Video inspection method and system for gas pipeline scene, terminal and medium

Abstract

The invention discloses a video inspection method and system for a gas pipeline scene, a terminal and a medium, and the method comprises the steps: obtaining a gas safety monitoring demand of the gas pipeline scene, collecting corresponding video file data according to the gas safety monitoring demand, and carrying out the abnormal recognition processing of the video file data, and obtaining a recognition result; if an abnormal event exists in the recognition result, making a pipeline inspection plan according to the abnormal event, and reminding corresponding inspection personnel to perform pipeline inspection according to the pipeline inspection plan; and receiving an inspection record uploaded by the inspection personnel, and performing data analysis on the inspection record to obtain a pipeline inspection result. The gas pipeline scene is subjected to video inspection, so that the inspection efficiency and the inspection accuracy can be improved, and a reasonable inspection plan can be made in time, thereby shortening the processing time of abnormal events, improving the processing efficiency of the abnormal events and reducing potential safety hazards.

Description

Technical Field

[0001] The present invention relates to the technical field of video patrol inspection, and particularly relates to a video patrol inspection method, system, terminal and computer-readable storage medium for a gas pipeline scenario. Background Art

[0002] Urban gas safety is an important part of urban safety. As an important link affecting urban gas safety, the special operations of gas pipelines are related to the normal operation of the pipe network. However, during the special operations of gas pipelines, there are often phenomena such as supervisors leaving their posts and operators impersonating others, and there are a series of problems such as the failure to implement safety construction guarantee measures in place and the non-standard operation process.

[0003] At present, for gas patrol inspection, it is monitored and identified manually. Not only is the efficiency of monitoring and identification low, resulting in low patrol inspection efficiency, but also the accuracy of patrol inspection is not high, and there are problems such as missed inspections and incorrect inspections, thus there are potential safety hazards. Therefore, a practical solution is urgently needed to solve the problems and potential safety hazards existing in the patrol inspection in gas stations.

[0004] Therefore, the prior art still needs to be improved and developed. Summary of the Invention

[0005] The main purpose of the present invention is to provide a video patrol inspection method, system, terminal and medium for a gas pipeline scenario, aiming to solve the problems of low patrol inspection efficiency and low patrol inspection accuracy caused by manual monitoring and identification in the prior art.

[0006] To achieve the above object, the present invention provides a video patrol inspection method for a gas pipeline scenario, and the video patrol inspection method for the gas pipeline scenario includes the following steps:

[0007] Obtain the gas safety monitoring requirements for the gas pipeline scenario, collect the corresponding video file data according to the gas safety monitoring requirements, and perform abnormal identification processing on the video file data to obtain an identification result;

[0008] If there is an abnormal event in the identification result, formulate a pipeline patrol inspection plan according to the abnormal event, and remind the corresponding patrol inspection personnel to conduct pipeline patrol inspection according to the pipeline patrol inspection plan;

[0009] Receive the patrol inspection records uploaded by the patrol inspection personnel, perform data analysis on the patrol inspection records to obtain the pipeline patrol inspection result.

[0010] Optionally, in the video inspection method for the gas pipeline scenario, the steps of obtaining the gas safety monitoring requirements for the gas pipeline scenario, collecting corresponding video file data according to the gas safety monitoring requirements, and performing anomaly recognition processing on the video file data to obtain a recognition result specifically include:

[0011] Obtain the gas safety monitoring requirements for the gas pipeline scenario, collect corresponding video file data according to the gas safety monitoring requirements, and perform image extraction on the video file data to obtain a target scenario image;

[0012] Extract features from the target scenario image according to the recognition objects to obtain image features, perform average pooling on the image features, and perform fully connected processing on the image features after average pooling to obtain convolutional features, where the recognition objects include station personnel, station vehicles, and station objects;

[0013] Fuse the image features and the convolutional features to obtain target image features, and perform anomaly recognition processing according to the target image features to obtain a recognition result.

[0014] Optionally, the recognition result includes a first recognition result, a second recognition result, and a third recognition result;

[0015] In the video inspection method for the gas pipeline scenario, the steps of performing anomaly recognition processing according to the target image features to obtain a recognition result specifically include:

[0016] If the recognition object is the station personnel, then identify the identity information and behavior actions of the station personnel according to the target image features to obtain a first recognition result;

[0017] If the recognition object is the station vehicle, then identify the license plate information and safety identification of the station vehicle according to the target image features to obtain a second recognition result;

[0018] If the recognition object is the station object, then identify the object information and object position of the station object according to the target image features to obtain a third recognition result.

