Underground pipe gallery structure health monitoring early warning system and monitoring device

Abstract

The present invention provides an underground pipeline gallery structure health monitoring and early warning system and a monitoring device thereof, which relate to the field of data processing technology. By acquiring a health monitoring data set, the underground pipeline gallery structure is modeled based on structural parameters, the health monitoring data set is integrated with the structural model, and the underground pipeline gallery structure model is obtained. When multiple health levels meet the preset health levels, the underground pipeline gallery structure model is analyzed for health decline based on a simulation system, and a health early warning of the underground pipeline gallery structure is performed according to the first health decline information. The technical problem that the existing technology does not adequately evaluate the health status of the underground pipeline gallery structure, resulting in structural safety hazards in the underground pipeline gallery and affecting the safety and stability of the pipeline gallery is solved, and the real-time monitoring, evaluation and accurate prediction of the health level of the underground pipeline gallery structure are achieved, and early warning is given in time according to the prediction results, thereby improving the work efficiency and the technical effect of improving the safety and stability of the underground pipeline gallery.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to an underground pipe gallery structure health monitoring and early warning system and a monitoring device thereof. Background Art

[0002] With the acceleration of urbanization and the continuous improvement of infrastructure construction, underground pipeline corridors, as one of the important urban infrastructures, undertake the important task of transporting key resources such as water, electricity, and gas. However, since underground pipeline corridors are in a complex and changeable environment for a long time, their structural health status is easily affected by various factors. The traditional underground pipeline corridor structural health assessment method mainly relies on manual inspection and regular testing, which has problems such as large workload, low efficiency, and difficulty in real-time grasp of the health status of the pipeline corridor.

[0003] The existing technology has the technical problem of inadequate assessment of the structural health status of underground pipeline corridors, resulting in structural safety hazards in underground pipeline corridors and affecting the safety and stability of the pipeline corridors. Summary of the invention

[0004] The present application provides an underground pipeline corridor structure health monitoring and early warning system and a monitoring device thereof, which are used to solve the technical problem that the prior art fails to adequately assess the structural health status of the underground pipeline corridor, resulting in structural safety hazards in the underground pipeline corridor and affecting the safety and stability of the pipeline corridor.

[0005] In view of the above problems, the present application provides an underground pipeline corridor structure health monitoring and early warning system and a monitoring device thereof.

[0006] In the first aspect, the present application provides an underground pipe gallery structure health monitoring and early warning system, the system is communicatively connected to a health monitoring device, the health monitoring device includes a structure monitoring unit, an environment monitoring unit, and a pipeline monitoring unit, the system includes: a data acquisition module, the data acquisition module is used to collect real-time health data of the underground pipe gallery structure through the structure monitoring unit, the environment monitoring unit, and the pipeline monitoring unit to obtain a health monitoring data set; a health assessment module, the health assessment module is used to perform health assessment on the health monitoring data set to obtain multiple health degrees, wherein the multiple health degrees include structural health, environmental health, and pipeline health; a three-dimensional structure model construction module, the three-dimensional structure model construction module is used In order to obtain the structural parameters of the underground pipeline gallery structure, based on the structural parameters, the underground pipeline gallery structure is modeled through the digital twin system to obtain a three-dimensional structural model; a pipeline gallery structure model acquisition module, the pipeline gallery structure model acquisition module is used to integrate the health monitoring data set with the three-dimensional structural model to obtain the underground pipeline gallery structure model; a health decline analysis module, the health decline analysis module is used to perform a health decline analysis on the underground pipeline gallery structure model based on the simulation system when the multiple health degrees all meet the preset health degrees, and obtain the first health decline information that does not meet the preset health degree; a health warning module, the health warning module is used to perform a health warning for the underground pipeline gallery structure based on the first health decline information.

[0007] In a second aspect, the present application provides an underground tunnel structure health monitoring device, comprising a memory and a processor, wherein the memory stores a computer program, and wherein the processor implements data interaction of the system described in any one of claims 1 to 8 when executing the computer program.

