A method and system for intelligently identifying multi-source diseases of urban manhole covers and proactively controlling health status

Abstract

The present invention relates to a method and system for intelligent identification of multi-source diseases of urban manhole covers and advanced control of health status. The method includes: establishing a classification system for multi-source diseases of manhole covers; intelligently identifying multi-source diseases of manhole covers, including: collecting basic information of manhole covers; collecting images of manhole covers; collecting vibrations of manhole covers; performing data analysis on manhole cover data obtained by intelligent identification, including: performing spatial feature analysis of manhole cover diseases; performing temporal feature analysis of manhole cover diseases; based on the occurrence rules of manhole cover diseases in different spatial scenes and in different time periods, advanced control of the health status of manhole covers, including: establishing a spatial control plan for the service life of manhole covers, and performing regional spatial control and optimization of multi-source diseases of manhole covers; establishing a time-sharing and stage-by-stage control plan for the service life of manhole covers, and performing time control and optimization of multi-source diseases of manhole covers in multiple time periods. The present invention can achieve precise control of the health status of manhole covers, actively carry out predictive maintenance, reduce the frequency of disease occurrence from the source, and minimize the impact of manhole cover diseases on urban operations.

Description

Technical Field

[0001] The present invention relates to the technical field of urban infrastructure operation and maintenance, and in particular to the operation and maintenance of urban manhole covers, and specifically to a method and system for intelligently identifying multi-source diseases of urban manhole covers and proactively controlling the health status of such covers. Background Art

[0002] Urban manhole covers are an important part of urban infrastructure. However, in recent years, urban manhole cover diseases have occurred frequently. Safety accidents caused by the failure to maintain and repair urban manhole covers in a timely manner have occurred from time to time, seriously restricting the high-quality development of cities.

[0003] At present, the operation and maintenance of urban manhole covers are mainly based on manual inspections, and the defects of manhole covers are manually identified. Due to the limitations of manual experience and level, the efficiency of manhole cover defect identification is low, and there is a lack of intelligent and accurate defect identification system. At the same time, the operation and maintenance of urban manhole covers has not been data-driven, and a mechanism for guiding maintenance work based on historical maintenance data of manhole covers has not been established. There is a lack of research on the distribution patterns and influencing factors of manhole cover defects, and it is impossible to form accurate intelligent management and control of urban manhole covers at the temporal and spatial levels, let alone effectively guide the predictive maintenance of urban manhole covers.

[0004] In view of the existing deficiencies, there is an urgent need to reduce the frequency of disease occurrence from the source and effectively improve the safe operation level of urban manhole covers. Summary of the invention

[0005] In view of the deficiencies in the prior art, the main purpose of the present invention is to provide a method and system for intelligent identification of multi-source diseases of urban manhole covers and advanced control of their health status, so as to solve one or more problems in the prior art.

[0006] The technical solution of the present invention is as follows:

[0007] The first aspect of the present invention provides a method for intelligently identifying multi-source diseases of urban manhole covers and advanced health status control, the method comprising:

[0008] Establish a classification system for multi-source diseases of manhole covers;

[0009] Based on the classification system of multi-source diseases of manhole covers, multi-source diseases of manhole covers are intelligently identified, including:

[0010] Collect basic information of manhole covers to match subsequent collected data with the basic information data of manhole covers;

[0011] Collect manhole cover images, and determine whether the manhole cover is damaged and the type and degree of damage based on the manhole cover image data;

[0012] Collect the vibration sound of the manhole cover, and determine whether the manhole cover is damaged and the type and degree of damage based on the vibration data;

[0013] Analyze the manhole cover data obtained by intelligent identification and establish a multi-source disease database for manhole covers, including:

[0014] Conduct spatial characteristic analysis of manhole cover diseases to obtain the occurrence patterns of manhole cover diseases in different spatial scenarios;

[0015] Conduct time characteristic analysis on manhole cover diseases to obtain the occurrence patterns of manhole cover diseases in different time periods;

[0016] Based on the occurrence patterns of manhole cover diseases in different spatial scenarios and time periods, the health status of manhole covers is controlled in advance, including:

[0017] Establish a spatial management and control plan for the service life of manhole covers, and conduct regional spatial control and optimization of multi-source diseases of manhole covers;

[0018] Establish a time- and phase-based management and control plan for the service life of manhole covers, and conduct multi-time period time control and optimization of multi-source diseases of manhole covers.

[0019] Preferably, the manhole cover image is collected, and based on the manhole cover image data, whether the manhole cover is damaged and the type and degree of the damage are determined, specifically:

[0020] The manhole cover image is collected, and based on the collected manhole cover image data, it is determined whether the manhole cover has Class I disease among multi-source diseases. Class I diseases include eight types of diseases: missing, disordered, displaced, damaged, damaged around the well, bulge, height difference, and subsidence of the manhole cover. The degree of damage of some or all of the Class I diseases can be further determined.

[0021] Preferably, the manhole cover image is collected, and based on the collected manhole cover image data, it is determined whether the manhole cover has Class I disease among multi-source diseases, Class I diseases include eight types of diseases such as missing, disorder, displacement, damage, damage around the well, protrusion, height difference, and subsidence of the manhole cover, and the degree of damage of some or all of the Class I diseases is further determined, including:

[0022] Use image acquisition equipment to capture image data of the manhole cover and its surrounding environment in real time;

[0023] A manhole cover disease recognition model was established to identify manhole cover image data and accurately determine eight types of manhole cover disease in Class I.

[0024] The binary image method is used to convert the pictures collected on site into grayscale images to determine the severity of the two types of damage, namely, damage to the manhole cover and damage around the well, which are Class I damages.

[0025] Preferably, the collecting of the vibration data of the manhole cover and determining whether the manhole cover is damaged and the type and degree of the damage based on the vibration data of the manhole cover are as follows:

[0026] The vibration sound of the manhole cover is collected, and based on the collected manhole cover vibration data, it is determined whether the manhole cover has Class II disease among multi-source diseases, Class II disease includes the vibration disease of the manhole cover, and the degree of the Class II disease is further determined.

[0027] Preferably, the collecting of the vibration data of the manhole cover and determining whether the manhole cover has a Class II disease among the multi-source diseases based on the collected vibration data of the manhole cover, the Class II disease includes the vibration disease of the manhole cover, and further determining the degree of the Class II disease, including:

[0028] Arrange vibration sensors on the manhole cover in the direction of vehicle flow, and use the vibration sensors to collect the vibration frequency of the manhole cover;

[0029] The vibration frequency of the manhole cover is collected by the vibration sensor, and the trend characteristics of the vibration frequency are used to determine whether the manhole cover has Class II disease, and the peak value of the vibration frequency is used to determine the severity of the Class II disease of the manhole cover.

