Method and system for monitoring abnormal noise of manhole covers based on dynamic inspection

Abstract

The present invention discloses a method and system for monitoring abnormal noise of manhole covers based on dynamic inspection. The method comprises: obtaining initial data collected by a data acquisition device arranged on a mobile device, wherein the data acquisition device comprises an image acquisition module, an audio acquisition module and a positioning module, and the initial data comprises an initial image, audio data and positioning information; performing manhole cover recognition on the initial image to obtain a recognition result; when a manhole cover exists in the recognition result, analyzing the sound field energy distribution, compression entropy and time delay of the sound wave propagation path in the audio data, and detecting whether there is an abnormal noise in the manhole cover according to the sound field energy distribution, compression entropy and time delay of the sound wave propagation path to obtain a detection result; when the detection result is that there is an abnormal noise in the manhole cover, an alarm message is generated and sent. By implementing the method of the present invention, it is possible to improve monitoring efficiency, reduce costs and ensure high coverage, and make up for the shortcomings of manual inspection and intelligent manhole cover monitoring.

Description

Technical Field

[0001] The invention relates to a method for monitoring abnormal noise of a manhole cover, and more specifically to a method and system for monitoring abnormal noise of a manhole cover based on dynamic inspection. Background Art

[0002] Manhole covers on urban roads are an important part of urban infrastructure, directly affecting road safety, residents' quality of life and the efficiency of urban management. Loose or damaged manhole covers not only produce noise, affecting the normal work and rest of surrounding residents, but may also pose a hidden danger of not closing tightly, posing safety risks to passing vehicles and pedestrians. In particular, when vehicles pass by, loose manhole covers will make a loud collision noise, affecting the living environment of surrounding residents. In addition, loose manhole covers may also cause more serious traffic accidents or cause pedestrians to fall and get injured. Therefore, timely monitoring the status of manhole covers and maintaining them has become an important task in urban road management.

[0003] At present, the monitoring of manhole covers on urban roads mainly relies on manual inspections. This method uses special inspection personnel to regularly check the condition of manhole covers, and promptly discover and deal with problems. Although manual inspections can cover all manhole covers more comprehensively, due to the limited inspection frequency due to manpower and time, abnormal problems with manhole covers are often not discovered in time. In particular, some manhole covers may become loose or damaged during inspections, leading to potential safety hazards. The number of manhole covers in the city is huge, and manual inspections require a lot of manpower and time, making it difficult to achieve full-time and full-coverage monitoring. Manual inspections rely on manual records and judgments, and there are certain errors and risks of missed inspections, resulting in unstable monitoring results.

[0004] With the advancement of technology, smart manhole cover monitoring has gradually become a new solution. By installing sensors on the manhole cover, the smart manhole cover can monitor the status of the manhole cover in real time and report the data to the monitoring system. However, a single manhole cover needs to be installed with at least one set of sensors, which means that each manhole cover requires a high equipment investment and subsequent maintenance costs. This may lead to excessive investment for cities, especially when deployed on a large scale. Due to the complexity of sensor equipment, maintenance and troubleshooting are difficult. If the equipment fails, it may affect the monitoring effect and even cause the appearance of blind spots in monitoring. The high equipment and maintenance costs make it difficult to deploy smart manhole covers on a large scale on all manhole covers, especially in some old or low-budget areas, where the coverage rate of smart manhole covers may be low and full coverage monitoring cannot be achieved.

[0005] Therefore, it is necessary to design a new method to improve monitoring efficiency, reduce costs and ensure high coverage, and make up for the shortcomings of manual inspection and intelligent manhole cover monitoring. Summary of the invention

[0006] The purpose of the present invention is to overcome the defects of the prior art and provide a method and system for monitoring abnormal noise of manhole covers based on dynamic inspection.

[0007] To achieve the above purpose, the present invention adopts the following technical solution: A method for monitoring abnormal noise of manhole covers based on dynamic inspection, comprising:

[0008] Acquire initial data collected by a data collection device disposed on a mobile device, wherein the data collection device includes an image collection module, an audio collection module, and a positioning module, and the initial data includes an initial image, audio data, and positioning information;

[0009] Performing manhole cover recognition on the initial image to obtain a recognition result;

[0010] When there is a manhole cover in the recognition result, analyzing the sound field energy distribution, compression entropy and time delay of the sound wave propagation path in the audio data, and detecting whether there is an abnormal sound in the manhole cover according to the sound field energy distribution, compression entropy and time delay of the sound wave propagation path to obtain a detection result;

[0011] When the detection result shows that the manhole cover has an abnormal sound, an alarm message is generated and sent.

[0012] A further technical solution is: the alarm information includes the time of occurrence of the abnormal noise of the manhole cover, positioning information, and the specific abnormal condition of the manhole cover.

[0013] A further technical solution is: the audio acquisition module includes a microphone array, and the microphone array includes multiple microphones.

[0014] A further technical solution is: analyzing the sound field energy distribution, compression entropy and time delay of the sound wave propagation path in the audio data, and detecting whether the manhole cover has abnormal sound according to the sound field energy distribution, compression entropy and time delay of the sound wave propagation path to obtain the detection result, including:

[0015] Calculate the sound field energy distribution around the manhole cover using a sound field energy distribution model according to the audio data;

[0016] Compressing the audio data, and analyzing the entropy change of the data before and after compression to obtain compression entropy;

[0017] Analyzing the time difference between different microphones receiving the sound according to the audio data, and calculating the path delay of the sound wave propagation according to the time difference to obtain the delay feature;

[0018] Whether there is an abnormal sound from the manhole cover is detected according to the energy distribution of the sound field, the compression entropy and the time delay characteristics to obtain a detection result.

[0019] A further technical solution is: calculating the sound field energy distribution around the manhole cover according to the audio data through a sound field energy distribution model, including:

[0020] According to the audio data Calculate the energy distribution of the sound field around the manhole cover, where N is the number of microphones, refers to the sound pressure level of the i-th microphone at time t, Represents the sound field energy of the spatial point (x, y) at time t; Represents the distance from the spatial point (x, y) to the i-th microphone; the sound pressure attenuation follows the 1 / d attenuation law, where d represents the transmission distance of the sound wave, the distance from the microphone to the spatial point.