[0019] Optionally, in the video inspection method for the gas pipeline scenario, after performing anomaly recognition processing on the video file data to obtain a recognition result, the following steps are further included:

[0020] If the verification of the identity information of the station personnel fails, or the behavior actions of the station personnel are unsafe actions, then it is determined that an abnormal event exists in the first recognition result;

[0021] If the license plate information of the station vehicle does not match, or the safety identification of the station vehicle does not exist, it is determined that an abnormal event exists in the second recognition result;

[0022] If the object information of the station object is incorrect, or the object position of the station object changes, it is determined that an abnormal event exists in the third recognition result.

[0023] Optionally, in the video inspection method for the gas pipeline scenario, where if an abnormal event exists in the recognition result, a pipeline inspection plan is formulated according to the abnormal event, and the corresponding inspection personnel are reminded to conduct pipeline inspection according to the pipeline inspection plan, specifically including:

[0024] If an abnormal event exists in the recognition result, an inspection task is generated according to the abnormal event, and an inspection management template is matched according to the inspection task to obtain a target inspection management template;

[0025] A target inspection route is obtained by formulating a route according to the inspection task, and inspection personnel are obtained by matching personnel according to the inspection task;

[0026] A pipeline inspection plan is formulated according to the target inspection management template, the target inspection route, and the inspection personnel, and the inspection personnel are reminded to conduct pipeline inspection according to the pipeline inspection plan.

[0027] Optionally, in the video inspection method for the gas pipeline scenario, where if an abnormal event exists in the recognition result, a pipeline inspection plan is formulated according to the abnormal event, and the corresponding inspection personnel are reminded to conduct pipeline inspection according to the pipeline inspection plan, and then it further includes:

[0028] If the number of abnormal events in the recognition result is greater than or equal to the warning peak value, a warning accusation command is generated, corresponding warning actions are executed according to the warning accusation command, and a personnel evacuation reminder is issued.

[0029] Optionally, in the video inspection method for the gas pipeline scenario, where the pipeline inspection result includes that the inspection has reached the standard and the inspection has not reached the standard;

[0030] Receiving the inspection record uploaded by the inspection personnel, and performing data analysis on the inspection record to obtain the pipeline inspection result, specifically including:

[0031] Receiving the inspection record uploaded by the inspection personnel, performing data analysis on the inspection time and inspection method of the inspection record to obtain the inspection analysis status, and judging whether the pipeline inspection result reaches the standard according to the inspection analysis status;

[0032] If the inspection time exceeds the preset time or the inspection method does not meet the inspection requirements, it is determined that the pipeline inspection result fails to meet the standard;

[0033] If the inspection time does not exceed the preset time and the inspection method meets the inspection requirements, it is determined that the pipeline inspection result meets the standard.

[0034] Optionally, in the video inspection method for the gas pipeline scenario, the video inspection system for the gas pipeline scenario includes:

[0035] Anomaly recognition module, configured to obtain the gas safety monitoring requirements for the gas pipeline scenario, collect the corresponding video file data according to the gas safety monitoring requirements, and perform anomaly recognition processing on the video file data to obtain the recognition result;

[0036] Plan formulation module, configured to, if an abnormal event exists in the recognition result, formulate a pipeline inspection plan according to the abnormal event, and remind the corresponding inspection personnel to perform pipeline inspection according to the pipeline inspection plan;

[0037] Data analysis module, configured to receive the inspection records uploaded by the inspection personnel, perform data analysis on the inspection records, and obtain the pipeline inspection result.

[0038] In addition, to achieve the above object, the present invention further provides a terminal, where the terminal includes: a memory, a processor, and a video inspection program for the gas pipeline scenario stored on the memory and executable on the processor. When the video inspection program for the gas pipeline scenario is executed by the processor, the steps of the video inspection method for the gas pipeline scenario as described above are implemented.

[0039] In addition, to achieve the above object, the present invention further provides a computer-readable storage medium, where the computer-readable storage medium stores a video inspection program for the gas pipeline scenario. When the video inspection program for the gas pipeline scenario is executed by a processor, the steps of the video inspection method for the gas pipeline scenario as described above are implemented.

