1147results about "Fluid-tightness measurement" patented technology

The invention provides a civil air defense engineering concealed conduit leakage positioning method based on acoustic characteristics, and belongs to the technical field of civil air defense engineering. An acoustic signal acquisition network is constructed by deploying a high-sensitivity hydrophone array, and signals are preprocessed by using a time division multiple access technology and a pulse compression technology; and carrying out time-frequency analysis by applying wavelet transform to extract acoustic features. A time reversal mirror technology is introduced to identify direct propagation and multipath reflection signals, a fluid acoustic coupling propagation equation is constructed to analyze a leakage sound source mechanism, and pipe network topological information and a sound wave speed correction function are combined to compensate a measurement error. Wherein the deep learning pipe network acoustic propagation multi-modal model is fused with a pipeline structure encoder, an acoustic feature extractor and a position prediction decoder, and high-precision leakage positioning and degree evaluation in a complex environment are realized through a three-stage pre-training strategy; the technical problem that it is difficult to accurately locate the position of a leakage point in the complex pipe network environment of civil air defense engineering is solved.

The invention provides an outer wall leakage point positioning detection method and system based on infrared thermal imaging, and relates to the technical field of computer vision, and the method comprises the steps: firstly collecting a multi-period infrared thermal imaging data set of a target building outer wall, covering a surface temperature distribution matrix at different environment temperatures, and then carrying out the dynamic temperature correction processing, the method comprises the following steps of: forming a standardized temperature distribution set for eliminating the influence of environment temperature fluctuation, extracting a thermal characteristic parameter set containing the characteristics of temperature gradient distribution and the like from the standardized temperature distribution set, calling a pre-trained thermal anomaly detection model to carry out leakage risk probability mapping on the thermal characteristic parameter set, and generating a leakage point probability distribution diagram; and finally, performing region segmentation processing according to the leakage point probability distribution diagram and a preset dynamic judgment threshold value, outputting a leakage point positioning coordinate set and a corresponding leakage strength grade identifier, and realizing accurate positioning and strength grade identification of the leakage points of the outer wall.

The invention relates to the technical field of methanol safety monitoring, in particular to a methanol leakage prediction system based on artificial intelligence. According to the method, structural extraction of potential leakage paths is realized through dynamic sorting and surge correlation combination of methanol concentration change trends in continuous time periods, and weighted calculation is carried out on conduction characteristics between monitoring nodes in double dimensions of time series and spatial topology by virtue of a graph attention mechanism, so that the detection accuracy of the leakage paths is improved. The method comprises the following steps: establishing a path, forming quantitative expression of node influence factors in the path, capturing synchronous abnormal behaviors under an environment disturbance background through a multi-parameter coupling sudden change identification mode of air pressure and wind speed, further constructing a high-timeliness sudden change event set, and performing index fusion on the influence degree and sudden change frequency of monitoring nodes on the basis to obtain a high-timeliness sudden change event set. And space risk score distribution is formed, and a leakage possibility region prediction map is generated in combination with two-dimensional coordinates, so that boundary fine depiction of a high-risk region is realized.

The invention relates to the technical field of gas leakage detection, and discloses an infrared imaging radiation correction method and system for gas leakage detection, and the method comprises the steps: obtaining the distribution data of dark current noise, and the mapping relation parameters of an image gray value and a radiation brightness value; acquiring infrared radiation of the gas leakage scene by using an infrared detector to obtain an original infrared image; based on the distribution data of the dark current noise, performing pixel-by-pixel compensation on the original infrared image to generate an infrared image after dark current correction; extracting the radiation intensity distribution of the infrared image after dark current correction, calibrating the radiation value of each pixel in the infrared image based on the mapping relation parameter between the image gray value and the absolute radiation brightness value, converting the image gray value into the absolute radiation brightness value, and generating the infrared image after radiation calibration; and outputting an infrared image after radiometric calibration for subsequent gas leakage area identification and feature analysis. According to the invention, a high-quality and quantifiable radiation quantification image can be output.