[0021] A further technical solution is: compressing the audio data and analyzing the entropy change of the data before and after compression to obtain compression entropy, including:

[0022] The audio data is compressed, and the ratio between the length of the audio data before compression and the length of the audio data after compression is calculated to obtain compression entropy.

[0023] A further technical solution is: analyzing the time difference of receiving sound between different microphones according to the audio data, and calculating the path delay of sound wave propagation according to the time difference to obtain the delay feature, including:

[0024] According to the audio data Calculate the path delay of sound wave propagation to obtain the delay characteristics, where i and j are any two microphones, represents the time delay between any two microphones i and j; is the sound source position vector; as well as are the position vectors of the two microphones i and j; c is the speed of sound.

[0025] A further technical solution is: detecting whether there is an abnormal sound in the manhole cover according to the energy distribution of the sound field, the compression entropy and the time delay characteristics to obtain a detection result, including:

[0026] Obtaining a comprehensive judgment value by weighted summation according to the sound field energy distribution, compression entropy and the time delay characteristics;

[0027] Whether the manhole cover has an abnormal sound is determined based on the comprehensive judgment value and a set threshold value to obtain a detection result.

[0028] A further technical solution is: the comprehensive judgment value is obtained by weighted summation according to the sound field energy distribution, compression entropy and the delay characteristics, including:

[0029] use Calculate the comprehensive judgment value, where , , is the weight coefficient, is the sound field energy weight, obtained through statistical analysis of a large number of sound field energy data of normal and abnormal manhole covers; is the compression entropy weight, based on the analysis of the difference in compression entropy characteristics of different types of abnormal noise; is the delay feature weight, taking into account the impact of environmental noise on delay estimation; is the expected time delay under normal circumstances, It refers to the comprehensive judgment value.

[0030] The present invention also provides a manhole cover abnormal noise monitoring system based on dynamic inspection, comprising:

[0031] A data acquisition unit, used to acquire initial data collected by a data acquisition device arranged on the mobile device, wherein the data acquisition device includes an image acquisition module, an audio acquisition module and a positioning module, and the initial data includes an initial image, audio data and positioning information;

[0032] A manhole cover recognition unit, used to perform manhole cover recognition on the initial image to obtain a recognition result;

[0033] an abnormal sound analysis unit, for analyzing the sound field energy distribution, compression entropy, and time delay of the sound wave propagation path in the audio data when there is a manhole cover in the recognition result, and detecting whether there is an abnormal sound in the manhole cover according to the sound field energy distribution, compression entropy, and time delay of the sound wave propagation path, so as to obtain a detection result;

[0034] The information generating unit is used to generate alarm information and send the alarm information when the detection result shows that the manhole cover has an abnormal sound.

[0035] Compared with the prior art, the present invention has the following beneficial effects: the present invention realizes efficient coverage of manhole cover monitoring by combining dynamic patrol with data acquisition equipment on mobile devices to collect images, audio and positioning information in real time; utilizes image recognition technology to automatically identify the position of the manhole cover, avoids omissions and inaccuracies in manual inspection, and improves patrol efficiency; by analyzing the sound field energy, compression entropy and time delay of the sound wave propagation path in the audio data, it can accurately detect whether there is abnormal noise in the manhole cover, reducing the error of relying on manual judgment; the method can generate alarm information in real time, and once the manhole cover is abnormal, it will immediately notify the relevant personnel, shorten the response time, and improve the efficiency of emergency handling; compared with traditional manual patrol, the manhole cover detection task can be automatically performed, reducing labor costs, and reducing the dependence on the frequency and range of manual patrol; by combining data from multiple sensors, the method not only improves the accuracy and coverage of monitoring, but also makes up for the shortcomings of the intelligent manhole cover monitoring system in complex environments.

[0036] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying any creative work.

[0038] Figure 1 A schematic diagram of a flow chart of a method for monitoring abnormal noise of a manhole cover based on dynamic inspection provided by an embodiment of the present invention;

[0039] Figure 2 A sub-process diagram of a method for monitoring abnormal noise of a manhole cover based on dynamic inspection provided by an embodiment of the present invention Figure 1 ;

[0040] Figure 3 A schematic diagram of a method for monitoring abnormal noise of a manhole cover based on dynamic inspection provided by an embodiment of the present invention Figure 2 ;

[0041] Figure 4 A schematic diagram of the energy distribution of a sound field provided by an embodiment of the present invention;

[0042] Figure 5 A data comparison curve diagram before compression provided by an embodiment of the present invention;

[0043] Figure 6 A comparison curve diagram of compressed data provided by an embodiment of the present invention;

[0044] Figure 7A schematic diagram of compression entropy provided by an embodiment of the present invention;

[0045] Figure 8 A schematic block diagram of a manhole cover abnormal noise monitoring system based on dynamic inspection provided by an embodiment of the present invention;

[0046] Fig. 9 A schematic block diagram of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0048] It should be understood that when used in this specification and the appended claims, the terms "include" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0049] It should also be understood that the terms used in this specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the specification of the present invention and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0050] It should be further understood that the term "and / or" used in the present description and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0051] See also Figure 1 , Figure 1 A schematic flow chart of a method for monitoring abnormal noise of manhole covers based on dynamic inspection provided by an embodiment of the present invention. The method for monitoring abnormal noise of manhole covers based on dynamic inspection is applied in a server. The server interacts with a data acquisition device provided on a mobile device. Specifically, the data acquisition device on the mobile device acquires initial data including images, audio and location information, and then analyzes the image to identify whether there is a manhole cover. Once the existence of a manhole cover is confirmed, the sound field energy distribution, compression entropy and sound wave propagation delay in the audio are evaluated to determine whether the manhole cover produces abnormal noise; if an abnormal noise is detected, an alarm message is immediately generated and sent.

