16585 results about "Drainage tubes" patented technology

The invention provides an urban intelligent drainage management system based on big data analysis, and relates to the technical field of urban drainage management, and the system comprises a multi-source data collection module which collects historical climate changes, rainfall curves, satellite meteorology, pipe network node water level flow and topological structure data in real time; the dynamic three-dimensional modeling module constructs a pipe network three-dimensional model according to a fluid mechanics principle, and binds real-time sensor data by a spatio-temporal data fusion algorithm; the drainage limit analysis module calculates the maximum drainage threshold value and the failure probability of the node under extreme rainfall; the intelligent early warning module fuses LSTM and ARIMA models, generates a drainage pressure thermodynamic diagram in the future 72 hours in combination with satellite meteorological data and triggers early warning; the health assessment module generates a node health index and a maintenance priority order; the resource scheduling engine generates a dynamic scheduling scheme. The urban drainage problem is effectively solved, the ability of a drainage system to deal with extreme weather and pipe network aging problems is improved, and accurate early warning and efficient resource allocation are achieved.

The invention discloses a drainage pipeline defect detection method based on improved YOLOv8s, and the method comprises the steps: obtaining a drainage pipeline defect data set, carrying out the data enhancement of the drainage pipeline defect data set, and dividing the drainage pipeline defect data set into a training set, a verification set and a test set; according to the method, YOLOv8s is used as a network basic model, a CBAM attention module is introduced into a backbone network, and feature extraction of pipeline defects is enhanced; an FPN-PAN structure of a neck network is replaced by a BiFPN structure, so that the network feature fusion capability is improved; a new Wise-IoU loss function is adopted to improve the detection precision of the model; and finally, a Conv module in a part of the network is replaced by a GhostConv module, and a C2f module is improved into a C2f-RepGhost module, so that the weight of the network is reduced. Conveying the training set to a drainage pipeline defect detection model for training; and conveying a to-be-detected drainage pipeline defect picture to the trained drainage pipeline defect detection model to obtain a final detection result. Compared with an original model, the detection precision is improved, and support is provided for defect detection of the drainage pipeline.

The invention discloses an intelligent monitoring system for a municipal drainage pipe network, and particularly relates to the technical field of drainage pipe network monitoring. The node operation mode identification module carries out real-time classification and confidence evaluation on the operation state of the pipe network, constructs a multi-attribute pipe network weighted graph based on pipe diameter difference, gradient and confluence density, and extracts multi-scale features through graph Fourier transform. A hybrid anomaly detection link is constructed in combination with an LSTM self-encoder, an isolated forest model and chemical oxygen demand and turbidity water quality verification, and the problems that traditional single-index monitoring is prone to false alarm and missing alarm and inaccurate in positioning are solved; sensor data compensation is realized through cooperation with digital twinning, a rapid detection mode is started during rainstorm early warning, key nodes are processed preferentially, and drainage scheduling is controlled in a closed-loop mode; and target nodes which are easy to accumulate grease are screened based on pipe network topology connectivity, accumulation risks are predicted by fusing multi-sensor data, and a preventive clearing instruction is triggered.

The invention relates to the technical field of digital twinning, in particular to a high-density urban ponding evolution and early warning method based on digital twinning. The method comprises the following steps: real-time ponding depth, real-time river water level, real-time meteorological conditions and real-time drainage pipe network water level conditions corresponding to a city are collected in real time through ponding depth, river water level, meteorological monitoring and drainage pipe network sensors installed in the city, digital twinborn construction is carried out, and an urban inland inundation digital twinborn model is generated; obtaining drainage pipe network distribution and carrying out drainage grid division to generate an urban drainage grid model; acquiring a historical ponding event rule, and performing ponding area prediction analysis and ponding evolution coupling analysis to generate an urban ponding evolution distribution field; performing ponding space-time evolution analysis and ponding early warning processing on the urban ponding evolution distribution field so as to execute corresponding urban ponding emergency response work. According to the invention, accurate ponding evolution prediction and effective early warning can be provided.