[0030] Preferably, the establishment of a spatial management and control plan for the service life of manhole covers to regionally control and optimize multi-source diseases of manhole covers includes:

[0031] Establish a spatial inspection plan for key points, key paths and key areas;

[0032] Smart manhole covers are deployed at key points to monitor the health status and surrounding environment of the manhole covers at key points in real time, and the monitoring frequency and sensitivity are automatically adjusted according to traffic flow and pedestrian flow to achieve key point control of the manhole covers;

[0033] Smart manhole covers are deployed on critical paths, the health status of manhole covers on critical paths is collected and analyzed, and the health status characteristics of manhole covers on critical paths are summarized to predict the defects of ordinary manhole covers on the entire route and realize critical path control of manhole covers;

[0034] Smart manhole covers are deployed in key areas, and the manhole cover operating space is divided into pedestrian and vehicle areas. The patterns and causes of manhole cover defects in areas with dense pedestrian and vehicle flow are analyzed. Based on the characteristics of manhole cover defects in key areas, the monitoring frequency and inspection efforts are increased in a targeted manner to achieve spatial regional control of manhole covers.

[0035] Preferably, the key points include intersections with heavy traffic and large passenger flow, and the vicinity of subway stations; the key paths include main roads or important passages of urban traffic; the key areas include areas with large passenger flow during the day, areas with large passenger flow during peak hours in the morning and evening, and areas with dense traffic.

[0036] Preferably, the establishment of a time-based and stage-based management and control plan for the service life of manhole covers to control and optimize multi-source defects of manhole covers over multiple time periods includes:

[0037] Choose different time periods: day / week, month / season;

[0038] Morning and evening peak traffic disease control: Analyze the impact of daily / weekly morning and evening traffic peaks on manhole covers, determine the category characteristics and causes of manhole cover diseases during morning and evening peaks, and control the health status of manhole covers based on the disease characteristics caused by daily traffic peaks;

[0039] Tidal traffic disease control: Based on daily / weekly traffic data, identify the direction and time period of tidal traffic, analyze the impact of daily / weekly tidal traffic on manhole covers, determine the category characteristics and causes of tidal traffic manhole cover diseases during the peak period of tidal traffic, and control the health status of manhole covers based on the disease characteristics caused by tidal traffic;

[0040] Seasonal disease control: According to seasonal changes and climate characteristics, analyze the impact of monthly / quarterly seasonal changes and climate characteristics on manhole covers, determine the category characteristics and causes of manhole cover diseases every month / quarter, and control the health status of manhole covers based on the disease characteristics caused by seasonal changes and climate characteristics.

[0041] The second aspect of the present invention provides a city manhole cover health status advanced control system for the above method, comprising:

[0042] A manhole cover multi-source disease classification layer, wherein the manhole cover multi-source disease classification layer classifies multi-source diseases of urban manhole covers;

[0043] An intelligent recognition layer, which intelligently recognizes multi-source diseases of urban manhole covers, determines whether the manhole covers are damaged and the type and degree of the damage;

[0044] The data analysis layer performs data analysis on the manhole cover data obtained by the intelligent recognition layer, analyzes the spatial and temporal characteristics of various manhole cover diseases, and obtains the occurrence patterns of manhole cover diseases in different spatial scenes and different time periods;

[0045] The space-time control layer conducts advanced control over the health status of manhole covers, establishes a spatial control plan for the service life of manhole covers and a time- and stage-by-stage control plan for the service life of manhole covers, conducts regional spatial control and optimization of multi-source diseases of manhole covers, and conducts time control and optimization over multiple time periods.

[0046] Preferably, the smart identification layer includes:

[0047] A manhole cover image intelligent collection and recognition system, which collects manhole cover images in actual scenes and determines whether the manhole cover has Class I disease among multi-source diseases based on the collected manhole cover image data. Class I diseases include eight types of diseases: missing, disordered, displaced, damaged, damaged around the well, bulge, height difference, and subsidence of the manhole cover. At the same time, the degree of some or all of the Class I diseases of the manhole cover is determined based on the binary image method;

[0048] A dynamic identification system for collecting and identifying the vibration of a manhole cover collects the vibration of the manhole cover and determines whether the manhole cover has a Class II disease among multi-source diseases based on the collected manhole cover vibration data. Class II diseases include vibration diseases of the manhole cover. At the same time, the degree of the Class II disease of the manhole cover is determined by the size of the manhole cover vibration frequency.

[0049] Preferably, the manhole cover image intelligent acquisition and recognition system uses image acquisition equipment installed at key positions to capture images of the manhole cover from multiple angles, such as the front view and the side view; at the same time, the manhole cover image data is recognized with the help of the manhole cover disease recognition model;

[0050] Preferably, the manhole cover vibration collection dynamic identification system uses vibration sensors arranged on the manhole cover in the direction of vehicle flow, and the vibration sensors collect the vibration frequency of the manhole cover.

[0051] Preferably, the space-time control layer includes a space control system and a time control system, wherein:

[0052] The spatial control system includes a key point control unit, a key path control unit and a key area control unit. The key point control unit monitors the state of the manhole cover at the key point in real time, and automatically adjusts the monitoring frequency and sensitivity according to the traffic flow and the flow of people, so as to realize the key point control of the manhole cover. The key path control unit predicts the disease of ordinary manhole covers on the key path, so as to realize the key path control of the manhole cover. The key area control unit analyzes the law and cause of the manhole cover disease in the area with dense human and vehicle flow, and increases the monitoring frequency and inspection intensity in a targeted manner based on the characteristics of the manhole cover disease in the key area, so as to realize the spatial regional control of the manhole cover.

[0053] The time control system determines the category characteristics and causes of manhole cover diseases during peak hours in the morning and evening, and based on the characteristics of the diseases, carries out targeted control of manhole cover diseases, identifies the direction and time period of tidal traffic, and at the same time strengthens real-time monitoring and early warning of manhole covers in specific directions during peak tidal traffic periods, as well as analyzes the category characteristics and causes of manhole cover diseases on a monthly / quarterly basis, and based on the characteristics of the diseases, formulates manhole cover disease control plans within different time periods, and carries out seasonal maintenance and management of manhole covers.

[0054] The beneficial effects of the present invention relative to the prior art are:

[0055] (1) The method provided by the present invention can realize the accurate identification of multi-source diseases of manhole covers and the evolution of damage degree. It can accurately control the health status of manhole covers according to the occurrence law of manhole cover diseases in the area with the goal of increasing the life of manhole covers and extending the health status of manhole covers, actively carry out predictive maintenance, reduce the frequency of disease occurrence from the source, and minimize the impact of manhole cover diseases on urban operations.

[0056] (2) The method provided by the present invention establishes a classification system for multi-source diseases of manhole covers. According to the characteristics of the occurrence and existence of nine kinds of diseases of manhole covers, they are divided into Class I diseases and Class II diseases, so as to facilitate the targeted collection of manhole cover data.

