Smart cloud box inspection system based on edge computing

Abstract

The invention provides a smart cloud box inspection system based on edge computing, which comprises an inspection planning module, an inspection control module, an image analysis module and an inspection adjustment module, and is characterized in that the inspection planning module is used for planning a basic inspection route, and the inspection control module is used for controlling shooting of a lens to meet inspection requirements; the image analysis module is used for performing analysis processing on an image collected in the inspection process, and the inspection adjustment module adjusts the inspection process based on an analysis result; according to the system, dynamic adjustment can be performed based on the basic inspection route in the inspection process, and more detailed inspection information can be obtained.

Description

Technical Field

[0001] The present invention relates to the field of electronic digital data processing, and in particular to a smart cloud box inspection system based on edge computing. Background Art

[0002] Inspection systems are widely used in equipment maintenance, fault detection, and safety management. Traditional inspection methods usually rely on manual operations, with inspectors regularly checking and recording equipment. Although this method is intuitive, it has problems such as low efficiency, poor accuracy, and missed inspections caused by human factors. Therefore, setting up network cameras near the equipment for inspection can effectively improve inspection efficiency. At the same time, a corresponding inspection system is needed to control the inspection process and better play the inspection effect.

[0003] The foregoing discussion of the background art is intended only to facilitate an understanding of the present invention. This discussion does not acknowledge or admit that any of the material referred to is part of the common general knowledge.

[0004] Many inspection systems have been developed. After a lot of searching and reference, it is found that the existing inspection systems are such as the system disclosed in the publication number CN114279572B. These system methods generally include: infrared thermal imaging camera; infrared thermal imaging camera is set on a terminal platform that can move along a preset rail; the preset rail is set around multiple electrical cabinets that need to be inspected; the terminal platform is provided with a lowering device for lifting the infrared thermal imaging camera to a height corresponding to the infrared transmission window of each electrical cabinet; the terminal platform and the infrared thermal imaging camera are connected to the monitoring cloud platform and work according to the instructions of the monitoring cloud platform. However, this system can only perform inspections according to the preset rails during the inspection process, and cannot cope with changing conditions. The inspection effect needs to be improved. Summary of the invention

[0005] The purpose of the present invention is to propose a smart cloud box inspection system based on edge computing to address the existing deficiencies.

[0006] The present invention adopts the following technical solution:

[0007] A smart cloud box inspection system based on edge computing, including an inspection planning module, an inspection control module, an image analysis module and an inspection adjustment module;

[0008] The inspection planning module is used to plan a basic inspection route, the inspection control module is used to control the shooting of the lens to achieve the inspection requirements, the image analysis module is used to analyze and process the images collected during the inspection process, and the inspection adjustment module adjusts the inspection process based on the analysis results;

[0009] The inspection planning module includes a node marking unit, a node connection unit, a parameter formulation unit and a resource release unit. The node marking unit is used to mark the shooting nodes including the smart cloud box hardware device, the node connection unit is used to connect the shooting nodes to form a closed route, the parameter formulation unit extracts the inspection parameters based on the closed route, and the resource release unit is used to release the used computing resources after completing the inspection route;

[0010] The inspection control module includes an inspection route storage unit and an inspection execution unit, wherein the inspection route storage unit is used to store inspection parameters, and the inspection execution unit is used to obtain inspection parameters and control the lens to execute the inspection process;

[0011] The image analysis module includes an abnormality analysis unit and an abnormality positioning unit, wherein the abnormality analysis unit is used to analyze abnormal phenomena in the image, and the abnormality positioning unit is used to locate the abnormal position;

[0012] The inspection adjustment module includes an inspection planning unit and an insertion interaction unit, wherein the inspection planning unit is used to plan out the temporarily added inspection parameters, and the insertion interaction unit is used to insert the new inspection parameters into the basic inspection route;