[0052] Figure 1FIG. 1 is a flow chart of a method for monitoring abnormal noise of a manhole cover based on dynamic inspection provided by an embodiment of the present invention. Figure 1 As shown, the method includes the following steps S110 to S140.

[0053] S110, acquiring initial data collected by a data collection device disposed on a mobile device, wherein the data collection device includes an image collection module, an audio collection module and a positioning module, and the initial data includes an initial image, audio data and positioning information.

[0054] In this embodiment, the mobile device may include a vehicle, etc. The lens of the data acquisition device faces the windshield, is installed in the vehicle, and starts working when the vehicle is started. Full coverage of road recognition can be achieved, and a set of sensors is not required for each manhole cover, which reduces maintenance costs.

[0055] By integrating data acquisition equipment inside the vehicle, the status of road manhole covers can be automatically monitored. These monitoring devices include but are not limited to image acquisition modules (such as lenses), audio acquisition modules (such as microphone arrays), and positioning modules (such as GPS). When the equipment is installed in the vehicle, specifically behind the windshield and in the same direction as the front of the vehicle, as the vehicle moves, these devices can effectively cover and monitor various locations on the road.

[0056] Specifically, the vehicle is cleverly used as a mobile platform to integrate the equipment required for monitoring into the vehicle, which not only avoids the high cost of deploying sensors on a single manhole cover, but also greatly improves the monitoring efficiency and coverage. Since there is no need to deploy sensors separately or modify manhole covers, this method can ensure that there is no impact on the existing infrastructure and can flexibly adapt to various types of vehicles in daily use, such as patrol cars, buses, etc., thereby further expanding the monitoring range. Among them, the audio acquisition module includes a microphone array, and the microphone array includes multiple microphones.

[0057] When the device is powered on, the data acquisition device immediately begins collecting initial data from three main areas:

[0058] The image acquisition module, i.e. the lens, is used to capture image information in the direction of vehicle travel. These images will serve as the basis for the subsequent manhole cover recognition process.

[0059] An array of multiple microphones is responsible for recording the sounds of the surrounding environment, especially for specific audio signals that may come from the manhole cover area, such as abnormal noises.

[0060] The GPS module is used to determine the vehicle's location information, including latitude and longitude coordinates and driving speed, providing accurate time and space reference points for all collected data.

[0061] The initial data obtained is a set of multi-dimensional information, including but not limited to:

[0062] Initial image: refers to the original image data captured by the image acquisition module, which is the key basis for manhole cover identification.

[0063] Audio data: The sound file recorded by the audio acquisition module contains important clues that can be used to analyze whether there is any abnormal noise from the manhole cover.

[0064] Positioning information: The geographic location and timestamp information provided by the positioning module enables each piece of data to be accurately associated with specific time and space coordinates, facilitating subsequent processing and analysis.

[0065] S120: Perform manhole cover recognition on the initial image to obtain a recognition result.

[0066] In this embodiment, the recognition result specifically refers to the information set obtained through the manhole cover recognition process, which not only reflects the existence and specific location of the manhole cover in the image, but also includes key assessments of the status of the manhole cover, providing solid technical support for achieving fast and accurate road facility management.

[0067] Specifically, before starting the formal manhole cover recognition, a series of preprocessing operations are performed on the initial image, such as adjusting the image brightness contrast, removing noise, correcting perspective deformation, etc., to ensure that the image quality meets the requirements of the recognition algorithm.

[0068] Preprocessing also includes converting color images into grayscale images, or cropping irrelevant parts of the image according to specific needs, thereby reducing the amount of calculation and improving recognition efficiency.

[0069] Use computer vision technology or deep learning models (such as convolutional neural networks (CNNs)) to analyze the processed images and automatically extract the unique features of manhole covers, such as shape, texture, color, etc. Based on the trained model, the system can distinguish different types of objects, accurately locate the manhole cover in the image, and output the specific coordinates of each detected manhole cover. In addition, by comparing the differences between the newly collected images and historical records or standard templates, it can be determined whether there are any abnormalities in the manhole covers, such as displacement, damage, loss, etc.

[0070] After the above processing, the final result is a recognition result containing multiple elements, each element corresponds to a manhole cover detected in the image and its related information. This information should at least include:

[0071] Location of manhole covers: Use a rectangular frame or other geometric shapes to mark the exact location of the manhole cover in the image;

[0072] Manhole cover status: describes the current status of the manhole cover, such as normal, damaged, missing, etc.;

[0073] Confidence score: Gives a reliability index for the recognition result, indicating the probability that the result is correct.

[0074] If the identification result shows that there is a potential problem with the manhole cover, the next step is triggered, such as entering the abnormal sound detection process to further confirm the actual condition of the manhole cover.

[0075] At the same time, all recognition results are stored together with the original image as an important basis for future maintenance decisions, and can also be used to optimize and improve the recognition algorithm.

[0076] Of course, the manhole cover identification of this embodiment can refer to the manhole cover disease detection method, device, computer equipment and storage medium disclosed in Chinese patent CN117350985B, and the process of manhole cover target identification will not be repeated here.

[0077] S130. When a manhole cover exists in the recognition result, the sound field energy distribution, compression entropy and time delay of the sound wave propagation path in the audio data are analyzed, and based on the sound field energy distribution, compression entropy and time delay of the sound wave propagation path, it is detected whether the manhole cover has an abnormal sound to obtain a detection result.

[0078] In this embodiment, the detection results include the presence of abnormal noise from the manhole cover or the absence of abnormal noise from the manhole cover. When there is an abnormal noise from the manhole cover, the type of abnormal noise can be further determined through image recognition technology, such as loose noise, damaged noise, and concave-convex deformation noise. Among them, the loose noise is usually caused by the manhole cover being loosely connected to the manhole base, and there is a gap between them, which causes shaking when the vehicle rolls over it; the damaged noise is usually caused by cracks on the surface of the manhole cover or local fractures, which causes abnormal noise when the vehicle passes by; the concave-convex deformation noise is usually caused by settlement of the pipe barrel, protrusion of the manhole cover, or deformation of the manhole cover due to force, resulting in the unevenness of the manhole cover surface and the road.