[0040] In the present invention, the gas safety monitoring requirements of the gas pipeline scenario are obtained, corresponding video file data is collected according to the gas safety monitoring requirements, and the video file data is subjected to abnormal identification processing to obtain an identification result; if there is an abnormal event in the identification result, a pipeline inspection plan is formulated according to the abnormal event, and the corresponding inspection personnel are reminded to conduct pipeline inspection according to the pipeline inspection plan; the inspection records uploaded by the inspection personnel are received, and the inspection records are analyzed to obtain the pipeline inspection result. By performing video inspections on the gas pipeline scenario, the present invention can not only improve the inspection efficiency and accuracy, but also timely formulate a reasonable inspection plan, thereby shortening the disposal time of abnormal events, improving the processing efficiency of abnormal events, and reducing potential safety hazards. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 is a flowchart of a preferred embodiment of the video inspection method for the gas pipeline scenario of the present invention;

[0042] Figure 2 is a structural diagram of a preferred embodiment of the video inspection system for the gas pipeline scenario of the present invention;

[0043] Figure 3 is a schematic diagram of the operating environment of a preferred embodiment of the terminal of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0044] To make the objectives, technical solutions and advantages of the present invention clearer and more explicit, the following further describes the present invention in detail with reference to the accompanying drawings and by way of examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0045] It should be noted that if there are directional indications (such as up, down, left, right, front, back...) involved in the embodiments of the present invention, the directional indications are only used to explain the relative positional relationship and movement conditions between components in a specific posture (as shown in the drawings). If the specific posture changes, the directional indications will also change accordingly.

[0046] In addition, if there are descriptions such as "first", "second", etc. involved in the embodiments of the present invention, the descriptions of "first", "second", etc. are only for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one of such features. In addition, the technical solutions between various embodiments can be combined with each other, but it must be based on the fact that those skilled in the art can implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the protection scope required by the present invention.

[0047] In the video inspection method for the gas pipeline scenario according to a preferred embodiment of the present invention, as Figure 1 shown, the video inspection method for the gas pipeline scenario includes the following steps:

[0048] Step S10: Obtain the gas safety monitoring requirements for the gas pipeline scenario, collect the corresponding video file data according to the gas safety monitoring requirements, and perform anomaly recognition processing on the video file data to obtain a recognition result.

[0049] The step S10 includes:

[0050] Step S11: Obtain the gas safety monitoring requirements for the gas pipeline scenario, collect the corresponding video file data according to the gas safety monitoring requirements, and perform image extraction on the video file data to obtain a target scenario image;

[0051] Step S12: Extract features from the target scenario image according to the recognition objects to obtain image features, perform average pooling on the image features, and perform fully connected processing on the image features after average pooling to obtain convolutional features, where the recognition objects include station personnel, station vehicles, and station objects;

[0052] Step S13: Perform feature fusion on the image features and the convolutional features to obtain target image features, and perform anomaly recognition processing according to the target image features to obtain a recognition result.

[0053] Specifically, to solve the problems of high labor and material costs in traditional video monitoring, long response time, low inspection efficiency, and low inspection accuracy, in the embodiment of the present invention, through video inspection of the gas pipeline scenario, not only can the inspection efficiency and inspection accuracy be improved, but also a reasonable inspection plan can be formulated in a timely manner, thereby shortening the disposal time of abnormal events, improving the processing efficiency of abnormal events, and thus reducing potential safety hazards; the specific processing process is to obtain the gas safety monitoring requirements for the gas pipeline scenario, collect the corresponding video file data according to the gas safety monitoring requirements, and perform image extraction on the video file data to obtain a target scenario image; then, it is necessary to extract features from the target scenario image. In the present invention, the target detection algorithm YOLOv5 based on deep learning is used for extraction. First, the recognition objects are determined, where the recognition objects include station personnel, station vehicles, and station objects; according to the target detection algorithm YOLOv5 and the recognition objects, features are extracted from the target scenario image to obtain image features.

