Method and device for detecting vault abnormity and computer equipment

Abstract

The invention relates to a vault abnormity detection method and device and computer equipment. The method comprises the following steps: acquiring pressure coverage sensing data of multiple areas of a vault, and generating area pressure distribution information of each area based on each piece of pressure coverage sensing data; generating vault pressure coverage information of the vault based on the pressure distribution information, and identifying each vault abnormal range of the vault and a vault abnormal type corresponding to each vault abnormal range based on the vault pressure coverage information; and generating a vault anomaly detection result of the vault based on the vault anomaly type corresponding to each vault anomaly range. By adopting the method, the detection accuracy of the vault abnormity under any environment condition can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of tunnel secondary lining vault quality detection, and in particular to a method, device and computer equipment for detecting vault anomalies. Background Art

[0002] In the field of tunnel secondary lining vault quality inspection, intelligent inspection solutions are provided for tunnel vault voids and bubbles. Voids and bubbles in tunnel vaults are important hidden dangers that affect the safety of tunnel structures. Traditional inspection methods such as manual, drilling and ultrasonic inspections have problems such as low efficiency, strong destructiveness and insufficient precision, which are difficult to meet the high efficiency and safety requirements of modern tunnel construction. Therefore, how to improve the accuracy of tunnel vault voids and bubbles detection is the current research focus.

[0003] The traditional method of detecting voids and bubbles in tunnel vaults is to combine tunnel lining quality detection technologies, such as ultrasonic detection and radar detection. However, in complex tunnel environments, ultrasonic and radar signals are easily interfered by surrounding media (such as steel bars, moisture, air, etc.), especially in humid environments or areas with dense steel bars. Signal attenuation and distortion are significant, resulting in reduced detection accuracy. Due to the limitations of signal penetration depth and resolution, it is difficult to accurately identify subtle voids or small bubbles. As a result, the detection accuracy of voids and bubbles in tunnel vaults is poor. Summary of the invention

[0004] Based on this, it is necessary to provide a method, device, computer equipment, computer-readable storage medium and computer program product for detecting vault anomalies in order to solve the above technical problems.

[0005] In a first aspect, the present application provides a method for detecting vault anomalies, comprising:

[0006] Acquire pressure coverage sensing data of multiple regions of the dome, and generate regional pressure distribution information of each region based on each of the pressure coverage sensing data;

[0007] Based on each of the pressure distribution information, generate the vault pressure coverage information of the vault, and based on the vault pressure coverage information, identify each vault abnormal range of the vault and the vault abnormality type corresponding to each of the vault abnormal ranges;

[0008] Based on the vault anomaly types corresponding to the vault anomaly ranges, a vault anomaly detection result of the vault is generated.

[0009] Optionally, generating regional pressure distribution information of each of the regions based on each of the pressure coverage sensing data includes:

[0010] For each region, based on the pressure coverage sensing data of the region, identifying the pressure information of the region, and based on the pressure coverage sensing data of the region, generating the sensing data distribution information of the region;

[0011] Based on the sensor data distribution information of the area, the pressure distribution information of the area is constructed through a sensor data analysis program, and based on the pressure distribution information of the area, the regional pressure distribution information of the area is calculated.

[0012] Optionally, generating the vault pressure coverage information of the vault based on each of the pressure distribution information includes:

[0013] Collecting the area range of each area and the relative position information between each area, performing distribution arrangement processing on the area pressure distribution information of each area, and obtaining the initial vault pressure coverage information of the vault;

[0014] Identify target pressure distribution information between the connections of each area in the initial vault pressure coverage information, and adjust each target pressure distribution information through an edge pressure linear identification strategy to obtain new pressure distribution information corresponding to each target pressure distribution information;

[0015] The new pressure distribution information is used to replace each target pressure distribution information in the initial dome pressure coverage information to obtain the dome pressure coverage information of the dome.

[0016] Optionally, the identifying, based on the vault pressure coverage information, each vault abnormality range of the vault and the vault abnormality type corresponding to each vault abnormality range includes:

[0017] Based on the vault pressure coverage information, constructing a vault pressure coverage distribution map of the vault, and identifying each abnormal pressure range in the vault pressure coverage distribution map;

[0018] Each abnormal pressure range is used as the vault abnormal range of the vault, and for each vault abnormal range, based on the pressure distribution information of the vault abnormal range, the abnormal feature information of the vault abnormal range is identified through a feature recognition network;

[0019] Based on the abnormal feature information of the vault abnormal range, the vault abnormal type corresponding to the vault abnormal range is identified through an abnormal classification network.