[0008] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0009] The system provided in the embodiment of the present application collects real-time health data of the underground pipeline corridor structure through the structure monitoring unit, the environment monitoring unit, and the pipeline monitoring unit, obtains a health monitoring data set, performs health assessment on the health monitoring data set, obtains multiple health levels, and models the underground pipeline corridor structure through a digital twin system based on structural parameters to obtain a three-dimensional structural model. The health monitoring data set is integrated with the three-dimensional structural model to obtain an underground pipeline corridor structure model. When multiple health levels meet the preset health levels, a health decline analysis is performed on the underground pipeline corridor structure model based on the simulation system to obtain first health decline information that does not meet the preset health level. Health warnings are performed on the underground pipeline corridor structure based on the first health decline information, thereby achieving real-time monitoring, evaluation, and accurate prediction of the health level of the underground pipeline corridor structure, timely warnings based on the prediction results, improving work efficiency, and improving the technical effect of the safety and stability of the underground pipeline corridor. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solution of the embodiment of the present invention, the accompanying drawings of the embodiment of the present invention will be briefly introduced below. A flow chart is used in the present application to illustrate the operations performed by the system according to the embodiment of the present application. It should be understood that the preceding or following operations are not necessarily performed accurately in order. On the contrary, various steps can be processed in reverse order or simultaneously as needed. At the same time, other operations can also be added to these processes, or one or more operations can be removed from these processes.

[0011] Figure 1 A schematic diagram of the structure of the underground pipe gallery structural health monitoring and early warning system provided for this application;

[0012] Figure 2 This is a schematic diagram of the structure of the health degradation analysis module in the underground pipeline corridor structure health monitoring and early warning system provided in this application.

[0013] Explanation of the accompanying drawings: data acquisition module 10, health assessment module 20, three-dimensional structure model construction module 30, pipeline corridor structure model acquisition module 40, health decline analysis module 50, health warning module 60, health decline simulation unit 51, decline health judgment unit 52, decline information recording unit 53. DETAILED DESCRIPTION

[0014] This application provides an underground pipe gallery structure health monitoring and early warning system and its monitoring device, which are used to solve the technical problem that the existing technology does not adequately evaluate the health status of the underground pipe gallery structure, resulting in structural safety hazards in the underground pipe gallery, affecting the safety and stability of the pipe gallery. It achieves real-time monitoring, evaluation and accurate prediction of the health of the underground pipe gallery structure, timely warning according to the prediction results, improves work efficiency, and improves the technical effect of the safety and stability of the underground pipe gallery.

[0015] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0016] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of this application.

[0017] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict, and the terms "first\second" involved are merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by technicians in the technical field of this application. The terms used herein are for the purpose of describing the embodiments of the present application only.

[0018] Embodiment 1

[0019] like Figure 1 As shown, the present application provides an underground pipe gallery structure health monitoring and early warning system, the system is communicatively connected with a health monitoring device, the health monitoring device includes a structure monitoring unit, an environment monitoring unit, and a pipeline monitoring unit, and the system includes:

[0020] The data acquisition module 10 is used to collect real-time health data of the underground pipe gallery structure through the structure monitoring unit, the environment monitoring unit, and the pipeline monitoring unit to obtain a health monitoring data set.

[0021] Specifically, the underground pipeline corridor structural health monitoring device is composed of a structural monitoring unit, an environmental monitoring unit, and a pipeline monitoring unit, which together constitute a comprehensive monitoring network. The structural monitoring unit is responsible for monitoring the main structure of the underground pipeline corridor, including the supporting structure, the enclosure structure, the foundation structure, the waterproof and anti-corrosion structure, etc. The environmental monitoring unit is used to monitor the environmental information of the underground pipeline corridor, including temperature and humidity, gas concentration, etc. The pipeline monitoring unit is used to detect the pipeline information in the pipeline corridor, including power pipelines, water supply and drainage pipelines, communication pipelines, gas pipelines, thermal pipelines, etc., which is achieved through the integration of multiple sensors and monitoring equipment, such as displacement sensors, settlement meters, crack monitors, temperature and humidity sensors, gas detectors, pipeline monitoring equipment, etc. The underground pipe gallery structure monitoring and early warning system is communicatively connected with the health monitoring device. The data acquisition module 10 is the core part of the system. The structure monitoring unit, the environmental monitoring unit and the pipeline monitoring unit in the monitoring device are used to monitor the underground pipe gallery structure comprehensively and in real time, and then the real-time health monitoring data of the underground pipe gallery structure is collected, such as foundation, pile foundation, waterproof coating, anti-corrosion material, bracket, beam, temperature and humidity, gas concentration, pipeline pressure, flow and other data. A health monitoring data set is formed based on the real-time health data collected, providing a data basis for subsequent data analysis and early warning.

