Industrial underwater camera monitoring and early warning system and method based on foreign matter detection

Abstract

The invention belongs to the technical field of underwater monitoring and alarming, and particularly relates to an industrial underwater camera monitoring and early warning system and method based on foreign matter detection, and the system comprises an underwater camera module, an underwater auxiliary illumination module, a multi-beam foresight sonar module, an underwater wireless communication module, an anomaly detection and recognition output module and a ground monitoring center. Real-time imaging is carried out on an industrial underwater environment through the underwater camera module, auxiliary imaging detection is carried out under low visibility through the multi-beam foresight sonar module, underwater foreign matter recognition is carried out based on underwater images and sonar data, omni-directional coverage of the underwater environment is achieved, underwater potential safety hazards can be found and processed in time, and the underwater foreign matter recognition system is suitable for being popularized and applied. And the operation control condition of the underwater inspection robot is analyzed, and reasonable regulation and control treatment measures are taken in time for the underwater inspection robot, so that the safe and stable operation of the underwater inspection robot is ensured, and the supervision difficulty of ground management personnel is remarkably reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of underwater monitoring and alarm, and specifically to an industrial underwater camera monitoring and early warning system and method based on foreign object detection. Background Art

[0002] In the industrial underwater environment, foreign object detection is crucial for ensuring the normal operation of equipment, preventing accidents, and protecting the ecological environment. Especially in underwater pipelines, underwater equipment, and underwater operation areas, the presence of foreign objects can easily lead to serious safety hazards. However, the industrial underwater environment is complex and difficult to directly observe, and traditional monitoring technologies face many challenges in underwater applications;

[0003] Currently, an underwater inspection robot equipped with a camera is mainly used to inspect and detect the industrial underwater environment to capture foreign objects. It is not only difficult to accurately identify underwater foreign objects and output their specific information, but also unable to perform step-by-step progressive and accurate analysis on the operation control performance of underwater detection and give early warnings in a timely manner. Ground management personnel cannot make reasonable adjustment and treatment measures for the underwater inspection robot in a timely manner, which is not conducive to ensuring the safe and stable operation of the underwater inspection robot and reducing the difficulty of its operation supervision, and the level of intelligence and automation is low;

[0004] In view of the above technical deficiencies, a solution is proposed now. Summary of the Invention

[0005] The purpose of the present invention is to provide an industrial underwater camera monitoring and early warning system and method based on foreign object detection, which solves the problems that the prior art is difficult to accurately identify underwater foreign objects and output their specific information, and is unable to perform step-by-step progressive and accurate analysis on the operation control performance of underwater detection and give early warnings in a timely manner, which is not conducive to ensuring the safety and stability of the detection process and reducing the supervision difficulty, and the level of intelligence and automation is low.

[0006] To achieve the above purpose, the present invention provides the following technical solutions:

[0007] An industrial underwater camera monitoring and early warning system based on foreign object detection includes an underwater camera module, an underwater auxiliary lighting module, a multi-beam forward-looking sonar module, an underwater wireless communication module, an abnormal detection, identification and output module, and a ground monitoring center. The underwater camera module, the underwater auxiliary lighting module, the multi-beam forward-looking sonar module, and the underwater wireless communication module are all arranged on an underwater inspection robot;

[0008] The underwater camera module performs real-time imaging on the industrial underwater environment. The underwater auxiliary lighting module provides light underwater to ensure normal imaging under low light conditions. The multi-beam forward-looking sonar module performs imaging detection under low visibility to accurately locate underwater foreign objects. The underwater wireless communication module sends underwater images and sonar data to the abnormal detection, identification and output module and the ground monitoring center;

[0009] The anomaly detection and recognition output module processes the collected underwater images and sonar data, identifies the type, location, and size of foreign objects, triggers the warning mechanism when foreign objects are found, and sends the foreign object information to the ground monitoring center. The ground monitoring center takes corresponding countermeasures based on the warning information.

[0010] Furthermore, the ground monitoring center is communicatively connected to the GIS map module and the inspection path planning module. The GIS map module creates a GIS map of the industrial underwater environment and sends the GIS map of the industrial underwater environment to the inspection path planning module and the ground monitoring center. The inspection path planning module is used to plan the underwater inspection path and send the underwater inspection path to the ground monitoring center.

[0011] The ground monitoring center sends the GIS map of the industrial underwater environment and the current underwater inspection path to the underwater inspection robot. The underwater wireless communication module receives the GIS map of the industrial underwater environment and the current underwater inspection path, and after starting the underwater inspection robot, makes it perform inspections along the preset underwater inspection path.