The invention discloses an optical fiber embankment underwater piping leakage event time-space correlation analysis method, and relates to the technical field of leakage event intelligent identification and risk assessment in embankment safety monitoring, and the method comprises the following steps: S1, obtaining continuous time-space monitoring data of an embankment underwater region obtained through monitoring by a distributed optical fiber sensing system; and S2, processing the continuous space-time monitoring data by adopting a feature recognition model based on a neural network, and recognizing a suspected leakage event. According to the time-space correlation analysis method for the underwater piping leakage event of the optical fiber embankment, by fusing multi-level data processing and self-adaptive feature learning, false alarms caused by environmental interference are effectively restrained, and the recognition accuracy of a real leakage event in a complex underwater scene is improved. An analysis framework combining space-time association diagram construction and physical mechanism verification is adopted, the internal relation between events can be deeply mined, and the space-time evolution rule of a seepage path is accurately restored.

The invention relates to a tunnel lining leakage infrared-millimeter wave fusion detection method and system, and belongs to the technical field of civil engineering detection, and the method comprises the steps: obtaining high-density millimeter wave radar data and thermal infrared imager data; performing data preprocessing to realize space alignment and time synchronization; topological features are extracted, manifold learning mapping is carried out on the preprocessed millimeter wave radar data, and a topological signature matrix is constructed; multi-phase spectrum analysis is carried out, nonlinear phase space reconstruction and multi-scale entropy feature analysis are carried out on the preprocessed infrared thermal imager data, and an entropy feature map is obtained; probability fusion and progressive reasoning are executed, and a leakage area probability graph is generated through a conditional random field model and a progressive belief propagation algorithm; the method overcomes the limitation of a single sensor detection method, achieves the high-precision detection and quantitative evaluation of the leakage of the tunnel lining, and has the technical effects of high detection accuracy, high environmental adaptability, high automation degree and the like.

The invention discloses a real-time target detection and intelligent identification system and method based on an unmanned aerial vehicle image, and relates to the technical field of image target detection. According to the invention, the dual-mode sensor is carried, and pixel-level data alignment is realized through a space-time synchronization error control matrix; a dynamic feature fusion module is utilized, and differential representation of visible light and methane data is captured and concentration-space joint features are enhanced through cross-modal weight learning, leakage feature perception and an adaptive fusion unit; a region attention calculation module is constructed, sub-region attention scores are generated based on multi-dimensional data such as historical leakage records and pipeline density, and resource priorities are dynamically distributed and calculated; and the model optimization module combines the attention level and the real-time computing power load, and dynamically adjusts the channel resources through a reference retention ratio and a dynamic pruning strategy.

The invention discloses an anesthesia equipment fault diagnosis method and system based on image recognition, particularly relates to the technical field of medical equipment fault detection, and is used for solving the problem that a non-contact image detection method in existing anesthesia equipment pipeline leakage detection is poor in transparent pipeline weak leakage signal recognition capability. Through combination of multispectral dynamic imaging and polarized light scattering mode analysis, pipeline surface microscopic deformation characteristics are obtained, and a leakage path prediction result is generated. Environmental reflective noise is inhibited based on spectral distribution characteristics of the reference image set, optical response changes of the candidate area are triggered in combination with active pressure disturbance, and the inverse proportion physical relation between the permeation rate and the fluid conduction speed is verified; through dynamic threshold screening and spatial continuity verification, accurate positioning of a target area is realized, finally, spectral features, path forms and real-time pressure parameters are fused to generate leakage risk assessment, non-intrusive high-sensitivity leakage identification is realized, and reliable guarantee is provided for safe operation of clinical anesthesia equipment.

The invention discloses a fire-fighting non-destructive detection method based on multi-modal detection, and relates to the technical field of fire-fighting engineering, and the method comprises the following steps: carrying out the rapid scanning of fire-fighting equipment through an ultrasonic array, analyzing and positioning a suspected defect region based on a time domain reflection signal, and generating a three-dimensional coordinate mapping model; and performing multi-angle X-ray projection acquisition on the positioning area, and generating an internal structure cross-sectional image through a three-dimensional reconstruction algorithm. According to the fire-fighting non-destructive detection method provided by the invention, by integrating various technical means such as ultrasonic array scanning, X-ray tomography, thermal imaging analysis and microwave sealing detection, comprehensive and accurate identification of potential defects of fire-fighting equipment is realized, and the dimensionality and precision of defect detection are improved; the structural integrity of the equipment is kept to the maximum extent, extra risks caused by destructive detection are avoided, and the reliability and accuracy of detection are improved through a data fusion algorithm.