This invention disclosed a full-space intelligent detection method and system for underground drainage networks, as well as storage media, including the following steps: image acquisition, intelligent image denoising, internal pipe defect segmentation, concealed defect detection around the pipe, 3D reconstruction with volume quantification, and pipeline life prediction. This invention introduced a bionic four-wheel-drive, all-terrain detection robot that can effectively navigate through mud and flowing water-challenges that hinder traditional detection devices. By leveraging deep learning algorithms as well as various techniques of computing vision, 3D reconstruction, and point cloud processing, the system thoroughly analyzed collected data to determine defect types and precise locations. Utilizing this analysis, precise location of different defect type and quantitative measurement of their dimensions can be realized. Based on the data analysis results, a deep-learning driven model was developed for predicting pipeline longevity to support maintenance staff with timely information on pipe defects and operational lifespan.

The invention discloses an intelligent discharge port dynamic regulation and control system and method based on multi-source time sequence fusion, and relates to the technical field of intelligent water affairs, and the system comprises a data collection module which is used for obtaining the multi-source data of a target area in real time; the space-time fusion module is used for mapping the meteorological radar data to the topological space of the drainage pipe network through a space-time alignment encoder, dynamically fusing the meteorological radar data, the surface runoff sensor data and the historical drainage data by adopting a multi-head attention mechanism, and generating a space-time fusion tensor; the prediction model module is used for constructing a TCN-LSTM hybrid model, taking the space-time fusion tensor as input and taking future drainage flow as output; and the dynamic regulation and control module is used for optimizing the gate opening degree and the pump station power control sequence in a rolling manner based on a model predictive control algorithm, and performing dual-target optimization by combining real-time electricity price data and overflow risks. According to the system, the prediction precision of the drainage flow can be improved, and double-target balance of the overflow risk and the energy consumption cost can be achieved.

The invention relates to the technical field of underground drainage pipeline monitoring and hidden danger analysis, and provides an underground drainage pipeline hidden danger data analysis method based on big data, which comprises the following steps: acquiring data such as flow, water level, pressure and pipeline structure by using a multi-source sensor to form an original monitoring data set; preprocessing the data, extracting time domain, frequency domain and spatial topological features, and constructing a multi-dimensional feature vector; and inputting the feature vectors into a pre-trained hidden danger prediction model, and outputting hidden danger types and position coordinates. And constructing a spatio-temporal data analysis model based on the hidden danger position, generating a spatio-temporal correlation feature matrix, and performing dynamic risk assessment to obtain hidden danger development trend parameters. And the hidden danger information is mapped to a geographic information system, a three-dimensional visual analysis result is generated, and a graded early warning instruction is transmitted to a drainage pipe network operation and maintenance management system through a communication interface. The operation and maintenance management efficiency of the drainage pipeline can be improved, the hidden danger checking cost is reduced, and the safety and reliability of the drainage system are enhanced.

The invention discloses a drainage pipe network water quality monitoring, early warning and traceability system and method, and the system comprises the steps: arranging pipe network water quality monitoring stations, building pipe network water quality early warning monitoring stations, carrying out water quality early warning, building a traceability business platform, and building a water quality early warning traceability model. Constructing a water quality pollution traceability mechanism flow; the pipe network early-warning traceability supervision mechanism can quickly study and judge the water quality of the inlet of the pipe network, can track pollution sources of secret discharge, leakage discharge and excessive discharge, provides early warning for inlet water of a sewage treatment plant, reserves emergency disposal time, realizes early-warning traceability of the sewage pipe network, quickly and efficiently searches for the pollution sources, improves supervision efficiency, and ensures that the water quality of the inlet of the sewage treatment plant is ensured. Stable operation of a sewage treatment plant is guaranteed, and impact is effectively reduced; the development of the project provided by the invention plays a demonstration role in an environmental protection system, plays a leading role in improving the water quality of a sewage pipe network and surface water, and provides a scientific basis for water environment management.