[0012] Furthermore, an underwater detection control and analysis module is also provided on the underwater inspection robot. The underwater detection control and analysis module analyzes the operation control status of the underwater inspection robot, generates a detection control qualified signal or a detection control unqualified signal through the analysis, and sends the detection control qualified signal or the detection control unqualified signal to the ground monitoring center via the underwater wireless communication module.

[0013] Furthermore, the specific analysis process of the underwater detection control and analysis module includes:

[0014] Collect the actual operation path of the underwater inspection robot within a unit time, perform a coincidence comparison between the actual operation path and the corresponding part of the preset underwater inspection path, mark the ratio of the length of the non - coincident path between the two as the path control anomaly value, compare the path control anomaly value with the preset path control anomaly threshold value. If the path control anomaly value exceeds the preset path control anomaly threshold value, generate a detection control unqualified signal.

[0015] Furthermore, if the path control anomaly value does not exceed the preset path control anomaly threshold value, mark the number of times and the total duration of the deviation of the actual operation path of the underwater inspection robot from the preset underwater inspection path within a unit time as the detection control deviation frequency and the detection control deviation duration respectively.

[0016] And obtain the traveling speed of the underwater inspection robot, calculate the difference between the traveling speed and the median of the preset traveling speed range and take the absolute value to obtain the traveling anomaly value, calculate the average value of all traveling anomaly values within a unit time to obtain the traveling anomaly table value, and mark the ratio of the number of traveling anomaly values exceeding the preset traveling anomaly threshold within a unit time as the traveling risk value;

[0017] By numerically calculating the path control anomaly value, the detection control deviation frequency, the detection control deviation duration, the traveling anomaly table value, and the traveling risk value to obtain the traveling pipe anomaly coefficient, numerically compare the traveling pipe anomaly coefficient with the corresponding preset traveling pipe anomaly coefficient threshold. If the traveling pipe anomaly coefficient exceeds the preset traveling pipe anomaly coefficient threshold, generate a detection control unqualified signal;

[0018] If the traveling pipe anomaly coefficient does not exceed the preset traveling pipe anomaly coefficient threshold, then obtain the detection device comprehensive inspection value through analysis, numerically compare the detection device comprehensive inspection value with the preset detection device comprehensive inspection threshold. If the detection device comprehensive inspection value exceeds the preset detection device comprehensive inspection threshold, generate a detection control unqualified signal; if the detection device comprehensive inspection value does not exceed the preset detection device comprehensive inspection threshold, generate a detection control qualified signal.

[0019] Furthermore, the method for analyzing and obtaining the detection device comprehensive inspection value is specifically as follows:

[0020] Obtain the detection devices that need to be supervised on the underwater inspection robot, including the underwater camera module, the underwater auxiliary lighting module, and the multi-beam forward-looking sonar module, and conduct operation monitoring on the detection devices that need to be supervised; obtain the operation parameters that the corresponding detection devices need to monitor, compare the real-time data of the corresponding operation parameters with the corresponding preset data requirements. If there are operation parameters that do not meet the corresponding preset data requirements, it is determined that the corresponding detection device is in a detection abnormal state;

[0021] Obtain the total duration of the corresponding detection device being in the detection abnormal state within a unit time and mark it as the detection abnormal time value, numerically compare the detection abnormal time value with the corresponding preset detection abnormal time threshold. If the detection abnormal time value exceeds the corresponding preset detection abnormal time threshold, mark the corresponding detection device as an abnormal device;

[0022] Obtain the number of detection devices marked as abnormal devices within a unit time and define it as the abnormal detection value, and calculate the ratio of the detection abnormal time value of the corresponding detection device to the corresponding preset detection abnormal time threshold to obtain the abnormal time ratio value. Calculate the average value of the abnormal time ratio values of all detection devices to obtain the abnormal time performance value, and mark the largest abnormal time ratio value as the abnormal time high amplitude value; obtain the detection device comprehensive inspection value by numerically calculating the abnormal detection value, the abnormal time performance value, and the abnormal time high amplitude value.

[0023] Further, the abnormal detection and recognition output module is communicatively connected to the underwater detection management module. The underwater detection management module is used to set a detection period of W1 days, analyze the detection management performance for the industrial underwater environment within the detection period, generate a detection management qualified signal or a detection management unqualified signal through the analysis, and send the detection management qualified signal or the detection management unqualified signal to the ground monitoring center. When the ground control center receives the detection management unqualified signal, it issues a corresponding warning.