[0079] In one embodiment, see Figure 2 The above-mentioned step S130 may include steps S131~S134.

[0080] S131. Calculate the sound field energy distribution around the manhole cover using a sound field energy distribution model according to the audio data.

[0081] In this embodiment, the sound field energy distribution refers to how the sound energy calculated from the audio data changes with position in a specific space. This helps to understand the propagation mode and intensity of the sound energy in the environment around the sound source (such as a manhole cover), such as Figure 4 shown.

[0082] According to the audio data Calculate the energy distribution of the sound field around the manhole cover, where N is the number of microphones, refers to the sound pressure level of the i-th microphone at time t, Represents the sound field energy of the spatial point (x, y) at time t; Represents the distance from the spatial point (x, y) to the i-th microphone; the sound pressure attenuation follows the 1 / d attenuation law, where d represents the transmission distance of the sound wave, the distance from the microphone to the spatial point.

[0083] This value is calculated by dividing the sound pressure level recorded by each microphone i Divide by the distance from the point to the microphone , which is then summed across all microphones. The sound pressure level reflects the instantaneous sound pressure level over a period of time, while the distance attenuation factor takes into account the natural attenuation of sound waves as they travel further.

[0084] S132: compress the audio data, and analyze the entropy change of the data before and after compression to obtain compression entropy.

[0085] In this embodiment, compression entropy is an indicator used to measure the compression efficiency of audio data. It describes the proportional change of the amount of compressed information relative to the amount of original information, that is, a quantitative expression of the degree of data compression.

[0086] Specifically, see Figures 5 to 7 , compress the audio data, and calculate the ratio between the length of the audio data before compression and the length of the audio data after compression to obtain compression entropy. The calculation formula used is: ,in, is the length of the compressed data; is the length of the original data. The lower the compression entropy, the more effectively the data with the same content is compressed, and the more information is retained.

[0087] S133. Analyze the time difference of receiving the sound between different microphones according to the audio data, and calculate the path delay of the sound wave propagation according to the time difference to obtain the delay feature.

[0088] In this embodiment, the delay feature refers to the information about the delay of the sound wave propagation path derived based on the time difference between different receiving points (such as multiple microphones) when receiving the sound emitted by the same sound source. This feature is very important for determining the location of the sound source or analyzing the multipath effect.

[0089] Specifically, according to the audio data, Calculate the path delay of sound wave propagation to obtain the delay characteristics, where i and j are any two microphones, represents the time delay between any two microphones i and j; is the sound source position vector; as well as is the position vector of the two microphones i and j; c is the speed of sound. By measuring this time difference, the specific path and characteristics of the sound wave from the sound source to each microphone can be inferred.

[0090] S134. Detect whether there is an abnormal sound from the manhole cover according to the energy distribution of the sound field, the compression entropy and the time delay characteristics to obtain a detection result.

[0091] In this embodiment, the sound field energy distribution focuses on the distribution of sound in space; compression entropy is an evaluation of the compression effect of audio data; and the time delay feature is used to characterize the time delay properties in the process of sound wave propagation. These concepts together form the basis for in-depth analysis of audio data.

[0092] In one embodiment, see Figure 3 , the above-mentioned step S134 may include steps S1341~S1342.

[0093] S1341. Obtain a comprehensive judgment value by weighted summation according to the sound field energy distribution, compression entropy and the time delay characteristics.

[0094] In this embodiment, the Calculate the comprehensive judgment value, where , , is the weight coefficient, is the sound field energy weight, obtained through statistical analysis of a large number of sound field energy data of normal and abnormal manhole covers; is the compression entropy weight, based on the analysis of the difference in compression entropy characteristics of different types of abnormal noise; is the delay feature weight, taking into account the impact of environmental noise on delay estimation; is the expected time delay under normal circumstances, It refers to the comprehensive judgment value.

[0095] In this embodiment, the selection of weight coefficients is based on statistical analysis of a large amount of normal and abnormal manhole cover sample data, ensuring that each factor can affect the final judgment result in an appropriate proportion.

[0096] S1342. Determine whether the manhole cover has abnormal noise based on the comprehensive judgment value and the set threshold value to obtain a detection result.

[0097] In this embodiment, the comprehensive judgment value is calculated The judgment threshold obtained from the experiment When comparing the values When the abnormal sound warning is triggered, data is sent back.

[0098] This method combines multiple audio features to not only improve the accuracy of detection, but also adapt to different environmental conditions and effectively reduce the possibility of false alarms. In this way, the status of manhole covers can be monitored more reliably, potential problems can be discovered in a timely manner, and public safety can be guaranteed.

[0099] In addition, if you need to further determine the cause of the abnormal noise produced by the manhole cover, you can use the following steps to determine the different types:

[0100] A high-resolution camera is used to take photos around the manhole cover, and the gap between the manhole cover and the base of the manhole is identified through edge detection algorithms. The position changes of the manhole cover are tracked in the video sequence. If the manhole cover is found to have obvious up-down or sideways movement, it may be a sign of looseness. The changes in the manhole cover surface over time are analyzed, especially the vibration pattern when vehicles pass by. Loose manhole covers may show abnormal vibration frequency or amplitude.

[0101] For abnormal noises caused by damage, image processing techniques such as Canny edge detection or other more advanced deep learning models are used to automatically identify cracks or fractures on the surface of the manhole cover. Changes in texture features (such as roughness and continuity) are used to determine whether the manhole cover has abnormal damage. For possible deep damage, three-dimensional reconstruction can be performed through multi-view images to more accurately assess the degree of damage.

[0102] For uneven deformation and noise, use distance measurement equipment to obtain the height information of the manhole cover relative to the ground to determine whether there is a protrusion or sinking phenomenon. Compare the collected manhole cover image with the standard template to find any deviation from the normal shape, such as depressions or protrusions. Detect the contour line of the edge of the manhole cover to observe whether there is an irregular bend or twist, which may be a sign of deformation.