The invention provides an AI flood real-time simulation method for urban hydrological multi-physics field decoupling supervision, and the method comprises the steps: constructing an intelligent physical prediction model of urban flood, carrying out the layered decoupling of an urban hydrological hydrodynamic system, separating a one-dimensional drainage pipe network submodule from a two-dimensional surface flood module, designing a multi-scale physical constraint loss function for different links, and carrying out the real-time simulation of the AI flood. Microcosmic, mesoscopic and macroscopic multi-scale physical constraint fusion is realized, and residual constraints of the Saint-Venant equation are embedded in a neural network agent of a drainage system in a microcosmic level; in the mid-level, embedding the residual constraint of the shallow water equation in the surface flood routing system; in the macroscopic level, the water balance constraint of the whole system is realized; urban hydrology and hydrodynamic force are decoupled, and multi-scale physical field supervision constraint is achieved.

A urinary output monitoring system including a urine collection assembly coupled with an automated urinary output monitoring device. The urine collection assembly includes a drainage tube, an accumulator coupled with the drainage tube, and a urine collection container fluidly coupled with the accumulator. The automated urinary output monitoring device operatively is coupled with the urine collection container. Logic determines a volume of urine collected in the container based on a signal from a load cell of the monitoring device. A vacuum pump coupled with the accumulator generates a flow of air that the drags the urine along the drainage tube to the accumulator. The accumulator separates the flow of air from the urine. The flow of air enters the drainage tube by way of a female external urinary catheter.

A vacuum system can include a vacuum chamber in fluid communication with each of a catheter, a suction tube, and a fluid collecting bag. The vacuum chamber can include a proximal opening covered by a lid, a lateral opening coupled to a first drainage tube configured to receive a volume of fluid, and a distal opening coupled to a proximal opening of a valve.

The invention provides a plant-network integrated intelligent linkage scheduling method and system based on real-time monitoring, and the method comprises the steps: collecting drainage data in a drainage pipe network, obtaining the working condition data of a sewage treatment plant, and obtaining meteorological early warning information; performing comprehensive analysis on the drainage data, the working condition data and the meteorological early warning information based on an intelligent algorithm model, and performing prediction to obtain an analysis result; the intelligent algorithm model is used for simulating the running state of the drainage pipe network and predicting the sewage amount, the water quality change and the mixed sewage overflow risk; and according to the analysis result, generating a dynamic linkage scheduling instruction for the storage tank, the intelligent catch basin and the sewage treatment plant. According to the invention, the running state of the drainage pipe network is accurately simulated through the intelligent algorithm model, the sewage amount, the water quality change and the mixed sewage overflow risk are predicted, then the dynamic linkage scheduling instruction for the regulation and storage tank, the intelligent catch basin and the sewage treatment plant is generated, and the situation that the environment is damaged by overflow is avoided.

Systems and methods directed to an assisted fluid drainage system including a proximal ejector pump and a distal ejector pump coupled to a drainage tube. At least one of the proximal ejector pump and the distal ejector pump can utilize a venturi effect to move a bodily fluid through the drainage tube to prevent the formation of dependent loops, which can form within fluid drainage tubes when slack portions create a positive incline. At least one of the proximal ejector pump and the distal ejector pump can include a converging section, a diffuser section, and a diverging section. A diameter of the diffuser section can be less than a diameter of the converging section or the diverging section. A controller can be coupled to the proximal ejector pump and the distal ejector pump to initiate operation of one or both of the pumps in response to an event.