[0024] Further, the specific analysis process of the underwater detection management module is as follows:

[0025] Obtain the start time of detecting the industrial underwater environment within the detection period, calculate the time difference between adjacent groups of start times to obtain the detection time difference, compare the detection time difference with the preset detection time difference threshold value numerically. If the detection time difference exceeds the preset detection time difference threshold value, mark the corresponding detection time difference as an abnormal time difference;

[0026] Obtain the number of abnormal time differences within the detection period and mark it as the abnormal detection value, and calculate the average value of all detection time differences to obtain the detection interval detection value. Compare the abnormal detection value and the detection interval detection value with the preset abnormal detection threshold value and the preset detection interval detection threshold value numerically respectively. If the abnormal detection value or the detection interval detection value exceeds the corresponding preset threshold value, generate a detection management unqualified signal;

[0027] If both the abnormal detection value and the detection interval detection value do not exceed the corresponding preset threshold values, at the end of the corresponding industrial underwater detection process, collect the detection duration for each area in the industrial underwater environment. Mark the corresponding area as a high foreign object risk area or a low foreign object risk area through foreign object risk level zoning detection and analysis. If the corresponding area is a high foreign object risk area, allocate the preset detection duration threshold value YL1 to it; if the corresponding area is a low foreign object risk area, allocate the preset detection duration threshold value YL2 to it, and YL1 > YL2 > 0;

[0028] Compare the detection duration of the corresponding area with the corresponding preset detection duration threshold value numerically. If the detection duration does not exceed the preset detection duration threshold value, mark the corresponding area as a non-optimal detection area; obtain the ratio of the number of non-optimal detection areas in the corresponding industrial underwater detection process and mark it as the non-optimal detection occupancy value. Compare the non-optimal detection occupancy value with the preset non-optimal detection occupancy threshold value numerically. If the non-optimal detection occupancy value exceeds the preset non-optimal detection occupancy threshold value, mark the corresponding industrial underwater detection process as an abnormal detection process;

[0029] Obtain the total number of abnormal detection processes within the detection period and calculate the ratio with the total number of detections of the industrial underwater environment within the detection period to obtain the abnormal detection eigenvalue. And calculate the average value of the detection non-optimal occupancy table values of all industrial underwater detection processes within the detection period to obtain the non-optimal eigenvalue. Numerically compare the abnormal detection eigenvalue and the non-optimal eigenvalue with the preset abnormal detection eigenvalue threshold and the preset non-optimal eigenvalue threshold respectively. If the abnormal detection eigenvalue or the non-optimal eigenvalue exceeds the corresponding preset threshold, generate a detection management unqualified signal. If both the abnormal detection eigenvalue and the non-optimal eigenvalue do not exceed the corresponding preset threshold, generate a detection management qualified signal.

[0030] Further, the specific analysis process of the foreign object risk level zoning detection and analysis is as follows:

[0031] Divide the underwater industrial environment into several regions. Collect the total number of foreign objects appearing in the corresponding region within the detection period and calculate the ratio with the total number of detections of the industrial underwater environment within the detection period to obtain the foreign object detection frequency value. And mark the ratio of the number of detection times of detecting foreign objects in the corresponding region within the detection period as the foreign object detection table value.

[0032] Perform numerical calculation on the foreign object detection frequency value and the foreign object detection table value to obtain the foreign object risk area table value. Numerically compare the foreign object risk area table value with the preset foreign object risk area table threshold. If the foreign object risk area table value exceeds the preset foreign object risk area table threshold, mark the corresponding region as a foreign object high-risk area. If the foreign object risk area table value does not exceed the preset foreign object risk area table threshold, mark the corresponding region as a foreign object low-risk area.

[0033] Further, the present invention also proposes an industrial underwater camera monitoring and early warning method based on foreign object detection, including the following steps:

[0034] Step 1: Establish a GIS map of the industrial underwater environment and plan an underwater inspection path based on the GIS map of the industrial underwater environment.

[0035] Step 2: Start the underwater inspection robot and make it perform inspections along the preset underwater inspection path.

[0036] Step 3: The underwater auxiliary lighting module provides light underwater, the underwater camera module performs real-time imaging of the industrial underwater environment, and the multi-beam forward-looking sonar module uses acoustic wave detection technology to perform imaging detection under low visibility.