[0103] In this embodiment, the abnormal sound is determined by analyzing audio data. By combining multiple audio features such as sound field energy distribution, compression entropy and time delay characteristics, this method can analyze sound data more comprehensively, thereby improving the accuracy of detecting abnormal sound of manhole covers. Each feature provides a different information angle, which helps to distinguish between normal and abnormal situations.

[0104] By using multimodal data analysis combining audio and images, and setting reasonable weight coefficients and thresholds based on statistical analysis of a large amount of sample data, false alarms caused by factors such as environmental noise can be effectively reduced. This ensures that the system can operate stably in various complex environments and improves the reliability of the system.

[0105] Once an abnormal sound is detected from the manhole cover and exceeds the preset threshold, an alarm is immediately triggered and data is sent back, allowing the management department to take quick action to resolve the problem and avoid the expansion of potential safety hazards.

[0106] For manhole covers with abnormal noises, further application of image recognition technology can help pinpoint the specific type of problem - whether it is loose, broken or deformed. This accuracy not only helps speed up the repair process, but also provides valuable information for subsequent maintenance, such as which types of damage are more likely to occur so that preventive measures can be taken.

[0107] S140. When the detection result shows that the manhole cover has an abnormal sound, an alarm message is generated and sent.

[0108] In this embodiment, the alarm information includes the time of occurrence of the abnormal noise of the manhole cover, the positioning information, and the specific abnormal condition of the manhole cover. The specific abnormal condition of the manhole cover refers to the type corresponding to the abnormal noise of the manhole cover. When the abnormal mutation is located, the GPS positioning longitude and latitude corresponding to the time scale, that is, the positioning information, and the abnormal state of the manhole cover are returned according to the time when the mutation occurs.

[0109] The above-mentioned manhole cover abnormal noise monitoring method based on dynamic inspection, through dynamic inspection combined with data acquisition equipment on mobile devices, collects images, audio and positioning information in real time, and realizes efficient coverage of manhole cover monitoring; uses image recognition technology to automatically identify the position of the manhole cover, avoids omissions and inaccuracies in manual inspection, and improves inspection efficiency; by analyzing the sound field energy, compression entropy and time delay of the sound wave propagation path in the audio data, it can accurately detect whether there is an abnormal noise in the manhole cover, reducing the error of relying on manual judgment; this method can generate alarm information in real time, and once the manhole cover is abnormal, it will immediately notify the relevant personnel, shorten the response time, and improve the efficiency of emergency handling; compared with traditional manual inspection, it can automatically perform manhole cover detection tasks, reduce labor costs, and reduce dependence on the frequency and range of manual inspections; by combining data from multiple sensors, this method not only improves the accuracy and coverage of monitoring, but also makes up for the shortcomings of the intelligent manhole cover monitoring system in complex environments.

[0110] Figure 8 FIG. 3 is a schematic block diagram of a manhole cover abnormal noise monitoring system 300 based on dynamic inspection provided by an embodiment of the present invention. Figure 8 As shown, corresponding to the above manhole cover abnormal noise monitoring method based on dynamic inspection, the present invention also provides a manhole cover abnormal noise monitoring system 300 based on dynamic inspection. The manhole cover abnormal noise monitoring system 300 based on dynamic inspection includes a unit for executing the above manhole cover abnormal noise monitoring method based on dynamic inspection, and the system can be configured in a server. Figure 8The manhole cover abnormal noise monitoring system 300 based on dynamic inspection includes a data acquisition unit 301, a manhole cover identification unit 302, an abnormal noise analysis unit 303 and an information generation unit 304.

[0111] The data acquisition unit 301 is used to acquire initial data collected by a data acquisition device set on a mobile device, wherein the data acquisition device includes an image acquisition module, an audio acquisition module and a positioning module, and the initial data includes an initial image, audio data and positioning information; the manhole cover recognition unit 302 is used to identify the manhole cover of the initial image to obtain a recognition result; the abnormal sound analysis unit 303 is used to analyze the sound field energy distribution, compression entropy and time delay of the sound wave propagation path in the audio data when a manhole cover exists in the recognition result, and detect whether the manhole cover has an abnormal sound based on the sound field energy distribution, compression entropy and time delay of the sound wave propagation path to obtain a detection result; the information generation unit 304 is used to generate an alarm message when the detection result is that the manhole cover has an abnormal sound, and send the alarm message.

[0112] In one embodiment, the abnormal sound analysis unit 303 includes:

[0113] A sound field energy distribution determination subunit is used to calculate the sound field energy distribution around the manhole cover through a sound field energy distribution model according to the audio data; a compression entropy determination subunit is used to compress the audio data and analyze the entropy change of the data before and after compression to obtain compression entropy; a delay determination subunit is used to analyze the time difference between the sounds received by different microphones according to the audio data, and calculate the path delay of the sound wave propagation according to the time difference to obtain the delay feature; a detection subunit is used to detect whether there is an abnormal sound from the manhole cover according to the sound field energy distribution, the compression entropy and the delay feature to obtain a detection result.

[0114] In one embodiment, the sound field energy distribution determination subunit is used to adopt Calculate the energy distribution of the sound field around the manhole cover, where N is the number of microphones, refers to the sound pressure level of the i-th microphone at time t, Represents the sound field energy of the spatial point (x, y) at time t; Represents the distance from the spatial point (x, y) to the i-th microphone; the sound pressure attenuation follows the 1 / d attenuation law, where d represents the transmission distance of the sound wave, the distance from the microphone to the spatial point.

[0115] In one embodiment, the compression entropy determination subunit is used to perform data compression on the audio data and calculate the ratio between the length of the audio data before compression and the length of the audio data after compression to obtain the compression entropy.

[0116] In one embodiment, the delay determination subunit is used to adopt Calculate the path delay of sound wave propagation to obtain the delay characteristics, where i and j are any two microphones, represents the time delay between any two microphones i and j; is the sound source position vector; as well as are the position vectors of the two microphones i and j; c is the speed of sound.