The invention discloses a pollution traceability analysis method based on a topological relation of a drainage pipe network, and the method comprises the steps: collecting drainage pipe data information in a project region, and generating a drainage pipe database; the pipeline database is imported into a general survey platform, a pipe network topological graph is generated, and inspection and correction of the pipe network topological relation are completed; according to a pipe network topological graph, catchment area division is carried out on a project area, monitoring and point distribution are carried out based on the thought of whole-process treatment and prevention and control of discharge ports, pipe network important nodes and drainage households, and on-line monitoring, early warning and pollution tracing are carried out on a drainage pipe network. According to the method disclosed by the invention, by establishing the topological graph of the drainage pipe network, carrying out monitoring and point distribution, and carrying out online monitoring, early warning and pollution tracing on the drainage pipe network, the phenomena of mixed connection of rain and sewage, incomplete diversion of rain and sewage, stealing and leakage of residential areas and enterprises and the like of the drainage pipe network can be found in time, 24-hour real-time monitoring and early warning are realized, and a monitoring and supervision linkage quick response mechanism is established; and normalized monitoring of sewage entering the river is realized.

The invention relates to the technical field of medical instruments, and provides a vacuum sealing drainage dressing and a wound surface treatment device.The vacuum sealing drainage dressing comprises a sealing layer and a dressing layer which are sequentially arranged in a stacked mode from top to bottom, and further comprises a drainage assembly; the drainage assembly comprises a sucker and a drainage tube, the sucker is arranged at the adsorption opening of the sealing layer, and the drainage tube is connected to the sucker; the dressing layer is of a porous structure, hole walls are communicated with one another to form a continuous channel, the dressing layer is provided with a flexible plasma patch, the flexible plasma patch is suitable for generating plasma acting on a wound surface, and the flexible plasma patch is provided with through holes communicated with pores. The flexible plasma patch is integrally arranged on the dressing layer, negative pressure drainage and wound sterilization and disinfection combined healing promoting treatment can be achieved, the wound or wound treatment process can be simplified, inconvenience caused by frequent dressing change is reduced, and the faster and better healing effect is achieved.

The invention provides an urban drainage pipe network monitoring data cleaning and intelligent prediction method, and the method comprises the steps: firstly obtaining pipe network monitoring data, and carrying out the classification tracking and repairing of missing values; adopting a dynamic IQR algorithm based on a sliding window to adaptively identify abnormal candidate points; secondly, introducing a pipe network topological relation, comparing upstream and downstream data change trends, eliminating non-physical anomalies caused by equipment faults, and reserving real hydraulic events; calculating the physical delay time between the nodes by using the cross correlation coefficient; and finally, constructing a random forest model, taking upstream historical data after delay alignment as feature input, and realizing accurate prediction of a future water level and quantification of a feature contribution degree. According to the method, a physical mechanism and machine learning are fused, the problems that data cleaning lacks adaptivity and a deep learning model lacks interpretability are effectively solved, and the accuracy of waterlogging early warning is improved.

An automated urinary output monitoring system includes a urine collection assembly, a scale, and a pump. The urine collection assembly includes a urinary catheter coupled to a first drainage tube. The interim container coupled to the first drainage tube and a second drainage coupled to a final container. The scale measures the weight of urine collected in the final container and a display can depict the volume of urine collected in the final container. A vacuum pump can be coupled with the final container to draw urine from the interim container into the final container, and an air vent can isolate the patient from the vacuum within the final container. The system can be configured to wirelessly transmit urine volume data to an external computing device. A gyroscope can be coupled with the scale to determine the orientation of the scale.

The invention relates to the technical field of image processing, and discloses an urban drainage pipe network functional defect automatic identification and maintenance grading method and system. The method comprises the following steps: acquiring a drainage pipe network video through pipeline detection equipment, and performing coding extraction according to six-dimensional information such as city and the like to obtain a defect picture; carrying out decoding and feature extraction on the picture to obtain a feature matrix; defect type data is formed through key defect screening, feature refinement and parameter quantification; performing grade evaluation and classification to obtain an evaluation result; and finally, matching and sequencing the maintenance schemes to generate a maintenance decision scheme. According to the invention, automatic identification and grading of defects are realized, and a scientific maintenance decision scheme is provided, so that the efficiency and accuracy of pipe network maintenance work are improved.