[0057] (3) The method provided by the present invention performs data analysis on manhole cover data, analyzes the spatial and temporal characteristics of various types of manhole cover diseases, finds the occurrence patterns of manhole cover diseases in different spatial scenes and different time periods, and establishes a manhole cover multi-source disease database.

[0058] (4) The method provided by the present invention conducts proactive control of the health status of manhole covers based on the occurrence patterns of manhole cover diseases in different spatial scenarios, establishes a spatial control plan for the service life of manhole covers (a spatial control system for multi-source diseases of manhole covers), establishes an inspection plan for key points, key paths and key areas, and proposes the layout principle of key points, key paths and key areas of smart manhole covers, so as to conduct regional spatial control and optimization of multi-source diseases of manhole covers.

[0059] (5) The method provided by the present invention conducts advance control of the health status of manhole covers based on the occurrence patterns of manhole cover diseases in different time periods, establishes a time-based and stage-based control plan for the service life of manhole covers (a time control system for multi-source diseases of manhole covers), and proposes key control principles for manhole covers in different time periods, thereby achieving short-term (morning and evening peak hours) - tidal pedestrian and vehicle traffic (tidal phenomena are formed by upward and downward movement due to urban planning) - seasonal (different damage modes in spring, summer, autumn and winter) disease control, and performing time control and optimization of multi-source diseases of manhole covers in multiple time periods.

[0060] It should be understood that the contents described in the Summary of the Invention section are not intended to limit the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easy to understand through the following description. In addition, the implementation of any embodiment of the present invention does not mean that multiple or all of the above-mentioned beneficial effects must be possessed or achieved at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] In order to more clearly illustrate the implementation methods of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for the implementation methods or the description of the prior art. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other implementation drawings can be derived from the provided drawings without creative work.

[0062] The structures, proportions, sizes, etc. illustrated in this specification are only used to match the contents disclosed in the specification so as to facilitate understanding and reading by persons familiar with the technology. They are not used to limit the conditions under which the present invention can be implemented, and therefore have no substantial technical significance. Any structural modification, change in proportion or adjustment in size shall still fall within the scope of the technical contents disclosed in the present invention without affecting the effects and purposes that can be achieved by the present invention.

[0063] Figure 1 A schematic diagram of the process of intelligently identifying multi-source diseases of urban manhole covers and preemptively controlling the health status according to some embodiments of the present invention is shown;

[0064] Figure 2 A schematic diagram of the overall framework structure of a method for intelligently identifying multi-source diseases of urban manhole covers and advanced health status control according to some embodiments of the present invention is shown;

[0065] Figure 3 A schematic diagram of collecting manhole cover vibration data according to some embodiments of the present invention is shown;

[0066] Figure 4 A schematic diagram of manhole cover vibration frequency analysis according to some embodiments of the present invention is shown;

[0067] Figure 5 A schematic diagram of key point-key path-key area control according to some embodiments of the present invention is shown.

[0068] In the various drawings, the same or corresponding reference numerals represent the same or corresponding parts. DETAILED DESCRIPTION

[0069] In order to make the purpose, technical solution and advantages of the embodiments of the present invention more clearly understood, the embodiments of the present invention are further described in detail below in conjunction with the embodiments and drawings. Here, the illustrative embodiments of the present invention and their description are used to explain the present invention, but are not intended to limit the present invention.

[0070] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0071] It should be understood that the terms "include / comprise", "consist of..." or any other variations are intended to cover non-exclusive inclusion, so that a product, device, process or method that includes a series of elements includes not only those elements, but also may include other elements not explicitly listed when necessary, or also includes elements inherent to such product, device, process or method. In the absence of more restrictions, the elements defined by the sentence "include / comprise...", "consist of..." do not exclude the presence of other identical elements in the product, device, process or method that includes the elements.

[0072] It is also necessary to understand that terms such as "upper", "lower", "front", "back", "left", "right", "top", "bottom", "inside" and "outside" to indicate directions or positional relationships are based on the directions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the referred device, component or structure must have a specific direction, be constructed or operate in a specific direction, and should not be understood as a limitation on the present invention.

[0073] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0074] In view of the current problems such as difficulty in classifying and identifying multiple types of manhole cover diseases, low accuracy in identifying the degree of damage, low utilization rate of manhole cover disease data, and difficulty in summarizing the occurrence patterns of diseases to increase the service life of manhole covers and extend the health time of manhole covers, the current technical shortcomings are as follows:

[0075] 1) The classification of manhole cover defects relies more on manual experience and is greatly influenced by individual experience. The maintenance goal is to increase the life of the manhole cover and simplify the maintenance process, which leads to conservative maintenance and increases the replacement rate of manhole covers;

[0076] 2) Manual inspection is a range inspection, and it is difficult to trace the source of a manhole cover vertically and observe the vertical evolution and development of a single manhole cover disease;

[0077] 3) The manhole cover disease data has not been classified in a targeted manner to find the pattern of disease occurrence and conduct targeted control of the manhole cover health status.

[0078] Therefore, there is an urgent need to accurately identify various diseases of manhole covers, deeply explore manhole cover maintenance data, clarify the occurrence patterns and life models of manhole cover diseases, establish a maintenance data-driven model for precise maintenance of urban manhole covers, effectively improve the service life of manhole covers, and realize predictive maintenance of urban manhole covers, thereby reducing the frequency of disease occurrence from the source and effectively improving the safe operation level of urban manhole covers.

[0079] Based on this, the present invention believes that the control of manhole cover diseases should be carried out from two aspects: the first is to increase the service life of the manhole cover before the manhole cover disease occurs, based on the maintenance data of the manhole cover, find out the relationship between the manhole cover disease category and time and space from the data, find out the occurrence law of various types of manhole cover diseases, so as to perform accurate health status control; the second is the current mainstream direction, through real-time monitoring of the health status of the manhole cover, identifying manhole cover diseases through machine learning algorithms, and performing point-to-point repairs on the diseases.

[0080] To this end, the present invention provides a method and system for intelligently identifying multi-source diseases of urban manhole covers and proactively controlling their health status to solve the above-mentioned problems.

[0081] The implementation of the present invention is described in detail below in conjunction with preferred embodiments.

[0082] See also Figure 1 The flow chart shown provides a method for intelligent identification of multi-source diseases of urban manhole covers and proactive control of their health status, the method comprising: S10, establishing a classification system for multi-source diseases of manhole covers; S20, intelligently identifying multi-source diseases of manhole covers based on the classification system for multi-source diseases of manhole covers; S30, performing data analysis on the manhole cover data obtained through intelligent identification and establishing a manhole cover multi-source disease database; S40, proactively controlling the health status of manhole covers based on the occurrence patterns of manhole cover diseases in different spatial scenarios and in different time periods obtained through data analysis.

[0083] The following further combines Figure 2 The modular schematic diagram shown elaborates on the specific implementation of each link.