[0013] Further, the node connection unit includes a conversion calculation processor, a node sorting processor and a sorting adjustment processor, wherein the conversion calculation processor is used to calculate the conversion time between two nodes, the node sorting processor is used to sort the shooting nodes according to a ring sequence, and the sorting adjustment processor is used to adjust the sorting of the shooting nodes in the ring sequence;

[0014] Furthermore, the processing process of the node connection unit on the photographed node includes the following steps:

[0015] S1, the node sorting processor sorts the shooting nodes in any order to form a ring sequence;

[0016] S2, the sorting adjustment processor selects two adjacent shooting nodes as target nodes;

[0017] S3, the conversion calculation processor calculates the inspection cycle change value after the target node swaps positions;

[0018] S4. If the inspection cycle change value is negative, the sorting adjustment processor swaps the target nodes, clears the accumulated value and returns to step S2. If the inspection cycle change value is positive, it proceeds to step S5.

[0019] S5, adding 1 to the accumulated value. If the accumulated value is n, the shooting node information in the ring sequence is sent to the parameter formulation unit. If the accumulated value is less than n, return to step S2, where n is the number of shooting nodes;

[0020] Furthermore, the conversion calculation processor calculates the conversion time Tc between two adjacent shooting nodes in the ring sequence according to the following formula:

[0021]

[0022] Among them, (α1, β1) is the state parameter of the previous shooting node in the adjacent shooting nodes, (α2, β2) is the state parameter of the next shooting node in the adjacent shooting nodes, and ω0 is the standard angular velocity;

[0023] The conversion calculation processor calculates the inspection period T of the entire ring sequence according to the following formula:

[0024]

[0025] Where n is the number of shooting nodes, Tc(i, i+1) represents the conversion time between the i-th shooting node and the i+1-th shooting node in the ring sequence, and Tc(n, 1) represents the conversion time between the n-th shooting node and the 1st shooting node in the ring sequence;

[0026] Further, the abnormality locating unit includes a region setting processor and a relative conversion processor, the region setting processor is used to set the position of the abnormal region in the image, and the relative conversion processor is used to convert the abnormal region position information into relative information with respect to the center of the image;

[0027] The abnormal area position information is represented by four rectangular positioning points, and the relative conversion processor calculates the relative information according to the following formula:

[0028]

[0029] Wherein, x, y are the pixel length and width of the captured image, a, b are the pixel length and width of the abnormal area, x1 and x2 are the two horizontal coordinates of the positioning point, y1 and y2 are the two vertical coordinates of the positioning point, η is the magnification factor, and θ is the alignment angle.

[0030] The beneficial effects achieved by the present invention are:

[0031] When planning basic inspection routes, this system can effectively improve inspection efficiency by changing the connection order of shooting nodes and continuously reducing the inspection cycle of basic inspection routes. By discovering abnormal information during the basic inspection process and inserting temporary inspections to obtain detailed information on the abnormalities, the inspection effect can be improved while ensuring inspection efficiency.

[0032] To further understand the features and technical contents of the present invention, please refer to the following detailed description and drawings of the present invention. However, the drawings provided are only for reference and description and are not intended to limit the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 It is a schematic diagram of the overall structural framework of the present invention;

[0034] Figure 2 This is a schematic diagram of the inspection planning module of the present invention;

[0035] Figure 3 This is a schematic diagram of the node marking unit of the present invention;

[0036] Figure 4 It is a schematic diagram of the node connection unit of the present invention;

[0037] Figure 5 This is a schematic diagram of the parameter formulation unit structure of the present invention. DETAILED DESCRIPTION

[0038] The following is an explanation of the embodiments of the present invention through specific embodiments. Those skilled in the art can understand the advantages and effects of the present invention from the contents disclosed in this specification. The present invention can be implemented or applied through other different specific embodiments, and the details in this specification can also be modified and changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. In addition, the drawings of the present invention are only simple schematic illustrations and are not depicted according to actual sizes. It is stated in advance. The following embodiments will further explain the relevant technical contents of the present invention in detail, but the disclosed contents are not intended to limit the scope of protection of the present invention.