[0022] The health assessment module 20 is used to perform health assessment on the health monitoring data set to obtain multiple healths, wherein the multiple healths include structural health, environmental health, and pipeline health.

[0023] Specifically, the health assessment module 20 is used to assess the health status of the underground pipe gallery. By collecting the health monitoring data set obtained by the data collection module 10, the monitoring data in the health monitoring data set is analyzed by using data analysis technology and algorithms, such as machine learning and artificial intelligence technology, rule evaluation methods, and expert knowledge and experience, combined with monitoring data, to assess the health status of the underground pipe gallery and obtain multiple health indicators, including structural health, environmental health, and pipeline health. The structural health is used to assess the stability and durability of the pipe gallery structure, including deformation, lifting, cracks, displacement, and tilt assessment of the pipe gallery. The environmental health is used to assess the internal environmental information of the pipe gallery, including temperature, humidity, concentration of harmful gases, etc. The pipeline health is used to assess the operation of the pipeline, including power, communication, gas, heat, and water supply and drainage pipelines. The health assessment module 20 provides strong support for the maintenance and management of the pipe gallery by continuously analyzing the monitoring data.

[0024] The three-dimensional structure model building module 30 is used to obtain the structural parameters of the underground pipe gallery structure, and based on the structural parameters, the underground pipe gallery structure is modeled by a digital twin system to obtain a three-dimensional structure model.

[0025] Specifically, the three-dimensional structure model building module 30 collects and obtains the structural parameters of the underground pipe gallery structure, including detailed information of the main structure of the pipe gallery, such as the length, width, height, material, connection method, pipeline diameter, valve position, equipment position, etc. of the pipe gallery. Then, the collected data is preprocessed, such as noise removal, data cleaning, format unification, etc. After obtaining the processed structural parameter data, the structure parameters are used to model the underground pipe gallery structure through the digital twin system on the basis of the digital twin and combined with the three-dimensional technology to obtain the three-dimensional structural model of the underground pipe gallery. The data twin system is a complex system that integrates a variety of advanced technologies. It can simulate physical objects or processes in the real world and perform real-time analysis and optimization in a virtual environment. The principle of digital twin technology is to make full use of physical models, sensor updates, operation history and other data, integrate multi-disciplinary, multi-physical quantity, multi-scale, multi-probability simulation processes, and complete mapping in the virtual space, thereby reflecting the full life cycle process of the corresponding physical equipment. By combining the digital twin model with the real environment to obtain a three-dimensional structural model, the actual structure and operation status of the underground pipe gallery can be simulated and reproduced in the virtual environment, realizing the digital presentation of real objects and space.

[0026] The pipeline gallery structure model acquisition module 40 is used to integrate the health monitoring data set with the three-dimensional structure model to obtain the underground pipeline gallery structure model.

[0027] Specifically, the tunnel structure model acquisition module 40 integrates the health monitoring data obtained by the data acquisition module 10 and the three-dimensional structure model constructed by the three-dimensional structure model construction module 30. In the three-dimensional structure model, the health monitoring data is mapped to the corresponding structure or area of ​​the three-dimensional structure according to the location and type of the health monitoring data. For example, environmental monitoring data such as temperature and humidity can be mapped to specific spatial positions in the tunnel, and structural monitoring data such as structural deformation and cracks can be mapped to specific structures such as pipes and supports. Using three-dimensional modeling software or visualization tools, the health monitoring data can be displayed in an intuitive way on the three-dimensional structure model to obtain the underground tunnel structure model, thereby providing comprehensive and accurate data support for the health assessment and early warning of the underground tunnel.