[0037] Step 4: Process the collected underwater images and sonar data to identify the type, location, and size of foreign objects in the industrial underwater environment.

[0038] Step 5: Trigger the early warning mechanism when a foreign object is found, send the foreign object information to the ground monitoring center, and the ground monitoring center takes corresponding countermeasures according to the early warning information.

[0039] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0040] 1. In the present invention, underwater foreign object recognition is carried out through underwater images and sonar data, achieving full coverage of the industrial underwater environment, which is beneficial to timely discovering and handling underwater safety hazards. Moreover, by analyzing the operation control status of the underwater inspection robot, reasonable regulation and treatment measures can be made for the underwater inspection robot in a timely manner to ensure the safe and stable operation of the underwater inspection robot, with high levels of intelligence and automation;

[0041] 2. In the present invention, the underwater detection management module analyzes the detection management performance of the industrial underwater environment during the detection period. When a detection management unqualified signal is generated, the ground monitoring center issues a warning to remind the ground management personnel to strengthen the subsequent detection supervision of the industrial underwater environment, ensuring detection timeliness and detection execution performance, and further guaranteeing the safety of the underwater industrial environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] For the convenience of those skilled in the art to understand, the present invention will be further described below with reference to the accompanying drawings;

[0043] Figure 1 It is the system block diagram of the first embodiment in the present invention;

[0044] Figure 2 It is the system block diagram of the second embodiment in the present invention;

[0045] Figure 3 It is the method flow chart of the third embodiment in the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0046] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0047] Embodiment 1: As Figure 1 shown, the industrial underwater camera monitoring and warning system based on foreign object detection proposed by the present invention includes a GIS map module, an inspection path planning module, an underwater camera module, an underwater auxiliary lighting module, a multi-beam forward-looking sonar module, an underwater wireless communication module, an abnormal detection and recognition output module, and a ground monitoring center;

[0048] The GIS map module creates a GIS map of the industrial underwater environment and sends the GIS map of the industrial underwater environment to the inspection path planning module and the ground monitoring center. The inspection path planning module is used to plan the underwater inspection path and send the underwater inspection path to the ground monitoring center;

[0049] The ground monitoring center sends the GIS map of the industrial underwater environment and the current underwater inspection path to the underwater inspection robot. The underwater wireless communication module receives the GIS map of the industrial underwater environment and the current underwater inspection path, and after starting the underwater inspection robot, makes it conduct inspections along the preset underwater inspection path;

[0050] The underwater camera module, the underwater auxiliary lighting module, the multi-beam forward-looking sonar module, and the underwater wireless communication module are all set on the underwater inspection robot. The underwater camera module conducts real-time imaging of the industrial underwater environment through a high-resolution camera, and the camera is equipped with automatic focusing and anti-shake functions to ensure stable and clear images;

[0051] The underwater auxiliary lighting module provides light underwater to ensure normal imaging under low-light conditions. The multi-beam forward-looking sonar module conducts imaging detection under low visibility to accurately locate underwater foreign objects. The underwater wireless communication module sends the underwater images and sonar data to the anomaly detection and recognition output module and the ground monitoring center;

[0052] The anomaly detection and recognition output module processes the collected underwater images and sonar data, identifies features such as the type, location, and size of foreign objects, triggers an early warning mechanism when foreign objects are found, and sends the foreign object information to the ground monitoring center. The ground monitoring center takes corresponding countermeasures according to the early warning information.

[0053] The present invention combines visual and acoustic monitoring to achieve full coverage of the underwater environment, improve the accuracy of foreign object detection, ensure timely discovery and handling of potential safety hazards through a real-time early warning mechanism, reduce the accident risk, and is applicable to different water depths, lighting conditions, and water quality environments to meet diverse monitoring needs.

[0054] Moreover, an underwater detection control and analysis module is also provided on the underwater inspection robot. The underwater detection control and analysis module analyzes the operation control status of the underwater inspection robot, generates a detection control qualified signal or a detection control unqualified signal through analysis, and sends the detection control qualified signal or the detection control unqualified signal to the ground monitoring center via the underwater wireless communication module. When the ground monitoring center receives the detection control unqualified signal, it issues a corresponding early warning to remind the ground management personnel to conduct cause investigation and analysis and make reasonable regulation and treatment measures for the underwater inspection robot to ensure the safe and stable operation of the underwater inspection robot and reduce the supervision difficulty of the ground management personnel. The specific analysis process of the underwater detection control and analysis module is as follows:

[0055] Collect the actual running path of the underwater inspection robot within a unit time, overlap and compare the actual running path with the corresponding part of the preset underwater inspection path, and mark the ratio of the length of the non-overlapped path between the two as the path control anomaly value. It should be noted that the larger the value of the path control anomaly value, the worse the performance of the detection path control execution within a unit time; compare the path control anomaly value with the preset path control anomaly threshold value. If the path control anomaly value exceeds the preset path control anomaly threshold value, it indicates that the performance of the detection path control execution within a unit time is poor, and then generate a detection control unqualified signal.