[0054] When the target detection algorithm YOLOv5 is actually applied, due to the certain gap from the laboratory environment, the detection effect of the algorithm is affected to a certain extent by factors such as weather and distance. Moreover, as the weather or distance changes, the pixels of the targets in the image will be inconsistent in the overall image, which makes it difficult for the algorithm to recognize and results in false detections and missed detections, affecting production safety. To address such problems, the present invention introduces an attention mechanism module, for example, the yolo-SE module, and embeds it into the algorithm. The attention mechanism is a unique brain signal processing mechanism in human vision. By quickly scanning the global image, it obtains the target areas that need to be focused on (for example, the personnel part in a gas station or the specific target part to be recognized), which is generally referred to as the attention focus. Then, more attention resources are invested in this area to obtain more detailed information of the targets that need to be concerned, while suppressing other useless information. Specifically, the image features are subjected to average pooling to obtain a global compressed feature quantity. After that, the image features after average pooling are subjected to fully connected processing to obtain convolutional features, that is, two fully connected operations are performed. The first fully connected layer has c / 16 neurons for dimensionality reduction, and the size of the second fully connected layer reaches C neurons. The advantage of this is to increase more non-linear processing to adapt to the complex correlations between channels. Subsequently, the image features and the convolutional features are subjected to feature fusion, that is, the image features and the convolutional features are multiplied to obtain a feature with different re-weights for different channels, that is, the target image features. And based on the target image features, anomaly recognition processing is performed to obtain the recognition result. The present invention improves the probability of successful detection and better reduces false alarms and missed detections by introducing the attention mechanism module to eliminate the influence of background, weather, human occlusion, and distance.

[0055] Further, in the embodiments of the present invention, different abnormal recognition processes are applicable to different recognition objects, and different recognition results can be obtained. Specifically, if the recognition object is the station personnel, the identity information and behavior actions of the station personnel are recognized based on the target image features to obtain a first recognition result. For example, for the identity information, face recognition is performed on the station personnel entering and leaving the station, and the station personnel who do not meet the requirements are intercepted and alerted, so as to prevent station personnel from leaving their posts during working hours or other workers impersonating them, thus avoiding serious work accidents. For the behavior actions, the wearing of safety helmets and the proper wearing of work clothes by the station personnel are detected in real time to ensure the proper dressing norms at the work site. If the recognition object is the station vehicle, the license plate information and safety signs of the station vehicle are recognized based on the target image features to obtain a second recognition result. For example, for the safety signs, the static grounding belt of the vehicle is recognized. If the recognition object is the station object, the object information and object position of the station object are recognized based on the target image features to obtain a third recognition result. For example, for the object information, warning signs, sleepers, fire extinguishers, etc. at the gas station are recognized; thus, the safe and efficient working environment at the gas station is guaranteed.

[0056] Further, for the station personnel, if the verification of the identity information of the station personnel fails, or the behavior actions of the station personnel are unsafe actions, it is determined that an abnormal event exists in the first recognition result; if the verification of the identity information of the station personnel is successful, and the behavior actions of the station personnel are safe actions, it is determined that no abnormal event exists in the recognition result. For the station vehicle, if the license plate information of the station vehicle does not match, or the safety signs of the station vehicle do not exist, it is determined that an abnormal event exists in the second recognition result; if the license plate information of the station vehicle matches, and the safety signs of the station vehicle exist, it is determined that no abnormal event exists in the recognition result. For the station object, if the object information of the station object is incorrect, or the object position of the station object has changed, it is determined that an abnormal event exists in the recognition result; if the object information of the station object is correct, and the object position of the station object has not changed, it is determined that no abnormal event exists in the third recognition result.

[0057] Step S20: If an abnormal event exists in the recognition result, a pipeline inspection plan is formulated based on the abnormal event, and the corresponding inspection personnel are reminded to conduct pipeline inspections according to the pipeline inspection plan.

[0058] The step S20 includes:

[0059] Step S21: If there is an abnormal event in the recognition result, generate an inspection task according to the abnormal event, perform matching with the inspection management template according to the inspection task, and obtain the target inspection management template;

[0060] Step S22: Develop a route according to the inspection task to obtain the target inspection route, and perform personnel matching according to the inspection task to obtain the inspection personnel;

[0061] Step S23: Develop a pipeline inspection plan according to the target inspection management template, the target inspection route and the inspection personnel, and remind the inspection personnel to conduct pipeline inspection according to the pipeline inspection plan.

[0062] Specifically, after obtaining the recognition result, it is necessary to determine whether to develop a pipeline inspection plan according to the recognition result. Specifically, if there is no abnormal event in the recognition result, there is no need to develop a pipeline inspection plan; if there is an abnormal event in the recognition result, generate an inspection task according to the abnormal event, perform matching with the inspection management template according to the inspection task, and obtain the target inspection management template; develop a route according to the inspection task to obtain the target inspection route, and perform personnel matching according to the inspection task to obtain the inspection personnel; develop a pipeline inspection plan according to the target inspection management template, the target inspection route and the inspection personnel, where the pipeline inspection plan contains information on each inspection point; and regularly send the pipeline inspection plan to the mobile terminal (such as PDA, etc.) of the inspection personnel to remind the inspection personnel to conduct inspections, thereby shortening the handling time of abnormal events, improving the handling efficiency of abnormal events, and thus reducing potential safety hazards.