[0084] In the S10 stage, a classification system for multi-source diseases of manhole covers is first established.

[0085] According to relevant specifications, manhole cover defects can be divided into nine categories, namely: missing manhole cover (missing manhole cover and seat), disordered manhole cover (the manhole cover is upside down and there is no prescribed marking on the surface), displacement of the manhole cover (tilted, loose, deviated from the wellhead, warped, or flipped), damaged manhole cover (cracks, notches, holes, and deformations), damaged well perimeter (broken road surface and potholes within 1m from the edge), bulging manhole cover (the top surface of the manhole cover or seat is more than 10mm higher than the road surface around the well), height difference of the manhole cover (the height difference between the top surface of the manhole cover and the seat is more than 10mm), subsidence of the manhole cover (the inspection well has sunk relative to the ground, 15mm below the surface), and vibration of the manhole cover (the vibration sound is loud when a vehicle runs over the manhole cover, causing noise).

[0086] In some feasible embodiments, the present invention divides the above nine kinds of diseases of manhole covers into Class I diseases and Class II diseases according to the characteristics of the diseases. Class I diseases include eight kinds of diseases of manhole covers, namely, missing, disordered, displaced, damaged, damaged around the well, bulge, height difference and subsidence. Class II diseases include vibration diseases of manhole covers. With the goal of accurately detecting the categories and identifying the degree of damage of the above nine kinds of diseases, appropriate discrimination methods are selected for the nine kinds of diseases, which will be elaborated in detail later.

[0087] In the S20 stage, based on the established manhole cover multi-source disease classification system, multi-source diseases of manhole covers are intelligently identified.

[0088] This step first includes: S201, collecting basic information of the manhole cover to match the subsequent collected data with the basic information data of the manhole cover.

[0089] Specifically: through basic design, construction and acceptance data, obtain the basic information of the manhole cover, such as the name and number of the manhole cover, geographical location, time of commissioning, connectivity between the well chamber and other wells, so as to match the above basic information of the manhole cover with the subsequent collection data at the location of the manhole cover.

[0090] The S20 step also includes: S202, collecting the manhole cover image, and determining whether the manhole cover is damaged and the type and degree of the damage based on the manhole cover image data.

[0091] Specifically, the manhole cover image is collected, and based on the collected manhole cover image data, it is determined whether the manhole cover has Class I disease among multi-source diseases, and the degree of disease of some or all of the Class I diseases is further determined.

[0092] The eight types of Class I diseases, namely missing, disordered, displaced, damaged, damage around the well, bulge, height difference, and subsidence, are determined based on the high efficiency of disease image recognition. The machine learning target detection technology is used to develop the manhole cover disease image recognition algorithm (Yolo, RetinaNet, Faster R-CNN, Cascade R-CNN) through machine image recognition to achieve accurate determination of the eight types of manhole cover diseases. In terms of detecting the degree of the eight types of manhole cover diseases, the characteristics of manhole cover diseases are fully considered. The three types of manhole cover diseases, namely missing, disordered, and displaced, do not need to determine the degree of the disease. It is believed that the five types of diseases, namely, manhole cover damage, damage around the well, bulge, height difference, and subsidence, need to determine the degree of manhole cover damage.

[0093] In some specific embodiments, in order to determine the damage of the manhole cover, the present invention can use a binary image method to convert the pictures collected on site into grayscale images, determine the degree of damage to the manhole cover and the surrounding area, trace the degree of damage evolution of the manhole cover, and formulate targeted maintenance plans. In this way, a manhole cover image intelligent collection and recognition system is formed.

[0094] The S20 step also includes: S203, collecting the vibration sound of the manhole cover and determining whether the manhole cover is damaged and the type and degree of the damage based on the manhole cover vibration data.

[0095] Specifically: collect the vibration data of the manhole cover and determine whether the manhole cover has Class II disease among multi-source diseases based on the collected manhole cover vibration data. Class II disease includes the vibration disease of the manhole cover, and further determine the degree of Class II disease.

[0096] With regard to the manhole cover rattling disease, the present invention fully considers the limitations of image detection. Two-dimensional images cannot accurately determine spatial problems. In view of the fact that rattling disease will cause abnormal noises in the manhole cover when vehicles and people pass by, the rattling frequency is used to determine whether the manhole cover has rattling disease, and the severity of the manhole cover disease is determined by the magnitude of the manhole cover rattling frequency. In this way, a dynamic identification system for manhole cover rattling disease is formed.

[0097] In some specific embodiments, Figure 3 As shown, vibration sensors are arranged on the manhole cover according to the direction of vehicle flow. The figure shows the position of a vibration sensor, and the vibration sensor collects the vibration frequency of the manhole cover respectively;

[0098] like Figure 4 As shown, the vibration frequency collected by the vibration sensor is used to determine whether the manhole cover has Class II disease based on the trend characteristics of the vibration frequency, and the severity of the Class II disease in the manhole cover is determined by the peak value of the vibration frequency.

[0099] In the S30 stage, data analysis is performed on the manhole cover data obtained by intelligent identification to establish a manhole cover multi-source disease database.

[0100] This link can be implemented in two aspects, space and time, according to the types and characteristics of various manhole covers, including:

[0101] S301, perform spatial characteristic analysis of manhole cover diseases, analyze the spatial characteristics of various manhole cover diseases, and obtain the occurrence rules of manhole cover diseases in different spatial scenes;

[0102] Specifically, nine types of defects are classified, including missing manhole cover (missing manhole cover and seat), disordered manhole cover (the manhole cover is upside down and there is no prescribed marking on the surface), displaced manhole cover (tilted, loose, deviated from the wellhead, warped, and flipped), damaged manhole cover (cracks, notches, holes, and deformations), damaged around the well (broken road surface and potholes within 1m outside the edge), bulged manhole cover (the top surface of the manhole cover or the well seat is more than 10 mm higher than the road surface around the well), height difference of the manhole cover (the height difference between the top surface of the manhole cover and the well seat is more than 10 mm), subsidence of the manhole cover (the inspection well sinks relative to the ground, 15 mm below the surface), and vibration of the manhole cover (the vibration sound is loud when a vehicle runs over the manhole cover, causing noise). The scenarios in which various manhole cover defects occur are analyzed, such as main roads, traffic intersections, parking lots, and office buildings, etc., the spatial characteristics of various manhole cover defects are summarized, and the occurrence patterns of various manhole cover defects in different spatial scenarios are found.

[0103] S302, analyzing the time characteristics of manhole cover diseases, analyzing the time characteristics of various manhole cover diseases, and obtaining the occurrence patterns of manhole cover diseases in different time periods;

[0104] Specifically, the occurrence time of various manhole cover diseases is analyzed, the occurrence characteristics of various diseases in different time periods (such as morning and evening peak hours, holidays and weekdays, different months and different seasons, etc.) are analyzed, and the high-frequency occurrence patterns of various manhole cover diseases in different time periods are summarized.