[0056] Furthermore, if the path control anomaly value does not exceed the preset path control anomaly threshold value, then mark the number of times and the total duration of the deviation of the actual running path of the underwater inspection robot within a unit time from the preset underwater inspection path as the detection deviation frequency and the detection deviation duration respectively;

[0057] And collect the traveling speed of the underwater inspection robot, calculate the difference between the traveling speed and the median of the preset traveling speed range and take the absolute value to obtain the traveling anomaly value, calculate the average value of all traveling anomaly values within a unit time to obtain the traveling anomaly table value, and compare the traveling anomaly value with the preset traveling anomaly threshold value, and mark the ratio of the number of traveling anomaly values exceeding the preset traveling anomaly threshold value within a unit time as the traveling risk value;

[0058] Perform numerical calculation on the path control anomaly value SY, the detection deviation frequency ZF, the detection deviation duration TW, the traveling anomaly table value HP, and the traveling risk value WX through the formula XP = eq×SY + uy×ZF + np×TW + re×HP + tu×WX to obtain the traveling pipe anomaly coefficient XP; where eq, uy, np, re, tu are preset proportionality coefficients greater than zero, and moreover, the larger the value of the traveling pipe anomaly coefficient XP, the worse the comprehensive performance of the traveling control of the underwater inspection robot within a unit time;

[0059] Compare the traveling pipe anomaly coefficient XP with the corresponding preset traveling pipe anomaly coefficient threshold value. If the traveling pipe anomaly coefficient XP exceeds the preset traveling pipe anomaly coefficient threshold value, it indicates that the comprehensive performance of the traveling control of the underwater inspection robot within a unit time is poor, and then generate a detection control unqualified signal;

[0060] If the traveling pipe anomaly coefficient XP does not exceed the preset traveling pipe anomaly coefficient threshold value, it indicates that the comprehensive performance of the traveling control of the underwater inspection robot within a unit time is good, and then obtain the detection devices on the underwater inspection robot that need to be supervised, mainly referring to the underwater camera module, the underwater auxiliary lighting module, and the multi-beam forward-looking sonar module, and perform operation monitoring on the detection devices that need to be supervised;

[0061] Obtain the operating parameters that the corresponding detection device needs to monitor (such as operating power, operating current and other parameters), compare the real-time data of the corresponding operating parameters with the corresponding preset data requirements. If there are operating parameters that do not meet the corresponding preset data requirements, it indicates that the operation of the corresponding detection device is abnormal, and then it is determined that the corresponding detection device is in a detection abnormal state;

[0062] Obtain the total duration of the corresponding detection device in the detection abnormal state within a unit time and mark it as the detection abnormal value. Compare the detection abnormal value with the corresponding preset detection abnormal threshold value. If the detection abnormal value exceeds the corresponding preset detection abnormal threshold value, it indicates that the operation performance of the corresponding detection device is poor, and then mark the corresponding detection device as an abnormal device;

[0063] Obtain the number of detection devices marked as abnormal devices within a unit time and define it as the abnormal detection value. Calculate the ratio of the detection abnormal value of the corresponding detection device to the corresponding preset detection abnormal threshold value to obtain the abnormal time occupancy ratio. Calculate the average value of the abnormal time occupancy ratios of all detection devices to obtain the abnormal performance value, and mark the largest abnormal time occupancy ratio as the abnormal high amplitude value;

[0064] Perform numerical calculation on the abnormal detection value HX, the abnormal performance value YM and the abnormal high amplitude value SF through the formula LW = ep×HX+(sg×YM + kt×SF) / 2 to obtain the comprehensive detection value LW of the detection device; where ep, sg, kt are preset weight coefficients with values greater than zero, and moreover, the larger the value of the comprehensive detection value LW of the detection device, the greater the adverse impact on the detection performance of the underwater inspection robot;

[0065] Compare the comprehensive detection value LW of the detection device with the preset comprehensive detection threshold value of the detection device. If the comprehensive detection value LW of the detection device exceeds the preset comprehensive detection threshold value of the detection device, it indicates that the adverse impact on the detection performance of the underwater inspection robot is relatively large, and then generate a detection control unqualified signal; if the comprehensive detection value LW of the detection device does not exceed the preset comprehensive detection threshold value of the detection device, it indicates that the current can ensure effective monitoring and detection of the industrial underwater environment, and then generate a detection control qualified signal.

