, wherein the preset inspection route comprises a plurality of inspection points, and each inspection point is provided with a corresponding inspection code for storing the identity information of the inspection point;
collecting inspection code images at each inspection point inspection robot, and dividing the inspection code images into different image blocks according to the positions of the locators;
extracting a locator image in each image block, determining a convolution kernel of the locator image, taking the convolution kernel of the locator image as the convolution kernel of the image block where the locator image is located, and carrying out deconvolution on the image block according to the convolution kernel of each image block to obtain an image-enhanced inspection code image;
decoding the image enhanced inspection code image to obtain inspection point identity verification information, carrying out identity verification on the inspection point according to the inspection point identity verification information, and acquiring the inspection image of the inspection point if the identity verification is passed;
the inspection robot sends the collected inspection images to a security management center and generates an inspection security report according to the inspection images.
2. The method of claim 1, wherein extracting the locator image in each image block specifically comprises:
denoising and smoothing each image block;
performing edge detection on each image block subjected to denoising and smoothing treatment to determine contour information of a locator image;
carrying out corner information of the locator image in corner detection on each image block subjected to denoising and smoothing treatment;
and extracting a corresponding locator image from each image block according to the determined contour information and the determined corner information.
3. The method of claim 1, wherein the number of the locators is 4, and the locators are distributed in an upper left, a lower left, an upper right and a lower right of the inspection code image, and the inspection code image is divided into different image blocks according to the location of the locators, specifically into an upper left image block, a lower left image block, an upper right image block and a lower right image block.
4. The method of claim 1, wherein deconvoluting the image blocks based on their convolutions to obtain an image-enhanced inspection code image comprises:
the convolution kernels of the image blocks are subjected to transposition to obtain deconvolution kernels corresponding to the image blocks;
dividing each image block into divided image blocks with the same size as the convolution kernel;
and performing edge filling on the segmented image blocks, and then performing convolution operation on the filled segmented image blocks and the deconvolution kernel to obtain an image-enhanced inspection code image.
5. The method of claim 1, wherein the predetermined inspection path comprises a slide rail, and the inspection robot moves on the inspection path via the slide rail.
6. The method of claim 1, wherein the inspection route comprises an indoor inspection route and an outdoor inspection route.
7. The method of claim 1, wherein the inspection robot is provided with a camera for acquiring inspection code images and inspection images of individual inspection points.
8. The intelligent safety inspection system for the data center engineering construction comprises an inspection robot and a safety management center, and is characterized in that the inspection robot performs inspection according to a preset inspection route, the preset inspection route comprises a plurality of inspection points, and each inspection point is provided with a corresponding inspection code for storing the identity information of the inspection point;
the inspection robot comprises an inspection control unit, wherein the inspection control unit comprises the following components in detail:
the inspection code acquisition module is used for acquiring inspection code images at each inspection point inspection robot and dividing the inspection code images into different image blocks according to the positions of the locators;
the inspection code image enhancement module is used for extracting a locator image in each image block, determining a convolution kernel of the locator image, taking the convolution kernel of the locator image as the convolution kernel of the image block where the locator image is located, and carrying out deconvolution on the image block according to the convolution kernel of each image block to obtain an image enhanced inspection code image;
the identity verification module is used for decoding the image-enhanced inspection code image to obtain inspection point identity verification information, carrying out identity verification on the inspection point according to the inspection point identity verification information, and acquiring an inspection image of the inspection point if the identity verification is passed;
and the inspection image processing module is used for sending the collected inspection image to the security management center and generating an inspection security report according to the inspection image.
9. A computer device, the computer device comprising a memory and a processor; the memory stores code, and the processor is configured to obtain the code and perform the data center engineering intelligent security inspection method of any one of claims 1 to 7.
10. A computer readable storage medium storing a computer program, wherein the computer program when executed by a processor implements the intelligent security inspection method for engineering construction of a data center according to any one of claims 1 to 7.
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