[0117] In one embodiment, the detection subunit comprises:

[0118] A weighted summation module is used to obtain a comprehensive judgment value by weighted summation according to the sound field energy distribution, compression entropy and the time delay characteristics; an abnormal sound judgment module is used to determine whether there is an abnormal sound in the manhole cover according to the comprehensive judgment value and a set threshold value to obtain a detection result.

[0119] In one embodiment, the weighted summation module is used to adopt Calculate the comprehensive judgment value, where , , is the weight coefficient, is the sound field energy weight, obtained through statistical analysis of a large number of sound field energy data of normal and abnormal manhole covers; is the compression entropy weight, based on the analysis of the difference in compression entropy characteristics of different types of abnormal noise; is the delay feature weight, taking into account the impact of environmental noise on delay estimation; is the expected time delay under normal circumstances, It refers to the comprehensive judgment value.

[0120] It should be noted that technicians in the relevant field can clearly understand that the specific implementation process of the above-mentioned manhole cover abnormal sound monitoring system 300 based on dynamic inspection and each unit can refer to the corresponding description in the aforementioned method embodiment, and for the convenience and conciseness of the description, it will not be repeated here.

[0121] The above-mentioned manhole cover abnormal noise monitoring system 300 based on dynamic inspection can be implemented in the form of a computer program, which can be used in Fig. 9 Runs on the computer device shown.

[0122] See also Fig. 9 , Fig. 9 5 is a schematic block diagram of a computer device provided in an embodiment of the present application. The computer device 500 may be a server, wherein the server may be an independent server or a server cluster composed of multiple servers.

[0123] See also Fig. 9 The computer device 500 includes a processor 502 , a memory and a network interface 505 connected via a system bus 501 , wherein the memory may include a non-volatile storage medium 503 and an internal memory 504 .

[0124] The non-volatile storage medium 503 can store an operating system 5031 and a computer program 5032. The computer program 5032 includes program instructions, and when the program instructions are executed, the processor 502 can execute a method for monitoring abnormal noise of a manhole cover based on dynamic inspection.

[0125] The processor 502 is used to provide computing and control capabilities to support the operation of the entire computer device 500 .

[0126] The internal memory 504 provides an environment for the operation of the computer program 5032 in the non-volatile storage medium 503. When the computer program 5032 is executed by the processor 502, the processor 502 can execute a method for monitoring abnormal noise of manhole covers based on dynamic inspections.

[0127] The network interface 505 is used to communicate with other devices over the network. Fig. 9 The structure shown in the figure is merely a block diagram of a portion of the structure related to the solution of the present application, and does not constitute a limitation on the computer device 500 to which the solution of the present application is applied. The specific computer device 500 may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0128] The processor 502 is used to run the computer program 5032 stored in the memory to implement the following steps:

[0129] Acquire initial data collected by a data acquisition device set on a mobile device, wherein the data acquisition device includes an image acquisition module, an audio acquisition module and a positioning module, and the initial data includes an initial image, audio data and positioning information; perform manhole cover recognition on the initial image to obtain a recognition result; when a manhole cover exists in the recognition result, analyze the sound field energy distribution, compression entropy and time delay of the sound wave propagation path in the audio data, and detect whether the manhole cover has an abnormal sound based on the sound field energy distribution, compression entropy and time delay of the sound wave propagation path to obtain a detection result; when the detection result is that the manhole cover has an abnormal sound, generate an alarm message and send the alarm message.

[0130] The alarm information includes the time of occurrence of the abnormal noise of the manhole cover, location information, and specific abnormal conditions of the manhole cover.

[0131] The audio acquisition module includes a microphone array, and the microphone array includes a plurality of microphones.

[0132] In one embodiment, when the processor 502 implements the step of analyzing the sound field energy distribution, compression entropy, and time delay of the sound wave propagation path in the audio data, and detecting whether there is an abnormal sound in the manhole cover according to the sound field energy distribution, compression entropy, and time delay of the sound wave propagation path to obtain the detection result, the processor 502 specifically implements the following steps:

[0133] The sound field energy distribution around the manhole cover is calculated according to the audio data through the sound field energy distribution model; the audio data is compressed, and the entropy change of the data before and after compression is analyzed to obtain the compression entropy; the time difference between the sounds received by different microphones is analyzed according to the audio data, and the path delay of the sound wave propagation is calculated according to the time difference to obtain the time delay feature; whether the manhole cover has abnormal sound is detected according to the sound field energy distribution, the compression entropy and the time delay feature to obtain the detection result.

[0134] In one embodiment, when the processor 502 implements the step of calculating the sound field energy distribution around the manhole cover by using the sound field energy distribution model according to the audio data, the processor 502 specifically implements the following steps:

[0135] According to the audio data Calculate the energy distribution of the sound field around the manhole cover, where N is the number of microphones, refers to the sound pressure level of the i-th microphone at time t, Represents the sound field energy of the spatial point (x, y) at time t; Represents the distance from the spatial point (x, y) to the i-th microphone; the sound pressure attenuation follows the 1 / d attenuation law, where d represents the transmission distance of the sound wave, the distance from the microphone to the spatial point.

[0136] In one embodiment, when the processor 502 implements the step of compressing the audio data and analyzing the entropy change of the data before and after compression to obtain the compression entropy, the processor 502 specifically implements the following steps:

[0137] The audio data is compressed, and the ratio between the length of the audio data before compression and the length of the audio data after compression is calculated to obtain compression entropy.

[0138] In one embodiment, when the processor 502 implements the step of analyzing the time difference of receiving the sound between different microphones according to the audio data, and calculating the path delay of the sound wave propagation according to the time difference to obtain the delay feature, the processor 502 specifically implements the following steps:

[0139] According to the audio data Calculate the path delay of sound wave propagation to obtain the delay characteristics, where i and j are any two microphones, represents the time delay between any two microphones i and j; is the sound source position vector; as well as are the position vectors of the two microphones i and j; c is the speed of sound.

