8752results about "Lubrication indication devices" patented technology

The invention discloses a water receiving mechanism for a cold drink machine and a liquid level detection method. The water receiving mechanism comprises a bearing seat and a water receiving disc, the bearing seat is installed on a box body of the cold drink machine, a motor seat is arranged at one end of the bearing seat, an ice making bin is arranged at one end of the motor seat, and one end of the ice making bin is installed on the motor seat; a sliding rail groove and a water receiving disc installed in the sliding rail groove are arranged in the other end of the bearing seat, the water receiving disc is connected with the sliding rail groove in a sliding mode, and a water receiving groove in the water receiving disc is located below the ice making bin; external water receiving channels are defined between the ice making bin and the bearing seat, are respectively positioned on two sides of the bearing seat, and are communicated with the water receiving groove; at least one liquid level detection device is arranged on the upper portion of the water receiving tank and electrically connected with a controller of the cold drink machine, and the controller is further electrically connected with a sound-light alarm device on the cold drink machine. By adopting the ice-making bin, materials flowing out of the ice-making bin can be collected, and the liquid level condition in the water pan can be monitored in real time, so that stable implementation of water receiving work of the ice-making bin is ensured, and the use comfort of a user is improved.

The invention relates to the technical field of water quality and water level monitoring, and discloses a water quality and water level monitoring method for a water conservancy project, which comprises the following steps: S1, arranging a multi-parameter water quality and water level monitoring sensor at a key position of the water conservancy project; s2, performing real-time processing on the data acquired by the multiple sensors based on a data fusion algorithm, wherein the data fusion algorithm is based on a Kalman filtering model; s3, acquiring external data through an environment sensor, and dynamically adjusting a water level and a water quality monitoring threshold value based on environment change; s4, predicting the water level and the water quality by using a deep learning algorithm based on LSTM (long short-term memory network); and S5, if the monitoring data exceed the dynamic threshold value, automatically triggering an early warning mechanism. By arranging the multi-parameter water quality sensor and the water level sensor at the key positions of the water conservancy project, the water quality and the water level can be comprehensively monitored, the coverage range and the precision of the monitoring system are greatly improved, and the complex monitoring requirements of multi-source pollution can be effectively met.

The invention relates to the technical field of hydrological monitoring, in particular to a multi-satellite collaborative hydrological monitoring system. The method comprises the following steps that a water level height measurement module obtains radar pulse recovery time delay data through a height measurement satellite and calculates the water level height, abnormal points are removed to generate river water level data, a water remote sensing module collects river water images through a remote sensing satellite to extract water boundary features, water area change data are deduced, and the water level height measurement module calculates the water level height. The meteorological wind shear analysis module obtains river channel meteorological data through a meteorological satellite, microwave scattering measurement and wind speed inversion are carried out, wind-induced shear stress parameters are generated, and the flow estimation module carries out section dynamic analysis and estimates the water flow in combination with river channel water level and water area data. And the flow correction module corrects the river water flow based on the wind-induced shear stress parameter and carries out real-time monitoring, and data are synchronously uploaded to the control terminal, so that comprehensive dynamic monitoring of the hydrological state of the river is realized. According to the invention, a more efficient multi-satellite collaborative hydrological monitoring system is realized.

The invention relates to the technical field of seepage monitoring, and discloses a seepage monitoring system based on a hydraulic engineering project. The system collects water level, flow velocity, seepage flow, soil humidity, soil temperature and soil pressure data through a data collection module, a data analysis module calculates standard soil humidity, standard water flow velocity, standard soil pressure, standard soil temperature and standard seepage flow according to the data, establishes a mathematical model, calculates seepage abnormal indexes, and calculates the seepage abnormal indexes according to the standard soil humidity, the standard water flow velocity, the standard soil pressure, the standard soil temperature and the standard seepage flow. The risk assessment and early warning module performs threshold judgment on the seepage abnormal indexes, sends out an overrun signal when an overrun condition occurs, predicts a future seepage trend by using a moving average method at the moment, generates a future seepage trend broken line graph and a seepage risk assessment report, and uniformly transmits the future seepage trend broken line graph and the seepage risk assessment report to the emergency response module; and when the emergency response module receives the overrun signal, an emergency plan is started, and related managers are informed of the emergency plan, the future seepage trend broken line graph and the seepage risk assessment report in a short message mode.