[0020] Optionally, the generating the vault anomaly detection result of the vault based on the vault anomaly type corresponding to each vault anomaly range includes:

[0021] Based on the distribution information of each of the vault abnormal ranges on the vault, identifying the range area of ​​each of the vault abnormal ranges and the position information of each of the vault abnormal ranges;

[0022] Based on the range area of ​​each of the vault abnormal ranges and the position information of each of the vault abnormal ranges, an abnormality distribution map of the vault is constructed, and based on the vault abnormality type corresponding to each of the vault abnormal ranges, type labeling processing is performed in the abnormality distribution map to obtain the vault abnormality detection result of the vault.

[0023] Optionally, after generating the vault anomaly detection result of the vault based on the vault anomaly type corresponding to each vault anomaly range, the method further includes:

[0024] Based on the position information of each of the vault abnormal ranges in the vault abnormality detection result, a range positioning process is performed in the vault through a range indicating device to obtain initial abnormality display information of the vault;

[0025] Based on the vault abnormality type corresponding to each vault abnormality range, the abnormality identification unit of the range indication device performs type identification processing in the initial abnormality display information to obtain the abnormality display information of the vault;

[0026] The abnormal display information is displayed to the staff through the range indication device for abnormal display processing.

[0027] In a second aspect, the present application also provides a device for detecting anomalies of a vault, comprising:

[0028] An acquisition module, used for acquiring pressure coverage sensing data of multiple regions of the dome, and generating regional pressure distribution information of each region based on each of the pressure coverage sensing data;

[0029] an identification module, configured to generate, based on each of the pressure distribution information, the vault pressure coverage information of the vault, and, based on the vault pressure coverage information, identify each vault abnormal range of the vault and the vault abnormality type corresponding to each of the vault abnormal ranges;

[0030] A generating module is used to generate a vault anomaly detection result of the vault based on the vault anomaly type corresponding to each vault anomaly range.

[0031] Optionally, the acquisition module is specifically used to:

[0032] For each region, based on the pressure coverage sensing data of the region, identifying the pressure information of the region, and based on the pressure coverage sensing data of the region, generating the sensing data distribution information of the region;

[0033] Based on the sensor data distribution information of the area, the pressure distribution information of the area is constructed through a sensor data analysis program, and based on the pressure distribution information of the area, the regional pressure distribution information of the area is calculated.

[0034] Optionally, the identification module is specifically used to:

[0035] Collecting the area range of each area and the relative position information between each area, performing distribution arrangement processing on the area pressure distribution information of each area, and obtaining the initial vault pressure coverage information of the vault;

[0036] Identify target pressure distribution information between the connections of each area in the initial vault pressure coverage information, and adjust each target pressure distribution information through an edge pressure linear identification strategy to obtain new pressure distribution information corresponding to each target pressure distribution information;

[0037] The new pressure distribution information is used to replace each target pressure distribution information in the initial dome pressure coverage information to obtain the dome pressure coverage information of the dome.

[0038] Optionally, the identification module is specifically used to:

[0039] Based on the vault pressure coverage information, constructing a vault pressure coverage distribution map of the vault, and identifying each abnormal pressure range in the vault pressure coverage distribution map;

[0040] Each abnormal pressure range is used as the vault abnormal range of the vault, and for each vault abnormal range, based on the pressure distribution information of the vault abnormal range, the abnormal feature information of the vault abnormal range is identified through a feature recognition network;

[0041] Based on the abnormal feature information of the vault abnormal range, the vault abnormal type corresponding to the vault abnormal range is identified through an abnormal classification network.

[0042] Optionally, the generating module is specifically used for:

[0043] Based on the distribution information of each of the vault abnormal ranges on the vault, identifying the range area of ​​each of the vault abnormal ranges and the position information of each of the vault abnormal ranges;

[0044] Based on the range area of ​​each of the vault abnormal ranges and the position information of each of the vault abnormal ranges, an abnormality distribution map of the vault is constructed, and based on the vault abnormality type corresponding to each of the vault abnormal ranges, type labeling processing is performed in the abnormality distribution map to obtain the vault abnormality detection result of the vault.

[0045] Optionally, the device further comprises:

[0046] Based on the position information of each of the vault abnormal ranges in the vault abnormality detection result, a range positioning process is performed in the vault through a range indicating device to obtain initial abnormality display information of the vault;

[0047] Based on the vault abnormality type corresponding to each vault abnormality range, the abnormality identification unit of the range indication device performs type identification processing in the initial abnormality display information to obtain the abnormality display information of the vault;

[0048] The abnormal display information is displayed to the staff through the range indication device for abnormal display processing.