[0063] Furthermore, the present invention can also perform emergency command management. Specifically, if the number of abnormal events in the recognition result is greater than or equal to the warning peak value, perform intelligent emergency processing according to the high, medium and low risks set in the warning, generate a warning control command, and execute corresponding warning actions according to the warning control command, such as automatically cutting off power and gas; and coordinate according to the actual operation conditions of each gas station, issue a reminder for personnel to evacuate in a timely manner when there is danger, and plan a route for personnel to evacuate in a timely manner, thereby reducing the losses of the gas station and ensuring the personal safety of personnel at the same time.

[0064] Step S30: Receive the inspection records uploaded by the inspection personnel, perform data analysis on the inspection records, and obtain the pipeline inspection results.

[0065] The said Step S30 includes:

[0066] Step S31: Receive the inspection records uploaded by the inspection personnel, analyze the inspection time, inspection method, and other data in the inspection records to obtain the inspection analysis status, and determine whether the pipeline inspection result meets the standard according to the inspection analysis status;

[0067] Step S32: If the inspection time exceeds the preset time or the inspection method does not meet the inspection requirements, it is determined that the pipeline inspection result is unqualified;

[0068] Step S33: If the inspection time does not exceed the preset time and the inspection method meets the inspection requirements, it is determined that the pipeline inspection result is qualified.

[0069] Specifically, in the embodiment of the present invention, after the inspection personnel complete the inspection according to the inspection plan, the corresponding inspection records are uploaded, and the inspection time, inspection method, and other data in the inspection records are analyzed to obtain the inspection analysis status, and it is determined whether the pipeline inspection result meets the standard according to the inspection analysis status; if the inspection time exceeds the preset time or the inspection method does not meet the inspection requirements, it is determined that the pipeline inspection result is unqualified; if the inspection time does not exceed the preset time and the inspection method meets the inspection requirements, it is determined that the pipeline inspection result is qualified.

[0070] Furthermore, the present invention also supports remote video data retrieval, and can play back and view the video for real-time intelligent analysis to achieve holographic perception and information collaboration; in addition, the operation status of the monitoring equipment can be understood in a timely manner in the system background. When the equipment has an abnormality, the system can respond quickly, automatically create a work order, and dispatch it to the corresponding inspection personnel, enabling the inspection personnel to timely count the operation conditions of various equipment and the equipment that needs to be repaired, which greatly facilitates the daily operation and maintenance management.

[0071] Furthermore, as Figure 2 shown, based on the above video inspection method for the gas pipeline scenario, the present invention also correspondingly provides a video inspection system for the gas pipeline scenario, wherein the video inspection system for the gas pipeline scenario includes:

[0072] Anomaly recognition module 51, which is used to obtain the gas safety monitoring requirements of the gas pipeline scenario, collect the corresponding video file data according to the gas safety monitoring requirements, and perform anomaly recognition processing on the video file data to obtain the recognition result;

[0073] Plan formulation module 52, which is used to, if an abnormal event exists in the recognition result, formulate a pipeline inspection plan according to the abnormal event, and remind the corresponding inspection personnel to perform pipeline inspection according to the pipeline inspection plan;

[0074] The data analysis module 53 is configured to receive the inspection records uploaded by the inspection personnel, perform data analysis on the inspection records, and obtain the pipeline inspection results.

[0075] Further, as Figure 3 shown, based on the above video inspection method for gas pipeline scenarios, the present invention also correspondingly provides a terminal, which includes a processor 10, a memory 20, and a display 30. Figure 3 Only some components of the terminal are shown, but it should be understood that it is not required to implement all the shown components, and more or fewer components can be alternatively implemented.