The invention belongs to the technical field of liquid level measurement and industrial process control, and particularly relates to a radar liquid level meter system fusing an adaptive algorithm and multi-modal data. Comprising a data acquisition unit, a signal acquisition and preprocessing unit, a signal denoising and optimizing unit, a data fusion and anomaly detection unit, a self-adaptive calibration and drift compensation unit and a display and alarm terminal. The system has the advantages that the radar liquid level meter, the auxiliary sensor, signal processing, data fusion, anomaly detection, self-adaptive calibration, drift compensation and other technical means are organically combined, and the system can achieve high-precision and real-time monitoring of the liquid level under the complex working condition.

The invention provides an intelligent water and soil conservation monitoring and management system, and belongs to the technical field of hydraulic engineering and environment monitoring. The data acquisition layer acquires data in real time by using an acoustic sensor network, machine vision monitoring equipment, Internet of Things monitoring equipment, satellite remote sensing monitoring, unmanned aerial vehicle inspection and other technologies. And the data transmission layer transmits the acquired data to the data processing and analyzing layer by adopting a wireless communication network. The data processing and analysis layer analyzes multi-source data through data fusion and preprocessing, GIS technology application and big data analysis and machine learning. And the decision support and application layer comprises a prevention and control measure generation and optimization unit, a real-time early warning and emergency response unit and a user interaction and decision support unit, provides a water and soil conservation and dike reinforcement strategy for a user, and has a feedback optimization mechanism. By comprehensively applying various monitoring technologies and data analysis methods, the accuracy and timeliness of water and soil loss monitoring are improved, and powerful guarantee is provided for dike safety.

The invention relates to the technical field of liquid level detection, in particular to a scrubber sewage tank water level detection system and method based on a liquid level sensor, and the system comprises a sensing data acquisition module, a liquid level signal conversion module, a multi-source numerical value comparison module, a liquid level fluctuation recognition module and an alarm action linkage module. According to the invention, through acquisition of a sensor capacitance change sequence, elimination of abnormal fluctuation, construction of a stable reference curve, enhancement of data immunity, mapping of a liquid level section based on an average capacitance value, accurate identification of liquid level elevation is realized, synchronous comparison of liquid level state information in various communication protocols is realized, and data consistency and reliability are improved. A liquid level fluctuation boundary is accumulatively recognized through trend direction change, a change section is dynamically marked, alarm triggering is based on boundary area and state mark double verification, warning response accuracy and effectiveness are enhanced, and a high-precision and high-stability liquid level detection and early warning system is constructed.

The invention discloses a transformer oil conservator oil level online monitoring method and system based on an ultrasonic technology, and belongs to the field of power equipment monitoring. The oil level of the transformer is related to equipment safety, a traditional monitoring means has defects, and false oil level is prone to misleading operation and maintenance. With the ultrasonic technology as the core, the multi-band ultrasonic sensor transmits and receives ultrasonic waves to the oil conservator, obtains oil level signals and collects oil temperature and load data at the same time. The oil level is calculated by means of ultrasonic propagation time and a multi-band weighted average algorithm, and the false oil level is discriminated according to oil temperature compensation and load correlation. Through signal conditioning and acquisition, microprocessor operation and wireless communication transmission, data is stored and analyzed in a background monitoring system. The innovative system architecture and algorithm realize high-precision oil level measurement, strong interference resistance, intelligent false oil level discrimination and real-time remote monitoring. On-site tests show that the system stably and accurately monitors complex working conditions, effectively prevents oil level abnormal faults, improves the operation and maintenance efficiency of the transformer and the power supply reliability of a power grid, and firmly guarantees the reliable operation of a power system.