[0028] The health decay analysis module 50 is used to perform a health decay analysis on the underground pipe gallery structure model based on a simulation system when the multiple health degrees all meet the preset health degrees, and obtain the first health decay information that does not meet the preset health degree.

[0029] The health warning module 60 is used to perform a health warning on the underground pipe gallery structure based on the first health degradation information.

[0030] Specifically, the health decline analysis module 50 judges the multiple healths obtained by the health assessment module 20 and the preset health threshold. The preset health threshold is set in advance based on historical data, equipment standards, expert advice, etc., indicating that the tunnel structure can operate safely and stably. The minimum health data value, when multiple health indicators meet the preset health threshold, indicates that the current state of the underground tunnel structure is good, and all key indicators are within an acceptable range. Further, the underground tunnel structure model is subjected to a health decline analysis based on the simulation system. The simulation system simulates the operation of the underground tunnel structure in a real environment, including the operation of the tunnel structure itself and external influencing factors, such as geological changes, climate conditions, human factors, etc. By analyzing the simulated data, it is possible to predict the development trend of the health status of the underground tunnel structure, and then find out the data part that does not meet the preset health through health decline analysis as the first health decline information. The health warning module 60 receives the first health decline information from the health decline analysis module 50, and performs a health warning for the underground pipeline corridor structure based on the first health decline information. The warning method can be set according to actual conditions, such as by sounding an alarm, displaying a warning message, sending an email or text message, etc., to notify relevant personnel of possible health problems in the underground pipeline corridor structure, thereby helping managers to take timely measures to prevent further decline of the underground pipeline corridor structure, avoid possible safety accidents, and provide strong technical effects for the safe operation of the underground pipeline corridor.

[0031] In one possible implementation, the system further includes: a warning instruction generation unit, which is used to generate a first warning instruction when a first health level does not meet a preset health level, wherein the first warning instruction includes first warning information; and a warning information execution unit, which is used to perform a health warning based on the first warning information.

[0032] Specifically, the early warning instruction generation unit and the early warning information execution unit are key components for ensuring that the underground pipe gallery responds and takes action in a timely manner. When the health decline analysis module analyzes that the first health does not meet the health, it means that the current state of the underground pipe gallery structure is poor, the health has exceeded the acceptable range of structural health, and there may be problems with the structure. Based on this, a first early warning instruction is generated. The first early warning instruction includes a first early warning information. The first early warning information includes a health description, which details which part or aspect of the health does not meet the preset standard, such as structural damage, corrosion degree, material aging, etc., and an impact assessment, and a preliminary assessment of the possible consequences of the problem, including the impact on the normal operation of the underground pipe gallery and the possible risk level. After the early warning instruction generation unit generates the first early warning instruction, the first early warning instruction is sent to the early warning information execution unit. After receiving the first early warning instruction, the early warning information execution unit parses the first early warning information in the first early warning instruction and performs a health warning according to the first early warning information, including sending an alarm notification to relevant personnel, triggering automatic response measures, triggering further diagnosis or inspection processes, to determine the root cause of the problem and other health warning measures. Through the collaborative work of these two units, the system can ensure that when the health of underground pipelines or other key facilities is abnormal, it can be discovered in time and effective response measures can be taken, thereby ensuring the safe and stable operation of the facilities.

[0033] In one possible implementation, the early warning information execution unit includes: a monitoring item acquisition unit, which is used to acquire the first monitoring item and the first health monitoring data corresponding to the first health degree; a feature analysis unit, which is used to perform feature analysis on the first health monitoring data to obtain the first health monitoring feature; a decision retrieval unit, which is used to retrieve the underground corridor structure processing decision record set, including the first processing decision record set of the first monitoring item, and the first processing decision record set includes a historical first health monitoring feature set and a historical first processing scheme record set; a feature alignment unit, which is used to align the first health monitoring feature in the first processing decision record set, and generate a first processing decision according to the alignment result; a processing decision adding unit, which is used to add the first processing decision to the first early warning information to perform a health warning.