[0076] The memory 20 may be an internal storage unit of the terminal in some embodiments, such as the hard disk or memory of the terminal. The memory 20 may also be an external storage device of the terminal in other embodiments, such as a plug-in hard disk equipped on the terminal, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, etc. Further, the memory 20 may also include both the internal storage unit and the external storage device of the terminal. The memory 20 is used to store application software installed on the terminal and various types of data, such as the program code installed on the terminal, etc. The memory 20 may also be used to temporarily store data that has been output or will be output. In one embodiment, a video inspection program 40 for gas pipeline scenarios is stored on the memory 20, and the video inspection program 40 for gas pipeline scenarios can be executed by the processor 10, thereby implementing the video inspection method for gas pipeline scenarios in the present application.

[0077] The processor 10 may be a central processing unit (CPU), a microprocessor, or other data processing chips in some embodiments, and is used to run the program code stored in the memory 20 or process data, such as executing the video inspection method for gas pipeline scenarios, etc.

[0078] The display 30 may be an LED display, a liquid crystal display, a touch liquid crystal display, and an OLED (Organic Light-Emitting Diode) toucher, etc. in some embodiments. The display 30 is used to display information on the terminal and to display a visual user interface. The components of the terminal communicate with each other through a system bus.

[0079] In one embodiment, when the processor 10 executes the video inspection program 40 for gas pipeline scenarios in the memory 20, the following steps are implemented:

[0080] Obtain the gas safety monitoring requirements for the gas pipeline scenario, collect the corresponding video file data according to the gas safety monitoring requirements, and perform anomaly recognition processing on the video file data to obtain a recognition result;

[0081] If there is an abnormal event in the recognition result, formulate a pipeline inspection plan according to the abnormal event, and remind the corresponding inspection personnel to conduct pipeline inspections according to the pipeline inspection plan;

[0082] Receive the inspection records uploaded by the inspection personnel, perform data analysis on the inspection records, and obtain the pipeline inspection results.

[0083] Among them, the obtaining of the gas safety monitoring requirements for the gas pipeline scenario, collecting the corresponding video file data according to the gas safety monitoring requirements, and performing anomaly recognition processing on the video file data to obtain a recognition result specifically includes:

[0084] Obtain the gas safety monitoring requirements for the gas pipeline scenario, collect the corresponding video file data according to the gas safety monitoring requirements, and perform image extraction on the video file data to obtain a target scene image;

[0085] Extract features from the target scene image according to the recognition object to obtain image features, perform average pooling on the image features, and perform fully connected processing on the image features after average pooling to obtain convolutional features, where the recognition object includes station personnel, station vehicles, and station objects;

[0086] Fuse the image features and the convolutional features to obtain target image features, and perform anomaly recognition processing according to the target image features to obtain a recognition result.

[0087] Among them, the recognition result includes a first recognition result, a second recognition result, and a third recognition result;

[0088] The performing of anomaly recognition processing according to the target image features to obtain a recognition result specifically includes:

[0089] If the recognition object is the station personnel, identify the identity information and behavior actions of the station personnel according to the target image features to obtain a first recognition result;

[0090] If the recognition object is the station vehicle, identify the license plate information and safety markings of the station vehicle according to the target image features to obtain a second recognition result;

[0091] If the recognition object is the station object, identify the object information and object position of the station object according to the target image features to obtain a third recognition result.

[0092] Among them, after performing abnormal recognition processing on the video file data to obtain a recognition result, the following steps are further included:

[0093] If the identity information verification of the station personnel fails, or the actions of the station personnel are unsafe actions, it is determined that an abnormal event exists in the first recognition result;

[0094] If the license plate information of the station vehicle does not match, or the safety identification of the station vehicle does not exist, it is determined that an abnormal event exists in the second recognition result;

[0095] If the object information of the station object is incorrect, or the object position of the station object changes, it is determined that an abnormal event exists in the third recognition result.

[0096] Among them, if an abnormal event exists in the recognition result, a pipeline inspection plan is formulated according to the abnormal event, and the corresponding inspection personnel are reminded to conduct pipeline inspection according to the pipeline inspection plan. Specifically, it includes:

[0097] If an abnormal event exists in the recognition result, an inspection task is generated according to the abnormal event, and a patrol management template matching is performed according to the inspection task to obtain a target patrol management template;

[0098] A route is formulated according to the inspection task to obtain a target inspection route, and inspection personnel are obtained by matching personnel according to the inspection task;

[0099] A pipeline inspection plan is formulated according to the target patrol management template, the target inspection route, and the inspection personnel, and the inspection personnel are reminded to conduct pipeline inspection according to the pipeline inspection plan.