[0049] In a third aspect, the present application provides a computer device, wherein the computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of any one of the methods in the first aspect are implemented.

[0050] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps of any one of the methods in the first aspect are implemented.

[0051] In a fifth aspect, the present application provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the steps of any one of the methods in the first aspect are implemented.

[0052] The above-mentioned method, device and computer equipment for detecting vault anomalies obtain pressure coverage sensor data of multiple areas of the vault, and generate regional pressure distribution information of each area based on each of the pressure coverage sensor data; generate vault pressure coverage information of the vault based on each of the pressure distribution information, and identify each vault anomaly range of the vault and the vault anomaly type corresponding to each of the vault anomaly ranges based on the vault pressure coverage information; generate a vault anomaly detection result of the vault based on the vault anomaly type corresponding to each of the vault anomaly ranges. This scheme collects regional pressure data of each area of ​​the vault by means of regional pressure coverage sensor data collection, thereby constructing the vault pressure coverage information of the vault, so that when facing different vault conditions, the vault abnormalities can be directly collected comprehensively, avoiding the signal attenuation of manual detection, ultrasonic detection and radar detection, which leads to the problem of low detection accuracy. Then, this scheme uses the constructed vault pressure coverage information to accurately locate and intelligently classify the vault abnormality type and abnormal range of the vault, thereby avoiding the problem that manual analysis relies on the operator's experience and judgment, manual interpretation of data is prone to errors, and is not suitable for fast and efficient detection in a narrow tunnel environment, thereby comprehensively improving the detection accuracy of vault abnormalities under any environmental conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments or the related technical descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0054] Figure 1 A schematic diagram of a flow chart of a method for detecting anomalies of a vault in one embodiment;

[0055] Figure 2 A schematic diagram of device components of a range indication device in one embodiment;

[0056] Figure 3 A schematic diagram of a process flow of an example of detecting an abnormality of a vault in one embodiment;

[0057] Figure 4 is a structural block diagram of a device for detecting anomalies of a vault in one embodiment;

[0058] Figure 5 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0059] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0060] The method for detecting anomalies of the vault provided in the embodiment of the present application can be applied to the application environment of detecting anomalies of the vault. The method can be applied to a terminal, a server, or a system including a terminal and a server, and is implemented through the interaction between the terminal and the server. The terminal can be, but is not limited to, various personal computers, laptops, medium-sized computers, etc. The terminal collects regional pressure data of each region of the vault by collecting regional pressure coverage sensing data, thereby constructing the vault pressure coverage information of the vault, so that when facing different vault conditions, the vault abnormality can be directly collected comprehensively, avoiding the signal attenuation of manual detection, ultrasonic detection and radar detection, thereby causing the problem of low detection accuracy. Then, the scheme uses the constructed vault pressure coverage information to accurately locate and intelligently classify the vault abnormality type and abnormal range of the vault, thereby avoiding the problem that manual analysis relies on the operator's experience and judgment, manual interpretation of data is prone to errors, and is not suitable for fast and efficient detection in a narrow tunnel environment, thereby comprehensively improving the detection accuracy of vault abnormalities under any environmental conditions.

[0061] In an exemplary embodiment, Figure 1 As shown, a method for detecting vault anomalies is provided, and the method is applied to a terminal as an example for explanation, including the following steps S101 to S104. Among them:

[0062] Step S101 : acquiring pressure coverage sensing data of multiple regions of the dome, and generating regional pressure distribution information of each region based on each pressure coverage sensing data.

[0063] In this embodiment, the terminal collects pressure coverage sensing data of multiple regions of the dome through piezoelectric sensors attached to each region of the dome. Then, the terminal generates regional pressure distribution information of each region based on each pressure coverage sensing data. The regional pressure distribution information is the pressure distribution information of each position corresponding to the regional pressure distribution information in the region. The specific generation process will be described in detail later.

[0064] Step S102: generating vault pressure coverage information of the vault based on each pressure distribution information, and identifying each vault abnormal range of the vault and the vault abnormality type corresponding to each vault abnormal range based on the vault pressure coverage information.