The invention relates to the technical field of gate groove measurement, in particular to a dam gate groove vertical plane measurement system and method based on an intelligent sensor, and the method comprises the steps: collecting a vertical plane image, vertical plane overflowing velocity data, vertical plane water level data, vertical plane height data and vertical plane sealing pressure data of a gate groove; extracting corrosion pit data in the vertical plane image and evaluating the flatness of the vertical plane based on the corrosion pit data; evaluating the vertical plane wetting-drying alternation influence degree based on the vertical plane water level data, and obtaining the vertical plane erosion degree by combining the vertical plane flatness; and integrating the vertical surface erosion degree and the vertical surface sealing pressure data to pre-estimate the gate leakproofness, and performing gate leakproofness early warning according to a gate leakproofness pre-estimation result. According to the method, the scientificity and the accuracy of gate leakproofness evaluation are improved by quantifying the vertical plane flatness of the gate groove of the gate and the influence of the vertical plane dry-wet alternation period on the vertical plane erosion degree.

The invention provides a molten pool level online monitoring system and method, and the system comprises a data collection module, a data preprocessing module, a model training and optimizing module, an angle detection and compensation module, a nonlinear data processing module, a system testing and optimizing module, a display module, a communication module, and a control module. The online real-time monitoring of the molten pool level can be realized, the production automation level is improved, when the data acquisition module reaches a detection position, the control system triggers a signal through the coil, the camera is started to capture the images of the liquid level of the slag surface and the liquid level of the copper solution surface of the current molten pool, the online real-time monitoring function of the molten pool level is realized, and the production efficiency is improved. Compared with a traditional manual measurement or intermittent monitoring method, the method has the advantages that the detection efficiency can be greatly improved, the dependence on manual operation is reduced, and the automation level of the production process is improved.

The invention discloses an unmanned aerial vehicle inspection method and system applied to foundation pit accumulated water monitoring, and the method comprises the steps: determining an optimal route node sequence, and generating an unmanned aerial vehicle control instruction set; acquiring internal and external parameters of a multi-source sensor, and performing time alignment compensation on image frames and sensor data; acquiring a ponding area image coordinate set and attribute data; a three-dimensional projection point set of the ponding area is obtained, and the real coverage area of the ponding area is calculated; generating a three-dimensional overview map of the foundation pit by using the multi-view image of the foundation pit area; determining a three-dimensional coordinate point set and an area estimation result of the ponding area; and projecting the three-dimensional coordinate point set of the ponding area to the three-dimensional overview map of the foundation pit to generate a hidden danger monitoring report. By integrating the unmanned aerial vehicle, the sensor data and the advanced image processing technology, the accuracy, stability and visualization effect of foundation pit accumulated water monitoring are greatly improved, more reliable and comprehensive technical support is provided for safety management of foundation pit engineering, and the safety risk in the construction process is remarkably reduced.

The invention provides an urban road ponding monitoring and drainage system. The urban road ponding monitoring and drainage system comprises a monitoring module which collects ponding depth, water velocity, rainfall intensity and field image data in real time; the initialization configuration module sets parameters such as an accumulated water depth threshold value; the data transmission module encrypts and transmits data to the central control module; the model algorithm optimization module constructs a three-dimensional ponding diffusion model and outputs a predicted ponding depth and an optimized drainage strategy; the central control module generates a drainage pump rotating speed instruction and the like; the drainage execution module dynamically adjusts drainage pump power and a drainage path; the self-checking and fault-tolerant module calculates a health index of drainage equipment and switches redundant equipment; the early warning module sends risk level information; and the interaction module displays information such as a real-time accumulated water thermodynamic diagram. The urban road drainage efficiency can be improved, the water accumulation risk is reduced, and smooth urban traffic and public travel safety are guaranteed.