[0066] Embodiment 2: As Figure 2 shown, the difference between this embodiment and Embodiment 1 is that the abnormal detection and recognition output module is communicatively connected to the underwater detection management module. The abnormal detection and recognition output module sends all the identified foreign object information to the underwater detection management module. The underwater detection management module is used to set a detection cycle with the number of days being W1. Preferably, W1 is thirty-five days;

[0067] Analyze the detection management performance for the industrial underwater environment during the detection period. Generate a qualified signal or an unqualified signal for detection management through the analysis, and send the qualified signal or unqualified signal for detection management to the ground monitoring center. When the ground control center receives the unqualified signal for detection management, it issues a corresponding warning to remind the ground management personnel to strengthen the detection supervision of the industrial underwater environment in the follow-up, ensure the timeliness of detection and the performance of detection execution, and further ensure the safety of the underwater industrial environment. The specific analysis process of the underwater detection management module is as follows:

[0068] Obtain the start time of detecting the industrial underwater environment during the detection period. Calculate the time difference between two adjacent start times to obtain the detection time difference. Compare the detection time difference with the preset detection time difference threshold. If the detection time difference exceeds the preset detection time difference threshold, it indicates that the interval time between the corresponding two detection processes is too long and the potential risk is relatively large. Then mark the corresponding detection time difference as an abnormal time difference.

[0069] Obtain the number of abnormal time differences during the detection period and mark it as the abnormal detection value. Calculate the average value of all detection time differences to obtain the interval detection value. Compare the abnormal detection value and the interval detection value with the preset abnormal detection threshold and the preset interval detection threshold respectively. If the abnormal detection value or the interval detection value exceeds the corresponding preset threshold, it indicates that the management status of detecting the industrial underwater environment during the detection period is poor. Then generate an unqualified signal for detection management.

[0070] If both the abnormal detection value and the interval detection value do not exceed the corresponding preset thresholds, then mark the corresponding area as a high foreign object risk area or a low foreign object risk area through the detection and analysis of the foreign object risk level zoning. Specifically: Divide the underwater industrial environment into several areas. Collect the total number of foreign objects appearing in the corresponding area during the detection period and calculate the ratio of it to the total number of detections of the industrial underwater environment during the detection period to obtain the foreign object detection frequency value. And mark the ratio of the number of detections of foreign objects in the corresponding area during the detection period (that is, the ratio of the number of detections of foreign objects in the corresponding area during the detection period to the total number of detections of the industrial underwater environment during the detection period) as the foreign object detection appearance value.

[0071] Perform numerical calculation on the foreign object detection frequency value GY and the foreign object detection appearance value PX through the formula QX = b×GY + m×PX to obtain the foreign object risk area appearance value QX. Where b and m are preset weight coefficients, m > b > 0. And the larger the value of the foreign object risk area appearance value QX, the higher the risk degree of foreign objects in the corresponding area, and the more necessary it is to conduct key detection on the corresponding area.

[0072] Compare the foreign object risk area table value QX with the preset foreign object risk area table threshold value. If the foreign object risk area table value QX exceeds the preset foreign object risk area table threshold value, it indicates that the risk degree of foreign objects in the corresponding area is relatively high, and key detection needs to be carried out on the corresponding area. Then, mark the corresponding area as a high foreign object risk area; if the foreign object risk area table value QX does not exceed the preset foreign object risk area table threshold value, it indicates that the risk degree of foreign objects in the corresponding area is relatively low. Then, mark the corresponding area as a low foreign object risk area;

[0073] If the corresponding area is a high foreign object risk area, allocate the preset detection duration threshold YL1 to it; if the corresponding area is a low foreign object risk area, allocate the preset detection duration threshold YL2 to it, and YL1 > YL2 > 0; at the end of the corresponding industrial underwater detection process, collect the detection duration for each area in the industrial underwater environment, and compare the detection duration of the corresponding area with the corresponding preset detection duration threshold value. If the detection duration does not exceed the preset detection duration threshold value, it indicates that the detection of the corresponding area during the corresponding industrial underwater detection process is too fast. Then, mark the corresponding area as a non-optimal detection area;