[0105] Finally, in the S40 stage, based on the occurrence patterns of manhole cover diseases in different spatial scenarios and in different time periods obtained through data analysis, the health status of manhole covers is proactively controlled.

[0106] The accurate control of manhole cover life needs to be achieved on the basis of accurate identification of the types of manhole cover multi-source diseases and the degree of damage. Therefore, after accurately exploring the various characteristics of manhole cover diseases, in order to control the health status of manhole covers to increase the operating life of manhole covers, it is planned to achieve spatial layout optimization of urban manhole covers and multi-cycle and multi-frequency time control through two levels of spatial disease control and temporal disease control, so as to improve the control of the operating status of manhole covers and realize refined management of manhole covers. Specifically including:

[0107] S401, establish a spatial management and control plan for the service life of manhole covers, and conduct regional spatial control and optimization of multi-source diseases of manhole covers;

[0108] In view of the problem that the inspection cycle range of urban manhole covers is fixed, resulting in discrete, inefficient and unfocused control of manhole covers, the present invention establishes a spatial management and control plan for the service life of manhole covers, proposes key inspection and control areas, increases the inspection frequency, and deploys high-standard bearing-capacity manhole covers in areas with high risk of disease occurrence in view of the differences in the life of manhole covers in different areas, and increases the frequency of health status collection and inspection during the maintenance stage.

[0109] (1) First, establish a key point-key path-key area spatial inspection plan, analyze the high-frequency points of manhole cover diseases through the category and location data of manhole cover diseases, connect the high-frequency points into lines, and thus form a mesh area. Establish the key inspection path through the frequency analysis of manhole cover diseases to achieve local regional control;

[0110] In an embodiment of the present invention, key points include intersections with heavy traffic and large passenger flow, and the vicinity of subway stations; key paths include main roads or important channels of urban traffic; key areas include areas with large passenger flow during the day, areas with large passenger flow during peak hours in the morning and evening, and areas with dense traffic. For example, the area near the subway is an area with large passenger flow during peak hours in the morning and evening, and the surrounding areas of Beijing's second, third, and fourth ring roads are dense traffic areas. Places such as Zhongguancun, where there are many office buildings, have large passenger flow during the day, and so on.

[0111] (2) Then, based on the key point-key path-key area division characteristics, smart manhole covers with the function of real-time monitoring of the health status of the manhole cover and the surrounding environment are deployed at the key points of manhole cover disease control to monitor the status of the manhole cover at the key points in real time, and automatically adjust the monitoring frequency and sensitivity according to the traffic flow and pedestrian flow, so as to realize the key point control of the manhole cover;

[0112] like Figure 5 As shown, Figure 5 It shows that smart manhole covers can be deployed based on the laws of disease occurrence at different points, paths, and areas. They can be deployed in areas with high disease frequency. Figure 5 Targeted key point arrangements are adopted for cross-shaped, Y-shaped, L-shaped, T-shaped and other paths, so as to realize the control of key points, paths and areas. At the same time, the occurrence pattern of disease types can be determined during the inspection process to realize targeted maintenance of manhole cover diseases.

[0113] (3) Based on the characteristics of traffic roads, smart manhole covers are deployed on critical paths, at road intersections and at the end of the road. By deploying smart manhole covers at both ends and in the middle of the road and analyzing the development trend of manhole cover defects, the defects of ordinary manhole covers on the entire route can be predicted, thereby achieving critical path control of manhole covers;

[0114] In realizing the critical path control of manhole covers, it can be linked with the traffic management system. By sharing traffic data in real time and based on road traffic flow data, manhole covers with different load-bearing standards can be deployed in sections and areas with high traffic volume and high risk of manhole cover diseases. At the same time, the frequency of inspections and health status monitoring can be increased to enhance the resistance of manhole covers.

[0115] (4) Based on the characteristics of the manhole cover layout, the manhole cover operation space is divided into a pedestrian area and a vehicle area. The characteristics of the manhole cover operation areas of pedestrian and vehicle traffic are distinguished. The law of manhole cover damage in areas with high density of pedestrian and vehicle traffic is identified. The causes of the damage to the manhole covers are analyzed. The impact of related factors such as pedestrian density and vehicle speed on the manhole covers is analyzed. Targeted reinforcement of the manhole covers is carried out according to the causes of the damage, thereby achieving key area control of the manhole covers.

[0116] S402, establish a time-based and phased management and control plan for the service life of manhole covers, and conduct multi-time period time control and optimization of multi-source diseases of manhole covers.

[0117] In order to solve the problem that the inspection cycle of manhole covers is fixed, resulting in uneven and unstable inspection work, the present invention establishes a time- and stage-by-stage management and control plan for the service life of manhole covers, and establishes a multi-factor and multi-scenario manhole cover life model to achieve early maintenance and proactive maintenance. Predictive maintenance measures are taken in advance when there is a trend of disease occurrence, and proactive maintenance is achieved before the disease occurs.

[0118] (1) First, select different time periods: day / week, month / season;

[0119] (2) Morning and evening peak traffic disease control: Analyze the impact of the daily / weekly morning and evening traffic peaks on manhole covers, determine the category characteristics and causes of manhole cover diseases during the morning and evening peaks, and control the health status of manhole covers based on the disease characteristics caused by the daily traffic peak;

[0120] (3) Tidal traffic hazard control: Based on the characteristics of urban planning distribution, for example, Beijing's urban planning causes tidal phenomena during peak hours in the morning and evening. In the morning, the traffic and pedestrian flow from north to south is denser, while in the evening, the traffic flow from south to north is denser. Therefore, the probability of the occurrence of hazards in the upstream and downstream areas of the traffic road is different on the same day. Analyze the daily / weekly traffic data, identify the direction and time period of tidal traffic, and strengthen real-time monitoring and early warning of manhole covers in specific directions during the peak period of tidal traffic.

[0121] (4) Seasonal disease control: Based on seasonal changes and climate characteristics, analyze the types, characteristics and causes of manhole cover diseases in each month / quarter, identify the weather (manhole cover floating and missing diseases are more likely to occur during the rainy season in July and August), population density (Beijing's floating population decreased in the first quarter, the number of diseases decreased, and the inspection frequency can be appropriately reduced), and temperature changes (temperature changes in spring, summer, autumn and winter, seasonal changes in thermal expansion and contraction cause cracks around the wells, such as cracks around the wells are more likely to occur in winter, and the well ring is more likely to be squeezed and damaged and the manhole cover is damaged in summer). Based on the characteristics of the diseases, formulate manhole cover disease control plans for different time periods and carry out seasonal maintenance and management of manhole covers.