The invention provides a coastal water level monitoring method based on a dynamic threshold algorithm, a medium and a system, and belongs to the technical field of coastal water level monitoring. The coastal water level monitoring method based on the dynamic threshold algorithm comprises the steps that data are collected through a water level sensor array, and a water level basic matrix and a floating matrix are constructed; a dynamic warning value is calculated by applying a tidal kinetic equation and a hydrometeorological coupling equation set, efficient resource scheduling is realized by utilizing a calculation jump matrix, self-learning optimization and water level prediction are performed based on a hydrological space-time network model, and water level monitoring and prediction data are output. Early warning of different levels is triggered according to the fact that the water level reaches the minimum range or the maximum range of the dynamic warning value, warning information is pushed to the disaster management platform through the edge computing gateway, a comprehensive warning report is finally generated for emergency decision making, and intelligent monitoring and accurate early warning of the coastal water level are achieved.

The invention relates to the technical field of chemical production process monitoring, and provides a chemical storage tank liquid level real-time monitoring method and system based on image recognition, which can automatically generate an accurate illumination threshold value by applying big data analysis and machine learning technologies, can adapt to illumination changes of different chemical scenes, and can realize real-time monitoring of the liquid level of a chemical storage tank. The accuracy of liquid level monitoring under various illumination conditions is greatly improved; for image enhancement and correction, the system adopts a local region adaptive adjustment histogram equalization and optimization CLAHE technology and constructs a feature database assisted threshold segmentation and environmental parameter dynamic adjustment SFS model, so that dark environment images can be enhanced more excellently, strong light reflection can be removed, and reduction liquid level details can be cleared; according to the system, a dynamic weight updating mechanism is created for the first time, the weight is adjusted in real time according to the liquid level change and the image quality, interference of a single image is effectively avoided, and the monitoring reliability is remarkably improved.

The invention discloses an underground water level monitoring method and system, and belongs to the technical field of water level monitoring, and the method specifically comprises the steps: arranging a pressure sensor and a temperature sensor in to-be-monitored underground water, initializing the sensors, carrying out the calibration, collecting the pressure and temperature data in an underground water well in real time, and carrying out the real-time monitoring of the pressure and temperature data; the height of the underground water level is calculated and corrected according to the pressure and temperature data, filtering calibration processing is conducted on the corrected height of the underground water level, environmental noise and sensor errors are eliminated, modeling and analysis are conducted on stored historical data of the underground water level, and the future change trend of the underground water level is predicted; transmitting the finally estimated underground water level data and the predicted change trend of the underground water level, storing the data in real time and monitoring the data in real time; model parameters can be dynamically adjusted according to historical data, high-precision prediction is performed on short-term and long-term trends of the underground water level, and the method adapts to underground water level characteristics of different regions and different time periods, so that abnormal fluctuation of the underground water level is monitored in real time.

The invention relates to the technical field of magnetic core product assembling equipment, and discloses full-automatic magnetic core dispensing and terminal assembling equipment which comprises a machine base. A magnetic core feeding device, a dispensing device, a terminal feeding device, a pre-pressing detection device, an oven curing device and a magnetic core charging pipe device are sequentially arranged in the conveying direction of the conveying device, and the oven curing device is arranged on the rear side of the conveying device. A first material taking mechanical arm is arranged between the oven curing device and the conveying device, a second material taking mechanical arm is arranged between the oven curing device and the magnetic core charging pipe device, and a jig block provided with a plurality of magnetic cores is conveyed on the conveying device. The magnetic core charging pipe device comprises a material pipe distribution frame, a plug pulling assembly, a quantitative material pushing assembly and a plug assembly, wherein the plug pulling assembly, the quantitative material pushing assembly and the plug assembly are sequentially arranged on the side of the material pipe distribution frame.