The invention discloses an urban underground pipe network multi-dimensional state perception and risk assessment method and system, and relates to the field of urban pipe network monitoring. The method comprises the following steps: S1, multi-source data acquisition: acquiring physical, chemical and environmental perception differentiation data of a gas pipe network and a drainage pipe network through a multi-source heterogeneous sensor network; s2, edge side data processing: preprocessing the data and dynamically weighting the data, and executing local anomaly recognition; s3, performing multi-parameter coupling analysis to obtain a coupling risk index; s4, carrying out three-dimensional dynamic evaluation, and carrying out differentiated evaluation from dimensions of probability, consequence and vulnerability; and S5, intelligent decision making is carried out, and grading early warning and linkage control are triggered. The system comprises a sensor layer, an edge calculation layer, a cloud analysis layer and an early warning platform. The problems of single dimension, response lag and the like of traditional monitoring are solved, full-life-cycle intelligent management of a pipe network is realized, and safe operation of a city is guaranteed.

The invention discloses an urban inland inundation optimization transformation method and system based on a pipe network earth surface coupling hydrodynamic model, and the method comprises the steps: firstly generalizing a pipeline and a catch basin, constructing a pipe network confluence model according to a pipe network hydrodynamic method, then dividing a sub-catchment area according to a river network flood routing method, building an urban comprehensive drainage model through the sub-catchment area, and carrying out the optimization transformation of the urban inland inundation. Then establishing a surface runoff model by using a surface flood routing method and a Horton penetration method; according to the system, the function of accurately and efficiently simulating the urban inland inundation process is achieved, urban rainwater circulation is completely simulated, an urban drainage pipe network and a river channel model are integrated, and the interaction between an urban drainage system and a ground surface storage water body is truly simulated; and necessary support is provided for disaster situation rehearsal and rainwater engineering planning and layout, so that urban inland inundation points can be removed in advance, influences on production and life of people are avoided, and the method is suitable for being widely popularized and used.

The invention discloses a drainage pipe network pollution traceability and alarm system based on invariant analysis, which belongs to the field of data communication of a data center and comprises a data collection module, a cloud platform processing module, an invariant analysis module, an abnormal emission identification and alarm module and a decision support system. The supervision efficiency of the drainage pipe network is improved, environmental pollution is reduced, and sustainable utilization of water resources is guaranteed; according to the system, various sensors are installed at key nodes of a drainage pipe network, data such as water quality, water level, water volume and flow velocity are collected in real time, and the data are transmitted to a cloud platform through a wireless communication technology; by utilizing the data processing capability of the cloud computing platform and combining with an invariant analysis algorithm, the system can quickly position a pollution source, track a pollution path and give an alarm to related personnel in time; the monitoring, management and pollution prevention and control capabilities of the drainage pipe network are effectively improved, and powerful technical support is provided for urban water resource management and environmental protection.

The invention discloses a tunnel drainage pipeline blockage condition monitoring and processing method and system, and the method comprises the steps: collecting data, such as optical images, three-dimensional point cloud, ultrasonic reflection, gas components, infrared imaging, sound wave images, electromagnetic induction and flow velocity, through a multi-mode sensor array, carrying out the denoising and normalization preprocessing, and extracting multi-scale features; fusing and analyzing the feature data by using a self-attention mechanism and a graph neural network to generate optimized multi-modal comprehensive feature data; based on the data, a full-connection neural network discriminates the type, the number, the size, the blockage degree and the cleaning difficulty of blockages, and dynamic correction is carried out through real-time data feedback and a self-learning mechanism; and finally, cleaning scheme data is generated, and a cleaning task is executed through the mechanical arm. According to the method, the comprehensiveness of data acquisition, the depth of feature extraction, the intelligentization of feature fusion and the accuracy and the real-time performance of a discrimination model are improved, and comprehensive monitoring and efficient processing of the blockage condition of the tunnel drainage pipeline are realized.