[0034] Specifically, a first health degree that does not meet a preset health degree is obtained through a monitoring item acquisition unit, and then a first monitoring item and a first health monitoring data corresponding to the first health degree are obtained, and the first monitoring item is any one of the structure, environment, and pipeline of the underground tunnel. The feature analysis unit receives the first health monitoring data obtained by the monitoring item acquisition unit, and performs feature analysis on the first health monitoring data to obtain a first health monitoring feature. When the first monitoring item is the tunnel structure, after obtaining the health monitoring data related to the tunnel structure, the feature analysis unit performs feature analysis on the health monitoring data of the tunnel structure. The first health monitoring feature is structural deformation, settlement, or movement. Similarly, for environmental health monitoring data, the health monitoring features are temperature, humidity, gas concentration changes, and the like. For pipeline health monitoring data, the health monitoring features are pipeline flow, pressure changes, and leakage, and the like. Then, the decision retrieval unit retrieves the underground pipe gallery structure processing decision record set stored in the underground pipe gallery structure monitoring system, which record set includes the first processing decision record set corresponding to the first monitoring item, and the first processing decision record set includes the historical first health monitoring set and the historical first processing scheme record set, that is, by retrieving the historical decision record, the system can make the current processing decision based on past experience and knowledge, and improve the accuracy and efficiency of the decision. The feature registration unit matches the first health monitoring feature in the first processing decision record set retrieved by the decision retrieval unit, matches and obtains the historical processing decision of the first health monitoring feature, and then generates the first processing decision according to the matching result. The processing decision adding unit adds the first processing decision generated by the feature registration unit to the first warning information, performs health warning, and makes the first warning information contain recommended measures, and gives suggestions or emergency response measures for the identified problems to slow down the further decline of health or prevent the occurrence of potential accidents. Through the collaborative work of the above functional units, a complete health monitoring and early warning processing process is formed to ensure that the system can efficiently and accurately complete the health monitoring and early warning tasks of the underground pipe gallery structure and ensure the safe and stable operation of the facilities.

[0035] In one possible implementation, the feature registration unit includes: a similarity matching unit, which is used to perform similarity matching on the first health monitoring feature and the historical first health monitoring feature set to obtain multiple similarities; and a processing decision acquisition unit, which is used to take the maximum value of the multiple similarities and obtain the historical first processing plan record corresponding to the maximum similarity as the first processing decision.

[0036] Specifically, the feature registration unit also includes two key components, a similarity matching unit and a processing decision obtaining unit, which work together to make reasonable processing decisions based on historical data and current monitoring data. The similarity matching unit performs similarity matching between the current first health monitoring feature and the historical first health monitoring feature set stored in the system. The matching method is optional, and the matching is performed through a similarity measurement algorithm, such as cosine similarity, Euclidean distance, etc. The similarity between the first health monitoring feature and the historical first health monitoring feature is calculated through the similarity measurement algorithm to obtain multiple similarities. The processing decision obtaining unit receives multiple similarity values ​​output by the similarity matching unit, and sorts the multiple similarity values ​​from large to small to obtain the maximum similarity of the multiple similarities. Then, according to the maximum similarity, the corresponding processing solution is found in the historical first processing solution record set as the first processing decision. By making full use of historical data and current monitoring data, more reasonable and effective processing decisions are formulated to ensure the stability and safety of the underground pipe gallery structure.

[0037] In a possible implementation, the health assessment module 20 further includes: a monitoring data extraction unit, which is used to extract an environmental health monitoring data set based on the health monitoring data set, wherein the environmental health monitoring data set includes temperature monitoring data, humidity monitoring data, and gas concentration monitoring data; a deviation calculation unit, which is used to perform deviation calculation on the temperature monitoring data, humidity monitoring data, and gas concentration monitoring data based on a preset environmental quality standard, and generate multiple environmental monitoring data deviation coefficients based on the deviation calculation results; a weighted summation calculation unit, which is used to perform weighted summation on the multiple environmental monitoring data deviation coefficients, obtain the environmental health according to the calculation results, and add the environmental health to the multiple healths.