The invention discloses a marine surveying and mapping method based on multi-beam sounding correction, and belongs to the technical field of marine surveying and mapping. The method comprises the following steps: acquiring sounding echo signals, sound wave propagation time delay data and temperature data through a multi-beam sonar array, an acoustic chromatography transceiving array and a laser Raman probe; and fusing the data to construct a dynamic refractive index field model, correcting sound ray refraction distortion by adopting an adaptive variable step size algorithm, carrying out weight allocation and data fusion on space-time adjacent beams to obtain high-confidence water depth, and generating an isobath topographic map. The problem of refraction distortion is solved through multi-source data fusion, the sound ray tracking step length is dynamically optimized, noise interference is suppressed through weighted fusion, and the precision and reliability of topographic surveying and mapping in complex environments such as a deep sea hydrothermal region are remarkably improved.

The invention discloses a hydropower station expansion tank water level prediction alarm method and system, belongs to the technical field of hydropower station automatic control, and aims to solve the technical problems of limited monitoring points, high false alarm rate, response delay and the like of a traditional hydropower station expansion tank water level alarm system. According to the invention, the multi-mode sensing network is constructed, and data of the pressure sensor array, the radar level meter and the float switch group are fused, so that space continuous monitoring is realized; a three-level sensing architecture is adopted, heterogeneous data is subjected to normalization processing, and dimensional differences are eliminated; the LSTM network is used for liquid level prediction, and a self-adaptive window adjustment mechanism is combined, so that the prediction flexibility and accuracy are improved; a DQN algorithm is adopted to optimize a control strategy, fine adjustment of the liquid level is achieved by adjusting the opening degree of the valve, the accuracy, timeliness and intelligent level of water level monitoring and alarming of the expansion water tank of the hydropower station are remarkably improved, the stability of the liquid level of the water tank is ensured, the system operation efficiency is optimized, the manual intervention requirement is reduced, and safety is improved.

The invention provides a water level and water quality monitoring method based on an AI technology energizing intelligent central pivot rod, which takes an AI intelligent central pivot sensing rod as a core and integrates various components such as a radar static pressure composite monitoring water level terminal, a water quality five-parameter monitoring terminal, a camera acquisition terminal and a cloud analysis full-amount meteorological sensing station. Through specific structure assembly and field installation, the device is deployed in different water areas such as inland rivers, lakes and rivers. The system collects data according to a set time interval and records environment and scene characteristic parameters. After collected data are preprocessed, adaptive lightweight model combinations are selected according to different scenes and data characteristics, a training set and a test set are divided for model training and fusion, and then the data are deployed to a monitoring terminal and verified by the test set. The system realizes intelligent data processing by means of the AI technology, has flexibility and reliability, can efficiently and accurately collect and stably transmit data, provides accurate technical support for water level and water quality monitoring, and has great significance for flood control and water body ecological protection.

The invention provides an intelligent analysis method for the oil temperature and the oil level of a transformer. The method comprises the following steps: S1, acquiring oil temperature and oil level data of a transformer, generating displacement diagrams of two data in a coordinate system, drawing an actual oil temperature and oil level curve, and comparing the actual oil temperature and oil level curve with a standard oil temperature and oil level curve given by a manufacturer; s2, generating a relation function between the oil level and the oil temperature by using the transformer oil temperature and oil level monitoring, checking and analyzing device, and performing data comparison with a standard oil temperature and oil level curve given by a manufacturer; s3, analyzing whether the deviation between the oil temperature and oil level curve and a standard oil temperature and oil level curve given by a manufacturer exceeds an allowable value or not under the high-temperature and low-temperature operation conditions; according to the invention, quantitative data analysis can be carried out on the oil temperature and the oil quantity of the oil-immersed transformer.