The invention discloses a hydraulic water quality monitoring control system for a drainage pipe network, which belongs to the field of data communication of a data center and comprises a rain gauge, a flow meter, a liquid level meter and a water quality monitor. The system also comprises an intelligent data analysis and diagnosis module, a remote control and automatic management module, an environment adaptability and safety protection design, a communication and data transmission optimization module, and an intelligent fault self-diagnosis and maintenance prompt module. A data analysis algorithm is adopted, data are transmitted to a central monitoring platform in real time through a wireless communication module, and centralized processing and analysis of the data are achieved. Meanwhile, the system has a remote control function and supports remote operation of drainage pipe network equipment through the intelligent tail end power supply controller. The environment adaptability design ensures that the equipment can stably operate in a severe environment, and the communication and data transmission optimization ensures the real-time performance and accuracy of data.

The utility model relates to the technical field of industrial sewage treatment, in particular to industrial sewage purification equipment for environmental protection engineering. The problems that in the flocculant adding operation process, the adding amount of a flocculant is difficult to control, and the overall sewage treatment efficiency of equipment is affected are solved. The device comprises a treatment tank and a drainage pipe fixedly connected to the side face of the treatment tank. The device further comprises a flocculating agent feeding assembly and a stirring assembly. The propeller can automatically drive the oval block to rotate, and then the baffle is driven to intermittently block the discharging opening of the flocculating agent adding box, so that the flocculating agent adding box can automatically and quantitatively add a flocculating agent into the water inlet pipe, and flocculates in the treatment tank can be conveniently discharged through the slag discharging pipe; sewage in the stirring barrel is stirred through the stirring rod, so that the sewage and a flocculating agent are fully mixed, the sewage purification effect is improved, and meanwhile, a scraping plate scrapes away impurity attachments on the inner wall of the stirring barrel.

The invention provides an urban drainage pipe network flow prediction method based on an improved Transform neural network model, and the method comprises the steps: S1, simulating the rainfall processes under different conditions through constructing a rainfall parameterization engine, and generating a rainfall data set; and S2, calculating the corresponding discharge port flow according to the rainfall data by using the calibrated physical model to form a flow data set. S3, preprocessing the data, including constructing a data set, deleting invalid data, and supplementing features and labels to form a training and verification data set; and S4, an RO-former model is constructed, the model adopts an encoder-decoder architecture, and rainfall and flow data are processed through a dynamic mask and a cross attention mechanism. And S5, training and optimizing the model through the loss function to obtain a model which can be used for predicting the urban drainage network flow in real time. The method improves the accuracy and efficiency of urban drainage pipe network flow prediction, and is of great significance to urban waterlogging early warning and drainage management.

The invention discloses an intelligent method and system for multi-source heterogeneous data fusion management, and belongs to the field of data processing, and the intelligent method for multi-source heterogeneous data fusion management comprises the following steps: deploying a sensor network in a historical ponding area based on historical ponding point data and urban hydrological geographic information, acquiring real-time monitoring data, wherein the real-time monitoring data comprises rainfall intensity, road waterlogging depth, community waterlogging condition and drainage pipe network water level / flow; compared with the prior art, the method has the beneficial effects that sensors are arranged in the historical ponding area to obtain real-time monitoring data, and weather forecast, a terrain model and a pipe network model are combined to construct a waterlogging prediction model to predict whether a ponding risk exists in the historical ponding area in future set time (such as 0.5-3 hours in the future); the ponding risk is treated in advance, so that the problems of traffic interruption caused by ponding, citizen travel obstruction and the like are solved.