[0038] Specifically, the monitoring data extraction unit extracts data related to environmental health from the health monitoring data set to form an environmental health monitoring data set, wherein the environmental health monitoring data set includes temperature monitoring data, humidity monitoring data and gas concentration monitoring data, providing necessary data support for subsequent environmental health assessment. The deviation calculation unit uses the preset environmental quality standard as a reference basis, and for each type of environmental monitoring data in the temperature, humidity and gas concentration monitoring data output by the monitoring data extraction unit, compares the actual monitoring data with the corresponding preset standard, and calculates the deviation. The deviation calculation includes absolute value difference, percentage difference or other measurement methods. Then, based on the calculated deviation value, the deviation calculation unit further generates multiple environmental monitoring data deviation coefficients, for example, first standardizing the obtained deviation, and then converting it through an algorithm to obtain multiple environmental monitoring data deviation systems. Finally, the deviation calculation unit outputs the generated environmental monitoring data deviation coefficient to the weighted summation calculation unit, and the weighted summation calculation unit performs weighted summation on the received multiple environmental deviation coefficients to obtain a comprehensive environmental health index, namely, the environmental health degree. The smaller the deviation, the higher the health degree. Finally, the environmental health degree is added to the multiple health degrees, so that the system can comprehensively and objectively evaluate the health status of the environment and provide a scientific basis for relevant decisions.

[0039] In one embodiment, Figure 2 As shown, the health decline analysis module 50 further includes: a health decline simulation unit 51, which is used to simulate the health decline process of the underground utility corridor structure through the simulation system based on the underground utility corridor structure model, and monitor the health level in real time to obtain multiple decline health levels; a decline health level judgment unit 52, which is used to record the first warning node and the first decline item when there is a first decline health level that does not meet the preset health level; and a decline information recording unit 53, which is used to add the first warning node and the first decline item to the first health decline information.

[0040] Specifically, the health decay simulation unit 51 simulates the health decay process of the underground pipe gallery structure through a simulation system based on the underground pipe gallery structure model, and considers various factors in the simulation process, such as weather conditions, natural disaster conditions, environmental corrosion and the degree of their influence on the health of the pipe gallery structure, etc., uses finite element analysis or other simulation software to establish a numerical model of the underground pipe gallery, sets various decay factors in the model, runs the simulation, and in the process of simulating the health decay, monitors and records the health data at different time points in real time to obtain multiple decay health degrees. The decay health judgment unit 52 receives multiple decay health degrees output from the health decay simulation unit 51, and judges whether the decay health degrees obtained in the simulation process meet the preset health threshold. When there is a decay health degree, that is, the first decay health degree does not meet the preset health degree, the time point and the corresponding decay item, that is, the first warning node and the first decay item are recorded, and the decay items are such as the aging of a certain pipe section and the increase of the gas concentration at a certain node. The decay information recording unit 53 receives the first warning node and the first decay item outputted by the decay health judgment unit 52, and adds the data information of the two to the first health decay information, so as to provide a scientific basis for the maintenance and repair of the pipe gallery structure.

[0041] In one possible implementation, the system further includes: a decline trend acquisition unit, the decline trend acquisition unit is used to obtain a first service record of the first decline item, and obtain a first decline trend based on the first service record; a decline health acquisition unit, the decline health acquisition unit is used to use the natural loss trend as a decline baseline, and combine the first decline trend to perform a decline prediction of the first warning node to obtain a predicted first decline health; a decline health compensation unit, the decline health compensation unit is used to compensate the first decline health based on the predicted first decline health.

[0042] Specifically, the decay trend acquisition unit is responsible for acquiring the first service record of the first decay project from the system, the first service record includes the time when the project was put into use, the data of previous inspections or maintenance, changes in environmental conditions and other information. According to the first service record, the decay trend acquisition unit uses time series analysis, regression analysis or other appropriate statistical methods to analyze the first service record, and determines the first decay trend of the first project based on the analysis result, and the first decay trend represents a function of the decay speed or decay degree. The decay health acquisition unit uses the natural loss trend as the decay baseline, and the natural loss trend is a function representing the natural loss trend determined based on historical data or expert knowledge. The first decay trend is superimposed on the natural loss trend to form a comprehensive decay model. The comprehensive decay model is used to predict the health of the first warning node to obtain the predicted first decay health, that is, the predicted first decay health is obtained by theoretical analysis based on historical conditions and natural decay. The decay health compensation unit receives the predicted first decay health obtained from the decay health acquisition unit, and compares the first decay health with the first decay health simulated by the actual three-dimensional model, calculates a compensation value, compensates the first decay health obtained by actual monitoring, and obtains the compensated decay health value. The compensated decay health value obtained through comprehensive calculation can more accurately predict and evaluate the health decay of underground pipeline corridor structures, providing important support for subsequent pipeline corridor maintenance and management.