[0074] Obtain the ratio of the number of non-optimal detection areas in the corresponding industrial underwater detection process and mark it as the non-optimal detection ratio table value. Compare the non-optimal detection ratio table value with the preset non-optimal detection ratio table threshold value. If the non-optimal detection ratio table value exceeds the preset non-optimal detection ratio table threshold value, it indicates that the management performance of the corresponding industrial underwater detection process is poor. Then, mark the corresponding industrial underwater detection process as an abnormal detection process; obtain the total number of abnormal detection processes within the detection period and calculate the ratio with the total number of detections of the industrial underwater environment during the detection period to obtain the abnormal detection characteristic value, and calculate the average value of the non-optimal detection ratio table values of all industrial underwater detection processes within the detection period to obtain the non-optimal characteristic value;

[0075] Compare the abnormal detection characteristic value and the non-optimal characteristic value with the preset abnormal detection characteristic threshold value and the preset non-optimal characteristic threshold value respectively. If the abnormal detection characteristic value or the non-optimal characteristic value exceeds the corresponding preset threshold value, it indicates that the management status of the detection of the industrial underwater environment during the detection period is poor. Then, generate a detection management unqualified signal; if both the abnormal detection characteristic value and the non-optimal characteristic value do not exceed the corresponding preset threshold values, it indicates that the management status of the detection of the industrial underwater environment during the detection period is good. Then, generate a detection management qualified signal.

[0076] Embodiment 3: The difference between this embodiment and Embodiment 1 and Embodiment 2 is that the industrial underwater camera monitoring and early warning method based on foreign object detection proposed by the present invention, as Figure 3 shown, includes the following steps:

[0077] Step 1: Establish a GIS map of the industrial underwater environment and plan an underwater inspection path based on the GIS map of the industrial underwater environment;

[0078] Step 2: Start the underwater inspection robot and make it perform inspections along the preset underwater inspection path;

[0079] Step 3: The underwater auxiliary lighting module provides light underwater, the underwater camera module performs real-time imaging of the industrial underwater environment, and the multi-beam forward-looking sonar module uses acoustic wave detection technology to perform imaging detection under low visibility;

[0080] Step 4: Process the collected underwater images and sonar data to identify the type, location, and size of foreign objects in the industrial underwater environment;

[0081] Step 5: Trigger the warning mechanism when a foreign object is found, send the foreign object information to the ground monitoring center, and the ground monitoring center takes corresponding countermeasures according to the warning information.

[0082] The working principle of the present invention: When in use, a GIS map of the industrial underwater environment is established through the GIS map module, the underwater inspection path is planned by the inspection path planning module, the underwater inspection robot performs inspections along the preset underwater inspection path, the underwater auxiliary lighting module provides light underwater, the underwater camera module performs real-time imaging of the industrial underwater environment, and the multi-beam forward-looking sonar module performs auxiliary imaging detection under low visibility to achieve full coverage of the underwater environment, improve the accuracy of foreign object detection, the abnormal detection and recognition output module performs underwater foreign object recognition based on underwater images and sonar data, triggers the warning mechanism when a foreign object is found to ensure timely discovery and handling of potential safety hazards, reduce the accident risk, and analyze the operation control status of the underwater inspection robot through the underwater detection control analysis module. When a detection control unqualified signal is generated, remind the ground management personnel to conduct a cause investigation and analysis and make reasonable regulation and treatment measures for the underwater inspection robot to ensure the safe and stable operation of the underwater inspection robot, reduce the supervision difficulty of the ground management personnel, and have a high level of intelligence and automation.

[0083] The above formulas are all dimensionless and take their numerical values for calculation. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain a formula that is closest to the actual situation. The preset parameters in the formulas are set by those skilled in the art according to the actual situation. The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only the specific implementation manners. Obviously, many modifications and variations can be made according to the content of this specification. This specification selects and specifically describes these embodiments to better explain the principle and practical application of the present invention, so that those skilled in the art in the technical field can well understand and utilize the present invention. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. The industrial underwater camera monitoring and early warning system based on foreign body detection is characterized by: It includes an underwater camera module, an underwater auxiliary lighting module, a multi-beam forward-looking sonar module, an underwater wireless communication module, an anomaly detection and recognition output module and a ground monitoring center; the underwater camera module performs real-time imaging of the industrial underwater environment, the underwater auxiliary lighting module provides lighting underwater, the multi-beam forward-looking sonar module performs imaging detection under low visibility, and the underwater wireless communication module sends underwater images and sonar data to the anomaly detection and recognition output module and the ground monitoring center; The anomaly detection and recognition output module processes the collected underwater images and sonar data, identifies the type, location and size of foreign objects, triggers the early warning mechanism when foreign objects are found, and sends the foreign object information to the ground monitoring center. The ground monitoring center takes corresponding response measures based on the early warning information.