[0122] Continue to see Figure 2 As shown, a modular schematic diagram of a city manhole cover health status advanced control system for executing and realizing the above method is shown. The system includes: a manhole cover multi-source disease classification layer, an intelligent identification layer, a data analysis layer, and a spatiotemporal control layer.

[0123] Manhole cover multi-source disease classification layer:

[0124] The classification layer of multi-source diseases of manhole covers classifies multi-source diseases of urban manhole covers, and classifies them into nine types of diseases: missing manhole cover (missing manhole cover and seat), disordered manhole cover (manhole cover is upside down, and there is no prescribed mark on the surface), displacement of manhole cover (tilted, loose, deviated from the wellhead, lame, flipped), damaged manhole cover (cracks, notches, holes, deformation), damaged around the well (cracks and potholes on the road surface within 1m outside the edge), raised manhole cover (the top surface of the manhole cover or the well seat is more than 10 mm higher than the road surface around the well), height difference of manhole cover (the height difference of the top surface of the manhole cover relative to the well seat is more than 1 0mm), manhole cover subsidence (the inspection well sinks relative to the ground, 15mm below the surface), and manhole cover vibration (the vibration sound is loud when the vehicle rolls over the manhole cover, causing noise) are divided into Class I and Class II diseases. Class I diseases include eight types of manhole cover defects: missing, disordered, displaced, damaged, damage around the well, bulge, height difference, and subsidence; Class II diseases include manhole cover vibration diseases. The purpose is to facilitate targeted and accurate detection of the types and damage degrees of the nine types of diseases, and to select appropriate discrimination methods for the nine types of diseases.

[0125] Smart recognition layer:

[0126] The intelligent recognition layer intelligently identifies multi-source defects of urban manhole covers, including the use of image acquisition, spatial inspection, image classification and recognition technologies to determine whether the manhole cover has defects and the type and degree of the defects.

[0127] In some feasible embodiments, the intelligent recognition layer includes: a manhole cover image intelligent collection and recognition system, and a manhole cover vibration collection and dynamic recognition system.

[0128] The intelligent acquisition and recognition system for manhole cover images captures images of manhole covers and their surroundings in real time, and performs two aspects of recognition, namely, classification and degree of disease recognition. On the one hand, based on the collected manhole cover image data, it determines whether the manhole cover has Class I disease among multi-source diseases. Class I diseases include eight types of diseases: missing, disordered, displaced, damaged, damaged around the well, bulge, height difference, and subsidence. The intelligent acquisition and recognition system for manhole cover images specifically uses image acquisition equipment (such as high-definition cameras) installed in key positions to capture images of the manhole cover from multiple angles, such as front and side views; then, the system uses image processing technology, such as edge detection and feature extraction, to pre-process and analyze the images. Through image segmentation, noise reduction, enhancement and other steps, the system can identify the missing, disordered, displaced, damaged and other diseases of the manhole cover, and mark and classify them.

[0129] On the other hand, the manhole cover image intelligent collection and recognition system is based on the binary image method and combines image processing technologies such as crack binary image and grayscale image to determine the degree of damage of some or all of the Class I manhole cover diseases. Specifically, it can accurately identify the degree of damage to the manhole cover and the surrounding area, and conduct a quantitative assessment of the degree of manhole cover damage.

[0130] The manhole cover vibration collection dynamic identification system is used to detect the sound signals generated by the manhole cover due to vehicle rolling or ground vibration. The manhole cover vibration collection dynamic identification system also performs two aspects of identification, namely, disease classification and vibration degree identification. On the one hand, the manhole cover vibration is collected and based on the collected manhole cover vibration data, it is determined whether the manhole cover has a Class II disease among the multi-source diseases. Class II diseases include vibration diseases of the manhole cover. On the other hand, the degree of the Class II disease of the manhole cover is determined by the magnitude of the manhole cover vibration frequency. Specifically, whether the manhole cover has a Class II disease is determined by the trend characteristics of the vibration frequency, and the severity of the Class II disease of the manhole cover is determined by the peak value of the vibration frequency.

[0131] The dynamic identification system for collecting vibrations of manhole covers contains three types of sensors: 1) Acceleration sensor: used to measure the acceleration changes of the manhole cover and its surrounding environment, so as to sense the intensity and frequency of vibration. 2) Sound sensor: used to collect the sound signal of the vibration of the manhole cover and convert it into an electrical signal for processing. 3) Vibration sensor: directly installed on the manhole cover, it can monitor the vibration of the manhole cover in real time and output the corresponding electrical signal. The data collected by these sensors are transmitted to the analysis module of the system after signal amplification, filtering, digitization and other processing steps. The analysis module uses advanced signal processing technology (such as spectrum analysis, time-frequency analysis, etc.) to analyze the signal to identify whether the manhole cover has abnormal vibrations and the corresponding vibration diseases.

[0132] Data analysis layer:

[0133] The data analysis layer analyzes the manhole cover data obtained by the intelligent recognition layer, analyzes the spatial and temporal characteristics of various manhole cover diseases, obtains the occurrence patterns of manhole cover diseases in different spatial scenarios and different time periods, and lays a foundation for manhole cover health life control measures;

[0134] The data analysis layer mainly serves as data support for the subsequent spatiotemporal control layer. Based on the manhole cover disease data obtained by the intelligent identification layer, it conducts statistical analysis on the time and space of the occurrence of manhole cover diseases, finds the temporal and spatial laws of the occurrence of various manhole cover diseases, and counts the frequency of occurrence of various manhole cover diseases (missing, disordered, displaced, damaged, damaged around the well, bulge, height difference, subsidence, vibration) in different spaces (main roads, traffic intersections, parking lots and office buildings, etc.) and in different time periods (morning and evening rush hours within 24 hours a day, holidays and working days within a week, different seasons of spring, summer, autumn and winter, etc.). It analyzes the characteristics of various manhole cover diseases in different time and space, and lays the foundation for the subsequent spatiotemporal control layer to establish targeted control measures for various manhole cover diseases.

[0135] Space-time control layer:

[0136] The space-time control layer conducts proactive control of the health status of manhole covers based on the identification results and actual conditions, establishes a spatial control plan for the service life of manhole covers and a time- and phase-based control plan for the service life of manhole covers, conducts regional spatial control and optimization of multi-source diseases of manhole covers, and performs time control and optimization for multiple time periods.

[0137] In the advanced control system of the health status of urban manhole covers, the time-space control layer plays a vital role. It implements targeted time-space control strategies based on the data and analysis results provided by the intelligent recognition layer and the data analysis layer. It is divided into two aspects: space control and time control.

[0138] For the spatial disease control system, in the construction of smart cities, the spatial control of smart manhole covers is a key link to ensure the safe and efficient operation of urban infrastructure, including key point control, key path control and key area control.