[0039] Embodiment 1.

[0040] This embodiment provides a smart cloud box inspection system based on edge computing, combined with Figure 1 , including inspection planning module, inspection control module, image analysis module and inspection adjustment module;

[0041] The inspection planning module is used to plan a basic inspection route, the inspection control module is used to control the shooting of the lens to achieve the inspection requirements, the image analysis module is used to analyze and process the images collected during the inspection process, and the inspection adjustment module adjusts the inspection process based on the analysis results;

[0042] The inspection planning module includes a node marking unit, a node connection unit, a parameter formulation unit and a resource release unit. The node marking unit is used to mark the shooting nodes including the smart cloud box hardware device, the node connection unit is used to connect the shooting nodes to form a closed route, the parameter formulation unit extracts the inspection parameters based on the closed route, and the resource release unit is used to release the used computing resources after completing the inspection route;

[0043] The inspection control module includes an inspection route storage unit and an inspection execution unit, wherein the inspection route storage unit is used to store inspection parameters, and the inspection execution unit is used to obtain inspection parameters and control the lens to execute the inspection process;

[0044] The image analysis module includes an abnormality analysis unit and an abnormality positioning unit, wherein the abnormality analysis unit is used to analyze abnormal phenomena in the image, and the abnormality positioning unit is used to locate the abnormal position;

[0045] The inspection adjustment module includes an inspection planning unit and an insertion interaction unit, wherein the inspection planning unit is used to plan out the temporarily added inspection parameters, and the insertion interaction unit is used to insert the new inspection parameters into the basic inspection route;

[0046] The node connection unit includes a conversion calculation processor, a node sorting processor and a sorting adjustment processor, wherein the conversion calculation processor is used to calculate the conversion time between two nodes, the node sorting processor is used to sort the shooting nodes according to a ring sequence, and the sorting adjustment processor is used to adjust the sorting of the shooting nodes in the ring sequence;

[0047] The processing process of the node connection unit on the photographed node includes the following steps:

[0048] S1, the node sorting processor sorts the shooting nodes in any order to form a ring sequence;

[0049] S2, the sorting adjustment processor selects two adjacent shooting nodes as target nodes;

[0050] S3, the conversion calculation processor calculates the inspection cycle change value after the target node swaps positions;

[0051] S4. If the inspection cycle change value is negative, the sorting adjustment processor swaps the target nodes, clears the accumulated value and returns to step S2. If the inspection cycle change value is positive, it proceeds to step S5.

[0052] S5, adding 1 to the accumulated value. If the accumulated value is n, the shooting node information in the ring sequence is sent to the parameter formulation unit. If the accumulated value is less than n, return to step S2, where n is the number of shooting nodes;

[0053] The conversion calculation processor calculates the conversion time Tc between two adjacent shooting nodes in the ring sequence according to the following formula:

[0054]

[0055] Among them, (α1, β1) is the state parameter of the previous shooting node in the adjacent shooting nodes, (α2, β2) is the state parameter of the next shooting node in the adjacent shooting nodes, and ω0 is the standard angular velocity;

[0056] The conversion calculation processor calculates the inspection period T of the entire ring sequence according to the following formula:

[0057]

[0058] Where n is the number of shooting nodes, Tc(i, i+1) represents the conversion time between the i-th shooting node and the i+1-th shooting node in the ring sequence, and Tc(n, 1) represents the conversion time between the n-th shooting node and the 1st shooting node in the ring sequence;

[0059] The abnormality positioning unit includes a region setting processor and a relative conversion processor, wherein the region setting processor is used to set the position of the abnormal region in the image, and the relative conversion processor is used to convert the abnormal region position information into relative information with respect to the center of the image;

[0060] The abnormal area position information is represented by four rectangular positioning points, and the relative conversion processor calculates the relative information according to the following formula:

[0061]

[0062]

[0063] Wherein, x, y are the pixel length and width of the captured image, a, b are the pixel length and width of the abnormal area, x1 and x2 are the two horizontal coordinates of the positioning point, y1 and y2 are the two vertical coordinates of the positioning point, η is the magnification factor, and θ is the alignment angle.