The invention discloses a convolutional neural network vehicle fuel consumption detection method based on ultrasonic sensors, and relates to the technical field of vehicle fuel consumption detection, and the method comprises the steps: 1, installing a plurality of ultrasonic sensor arrays on a vehicle, and monitoring the liquid level change of a fuel tank through the ultrasonic sensors; step 2, performing normalization processing on data acquired by the ultrasonic sensor, and eliminating differences caused by different measuring devices and measuring environments; and step 3, analyzing the preprocessed data through a convolutional neural network model to obtain the vehicle fuel consumption. According to the convolutional neural network vehicle fuel consumption detection method based on the ultrasonic sensor, the ultrasonic sensor is adopted, non-contact measurement is achieved, mechanical abrasion is reduced, key parameters related to fuel consumption, such as the fuel oil liquid level and the distance from a fuel spray nozzle to a combustion chamber can be accurately measured, and the fuel consumption can be accurately detected through accurate measurement of the parameters. And the actual fuel consumption of the diesel engine can be calculated more accurately.

The invention provides an underground water overdraft area water level early warning method and system, and relates to the technical field of water quality dynamic monitoring, and the method comprises the steps: building an underground water overdraft area water level early warning model based on the corrected overdraft area range and overdraft degree; inputting the water level change data monitored in real time into the underground water overdraft area water level early warning model, and performing water level early warning to obtain a preliminary early warning result; water level change data of the underground water overdraft area are monitored in real time, related dynamic influence factor data are recorded, and the dynamic influence factor data comprise the rainfall capacity, the evaporation capacity and the man-made mining quantity; calculating a dynamic factor according to the dynamic influence factor data; and correcting the preliminary early warning result through the dynamic factor to obtain a final early warning result. According to the final early warning result, when it is judged that the groundwater level is about to drop to an early warning threshold value, an early warning signal is sent out. According to the invention, the accuracy and timeliness of early warning are improved.

A locomotive sensor system includes a sensor configured to be in contact with lubricant within an engine of a locomotive. The sensor includes a sensing region circuit that is configured to generate stimuli at different times during an operational life of the engine. The system also includes one or more processors configured to receive signals from the sensor. The signals are representative of responses of the lubricant to the stimuli. The one or more processors are configured to analyze the responses and determine a characteristic of the lubricant that represents one or more of a total base number (TBN) or a total acid number (TAN) of the lubricant. The are configured to determine an unhealthy state of one or more of the engine or the lubricant based on the characteristic of the lubricant that is determined.

The invention discloses an automatic data processing method and device for a flat beach river channel and a medium. The automatic data processing method for the flat beach river channel comprises the following steps: acquiring historical observation data of a target section in a target river reach; for each historical observation frequency, determining the beach lip position of the target section at the historical observation frequency by using the observation point where the lowest point elevation is located and the riverbed elevations of the plurality of observation points at the historical observation frequency; based on the riverbed elevation of the beach lip position of the target section at the historical observation times, determining the flat beach water level of the target section at the historical observation times; and determining the actual flat beach water level of the target section according to the flat beach water levels of the target section at the plurality of historical observation times. The flat beach water level identification efficiency and accuracy can be improved.

The present invention discloses a flooding water level monitoring method and system for power facilities, including after receiving a flooding emergency response notification and a heavy rainfall defense alarm, starting facility flooding water level monitoring; and based on the individual area and total area of facilities affected by flooding and water level sensing monitoring information, establishing a neural network measuring an affected range, and outputting the monitoring result of a flooded surface height in a region, thereby achieving all-weather real-time monitoring, and accurately measuring and timely reporting a flooding height.

The present invention is a wireless vehicle tank monitoring system using non-contact fluid level sensors with adjustable sensitivity to measure fluid levels in recreational vehicle holding tanks. A smart device application on a portable computer receives real-time data via Bluetooth Low Energy (BLE) communication. The user-friendly interface displays graphical tank states. The system optimizes power efficiency through deep sleep and selective notification techniques, extending battery life. Sensors' sensitivity adapts to different tank wall thicknesses for accurate readings. The integration of non-contact sensors and power-efficient communication ensures reliability, easy installation, and real-time data transmission. This cost-effective solution effectively manages fluid levels in recreational vehicles.