[0065] In this embodiment, the terminal generates the vault pressure coverage information of the vault based on the pressure distribution information through the Internet of Things system where each piezoelectric sensor is located. Then, based on the vault pressure coverage information, the terminal identifies each vault area with pressure anomaly as each vault abnormal range of the vault, and the vault abnormality type corresponding to each vault abnormal range. Among them, the pressure anomaly is an area where the pressure deviation value with other areas of the vault is greater than the deviation threshold. Then, based on the range characteristics such as the range size of each vault abnormal range and the extreme value size of the pressure deviation, the terminal identifies the vault abnormality type corresponding to each vault abnormal range. The specific identification process will be described in detail later.

[0066] Step S103: generating a vault anomaly detection result of the vault based on the vault anomaly type corresponding to each vault anomaly range.

[0067] In this embodiment, the terminal generates a vault anomaly detection result of the vault based on the vault anomaly type corresponding to each vault anomaly range. The vault anomaly detection result is an anomaly distribution map corresponding to each vault anomaly range with an abnormality in the vault and the vault anomaly type corresponding to each vault anomaly range. The specific generation process will be described in detail later.

[0068] Based on the above scheme, regional pressure data of each area of ​​the vault is collected by means of regional pressure coverage sensor data collection, so as to construct the vault pressure coverage information of the vault, so that when facing different vault conditions, the vault abnormality can be directly collected comprehensively, avoiding the signal attenuation of manual detection, ultrasonic detection and radar detection, which leads to the problem of low detection accuracy. Then, this scheme uses the constructed vault pressure coverage information to accurately locate and intelligently classify the vault abnormality type and abnormal range of the vault, thereby avoiding the problem that manual analysis relies on the operator's experience and judgment, manual interpretation of data is prone to errors, and is not suitable for fast and efficient detection in a narrow tunnel environment, thereby comprehensively improving the detection accuracy of vault abnormalities under any environmental conditions.

[0069] Optionally, based on each pressure coverage sensor data, regional pressure distribution information of each area is generated, including: for each area, based on the pressure coverage sensor data of the area, the pressure information of the area is identified, and based on the pressure coverage sensor data of the area, the sensor data distribution information of the area is generated; based on the sensor data distribution information of the area, the pressure distribution information of the area is constructed through a sensor data analysis program, and based on the pressure distribution information of the area, the regional pressure distribution information of the area is calculated.

[0070] In this embodiment, the terminal identifies the pressure information of each area based on the pressure coverage sensor data of the area, and generates the sensor data distribution information of the area based on the pressure coverage sensor data of the area. The pressure coverage sensor data is a pressure signal, and the terminal presets a conversion strategy between the pressure signal and the pressure information, and converts the pressure coverage sensor data into the pressure information of the area through the conversion strategy. Then, the terminal distributes and arranges the pressure coverage sensor data according to the position information of each acquisition position point in the area covered by the piezoelectric sensor, and then uses the piezoelectric sensor to perform signal fitting processing on the pressure signal between each acquisition position point to obtain the sensor data distribution information of the area.

[0071] Then, based on the sensor data distribution information of the region, the terminal constructs the pressure distribution information of the region through the sensor data analysis program, and calculates the regional pressure distribution information of the region based on the pressure distribution information of the region. Among them, the pressure distribution information is the sensor data distribution information corresponding to the pressure signal distribution, which is converted into initial pressure distribution information by a preset conversion strategy between the pressure signal and the pressure information, and the initial pressure distribution information is fitted and adjusted based on the pressure information of each acquisition position point to obtain the pressure distribution information. After that, the terminal fits the pressure distribution information corresponding to the pressure distribution information through an integral fitting algorithm to obtain the regional pressure distribution information of the region. Among them, the integral algorithm is a data fitting algorithm based on the MATLAB program with integral constraints.

[0072] Based on the above scheme, the pressure distribution information is identified through the pressure conversion strategy, and then the regional pressure distribution information of the area is obtained through the integral fitting algorithm, which improves the recognition accuracy of the regional pressure distribution information.

[0073] Optionally, based on each pressure distribution information, the vault pressure coverage information of the vault is generated, including: collecting the regional range of each area and the relative position information between each area, and distributing and arranging the regional pressure distribution information of each area to obtain the initial vault pressure coverage information of the vault; identifying the target pressure distribution information between the connections of each area in the initial vault pressure coverage information, and adjusting each target pressure distribution information through the edge pressure linear recognition strategy to obtain new pressure distribution information corresponding to each target pressure distribution information; replacing each target pressure distribution information in the initial vault pressure coverage information with the new pressure distribution information to obtain the vault pressure coverage information of the vault.