The invention relates to the technical field of oil and gas transmission, and discloses an intelligent leakage early warning flexible composite pipeline system and an early warning method.The system comprises a composite pipeline body, an optical signal processing device and a data processing unit, and the optical signal processing device is in communication connection with the data processing unit to achieve data transmission. The early warning method corresponds to the system. According to the invention, intelligent leakage early warning and monitoring of the flexible composite pipeline system are realized; the distributed temperature sensing element can sense the temperature change of the pipeline; the optical signal processing device converts the laser signal into an electric signal and transmits the electric signal to the data processing unit; the data processing unit calculates the on-way temperature and the leakage position of the pipeline and gives an alarm for abnormal data; the problem that a traditional flexible composite pipe lacks a sensing function is solved, environmental pollution and energy loss caused by pipe transportation oil gas leakage are effectively reduced, safety and stability of oil gas transportation are guaranteed, and the intelligent development of the composite pipeline industry is promoted.

System and associated methods relate to detecting and responding to hydrogen leakage in an aircraft. The system includes a hydrogen tank and a fuel pipeline surrounded by an enclosed chamber. The system further includes one or more vacuum pumps fluidly coupled to the enclosed chamber to create the control volume vacuum. The system further includes vacuum sensors mounted within the control volume vacuum, configured to sense a vacuum pressure value. The system further includes hydrogen detectors fluidly connected downstream of the one or more vacuum pumps, configured to sense the hydrogen concentration of the exhaust from the one or more vacuum pumps. The system further includes a controller and an emergency vacuum. The controller is configured to evaluate whether an emergency hydrogen leak condition exists based upon the vacuum pressure value and the hydrogen concentration. The controller can then open a valve to operate emergency vacuum if necessary.

A navigation apparatus for use in navigating a pipe includes a body, a movable core coupled to the body by a sacrificial connector, and a drive assembly configured to engage an interior wall of the pipe to propel the navigation apparatus through the pipe. The drive assembly including a first arm, a second arm, and a wheel, wherein the first arm is pivotably coupled to the core and the wheel, and the second arm is pivotably coupled to the body and the wheel.

The invention relates to an industrial gas tank storage place early warning method and system. The method comprises the following steps: acquiring image time sequence data at least representing temperature field distribution of a target monitoring area, generating a temperature image sequence, determining area temperature change characteristics and tank body surface reflection characteristics in the area, and generating reflection area probability distribution of the target monitoring area to determine initial gas leakage probability data of the target monitoring area; generating baseline feature data at least representing background thermal field distribution of the target monitoring area; and performing association processing on the initial gas leakage probability data and the baseline feature data to generate fusion time sequence features and determine a gas leakage diffusion weight so as to correct the initial gas leakage probability data to obtain corrected gas leakage probability data. By adopting the method, the gas leakage probability can be accurately judged by comprehensively utilizing temperature field time sequence information, tank body surface reflection characteristics and background thermal field distribution characteristics under the condition of a complex background thermal field, so that early warning is realized.

The invention relates to the technical field of packaging quality detection, and discloses an aluminum foil sealing quality detection system, which comprises a transmission module, a detection module and a control module, the thermal imaging acquisition module is used for acquiring temperature distribution data of a sealing area on the to-be-detected container; the image processing module is used for analyzing the temperature distribution data based on an image recognition algorithm and extracting defect characteristics of the aluminum foil seal; the temperature calibration module is used for dynamically calibrating the thermal imaging acquisition module according to preset parameters; the sorting module is used for removing defective products from the conveying module according to the extracted defect features; and the intelligent decision module is used for integrating the detection data and the production parameters, generating process optimization suggestions and outputting regulation and control instructions. According to the system and the method, high-precision real-time detection and classification of aluminum foil sealing defects are realized, and meanwhile, the automation level, the detection stability and the quality control efficiency of a production line are improved through dynamic sorting and process optimization suggestion output.