[0100] Among them, if an abnormal event exists in the recognition result, a pipeline inspection plan is formulated according to the abnormal event, and the corresponding inspection personnel are reminded to conduct pipeline inspection according to the pipeline inspection plan. The following steps are further included:

[0101] If the number of abnormal events in the recognition result is greater than or equal to the warning peak value, a warning accusation command is generated, corresponding warning actions are executed according to the warning accusation command, and a personnel evacuation reminder is issued.

[0102] Among them, the pipeline inspection result includes that the inspection has reached the standard and the inspection has not reached the standard;

[0103] Receiving the inspection records uploaded by the inspection personnel, analyzing the inspection records to obtain the pipeline inspection result, specifically including:

[0104] Receive the inspection records uploaded by the inspection personnel, analyze the inspection time and inspection method of the inspection records, obtain the inspection analysis status, and judge whether the pipeline inspection result meets the standard according to the inspection analysis status;

[0105] If the inspection time exceeds the preset time or the inspection method does not meet the inspection requirements, it is determined that the pipeline inspection result is unqualified;

[0106] If the inspection time does not exceed the preset time and the inspection method meets the inspection requirements, it is determined that the pipeline inspection result is qualified.

[0107] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a video inspection program for a gas pipeline scenario, and when the video inspection program for the gas pipeline scenario is executed by a processor, the steps of the above-mentioned video inspection method for the gas pipeline scenario are realized.

[0108] In summary, the present invention provides a video inspection method, system, terminal and medium for a gas pipeline scenario. The method includes: obtaining the gas safety monitoring requirements of the gas pipeline scenario, collecting corresponding video file data according to the gas safety monitoring requirements, and performing anomaly recognition processing on the video file data to obtain a recognition result; if there is an abnormal event in the recognition result, formulating a pipeline inspection plan according to the abnormal event, and reminding the corresponding inspection personnel to conduct pipeline inspection according to the pipeline inspection plan; receiving the inspection records uploaded by the inspection personnel, and performing data analysis on the inspection records to obtain the pipeline inspection result. By performing video inspection on the gas pipeline scenario, the present invention can not only improve the inspection efficiency and inspection accuracy, but also timely formulate a reasonable inspection plan, thereby shortening the disposal time of abnormal events, improving the processing efficiency of abnormal events, and thus reducing potential safety hazards.

[0109] It should be noted that in this article, the term "including", "comprising" or any other variant thereof is intended to cover a non-exclusive inclusion, so that a process, method, article or terminal including a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or terminal. Without further limitation, an element defined by the statement "including a..." does not exclude the existence of additional identical elements in the process, method, article or terminal including the element.

[0110] Of course, those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware (such as a processor, a controller, etc.) through a computer program. The program can be stored in a computer-readable storage medium readable by a computer. When the program is executed, it can include the processes of the above method embodiments. The computer-readable storage medium can be a memory, a magnetic disk, an optical disk, etc.

[0111] It should be understood that the application of the present invention is not limited to the above examples. For those of ordinary skill in the art, improvements or transformations can be made according to the above description. All such improvements and transformations should fall within the protection scope of the appended claims of the present invention.

Claims

1. A video inspection method for a gas pipeline scene, characterized in that: The video inspection method for the gas pipeline scene includes: Obtaining the gas safety monitoring requirements of the gas pipeline scene, collecting corresponding video file data according to the gas safety monitoring requirements, and performing abnormality recognition processing on the video file data to obtain recognition results; If there is an abnormal event in the identification result, a pipeline inspection plan is formulated according to the abnormal event, and corresponding inspection personnel are reminded to conduct pipeline inspection according to the pipeline inspection plan; The inspection records uploaded by the inspection personnel are received, and data analysis is performed on the inspection records to obtain pipeline inspection results.

2. The video inspection method for gas pipeline scenes according to claim 1 is characterized in that: The obtaining of the gas safety monitoring requirements of the gas pipeline scene, collecting corresponding video file data according to the gas safety monitoring requirements, and performing abnormality recognition processing on the video file data to obtain a recognition result specifically includes: Obtaining gas safety monitoring requirements for a gas pipeline scene, collecting corresponding video file data according to the gas safety monitoring requirements, and performing image extraction on the video file data to obtain a target scene image; Extracting features of the target scene image according to the identification object to obtain image features, performing average pooling on the image features, and performing full connection processing on the image features after the average pooling to obtain convolution features, wherein the identification object includes station personnel, station vehicles and station objects; The image features are fused with the convolution features to obtain target image features, and abnormality recognition processing is performed according to the target image features to obtain recognition results.