[0074] In this embodiment, the terminal collects the area range of each area and the relative position information between each area, and performs distribution arrangement processing on the area pressure distribution information of each area to obtain the initial dome pressure coverage information of the dome.

[0075] Then, the terminal identifies the target pressure distribution information between the connections of each area in the initial vault pressure coverage information. The target pressure distribution information is the pressure distribution information of the connection area corresponding to the area connection line corresponding to the connection of each area extending to both sides by a preset distance. The preset distance length can be 1 cm, 2 cm, 5 cm, 10 cm, etc.

[0076] Then, the terminal adjusts each target pressure distribution information through the edge pressure linear identification strategy to obtain new pressure distribution information corresponding to each target pressure distribution information. The edge pressure linear identification strategy is to perform linear fitting processing on the target pressure distribution information through a plane linear fitting algorithm to obtain new pressure distribution information.

[0077] Finally, the terminal replaces each target pressure distribution information in the initial vault pressure coverage information with the new pressure distribution information to obtain the vault pressure coverage information of the vault.

[0078] Based on the above scheme, after position splicing, pressure fitting processing is performed on the joints of each area to avoid abnormal pressure distribution at the joints, which will lead to abnormal identification of the subsequent vault Yichang range, thereby improving the accuracy and comprehensiveness of the recognition of the vault pressure coverage information of the vault.

[0079] Optionally, based on the vault pressure coverage information, each vault abnormality range of the vault and the vault abnormality type corresponding to each vault abnormality range are identified, including: based on the vault pressure coverage information, a vault pressure coverage distribution map of the vault is constructed, and each abnormal pressure range in the vault pressure coverage distribution map is identified; each abnormal pressure range is used as the vault abnormality range of the vault, and for each vault abnormality range, based on the pressure distribution information of the vault abnormality range, the abnormal feature information of the vault abnormal range is identified through a feature recognition network; based on the abnormal feature information of the vault abnormal range, the vault abnormality type corresponding to the vault abnormal range is identified through an abnormal classification network.

[0080] In this embodiment, the terminal constructs a vault pressure coverage distribution map of the vault based on the vault pressure coverage information, and identifies each abnormal pressure range in the vault pressure coverage distribution map. Specifically, the terminal calculates the deviation value between each position point of the vault and the preset pressure threshold based on the vault pressure coverage distribution map. Then, the terminal selects each position point greater than the deviation value threshold as an abnormal position point. Then, based on the position information of each abnormal position point, the terminal divides it into each abnormal position point group through a clustering algorithm, and uses each abnormal position point group as each abnormal pressure range.

[0081] Then, the terminal uses each abnormal pressure range as the vault abnormal range of the vault, and for each vault abnormal range, based on the pressure distribution information of the vault abnormal range, identifies the abnormal feature information of the vault abnormal range through a feature recognition network. Specifically, the terminal constructs a deviation value image based on the deviation value of each position point in the abnormal pressure range, and then identifies each image feature of the deviation value image through a feature recognition network based on a convolutional neural network to obtain abnormal feature information, wherein the abnormal feature information includes range area features, range pressure deviation features, and range shape features.

[0082] Finally, based on the abnormal feature information of the vault abnormal range, the terminal identifies the vault abnormality type corresponding to the vault abnormal range through an abnormal classification network, wherein the abnormal classification network is a classifier network based on an artificial neural network.

[0083] Based on the above scheme, the abnormal range of each vault is identified by screening the deviation value of the pressure distribution, and the recognition accuracy of the vault abnormal range and the vault abnormal type are improved through the feature extraction network, the abnormal classification network, and the vault abnormality type corresponding to the vault abnormal range.

[0084] Optionally, based on the vault anomaly type corresponding to each vault anomaly range, a vault anomaly detection result of the vault is generated, including: based on the distribution information of each vault anomaly range in the vault, identifying the range area of ​​each vault anomaly range and the position information of each vault anomaly range; based on the range area of ​​each vault anomaly range and the position information of each vault anomaly range, constructing an anomaly distribution map of the vault, and based on the vault anomaly type corresponding to each vault anomaly range, performing type annotation processing in the anomaly distribution map to obtain the vault anomaly detection result of the vault.

[0085] In this embodiment, the terminal identifies the range area of ​​each vault abnormal range and the position information of each vault abnormal range based on the distribution information of each vault abnormal range in the vault.