The invention provides a molecular air chamber leakage rate detection method, electronic equipment and a detection system, and the method comprises the steps: testing the spectrum data of a to-be-detected molecular air chamber; calculating the full width at half maximum of the wave spectrum data according to the wave spectrum data; and determining the leak rate of the molecular air chamber to be detected based on the full width at half maximum obtained at multiple times. According to the method, the degree of purity in the molecular air chamber cannot be affected under the condition that the leak rate detection precision of the molecular air chamber is better guaranteed.

The invention provides a method and a device for detecting damage points of a drainage pipe network. The method comprises the following steps: acquiring water quality fluorescence fingerprint data corresponding to upstream and downstream target inspection nodes of the drainage pipe network respectively; performing water quality fluorescence fingerprint similarity comparison based on the water quality fluorescence fingerprint spectrum data to obtain a water quality fluorescence fingerprint similarity result between the upstream and downstream target inspection nodes; based on the water quality fluorescence fingerprint data of the upstream target inspection node and the water quality fluorescence fingerprint data of the downstream target inspection node, obtaining a water quality fluorescence fingerprint intensity change value between the upstream target inspection node and the downstream target inspection node; and based on the water quality fluorescence fingerprint similarity result and the water quality fluorescence fingerprint intensity change value, determining a comprehensive judgment result of damage between the upstream and downstream target inspection nodes of the drainage pipe network. The method provided by the invention is high in detection sensitivity and simple and convenient to operate, and can effectively improve the efficiency and accuracy of drainage pipe network damage result detection, so that the economic cost and the time cost are greatly reduced.

The invention provides an engine gas circuit pipeline blockage monitoring and early warning method and device, and the method comprises the steps: (1) arranging a vibration collection device on an engine gas circuit pipeline, obtaining vibration data of multiple working conditions, and dividing the vibration data into a training set, a verification set and a test set; (2) calculating a spectrum centroid, a short-time zero-crossing rate and a short-time energy feature, and fusing by using a cross attention mechanism to generate a multi-granularity feature; (3) introducing a channel attention module, a space attention module, a multi-view bidirectional LSTM module and a multi-scale self-attention module, and capturing subtle difference features of the vibration signals; (4) designing a conditional fault feature diffusion module and a progressive interlaced learning strategy, and improving the generalization ability and adaptability of the model on different models of engines through feature domain distribution bridging and alternate optimization; and (5) inputting test set data into the model, accurately judging the blockage degree according to classification scores, covering three states of unobstructed, semi-blocked and blocked, and realizing multi-level blockage monitoring and early warning of the gas path pipeline of the engine.

The utility model discloses a watertight connector leakage and damage monitoring device based on a fiber grating. The device comprises a watertight connector socket, a watertight connector plug and a fiber grating sensor, the watertight connector plug is inserted into the watertight connector socket, and the fiber grating sensor is arranged in a monitoring hole of the watertight connector socket. According to the utility model, the fiber grating sensor is used for monitoring the watertight connector, so that real-time and accurate monitoring of leakage and damage of the watertight connector is realized, and the limitation of a traditional manual inspection method is effectively overcome.

A system of evaluating a mobile device includes a sensing device that captures data while a force is being applied to a display of the mobile device while the mobile device is held stationary; and a processing device to process the data and determine the force applied and a displacement of the display while the force is being applied.