The invention relates to the technical field of industrial process measurement, and discloses a high-precision liquid level measurement anti-interference calibration method, which comprises the following steps of: 1, synchronously acquiring a liquid level signal, a mechanical vibration signal, an electromagnetic field intensity signal and a temperature distribution signal through a multi-mode sensor array to form multi-physical field data; 2, constructing a hypergraph adjacency tensor based on the coupling relationship of the multi-physics field data, and generating a Laplacian matrix constraint; step 3, performing CP tensor decomposition with hypergraph constraint on an original signal tensor formed by the multi-physical field data, and separating a liquid level signal kernel from an interference kernel; and step 4, inputting the decomposed signal kernel characteristics and the sensor impedance parameters into a depth deterministic strategy gradient algorithm to realize hardware acceleration of a processing flow. A multi-physics field coupling relation is constructed through a hypergraph adjacency tensor and a Laplacian matrix, and the limitation of a traditional binary correlation model is broken through.

The invention belongs to the technical field of water conservancy monitoring, and discloses a water conservancy water level monitoring device and method, and the method comprises the steps: a monitoring point arrangement module of a monitoring mechanism reasonably arranges the number and positions of monitoring points; the flow velocity monitoring module monitors the water velocity; the meteorological data acquisition module acquires meteorological data; the echo sounder emits sound waves, and the water depth is calculated according to the sound wave propagation time and the sound velocity in water; the pressure water level gauge, the laser water level gauge and the radar water level gauge monitor the water level of water conservancy. The echo data analysis module analyzes the echo data; the comprehensive analysis module comprehensively analyzes the water level; the predictive analysis module predicts a water level trend and potential risks. The water level of water conservancy is monitored through various water level gauges, cross validation and high precision are achieved, and the sediment deposition thickness is accurately calculated by analyzing echo data; the comprehensive analysis module comprehensively evaluates the water level; the prediction analysis module integrates various monitoring equipment data and meteorological data, and predicts the water level trend and potential risks.

The invention relates to the technical field of water flow monitoring, and particularly discloses a flow monitoring method and system based on video image analysis and processing. The method comprises the following steps: carrying out communication acquisition of image monitoring and water level monitoring at a plurality of monitoring acquisition sites; performing video frame extraction and image preprocessing; feature point detection and displacement analysis; converting the water surface flow velocity into a plurality of station water surface flow velocities, and performing fitting correction; and calculating station flow data of the plurality of monitoring acquisition stations. Water surface image data are obtained through image monitoring and water level monitoring communication collection of a plurality of monitoring collection sites in combination with video frame extraction and image preprocessing, the site pixel flow velocity is calculated through feature point detection and displacement analysis, the site pixel flow velocity is converted into corrected water surface flow velocity through a space projection model, and site flow data are calculated. Non-contact full-flow monitoring is achieved, the potential safety hazard that equipment needs to be arranged in water in a traditional method is eliminated, the maintenance difficulty is remarkably reduced, and the method is particularly suitable for flow monitoring in flood periods and dangerous water areas.

A fault detection method and equipment for a drainage pipe network, a server, and a storage medium. In the fault detection method for the drainage pipe network, a liquid level time sequences of monitoring nodes in the drainage pipe network can be collected, and an abnormal event type of the current node may be identified according to the liquid level time sequences. After the abnormal event type is determined, a fault diagnosis algorithm corresponding to the abnormal event type can be adopted to perform hydraulic feature matching on the liquid level time sequence of the current node and the liquid level time sequence current node corresponding to a neighbor neighboring node, to obtain a fault diagnosis result corresponding to the current node.