[0086] Then, the terminal constructs an abnormal distribution map of the vault based on the range area of ​​each vault abnormal range and the position information of each vault abnormal range. The abnormal distribution map is an image obtained by taking all the areas of the vault as the image background and marking the abnormal range of each vault in the image background.

[0087] Finally, the terminal performs type labeling processing in the anomaly distribution map based on the vault anomaly type corresponding to the anomaly range of each vault, and obtains the vault anomaly detection result of the vault.

[0088] Based on the above scheme, after marking the vault anomaly range, the vault anomaly type is marked, thereby ensuring the accuracy and efficiency of the marking, avoiding the problems of inefficiency and low precision of simultaneous marking, and improving the accuracy of the vault anomaly detection results.

[0089] Optionally, after generating the vault abnormality detection result of the vault based on the vault abnormality type corresponding to each vault abnormality range, it also includes: based on the position information of each vault abnormality range in the vault abnormality detection result, performing range positioning processing in the vault through a range indicating device to obtain initial abnormality display information of the vault; based on the vault abnormality type corresponding to each vault abnormality range, performing type identification processing in the initial abnormality display information through the abnormality identification unit of the range indicating device to obtain the abnormal display information of the vault; and performing abnormal display processing on the abnormal display information to the staff through the range indicating device.

[0090] In this embodiment, the terminal performs range positioning processing in the vault through the range indicating device based on the location information of each vault abnormal range in the vault abnormality detection result, and obtains the initial abnormality display information of the vault. Then, based on the vault abnormality type corresponding to each vault abnormal range, the terminal performs type identification processing in the initial abnormality display information through the abnormality identification unit of the range indicating device, and obtains the abnormality display information of the vault. Figure 2 The figure shows a range indication device arranged on a piezoelectric sensor, which includes a voice module (used to prompt staff members with range characteristic information of each vault abnormal range and the type of vault abnormality), a pressure sensor (or a piezoelectric sensor), a simulator (used to project an indication laser), a speaker, a control main board (used to perform range positioning in the vault to process the position information of each vault abnormal range, obtain the initial abnormal display information of the vault, and perform type identification processing in the initial abnormal display information to obtain the abnormal display information of the vault), and a visualization window (which can display the abnormal display information in all areas of the vault area).

[0091] Finally, the terminal displays the abnormality information to the staff through the range indicating device for abnormal display processing.

[0092] Based on the above scheme, the results of the vault anomaly detection are displayed to the staff through the range indication device, so that the staff can correct the abnormal range of each vault and provide accurate guidance, thereby improving the auxiliary guidance effect of the vault anomaly detection.

[0093] This application also provides an example of detecting anomalies of a vault, such as Figure 3 As shown, the specific processing process includes the following steps:

[0094] Step S301, obtaining pressure coverage sensing data of multiple areas of the dome.

[0095] Step S302 , for each region, based on the pressure coverage sensing data of the region, the pressure information of the region is identified, and based on the pressure coverage sensing data of the region, the sensing data distribution information of the region is generated.

[0096] Step S303, based on the sensor data distribution information of the region, the pressure distribution information of the region is constructed through a sensor data analysis program, and based on the pressure distribution information of the region, the regional pressure distribution information of the region is calculated.

[0097] Step S304, collecting the area range of each area and the relative position information between each area, and performing distribution arrangement processing on the regional pressure distribution information of each area to obtain the initial dome pressure coverage information of the dome.

[0098] Step S305 , identifying target pressure distribution information between the connections of each area in the initial dome pressure coverage information, and adjusting each target pressure distribution information through an edge pressure linear recognition strategy to obtain new pressure distribution information corresponding to each target pressure distribution information.

[0099] Step S306: Replace each target pressure distribution information in the initial dome pressure coverage information with the new pressure distribution information to obtain the dome pressure coverage information of the dome.

[0100] Step S307: constructing a vault pressure coverage distribution map of the vault based on the vault pressure coverage information, and identifying each abnormal pressure range in the vault pressure coverage distribution map.

[0101] Step S308, taking each abnormal pressure range as the vault abnormal range of the vault, and for each vault abnormal range, based on the pressure distribution information of the vault abnormal range, identifying the abnormal feature information of the vault abnormal range through a feature recognition network.

[0102] Step S309: Based on the abnormal feature information of the vault abnormal range, the vault abnormal type corresponding to the vault abnormal range is identified through an abnormal classification network.

[0103] Step S310 , based on the distribution information of each vault abnormal range on the vault, identifying the range area of ​​each vault abnormal range and the position information of each vault abnormal range.