[0043] In one possible implementation, the system further includes: a deviation calculation unit, which is used to perform a deviation calculation on the first decay health degree based on the predicted first decay health degree to obtain a first deviation coefficient; and a model adjustment unit, which is used to adjust the underground pipeline corridor structure model based on the first deviation coefficient when the first deviation coefficient is greater than or equal to a preset deviation coefficient.

[0044] Specifically, the deviation calculation unit receives the predicted first decay health degree obtained from the decay health degree obtaining unit, and calculates the difference between the predicted first decay health degree and the first decay health degree, and obtains the first deviation coefficient based on the difference calculation result. The deviation coefficient is a value between 0 and 1, or a percentage form, which is used to quantify the degree of deviation between the prediction and the actual. The larger the deviation coefficient, the greater the degree of deviation of the prediction. The model adjustment unit compares the first deviation coefficient obtained by the deviation calculation unit with the preset deviation coefficient. When the first deviation coefficient is greater than or equal to the preset deviation coefficient, it indicates that there is a large deviation between the prediction result and the actual simulated decay health degree, and analyzes the cause of the deviation to obtain the model adjustment strategy, for example, update the model parameters, modify the model structure, improve the data preprocessing method, etc., and adjust the model of the underground pipe gallery structure model based on the first deviation coefficient. Through the combined use of the deviation calculation unit and the model adjustment unit, the system can continuously verify and adjust the three-dimensional model simulation results, further improve the accuracy and reliability of the model simulation results, and then improve the scientificity and effectiveness of the underground pipe gallery structure management, and provide a strong guarantee for the long-term stable operation of the pipe gallery.

[0045] Although the present application makes various references to certain modules in the system according to the embodiments of the present application, any number of different modules may be used and run on the user terminal and / or server, and the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0046] Embodiment 2

[0047] The present application provides an underground tunnel structure health monitoring device, including a memory and a processor, wherein the memory stores a computer program, and the monitoring device includes a processor, a memory, and a network interface connected via a system bus. The processor of the monitoring device is used to provide computing and control capabilities. The memory of the monitoring device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the monitoring device is used to store monitoring data and data such as time attenuation factors. The network interface of the monitoring device is used to communicate with the terminal of the system via a network connection. When the computer program is executed by the processor, data interaction of the underground tunnel structure health monitoring and early warning system is realized.