[0064] Embodiment 2.

[0065] This embodiment includes all the contents of the first embodiment, and provides a smart cloud box inspection system based on edge computing, including an inspection planning module, an inspection control module, an image analysis module, and an inspection adjustment module;

[0066] The inspection planning module is used to plan a basic inspection route, the inspection control module is used to control the shooting of the lens to achieve the inspection requirements, the image analysis module is used to analyze and process the images collected during the inspection process, and the inspection adjustment module adjusts the inspection process based on the analysis results;

[0067] Combination Figure 2 The inspection planning module includes a node marking unit, a node connection unit, a parameter formulation unit and a resource release unit. The node marking unit is used to mark the shooting nodes including the smart cloud box hardware device, the node connection unit is used to connect the shooting nodes to form a closed route, the parameter formulation unit extracts the inspection parameters based on the closed route, and the resource release unit is used to release the used computing resources after completing the inspection route;

[0068] The inspection control module includes an inspection route storage unit and an inspection execution unit, wherein the inspection route storage unit is used to store inspection parameters, and the inspection execution unit is used to obtain inspection parameters and control the lens to execute the inspection process;

[0069] The image analysis module includes an abnormality analysis unit and an abnormality positioning unit, wherein the abnormality analysis unit is used to analyze abnormal phenomena in the image, and the abnormality positioning unit is used to locate the abnormal position;

[0070] The inspection adjustment module includes an inspection planning unit and an insertion interaction unit, wherein the inspection planning unit is used to plan out the temporarily added inspection parameters, and the insertion interaction unit is used to insert the new inspection parameters into the basic inspection route;

[0071] Combination Figure 3 The node marking unit includes a device identification processor, a center calibration processor and a state recording processor, wherein the device identification processor is used to identify the hardware device in the captured image, the center calibration processor is used to adjust the lens so that the hardware device is at the center of the image, and the state recording processor is used to record the lens state parameters as the capture node;

[0072] The state parameters of each shooting node are represented by the horizontal angle α and the pitch angle β;

[0073] Combination Figure 4 , the node connection unit includes a conversion calculation processor, a node sorting processor and a sorting adjustment processor, the conversion calculation processor is used to calculate the conversion time between two nodes, the node sorting processor is used to sort the shooting nodes according to the ring sequence, and the sorting adjustment processor is used to adjust the sorting of the shooting nodes in the ring sequence;

[0074] The conversion calculation processor calculates the conversion time Tc between two adjacent shooting nodes in the ring sequence according to the following formula:

[0075]

[0076] Among them, (α1, β1) is the state parameter of the previous shooting node in the adjacent shooting nodes, (α2, β2) is the state parameter of the next shooting node in the adjacent shooting nodes, and ω0 is the standard angular velocity;

[0077] The conversion calculation processor calculates the inspection period T of the entire ring sequence according to the following formula:

[0078]

[0079] Where n is the number of shooting nodes, Tc(i, i+1) represents the conversion time between the i-th shooting node and the i+1-th shooting node in the ring sequence, and Tc(n, 1) represents the conversion time between the n-th shooting node and the 1st shooting node in the ring sequence;

[0080] The processing process of the node connection unit on the photographed node includes the following steps:

[0081] S1, the node sorting processor sorts the shooting nodes in any order to form a ring sequence;

[0082] S2, the sorting adjustment processor selects two adjacent shooting nodes as target nodes;

[0083] S3, the conversion calculation processor calculates the inspection cycle change value after the target node swaps positions;

[0084] S4. If the inspection cycle change value is negative, the sorting adjustment processor swaps the target nodes, clears the accumulated value and returns to step S2. If the inspection cycle change value is positive, it proceeds to step S5.