[0104] Step S311, based on the range area of ​​each vault abnormal range and the position information of each vault abnormal range, construct an abnormal distribution map of the vault, and based on the vault abnormality type corresponding to each vault abnormal range, perform type labeling processing in the abnormal distribution map to obtain the vault abnormality detection result of the vault.

[0105] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0106] Based on the same inventive concept, the embodiment of the present application also provides a device for detecting vault anomalies for implementing the method for detecting vault anomalies involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the method above, so the specific definition in the embodiment of one or more devices for detecting vault anomalies provided below can refer to the definition of the method for detecting vault anomalies above, and will not be repeated here.

[0107] In an exemplary embodiment, Figure 4 As shown, a device for detecting anomalies of a vault is provided, comprising: a collection module 410, a recognition module 420 and a generation module 430, wherein:

[0108] An acquisition module 410 is used to acquire pressure coverage sensing data of multiple regions of the dome, and generate regional pressure distribution information of each region based on each of the pressure coverage sensing data;

[0109] An identification module 420 is used to generate the vault pressure coverage information of the vault based on each of the pressure distribution information, and to identify each vault abnormal range of the vault and the vault abnormality type corresponding to each of the vault abnormal ranges based on the vault pressure coverage information;

[0110] The generating module 430 is used to generate a vault anomaly detection result of the vault based on the vault anomaly type corresponding to each vault anomaly range.

[0111] Optionally, the acquisition module 410 is specifically configured to:

[0112] For each region, based on the pressure coverage sensing data of the region, identifying the pressure information of the region, and based on the pressure coverage sensing data of the region, generating the sensing data distribution information of the region;

[0113] Based on the sensor data distribution information of the area, the pressure distribution information of the area is constructed through a sensor data analysis program, and based on the pressure distribution information of the area, the regional pressure distribution information of the area is calculated.

[0114] Optionally, the identification module 420 is specifically configured to:

[0115] Collecting the area range of each area and the relative position information between each area, performing distribution arrangement processing on the area pressure distribution information of each area, and obtaining the initial vault pressure coverage information of the vault;

[0116] Identify target pressure distribution information between the connections of each area in the initial vault pressure coverage information, and adjust each target pressure distribution information through an edge pressure linear identification strategy to obtain new pressure distribution information corresponding to each target pressure distribution information;

[0117] The new pressure distribution information is used to replace each target pressure distribution information in the initial dome pressure coverage information to obtain the dome pressure coverage information of the dome.

[0118] Optionally, the identification module 420 is specifically configured to:

[0119] Based on the vault pressure coverage information, constructing a vault pressure coverage distribution map of the vault, and identifying each abnormal pressure range in the vault pressure coverage distribution map;

[0120] Each abnormal pressure range is used as the vault abnormal range of the vault, and for each vault abnormal range, based on the pressure distribution information of the vault abnormal range, the abnormal feature information of the vault abnormal range is identified through a feature recognition network;

[0121] Based on the abnormal feature information of the vault abnormal range, the vault abnormal type corresponding to the vault abnormal range is identified through an abnormal classification network.

[0122] Optionally, the generating module 430 is specifically configured to:

[0123] Based on the distribution information of each of the vault abnormal ranges on the vault, identifying the range area of ​​each of the vault abnormal ranges and the position information of each of the vault abnormal ranges;

[0124] Based on the range area of ​​each of the vault abnormal ranges and the position information of each of the vault abnormal ranges, an abnormality distribution map of the vault is constructed, and based on the vault abnormality type corresponding to each of the vault abnormal ranges, type labeling processing is performed in the abnormality distribution map to obtain the vault abnormality detection result of the vault.

[0125] Optionally, the device further comprises:

[0126] Based on the position information of each of the vault abnormal ranges in the vault abnormality detection result, a range positioning process is performed in the vault through a range indicating device to obtain initial abnormality display information of the vault;

[0127] Based on the vault abnormality type corresponding to each vault abnormality range, the abnormality identification unit of the range indication device performs type identification processing in the initial abnormality display information to obtain the abnormality display information of the vault;

[0128] The abnormal display information is displayed to the staff through the range indication device for abnormal display processing.

[0129] Each module in the above-mentioned device for detecting anomalies of the vault can be implemented in whole or in part by software, hardware or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each module.

[0130] In an exemplary embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 5 As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a method for detecting an abnormality of a vault is implemented. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0131] Those skilled in the art will understand that Figure 5 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0132] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, steps corresponding to the following method for detecting anomalies of a vault are implemented.