[0048] The above specific implementation manner does not constitute a limitation to the protection scope of the present application. It should be understood by those skilled in the art that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application should be included in the protection scope of the present application. In some cases, the actions or steps recorded in the present application can be performed in an order different from that in the embodiment and can still achieve the desired results. In addition, the process depicted in the accompanying drawings does not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. The underground pipe gallery structure health monitoring and early warning system is characterized by: The system is in communication with a health monitoring device, the health monitoring device includes a structure monitoring unit, an environment monitoring unit, and a pipeline monitoring unit. The system includes: A data acquisition module, wherein the data acquisition module is used to collect real-time health data of the underground pipe gallery structure through the structure monitoring unit, the environment monitoring unit, and the pipeline monitoring unit to obtain a health monitoring data set; A health evaluation module, the health evaluation module is used to perform health evaluation on the health monitoring data set to obtain multiple healths, wherein the multiple healths include structural health, environmental health, and pipeline health; A three-dimensional structure model building module, wherein the three-dimensional structure model building module is used to obtain structural parameters of the underground pipe gallery structure, and based on the structural parameters, model the underground pipe gallery structure through a digital twin system to obtain a three-dimensional structure model; A pipeline gallery structure model acquisition module, the pipeline gallery structure model acquisition module is used to integrate the health monitoring data set with the three-dimensional structure model to obtain an underground pipeline gallery structure model; A health decay analysis module, wherein the health decay analysis module is used to perform a health decay analysis on the underground pipe gallery structure model based on a simulation system when the multiple health degrees all meet the preset health degrees, and obtain first health decay information that does not meet the preset health degree; A health warning module, the health warning module is used to perform a health warning for the underground pipe gallery structure based on the first health decay information; Wherein, the health assessment module includes: A monitoring data extraction unit, the monitoring data extraction unit is used to extract an environmental health monitoring data set based on the health monitoring data set, wherein the environmental health monitoring data set includes temperature monitoring data, humidity monitoring data, and gas concentration monitoring data; A deviation calculation unit, the deviation calculation unit is used to perform deviation calculation on the temperature monitoring data, humidity monitoring data, and gas concentration monitoring data based on a preset environmental quality standard, and generate a plurality of environmental monitoring data deviation coefficients based on the deviation calculation results; A weighted sum calculation unit, the weighted sum calculation unit is used to perform weighted summation on the deviation coefficients of the plurality of environmental monitoring data, obtain the environmental health degree according to the calculation result, and add the environmental health degree to the plurality of health degrees; Wherein, the health decline analysis module includes: A health decay simulation unit, wherein the health decay simulation unit is used to simulate the health decay process of the underground pipe gallery structure through the simulation system based on the underground pipe gallery structure model, and monitor the health degree in real time to obtain multiple decay health degrees; A decay health judgment unit, the decay health judgment unit is used to record a first warning node and a first decay item when there is a first decay health that does not meet the preset health; a decay information recording unit, the decay information recording unit being used to add the first warning node and the first decay item to the first health decay information; Wherein, the system further comprises: a decay trend acquisition unit, the decay trend acquisition unit being configured to acquire a first service record of the first decay item, and acquire a first decay trend based on the first service record; A decay health degree obtaining unit, the decay health degree obtaining unit is used to perform a decay prediction of the first warning node based on the natural loss trend as a decay baseline and the first decay trend to obtain a predicted first decay health degree; a decayed health compensating unit, the decayed health compensating unit being configured to compensate the first decayed health based on the predicted first decayed health; Wherein, the system further comprises: a deviation calculation unit, the deviation calculation unit being used to perform deviation calculation on the first decay health level based on the predicted first decay health level to obtain a first deviation coefficient; A model adjustment unit, wherein the model adjustment unit is used to adjust the underground pipe gallery structure model based on the first deviation coefficient when the first deviation coefficient is greater than or equal to a preset deviation coefficient.

2. The system according to claim 1, characterized in that The system further comprises: A warning instruction generating unit, wherein the warning instruction generating unit is used to generate a first warning instruction when the first health level does not meet the preset health level, wherein the first warning instruction includes first warning information; An early warning information execution unit, wherein the early warning information execution unit is used to perform a health early warning based on the first early warning information.

3. The system according to claim 2, characterized in that The early warning information execution unit includes: a monitoring item acquisition unit, the monitoring item acquisition unit being used to acquire a first monitoring item and first health monitoring data corresponding to the first health level; a feature analysis unit, configured to perform feature analysis on the first health monitoring data to obtain a first health monitoring feature; A decision retrieval unit, the decision retrieval unit is used to retrieve an underground pipe gallery structure processing decision record set, including a first processing decision record set for a first monitoring project, the first processing decision record set including a historical first health monitoring feature set and a historical first processing solution record set; a feature registration unit, the feature registration unit being used to perform registration with the first health monitoring feature in the first processing decision record set, and generate a first processing decision according to the registration result; A processing decision adding unit, wherein the processing decision adding unit is used to add the first processing decision to the first warning information to perform a health warning.

4. The system according to claim 3, characterized in that The feature registration unit comprises: a similarity matching unit, the similarity matching unit being used to perform similarity matching between the first health monitoring feature and the historical first health monitoring feature set to obtain a plurality of similarities; A processing decision obtaining unit is used to obtain a maximum value of the multiple similarities and obtain a historical first processing solution record corresponding to the maximum similarity as the first processing decision.

5. An underground pipe gallery structure health monitoring device, comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, data interaction of the system according to any one of claims 1 to 4 is realized.

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