[0085] S5, add 1 to the accumulated value. If the accumulated value is n, go to step S6, and send the shooting node information in the ring sequence to the parameter setting unit. If the accumulated value is less than n, go back to step S2;

[0086] It should be noted that each time the shooting nodes are selected in step S2, the sequence number is advanced by one compared with the previous time, that is, if the 3rd and 4th shooting nodes are used as the target nodes in the previous time, the 4th and 5th shooting nodes are used as the target nodes next time;

[0087] Combination Figure 5The parameter formulation unit includes a rotation parameter processor, a focus parameter processor and a format conversion processor. The rotation parameter processor obtains the rotation parameter based on two adjacent shooting nodes, the focus parameter processor obtains the focal length parameter based on the image information of a single shooting node, and the format conversion processor is used to convert the rotation parameter and the focal length parameter into an execution data packet in an executable data format after matching them;

[0088] The resource release unit includes an event activation processor and a resource release processor, wherein the event activation processor is used to generate an activation signal after waiting for the complete execution data packet to be produced, and the resource release processor is used to release the computing power resources used by the inspection planning module after the activation signal is generated;

[0089] The inspection route storage unit includes a data packet register and a data packet management processor, wherein the data packet register is used to store executable data packets, and the data packet management processor is used to control and manage the process of sending executable data packets to the inspection execution unit;

[0090] The inspection execution unit includes an inspection management processor and a lens control processor, wherein the inspection management processor is used to receive and manage executable data packets, and the shooting execution processor controls the lens to rotate, focus and shoot based on the executable data packets;

[0091] The abnormality analysis unit includes a standard image register and an image comparison processor, wherein the standard image register is used to store the normal hardware device image of each shooting node, and the image comparison processor is used to compare the normal hardware device image with the inspection shooting image to determine whether there is an abnormality;

[0092] The abnormality positioning unit includes a region setting processor and a relative conversion processor, wherein the region setting processor is used to set the position of the abnormal region in the image, and the relative conversion processor is used to convert the abnormal region position information into relative information with respect to the center of the image;

[0093] The abnormal area position information is represented by four rectangular positioning points, and the relative conversion processor calculates the relative information according to the following formula:

[0094]

[0095] Where x, y are the pixel length and width of the captured image, a, b are the pixel length and width of the abnormal area, x1 and x2 are the two horizontal coordinates of the positioning point, y1 and y2 are the two vertical coordinates of the positioning point, η is the magnification factor, and θ is the alignment angle;

[0096] The inspection planning unit includes a steering planning processor and a focal length adjustment processor, wherein the steering planning processor plans temporary steering parameters based on the straightening angle, and the prime focal length adjustment processor plans temporary focusing parameters based on the magnification factor;

[0097] The insertion interaction unit includes a time stop signal processor and a data packet insertion processor, wherein the time stop signal processor is used to send a time stop signal to the inspection execution unit when an abnormality is found, and the data packet insertion processor is used to generate a temporary executable data packet and send it to the inspection execution unit;

[0098] After receiving the time-stop signal, the inspection management processor interrupts the execution process of the next execution data packet and waits for receiving a temporary executable data packet, and the inspection management processor inserts and executes the temporary executable data packet;

[0099] The i appearing in the above text is an ordinal number used to indicate a sequence number.

[0100] The contents disclosed above are only preferred feasible embodiments of the present invention, and do not limit the protection scope of the present invention. Therefore, all equivalent technical changes made using the contents of the present invention specification and drawings are included in the protection scope of the present invention. In addition, the elements therein can be updated as technology develops.