[0140] In one embodiment, when the processor 502 implements the step of detecting whether there is an abnormal sound in the manhole cover according to the sound field energy distribution, the compression entropy and the time delay characteristics to obtain the detection result, the processor 502 specifically implements the following steps:

[0141] A comprehensive judgment value is obtained by weighted summation according to the energy distribution of the sound field, the compression entropy and the time delay characteristics; and whether there is an abnormal sound from the manhole cover is determined according to the comprehensive judgment value and a set threshold to obtain a detection result.

[0142] In one embodiment, when the processor 502 implements the step of obtaining a comprehensive judgment value by weighted summation according to the sound field energy distribution, compression entropy and the delay feature, the processor 502 specifically implements the following steps:

[0143] use Calculate the comprehensive judgment value, where , , is the weight coefficient, is the sound field energy weight, obtained through statistical analysis of a large number of sound field energy data of normal and abnormal manhole covers; is the compression entropy weight, based on the analysis of the difference in compression entropy characteristics of different types of abnormal noise; is the delay feature weight, taking into account the impact of environmental noise on delay estimation; is the expected time delay under normal circumstances, It refers to the comprehensive judgment value.

[0144] It should be understood that in the embodiment of the present application, the processor 502 may be a central processing unit (CPU), and the processor 502 may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0145] It can be understood by those skilled in the art that all or part of the processes in the method for implementing the above embodiment can be completed by instructing the relevant hardware through a computer program. The computer program includes program instructions, and the computer program can be stored in a storage medium, which is a computer-readable storage medium. The program instructions are executed by at least one processor in the computer system to implement the process steps of the embodiment of the above method.

[0146] Therefore, the present invention also provides a storage medium. The storage medium may be a computer-readable storage medium. The storage medium stores a computer program, wherein when the computer program is executed by a processor, the processor executes the following steps:

[0147] Acquire initial data collected by a data acquisition device set on a mobile device, wherein the data acquisition device includes an image acquisition module, an audio acquisition module and a positioning module, and the initial data includes an initial image, audio data and positioning information; perform manhole cover recognition on the initial image to obtain a recognition result; when a manhole cover exists in the recognition result, analyze the sound field energy distribution, compression entropy and time delay of the sound wave propagation path in the audio data, and detect whether the manhole cover has an abnormal sound based on the sound field energy distribution, compression entropy and time delay of the sound wave propagation path to obtain a detection result; when the detection result is that the manhole cover has an abnormal sound, generate an alarm message and send the alarm message.

[0148] The alarm information includes the time of occurrence of the abnormal noise of the manhole cover, location information, and specific abnormal conditions of the manhole cover.

[0149] The audio acquisition module includes a microphone array, and the microphone array includes a plurality of microphones.

[0150] In one embodiment, when the processor executes the computer program to implement the step of analyzing the sound field energy distribution, compression entropy and time delay of the sound wave propagation path in the audio data, and detecting whether there is an abnormal sound in the manhole cover according to the sound field energy distribution, compression entropy and time delay of the sound wave propagation path to obtain the detection result, the following steps are specifically implemented:

[0151] The sound field energy distribution around the manhole cover is calculated according to the audio data through the sound field energy distribution model; the audio data is compressed, and the entropy change of the data before and after compression is analyzed to obtain the compression entropy; the time difference between the sounds received by different microphones is analyzed according to the audio data, and the path delay of the sound wave propagation is calculated according to the time difference to obtain the time delay feature; whether the manhole cover has abnormal sound is detected according to the sound field energy distribution, the compression entropy and the time delay feature to obtain the detection result.

[0152] In one embodiment, when the processor executes the computer program to implement the step of calculating the sound field energy distribution around the manhole cover through the sound field energy distribution model according to the audio data, the processor specifically implements the following steps:

[0153] According to the audio data Calculate the energy distribution of the sound field around the manhole cover, where N is the number of microphones, refers to the sound pressure level of the i-th microphone at time t, Represents the sound field energy of the spatial point (x, y) at time t; Represents the distance from the spatial point (x, y) to the i-th microphone; the sound pressure attenuation follows the 1 / d attenuation law, where d represents the transmission distance of the sound wave, the distance from the microphone to the spatial point.

[0154] In one embodiment, when the processor executes the computer program to implement the step of compressing the audio data and analyzing the entropy change of the data before and after compression to obtain the compression entropy, the processor specifically implements the following steps:

[0155] The audio data is compressed, and the ratio between the length of the audio data before compression and the length of the audio data after compression is calculated to obtain compression entropy.

[0156] In one embodiment, when the processor executes the computer program to implement the step of analyzing the time difference of receiving the sound between different microphones according to the audio data, and calculating the path delay of the sound wave propagation according to the time difference to obtain the delay feature, the following steps are specifically implemented:

[0157] According to the audio data Calculate the path delay of sound wave propagation to obtain the delay characteristics, where i and j are any two microphones, represents the time delay between any two microphones i and j; is the sound source position vector; as well as are the position vectors of the two microphones i and j; c is the speed of sound.

[0158] In one embodiment, when the processor executes the computer program to implement the step of detecting whether there is an abnormal sound in the manhole cover according to the sound field energy distribution, compression entropy and the time delay characteristics to obtain a detection result, the processor specifically implements the following steps:

[0159] A comprehensive judgment value is obtained by weighted summation according to the energy distribution of the sound field, the compression entropy and the time delay characteristics; and whether there is an abnormal sound from the manhole cover is determined according to the comprehensive judgment value and a set threshold to obtain a detection result.

[0160] In one embodiment, when the processor executes the computer program to implement the step of obtaining a comprehensive judgment value by weighted summation according to the sound field energy distribution, compression entropy and the delay characteristics, the following steps are specifically implemented:

[0161] use Calculate the comprehensive judgment value, where , , is the weight coefficient, is the sound field energy weight, obtained through statistical analysis of a large number of sound field energy data of normal and abnormal manhole covers; is the compression entropy weight, based on the analysis of the difference in compression entropy characteristics of different types of abnormal noise; is the delay feature weight, taking into account the impact of environmental noise on delay estimation; is the expected time delay under normal circumstances, It refers to the comprehensive judgment value.