[0139] Key point control is achieved by real-time monitoring of the status of manhole covers at key points, and automatically adjusting the monitoring frequency and sensitivity according to traffic flow and pedestrian flow. By deploying smart manhole covers at key points, smart manhole covers need to be deployed at key points with heavy traffic and large pedestrian flow, such as intersections and near subway stations. These manhole covers not only have the function of real-time monitoring of the status of manhole covers, but also can automatically adjust the monitoring frequency and sensitivity according to traffic flow and pedestrian flow. Once an abnormality is detected, such as displacement or damage of the manhole cover, the system will immediately issue an alarm and automatically transmit the information to the management center for rapid response and processing.

[0140] Critical path control achieves critical path control of manhole covers by predicting the defects of ordinary manhole covers on critical paths. Critical paths are usually the main roads or important channels of urban traffic, and the status of the manhole covers on them directly affects the safety and smoothness of the roads. Smart manhole covers are also deployed on critical paths. By deploying smart manhole covers at both ends and in the middle of the road, the development trend of manhole cover defects can be analyzed. In addition to deploying smart manhole covers for real-time monitoring, it can also be linked with the traffic management system. By sharing traffic data in real time and based on road traffic flow data, manhole covers with different load-bearing standards are deployed on sections and areas with high traffic volume and high risk of manhole cover defects, and the frequency of inspections and health status monitoring is increased to enhance the resistance of manhole covers.

[0141] Key area control analyzes the patterns and causes of manhole cover defects in areas with dense pedestrian and vehicle traffic, and increases the monitoring frequency and inspection intensity based on the characteristics of manhole cover defects in key areas to achieve spatial regional control of manhole covers. Key area control also uses smart manhole covers, which are deployed in key areas. Smart manhole covers need to be densely deployed on paths and points in key areas to achieve more accurate perception of key areas.

[0142] The time disease control system includes two aspects: daily / weekly disease control and monthly / quarterly disease control. Daily / weekly disease control includes morning and evening peak disease control and tidal traffic flow disease control.

[0143] First, morning and evening peak disease control: The system analyzes historical traffic data to identify the morning and evening peak hours, determine the category characteristics and causes of manhole cover diseases during the morning and evening peak hours, and conduct targeted manhole cover disease control based on the characteristics of the diseases. During these periods, strengthen real-time monitoring and early warning of manhole covers to ensure that the manhole covers remain stable and safe under increased traffic pressure. Through linkage with traffic management departments, based on road traffic flow data, manhole covers of different load-bearing standards are deployed in sections and areas with high traffic volume and high risk of manhole cover diseases, reducing traffic congestion and safety hazards caused by manhole cover problems.

[0144] Second, tidal traffic disease control: According to the characteristics of urban planning distribution, the system analyzes traffic data to identify the direction and time period of tidal traffic. During the peak period of tidal traffic, strengthen the real-time monitoring and early warning of manhole covers in specific directions to ensure that these manhole covers can withstand greater traffic pressure. At the same time, based on the actual situation of tidal traffic, arrange inspections and health status monitoring of manhole covers on corresponding roads to achieve effective monitoring of the health status of manhole covers.

[0145] Third, seasonal disease control: According to seasonal changes and climate characteristics, analyze the category characteristics and causes of manhole cover diseases every month / quarter, and formulate manhole cover disease control plans in different time periods based on the characteristics of the diseases, and perform seasonal maintenance and management of manhole covers. For example, strengthen the inspection of the drainage function of manhole covers before the rainy season to prevent manhole cover diseases caused by water accumulation; increase the inspection of manhole cover antifreeze measures in cold seasons to ensure that the manhole covers will not be damaged by ice. At the same time, the system will adjust the monitoring frequency and warning threshold according to seasonal changes to adapt to the changing characteristics of manhole cover diseases in different seasons.

[0146] In short, daily / weekly disease control (tidal traffic disease control) is mainly based on the location of manhole covers during the morning and evening rush hours. Due to the characteristics of the city, it will cause tidal traffic. Taking Beijing as an example, the morning rush hour is more from north to south, and the evening rush hour is more from south to north. Therefore, the imbalance of two-way traffic in the morning and evening rush hours will cause the probability of manhole cover damage in the morning rush hour from north to south. Therefore, it is necessary to focus on the control of manhole covers distributed on the upward traffic routes before and after the morning rush hour. Similarly, before and after the evening rush hour, focus on disease control of manhole covers distributed on the downward traffic routes.

[0147] The monthly / quarterly disease control unit is based on the disease occurrence data of each month and quarter, the seasonal characteristics of manhole cover diseases and the different characteristics of diseases in each month. For example, the disease characteristics of manhole covers are different in spring, summer, autumn and winter. They are prone to sinking and bulging in winter and spring, and prone to damage in summer and autumn, etc. Control is strengthened every month (such as important months such as the Spring Festival in January and February, the Mid-Autumn Festival and National Day in September and October), and the control frequency can be reduced on Saturdays and Sundays when there are fewer people near the CBD of office buildings, etc.

[0148] The above control measures are aimed at reducing the probability of manhole cover damage, reducing the cost of manhole cover maintenance and saving human resources, ensuring the safe and stable operation of urban infrastructure, and providing citizens with a safer and more convenient travel environment.

[0149] The embodiments of the present invention have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments.

[0150] Although several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of the present invention. Certain features described in the context of separate embodiments may also be implemented in a single implementation in combination. On the contrary, the various features described in the context of a single implementation may also be implemented in multiple implementations individually or in any suitable sub-combination.

Claims

1. A method for intelligently identifying multi-source diseases of urban manhole covers and preemptively controlling health status, characterized in that: The method includes: Establish a classification system for multi-source diseases of manhole covers; Based on the classification system of multi-source diseases of manhole covers, multi-source diseases of manhole covers are intelligently identified, including: Collect basic information of manhole covers to match subsequent collected data with the basic information data of manhole covers; Collect manhole cover images, and determine whether the manhole cover is damaged and the type and degree of damage based on the manhole cover image data; Collect the vibration sound of the manhole cover, and determine whether the manhole cover is damaged and the type and degree of damage based on the vibration data; Analyze the manhole cover data obtained by intelligent identification and establish a multi-source disease database for manhole covers, including: Conduct spatial characteristic analysis of manhole cover diseases to obtain the occurrence patterns of manhole cover diseases in different spatial scenarios; Conduct time characteristic analysis on manhole cover diseases to obtain the occurrence patterns of manhole cover diseases in different time periods; Based on the occurrence patterns of manhole cover diseases in different spatial scenarios and time periods, the health status of manhole covers is controlled in advance, including: Establish a spatial management and control plan for the service life of manhole covers, and conduct regional spatial control and optimization of multi-source diseases of manhole covers, further including: establishing a key point-key path-key area spatial inspection plan; deploying smart manhole covers at key points to monitor the health status and surrounding environment of manhole covers at key points in real time, and automatically adjust the monitoring frequency and sensitivity according to traffic flow and pedestrian flow to achieve key point control of manhole covers; deploying smart manhole covers on key paths, collecting and analyzing the health status of manhole covers on key paths, and summarizing the health status characteristics of manhole covers on key paths to predict the diseases of ordinary manhole covers on the entire route and achieve critical path control of manhole covers; deploying smart manhole covers in key areas, and dividing the manhole cover operation space into pedestrian flow areas and vehicle flow areas, analyzing the laws and causes of manhole cover diseases in areas with dense pedestrian and vehicle flow, and targetedly increasing the monitoring frequency and inspection intensity based on the characteristics of manhole cover diseases in key areas to achieve spatial regional control of manhole covers; Establish a time- and phase-based management and control plan for the service life of manhole covers, and conduct multi-time period time control and optimization of multi-source diseases of manhole covers.