[0133] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps corresponding to the following method for detecting anomalies of a vault are implemented.

[0134] In one embodiment, a computer program product is provided, including a computer program, which implements the steps corresponding to the following method for detecting vault anomalies when executed by a processor.

[0135] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0136] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0137] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0138] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for detecting vault anomalies, characterized in that: The method comprises: Acquire pressure coverage sensing data of multiple regions of the dome, and generate regional pressure distribution information of each region based on each of the pressure coverage sensing data; Based on each of the pressure distribution information, generate the vault pressure coverage information of the vault, and based on the vault pressure coverage information, identify each vault abnormal range of the vault and the vault abnormality type corresponding to each of the vault abnormal ranges; Based on the vault anomaly types corresponding to the vault anomaly ranges, a vault anomaly detection result of the vault is generated.

2. The method according to claim 1, characterized in that The generating of regional pressure distribution information of each of the regions based on each of the pressure coverage sensing data comprises: For each region, based on the pressure coverage sensing data of the region, identifying the pressure information of the region, and based on the pressure coverage sensing data of the region, generating the sensing data distribution information of the region; Based on the sensor data distribution information of the area, the pressure distribution information of the area is constructed through a sensor data analysis program, and based on the pressure distribution information of the area, the regional pressure distribution information of the area is calculated.

3. The method according to claim 1, characterized in that: The generating the vault pressure coverage information of the vault based on each of the pressure distribution information comprises: Collecting the area range of each area and the relative position information between each area, performing distribution arrangement processing on the area pressure distribution information of each area, and obtaining the initial vault pressure coverage information of the vault; Identify target pressure distribution information between the connections of each area in the initial vault pressure coverage information, and adjust each target pressure distribution information through an edge pressure linear identification strategy to obtain new pressure distribution information corresponding to each target pressure distribution information; The new pressure distribution information is used to replace each target pressure distribution information in the initial dome pressure coverage information to obtain the dome pressure coverage information of the dome.

4. The method according to claim 1, characterized in that: The step of identifying each vault abnormal range of the vault and the vault abnormality type corresponding to each vault abnormal range based on the vault pressure coverage information includes: Based on the vault pressure coverage information, constructing a vault pressure coverage distribution map of the vault, and identifying each abnormal pressure range in the vault pressure coverage distribution map; Each abnormal pressure range is used as the vault abnormal range of the vault, and for each vault abnormal range, based on the pressure distribution information of the vault abnormal range, the abnormal feature information of the vault abnormal range is identified through a feature recognition network; Based on the abnormal feature information of the vault abnormal range, the vault abnormal type corresponding to the vault abnormal range is identified through an abnormal classification network.

5. The method according to claim 1, characterized in that The generating of the vault anomaly detection result of the vault based on the vault anomaly type corresponding to each vault anomaly range includes: Based on the distribution information of each of the vault abnormal ranges on the vault, identifying the range area of ​​each of the vault abnormal ranges and the position information of each of the vault abnormal ranges; Based on the range area of ​​each of the vault abnormal ranges and the position information of each of the vault abnormal ranges, an abnormality distribution map of the vault is constructed, and based on the vault abnormality type corresponding to each of the vault abnormal ranges, type labeling processing is performed in the abnormality distribution map to obtain the vault abnormality detection result of the vault.

6. The method according to claim 1, characterized in that After generating the vault anomaly detection result of the vault based on the vault anomaly type corresponding to each vault anomaly range, the method further includes: Based on the position information of each of the vault abnormal ranges in the vault abnormality detection result, a range positioning process is performed in the vault through a range indicating device to obtain initial abnormality display information of the vault; Based on the vault abnormality type corresponding to each vault abnormality range, the abnormality identification unit of the range indication device performs type identification processing in the initial abnormality display information to obtain the abnormality display information of the vault; The abnormal display information is displayed to the staff through the range indication device for abnormal display processing.

7. A device for detecting anomalies of a vault, characterized in that: The device comprises: An acquisition module, used for acquiring pressure coverage sensing data of multiple regions of the dome, and generating regional pressure distribution information of each region based on each of the pressure coverage sensing data; an identification module, configured to generate, based on each of the pressure distribution information, the vault pressure coverage information of the vault, and, based on the vault pressure coverage information, identify each vault abnormal range of the vault and the vault abnormality type corresponding to each of the vault abnormal ranges; A generating module is used to generate a vault anomaly detection result of the vault based on the vault anomaly type corresponding to each vault anomaly range.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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