Claims

1. A smart cloud box inspection system based on edge computing, characterized in that: It includes inspection planning module, inspection control module, image analysis module and inspection adjustment module; The inspection planning module is used to plan a basic inspection route, the inspection control module is used to control the shooting of the lens to achieve the inspection requirements, the image analysis module is used to analyze and process the images collected during the inspection process, and the inspection adjustment module adjusts the inspection process based on the analysis results; The inspection planning module includes a node marking unit, a node connection unit, a parameter formulation unit and a resource release unit. The node marking unit is used to mark the shooting nodes including the smart cloud box hardware device, the node connection unit is used to connect the shooting nodes to form a closed route, the parameter formulation unit extracts the inspection parameters based on the closed route, and the resource release unit is used to release the used computing resources after completing the inspection route; The inspection control module includes an inspection route storage unit and an inspection execution unit, wherein the inspection route storage unit is used to store inspection parameters, and the inspection execution unit is used to obtain inspection parameters and control the lens to execute the inspection process; The image analysis module includes an abnormality analysis unit and an abnormality positioning unit, wherein the abnormality analysis unit is used to analyze abnormal phenomena in the image, and the abnormality positioning unit is used to locate the abnormal position; The inspection adjustment module includes an inspection planning unit and an insertion interaction unit. The inspection planning unit is used to plan out temporarily added inspection parameters, and the insertion interaction unit is used to insert new inspection parameters into the basic inspection route.

2. The edge computing-based smart cloud box inspection system according to claim 1, characterized in that: The node connection unit includes a conversion calculation processor, a node sorting processor and a sorting adjustment processor. The conversion calculation processor is used to calculate the conversion time between two nodes, the node sorting processor is used to sort the shooting nodes according to a ring sequence, and the sorting adjustment processor is used to adjust the sorting of the shooting nodes in the ring sequence.

3. The edge computing-based smart cloud box inspection system according to claim 2, characterized in that: The processing process of the node connection unit on the photographed node includes the following steps: S1, the node sorting processor sorts the shooting nodes in any order to form a ring sequence; S2, the sorting adjustment processor selects two adjacent shooting nodes as target nodes; S3, the conversion calculation processor calculates the inspection cycle change value after the target node swaps positions; S4. If the inspection cycle change value is negative, the sorting adjustment processor swaps the target nodes, clears the accumulated value and returns to step S2. If the inspection cycle change value is positive, it proceeds to step S5. S5. Add 1 to the accumulated value. If the accumulated value is n, send the shooting node information in the ring sequence to the parameter formulation unit. If the accumulated value is less than n, return to step S2, where n is the number of shooting nodes.

4. The edge computing-based smart cloud box inspection system according to claim 3, characterized in that: The conversion calculation processor calculates the conversion time Tc between two adjacent shooting nodes in the ring sequence according to the following formula: Among them, (α1, β1) is the state parameter of the previous shooting node in the adjacent shooting nodes, (α2, β2) is the state parameter of the next shooting node in the adjacent shooting nodes, and ω0 is the standard angular velocity; The conversion calculation processor calculates the inspection period T of the entire ring sequence according to the following formula: Wherein, n is the number of shooting nodes, Tc(i, i+1) represents the transition time between the i-th shooting node and the i+1-th shooting node in the ring sequence, and Tc(n, 1) represents the transition time between the n-th shooting node and the 1st shooting node in the ring sequence.

5. The edge computing-based smart cloud box inspection system according to claim 4, characterized in that: The abnormality positioning unit includes a region setting processor and a relative conversion processor, wherein the region setting processor is used to set the position of the abnormal region in the image, and the relative conversion processor is used to convert the abnormal region position information into relative information with respect to the center of the image; The abnormal area position information is represented by four rectangular positioning points, and the relative conversion processor calculates the relative information according to the following formula: Wherein, x, y are the pixel length and width of the captured image, a, b are the pixel length and width of the abnormal area, x1 and x2 are the two horizontal coordinates of the positioning point, y1 and y2 are the two vertical coordinates of the positioning point, η is the magnification factor, and θ is the alignment angle.

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