2. The industrial underwater camera monitoring and early warning system based on foreign body detection according to claim 1 is characterized in that: The ground monitoring center communicates with the GIS map module and the inspection path planning module. The GIS map module establishes a GIS map of the industrial underwater environment. The inspection path planning module is used to plan the underwater inspection path. After the underwater inspection robot is started, it inspects along the preset underwater inspection path.

3. The industrial underwater camera monitoring and early warning system based on foreign body detection according to claim 2 is characterized in that: The underwater inspection robot is also equipped with an underwater detection control analysis module, which analyzes the operation control status of the underwater inspection robot, generates a detection control qualified signal or a detection control unqualified signal through analysis, and sends the detection control qualified signal or the detection control unqualified signal to the ground monitoring center via the underwater wireless communication module.

4. The industrial underwater camera monitoring and early warning system based on foreign body detection according to claim 3 is characterized in that: The specific analysis process of the underwater detection control analysis module includes: The actual running path of the underwater inspection robot in unit time is collected, and the actual running path is compared with the corresponding part of the preset underwater inspection path for overlap. The proportion of the path length that does not overlap between the two is marked as a path control anomaly value. If the path control anomaly value exceeds the preset path control anomaly threshold, a detection control failure signal is generated.

5. The industrial underwater camera monitoring and early warning system based on foreign body detection according to claim 4 is characterized in that: If the path control abnormality value does not exceed the preset path control abnormality threshold, the path control abnormality value, the detection control deviation frequency, the detection control deviation duration, the travel abnormality table value and the travel abnormality risk value are numerically calculated to obtain the travel control abnormality coefficient. If the travel control abnormality coefficient exceeds the preset travel control abnormality coefficient threshold, a detection control unqualified signal is generated; If the travel pipe abnormal coefficient does not exceed the preset travel pipe abnormal coefficient threshold, the detection equipment comprehensive inspection value is obtained through analysis. If the detection equipment comprehensive inspection value exceeds the preset detection equipment comprehensive inspection threshold, a detection control unqualified signal is generated; otherwise, a detection control qualified signal is generated.

6. The industrial underwater camera monitoring and early warning system based on foreign body detection according to claim 5 is characterized in that: The analysis and acquisition method of the comprehensive inspection value of the detection equipment is as follows: The detection equipment that needs to be supervised on the underwater inspection robot is obtained. If the detection anomaly value exceeds the corresponding preset detection anomaly threshold, the corresponding detection equipment will be marked as an abnormal device; the comprehensive inspection value of the detection equipment is obtained by numerically calculating the abnormal detection value, the anomaly performance value and the anomaly high amplitude value.

7. The industrial underwater camera monitoring and early warning system based on foreign body detection according to claim 1 is characterized in that: The anomaly detection and identification output module is communicatively connected to the underwater detection management module. The underwater detection management module analyzes the detection management performance of the industrial underwater environment during the detection cycle, generates a detection management qualified signal or a detection management unqualified signal through the analysis, and sends the detection management qualified signal or the detection management unqualified signal to the ground monitoring center.

8. The industrial underwater camera monitoring and early warning system based on foreign body detection according to claim 7 is characterized in that: The specific analysis process of the underwater detection management module is as follows: The number of detection anomaly time differences within the detection period is obtained and marked as the detection anomaly detection value, and the detection interval detection value is obtained by averaging all the detection time differences. If the detection anomaly detection value or the detection interval detection value exceeds the corresponding preset threshold, a detection management unqualified signal is generated; If both the detection anomaly value and the detection interval value do not exceed the corresponding preset threshold, the detection anomaly characteristic value and the non-optimal characteristic value are obtained. If the detection anomaly characteristic value or the non-optimal characteristic value exceeds the corresponding preset threshold, a detection management unqualified signal is generated; otherwise, a detection management qualified signal is generated.

9. An industrial underwater camera monitoring and early warning method based on foreign body detection, characterized in that: The method adopts the industrial underwater camera monitoring and early warning system based on foreign body detection as described in any one of claims 1-8.

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