2. The method according to claim 1, characterized in that The collecting of manhole cover images and determining whether the manhole cover is damaged and the type and degree of the damage based on the manhole cover image data are specifically as follows: The manhole cover image is collected, and based on the collected manhole cover image data, it is determined whether the manhole cover has Class I disease among multi-source diseases. Class I diseases include eight types of diseases: missing, disordered, displaced, damaged, damaged around the well, bulge, height difference, and subsidence of the manhole cover. The degree of damage of some or all of the Class I diseases can be further determined.

3. The method according to claim 2, characterized in that The manhole cover image is collected, and based on the collected manhole cover image data, it is determined whether the manhole cover has Class I disease among the multi-source diseases. Class I diseases include eight types of diseases: missing, disordered, displaced, damaged, damaged around the well, bulge, height difference, and subsidence of the manhole cover. The degree of disease of some or all of the diseases in Class I is further determined, including: Use image acquisition equipment to capture image data of the manhole cover and its surrounding environment in real time; A manhole cover disease recognition model was established to identify manhole cover image data and accurately determine eight types of manhole cover disease in Class I. The binary image method is used to convert the pictures collected on site into grayscale images to determine the severity of the two types of damage, namely, damage to the manhole cover and damage around the well, which are Class I damages.

4. The method according to claim 1, characterized in that: The collecting of the manhole cover vibration data and determining whether the manhole cover is damaged and the type and degree of the damage based on the manhole cover vibration data are specifically as follows: The vibration sound of the manhole cover is collected, and based on the collected manhole cover vibration data, it is determined whether the manhole cover has Class II disease among multi-source diseases, Class II disease includes the vibration disease of the manhole cover, and the degree of the Class II disease is further determined.

5. The method according to claim 4, characterized in that The collecting of the manhole cover vibration data and determining whether the manhole cover has a Class II disease among the multi-source diseases based on the collected manhole cover vibration data, the Class II disease includes the manhole cover vibration disease, and further determining the degree of the Class II disease, including: Arrange vibration sensors on the manhole cover in the direction of vehicle flow, and use the vibration sensors to collect the vibration frequency of the manhole cover; The vibration frequency of the manhole cover is collected by the vibration sensor, and the trend characteristics of the vibration frequency are used to determine whether the manhole cover has Class II disease, and the peak value of the vibration frequency is used to determine the severity of the Class II disease of the manhole cover.

6. The method according to claim 1, characterized in that The key points include intersections with heavy traffic and large passenger flow, and areas near subway stations; the key paths include main roads or important channels of urban traffic; the key areas include areas with large passenger flow during the day, areas with large passenger flow during peak hours in the morning and evening, and areas with dense traffic.

7. The method according to claim 1, characterized in that The establishment of a time-based and stage-based management and control plan for the service life of manhole covers to control and optimize multi-source defects of manhole covers over multiple time periods includes: Choose different time periods: day / week, month / season; Morning and evening peak traffic disease control: Analyze the impact of daily / weekly morning and evening traffic peaks on manhole covers, determine the category characteristics and causes of manhole cover diseases during morning and evening peaks, and control the health status of manhole covers based on the disease characteristics caused by daily traffic peaks; Tidal traffic disease control: Based on daily / weekly traffic data, identify the direction and time period of tidal traffic, analyze the impact of daily / weekly tidal traffic on manhole covers, determine the category characteristics and causes of tidal traffic manhole cover diseases during the peak period of tidal traffic, and control the health status of manhole covers based on the disease characteristics caused by tidal traffic; Seasonal disease control: According to seasonal changes and climate characteristics, analyze the impact of monthly / quarterly seasonal changes and climate characteristics on manhole covers, determine the category characteristics and causes of manhole cover diseases every month / quarter, and control the health status of manhole covers based on the disease characteristics caused by seasonal changes and climate characteristics.

8. An advanced control system for the health status of urban manhole covers used in the method according to any one of claims 1 to 7, characterized in that: include: A manhole cover multi-source disease classification layer, wherein the manhole cover multi-source disease classification layer classifies multi-source diseases of urban manhole covers; An intelligent recognition layer, which intelligently recognizes multi-source diseases of urban manhole covers, determines whether the manhole covers are damaged and the type and degree of the damage; The data analysis layer performs data analysis on the manhole cover data obtained by the intelligent recognition layer, analyzes the spatial and temporal characteristics of various manhole cover diseases, and obtains the occurrence patterns of manhole cover diseases in different spatial scenes and different time periods; The space-time control layer conducts advanced control over the health status of manhole covers, establishes a spatial control plan for the service life of manhole covers and a time- and stage-by-stage control plan for the service life of manhole covers, conducts regional spatial control and optimization of multi-source diseases of manhole covers, and conducts time control and optimization over multiple time periods.

9. The system according to claim 8, characterized in that The smart recognition layer includes: A manhole cover image intelligent collection and recognition system, which collects manhole cover images in actual scenes and determines whether the manhole cover has Class I disease among multi-source diseases based on the collected manhole cover image data. Class I diseases include eight types of diseases: missing, disordered, displaced, damaged, damaged around the well, bulge, height difference, and subsidence of the manhole cover. At the same time, the degree of some or all of the Class I diseases of the manhole cover is determined based on the binary image method; A dynamic identification system for collecting and identifying the vibration of a manhole cover collects the vibration of the manhole cover and determines whether the manhole cover has a Class II disease among multi-source diseases based on the collected manhole cover vibration data. Class II diseases include vibration diseases of the manhole cover. At the same time, the degree of the Class II disease of the manhole cover is determined by the size of the manhole cover vibration frequency.

10. The system according to claim 9, characterized in that The manhole cover image intelligent acquisition and recognition system uses image acquisition equipment installed at key positions to capture images of the manhole cover from multiple angles, including the front view and side view; at the same time, the manhole cover image data is recognized with the help of a manhole cover disease recognition model.

11. The system according to claim 9, characterized in that The manhole cover vibration collection dynamic identification system adopts vibration sensors arranged on the manhole cover according to the direction of vehicle flow, and the vibration sensors collect the vibration frequency of the manhole cover.

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