The invention belongs to the technical field of medical instruments, and discloses a dynamic pressure adjusting thoracic surgery anti-blocking drainage system which comprises a drainage tube, a drainage bag, a backflow tube, a positioning disc, an electric rotating disc, a blade, an electric vacuum pump and a monitoring mechanism. A drainage tube and a return tube are arranged on the special-shaped tee joint; the tail end of the return pipe is connected with the input end of the electric vacuum pump; the output end of the electric vacuum pump communicates with the drainage bag; a protective shell is arranged on the positioning disc; an electric turntable is arranged on the protective shell, a plurality of blades are arranged at the tail end of a movable rod of the multi-stage medical electric push rod, and a monitoring mechanism is arranged on the protective shell. The internal pressure of the thoracic cavity is monitored in real time, the drainage process is accurately controlled in combination with other physical sign data, and the proper pressure of the thoracic cavity is maintained to improve drainage efficiency; a real-time monitoring and abnormity identification function can timely perceive drainage abnormity; normal saline flushing and mechanical crushing are combined, so that the drainage tube is smooth; the drainage process is comprehensively evaluated in combination with various monitoring data, and potential risks are found as early as possible.

The invention relates to the technical field of urban drainage management, and discloses a municipal sewage pipe network dynamic drainage system and a control method, and the system comprises a sewage pipe network, a central controller, a pump station, a valve and an edge control terminal; the control method comprises the following steps that real-time data are obtained from a plurality of sensors arranged in a sewage pipe network, the plurality of sensors comprise a flow sensor, a water level sensor, a pressure sensor and a rainfall sensor, and the obtained real-time data comprise the sewage flow, the water level, the pipeline pressure and the external rainfall inflow in the pipe network; based on the collected real-time data, dynamic hydraulic modeling is carried out on the sewage pipe network through a central controller, a mathematical model for describing the hydraulic state change of the pipe network is established, and the mathematical model comprises spatio-temporal evolution of flow, water level and pressure. According to the invention, by constructing a drainage scheduling mechanism based on real-time data modeling and edge control linkage, dynamic adjustment and stable control of the running state of the sewage pipe network are realized.

The invention discloses a tunnel construction quality evaluation system and method. The evaluation system comprises a data acquisition module, a quality evaluation standard system, an early warning and notification module and a data management module. Wherein the data acquisition module is used for acquiring construction vehicle data, construction site sensors and site photographing; the quality evaluation standard system comprises drilling quality evaluation, back break evaluation, primary support thickness evaluation, anchor rod construction quality evaluation, waterproof and drainage pipe quality evaluation, steel bar binding quality evaluation, secondary lining quality evaluation and primary support flatness evaluation; the early warning and notification module integrates early warning signals from all the evaluation modules; and the data management module is responsible for storing data generated by each independent module and executing cross-module data analysis. According to the tunnel construction quality evaluation system, by integrating advanced monitoring equipment, an automatic algorithm and comprehensive data analysis, the quality control effect in the tunnel construction process is remarkably improved.

The invention belongs to the technical field of rock-soil side slope protection, and particularly relates to an expansive soil side slope flexible ecological comprehensive supporting system which comprises an intercepting ditch, a vegetation protection layer, a composite waterproof layer, flexible anchor rods, water seepage and drainage pipes, cultivation and planting soil, a drainage ditch, a backfill soil layer, a step-shaped slope surface, a slope surface and slope protection vegetation. The slope surface is excavated into a step-shaped slope surface, a composite waterproof layer, expansive soil backfill soil, a vegetation protection layer and cultivation and planting soil are sequentially arranged on the step-shaped slope surface from bottom to top, and slope protection vegetation is planted and formed on the cultivation and planting soil; the composite waterproof layer is fixed to the step-shaped slope face through the flexible anchor rods. The vegetation protection layer and the slope protection vegetation together reinforce the shallow soil body, and the composite waterproof layer and the flexible anchor rod play a role in absorbing and relieving the received expansive force. The method has an ecological greening effect, has the functions of common supporting of the shallow surface layer and the deep layer of the expansive soil slope, flexible reinforcement and expansion reduction and allowable generation of a small amount of deformation, is simple in construction and high in efficiency, and can realize long-term stability of the shallow surface layer and the deep layer of the expansive soil slope.