[0162] The storage medium may be a USB flash drive, a mobile hard disk, a read-only memory (ROM), a magnetic disk, or an optical disk, etc., which are computer-readable storage media that can store program codes.

[0163] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0164] In the several embodiments provided by the present invention, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are only schematic. For example, the division of each unit is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0165] The steps in the method of the embodiment of the present invention can be adjusted in order, combined and deleted according to actual needs. The units in the system of the embodiment of the present invention can be combined, divided and deleted according to actual needs. In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0166] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, terminal, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention.

[0167] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A method for monitoring abnormal noise of manhole covers based on dynamic inspection, characterized in that: include: Acquire initial data collected by a data collection device disposed on a mobile device, wherein the data collection device includes an image collection module, an audio collection module, and a positioning module, and the initial data includes an initial image, audio data, and positioning information; Performing manhole cover recognition on the initial image to obtain a recognition result; When there is a manhole cover in the recognition result, analyzing the sound field energy distribution, compression entropy and time delay of the sound wave propagation path in the audio data, and detecting whether there is an abnormal sound in the manhole cover according to the sound field energy distribution, compression entropy and time delay of the sound wave propagation path to obtain a detection result; When the detection result shows that the manhole cover has an abnormal sound, an alarm message is generated and sent.

2. The method for monitoring abnormal noise of manhole covers based on dynamic inspection according to claim 1 is characterized in that: The alarm information includes the time when the abnormal noise of the manhole cover occurs, the location information, and the specific abnormal condition of the manhole cover.

3. The method for monitoring abnormal noise of manhole covers based on dynamic inspection according to claim 1 is characterized in that: The audio acquisition module includes a microphone array, and the microphone array includes a plurality of microphones.

4. The method for monitoring abnormal noise of manhole covers based on dynamic inspection according to claim 1 is characterized in that: The analyzing the sound field energy distribution, compression entropy and time delay of the sound wave propagation path in the audio data, and detecting whether the manhole cover has abnormal sound according to the sound field energy distribution, compression entropy and time delay of the sound wave propagation path to obtain the detection result, includes: Calculate the sound field energy distribution around the manhole cover using a sound field energy distribution model according to the audio data; Compressing the audio data, and analyzing the entropy change of the data before and after compression to obtain compression entropy; Analyzing the time difference between different microphones receiving the sound according to the audio data, and calculating the path delay of the sound wave propagation according to the time difference to obtain the delay feature; Whether there is an abnormal sound from the manhole cover is detected according to the energy distribution of the sound field, the compression entropy and the time delay characteristics to obtain a detection result.

5. The method for monitoring abnormal noise of manhole covers based on dynamic inspection according to claim 4 is characterized in that: The calculating the sound field energy distribution around the manhole cover by using a sound field energy distribution model according to the audio data includes: According to the audio data Calculate the energy distribution of the sound field around the manhole cover, where N is the number of microphones, refers to the sound pressure level of the i-th microphone at time t, Represents the sound field energy of the spatial point (x, y) at time t; Represents the distance from the spatial point (x, y) to the i-th microphone; the sound pressure attenuation follows the 1 / d attenuation law, where d represents the transmission distance of the sound wave, the distance from the microphone to the spatial point.

6. The method for monitoring abnormal noise of manhole covers based on dynamic inspection according to claim 4 is characterized in that: The step of compressing the audio data and analyzing the entropy change of the data before and after compression to obtain compression entropy includes: The audio data is compressed, and the ratio between the length of the audio data before compression and the length of the audio data after compression is calculated to obtain compression entropy.

7. The method for monitoring abnormal noise of manhole covers based on dynamic inspection according to claim 6 is characterized in that: Analyzing the time difference between different microphones receiving the sound according to the audio data, and calculating the path delay of the sound wave propagation according to the time difference to obtain the delay feature, includes: According to the audio data Calculate the path delay of sound wave propagation to obtain the delay characteristics, where i and j are any two microphones, represents the time delay between any two microphones i and j; is the sound source position vector; as well as are the position vectors of the two microphones i and j; c is the speed of sound.

8. The method for monitoring abnormal noise of manhole covers based on dynamic inspection according to claim 4 is characterized in that: The detecting whether the manhole cover has abnormal sound according to the sound field energy distribution, compression entropy and the time delay characteristics to obtain the detection result includes: Obtaining a comprehensive judgment value by weighted summation according to the sound field energy distribution, compression entropy and the time delay characteristics; Whether the manhole cover has an abnormal sound is determined based on the comprehensive judgment value and a set threshold value to obtain a detection result.

9. The method for monitoring abnormal noise of manhole covers based on dynamic inspection according to claim 8, characterized in that: The method of obtaining a comprehensive judgment value by weighted summation according to the sound field energy distribution, compression entropy and the delay characteristics includes: use Calculate the comprehensive judgment value, where , , is the weight coefficient, is the sound field energy weight, obtained through statistical analysis of a large number of sound field energy data of normal and abnormal manhole covers; is the compression entropy weight, based on the analysis of the difference in compression entropy characteristics of different types of abnormal noise; is the delay feature weight, taking into account the impact of environmental noise on delay estimation; is the expected time delay under normal circumstances, It refers to the comprehensive judgment value.

10. The manhole cover abnormal noise monitoring system based on dynamic inspection is characterized by: include: A data acquisition unit, used to acquire initial data collected by a data acquisition device arranged on the mobile device, wherein the data acquisition device includes an image acquisition module, an audio acquisition module and a positioning module, and the initial data includes an initial image, audio data and positioning information; A manhole cover recognition unit, used to perform manhole cover recognition on the initial image to obtain a recognition result; an abnormal sound analysis unit, for analyzing the sound field energy distribution, compression entropy, and time delay of the sound wave propagation path in the audio data when there is a manhole cover in the recognition result, and detecting whether there is an abnormal sound in the manhole cover according to the sound field energy distribution, compression entropy, and time delay of the sound wave propagation path, so as to obtain a detection result; The information generating unit is used to generate alarm information and send the alarm information when the detection result shows that the manhole cover has an abnormal sound.

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