3. The video inspection method for gas pipeline scenes according to claim 2 is characterized in that: The recognition result includes a first recognition result, a second recognition result and a third recognition result; The performing of abnormality recognition processing according to the target image features to obtain a recognition result specifically includes: If the identification object is the station personnel, the identity information and behavior of the station personnel are identified according to the target image features to obtain a first identification result; If the identification object is the station vehicle, the license plate information and the safety mark of the station vehicle are identified according to the target image feature to obtain a second identification result; If the identification object is the station object, the object information and the object position of the station object are identified according to the target image feature to obtain a third identification result.

4. The video inspection method for gas pipeline scenes according to claim 3 is characterized in that: The abnormality recognition process is performed on the video file data to obtain a recognition result, and then the following steps are further included: If the identity information verification of the station personnel fails, or the behavior of the station personnel is an unsafe action, it is determined that there is an abnormal event in the first recognition result; If the license plate information of the station vehicle does not match, or the safety mark of the station vehicle does not exist, it is determined that the second recognition result has an abnormal event; If the object information of the station object is incorrect, or the object position of the station object changes, it is determined that an abnormal event exists in the third recognition result.

5. The video inspection method for gas pipeline scenes according to claim 1 is characterized in that: If the identification result shows an abnormal event, a pipeline inspection plan is formulated according to the abnormal event, and corresponding inspection personnel are reminded to conduct pipeline inspection according to the pipeline inspection plan, specifically including: If the recognition result contains an abnormal event, an inspection task is generated according to the abnormal event, and an inspection management template is matched according to the inspection task to obtain a target inspection management template; A route is formulated according to the inspection task to obtain a target inspection route, and personnel are matched according to the inspection task to obtain inspection personnel; A pipeline inspection plan is formulated according to the target inspection management template, the target inspection route and the inspection personnel, and the inspection personnel are reminded to conduct pipeline inspections according to the pipeline inspection plan.

6. The video inspection method for gas pipeline scenes according to claim 1 is characterized in that: If the identification result shows an abnormal event, a pipeline inspection plan is formulated according to the abnormal event, and corresponding inspection personnel are reminded to perform pipeline inspection according to the pipeline inspection plan, and then the method further includes: If the number of abnormal events in the recognition result is greater than or equal to the warning peak value, a warning charge command is generated, a corresponding warning action is executed according to the warning charge command, and a personnel evacuation reminder is issued.

7. The video inspection method for gas pipeline scenes according to claim 1 is characterized in that: The pipeline inspection results include inspection results that have met the standards and inspection results that have not met the standards; The receiving of the inspection records uploaded by the inspection personnel, performing data analysis on the inspection records, and obtaining pipeline inspection results specifically includes: Receive the inspection records uploaded by the inspection personnel, perform data analysis on the inspection time and inspection method of the inspection records, obtain the inspection analysis status, and determine whether the pipeline inspection results meet the standards based on the inspection analysis status; If the inspection time exceeds the preset time or the inspection method does not meet the inspection requirements, the pipeline inspection result is determined to be unsatisfactory. If the inspection time does not exceed the preset time and the inspection method meets the inspection requirements, the pipeline inspection result is determined to be up to standard.

8. A video inspection system for gas pipeline scenes, characterized in that: The video inspection system for the gas pipeline scene includes: The abnormality recognition module is used to obtain the gas safety monitoring requirements of the gas pipeline scene, collect the corresponding video file data according to the gas safety monitoring requirements, and perform abnormality recognition processing on the video file data to obtain the recognition result; A plan making module, for making a pipeline inspection plan according to an abnormal event if the identification result shows an abnormal event, and reminding corresponding inspection personnel to conduct pipeline inspection according to the pipeline inspection plan; The data analysis module is used to receive the inspection records uploaded by the inspection personnel, perform data analysis on the inspection records, and obtain pipeline inspection results.

9. A terminal, characterized in that: The terminal includes: a memory, a processor, and a video inspection program for gas pipeline scenes stored in the memory and executable on the processor. When the video inspection program for gas pipeline scenes is executed by the processor, the steps of the video inspection method for gas pipeline scenes as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a video inspection program for a gas pipeline scene, and when the video inspection program for a gas pipeline scene is executed by a processor, the steps of the video inspection method for a gas pipeline scene as described in any one of claims 1 to 7 are implemented.

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