SOLUTION: A gas leakage detector may include a movement control unit for controlling the movement of a mobile body to which a gas sensor is mounted. The gas leakage detector may include an acquisition unit for acquiring a target gas measurement result having been measured by the gas sensor while the mobile body is moving in a target area and a response time from when the gas sensor started measurement to when it outputs the measurement result. The gas leakage detector may include a detection unit for detecting the leakage of the target gas in the target area on the basis of the measurement result and the response time. The detection unit may detect leakage of the target gas in the target area and identify a gas leakage point on the basis of the measurement result and location information of the mobile body.SELECTED DRAWING: Figure 1

The present application relates to the field of crane pipe leak testing, and specifically discloses a crane pipe leak testing system for liquid chlorine unloading. The crane pipe includes a fixed pipe and a movable pipe, and a heat insulation structure is arranged on the fixed pipe and the movable pipe; the heat insulation structure is used to insulate the inside of the fixed pipe and the movable pipe; a temperature detection component for obtaining the temperature of the heat insulation structure is arranged at the heat insulation structure; a socket matching the filling port of the tank truck is formed on the fixed pipe; the movable pipe is inserted into the socket so that the fixed pipe and the movable pipe form a closed loop; a gas thermal imaging component is arranged on the fixed pipe, and the gas thermal imaging component forms a gas detection area, and the gas detection area covers the movable pipe. The present application has the effect of ensuring that the liquid chlorine will not be vaporized when unloading the truck, and better protecting the crane pipe, while using the temperature detection component and the gas thermal imaging component to detect the temperature outside the heat insulation structure, and when the crane pipe leaks, it will cause the temperature outside the heat insulation structure to change significantly, thereby using liquid chlorine to directly perform leak testing.

The invention discloses a smart city gas pipeline safety intelligent monitoring method based on digital twinning, and relates to the technical field of gas pipeline monitoring, and the method comprises the steps: building a gas pipe network digital twinning body of a target city gas pipeline based on digital twinning technology simulation; performing pipeline state calculation on a monitoring blind area pipeline section in the gas pipe network by using an interpolation prediction algorithm and a fluid simulation technology to generate a global monitoring data sequence network; performing pipeline leakage risk prediction on the plurality of pipeline sections according to the global monitoring data sequence network, outputting a plurality of pipeline leakage risk indexes, and constructing a pipeline leakage risk thermodynamic diagram; and identifying and marking a high-risk leakage area as a priority inspection area in the pipeline leakage risk thermodynamic diagram, generating an inspection work order based on the priority inspection area, and assigning the inspection work order to an inspection personnel terminal for manual inspection of pipeline leakage. The technical problems of low efficiency and poor early warning effect caused by blindness of gas pipeline inspection in the prior art are solved.

Systems and methods include a sensor device for detecting passing valves. The sensor device includes a housing including a first side configured to contact a wall of a pipe in a pipe system. A cover plate is coupled to a second side of the housing opposite the first side. A piezoelectric sensor is disposed in the housing and configured to detect acoustic emissions from a valve in the pipe system. A sensor holder is disposed within the housing to maintain a position of the piezoelectric sensor. A spring is positioned around a portion of the sensor holder and configured to bias the sensor holder away from the cover plate and toward the first side of the housing. A computer system is mounted to the housing and configured to determine that a valve is a passing valve based on acoustic emissions detected by the piezoelectric sensor.

The present invention discloses a rock and soil leakage detection device with distributed optical fiber temperature measurement, which relates to the technical field of rock and soil leakage detection. The device comprises longitudinal steel bars, transverse steel bars connected to the longitudinal steel bars, a second limiting buckle sleeved on one end of the longitudinal steel bars, a first connecting block provided with a latching unit on both sides, two ends of a sensing optical cable connected to an external optical fiber demodulator, and a heating wire inside the sensing optical cable connected to an external heating control module. The present invention provides a connection processing part, and when one end of the sensing optical cable passes through the second hanging ring, the sensing optical cable is pulled toward the first connecting block, so that the second hanging ring is pulled upward by the pulling force of the sensing optical cable, thereby preventing the sensing optical cable between the first connecting block and the second hanging ring from bending irregularly, so that the sensing optical cable is laid in an S-shaped regular manner on one side of the steel cage, thereby preventing the sensing optical cable from bending irregularly and affecting the calculation of the leakage point.

The invention relates to the technical field of infrared thermal imaging, in particular to a gas leakage quantitative calibration method and system based on multispectral feature fusion, and the method comprises the steps: configuring a multiband blackbody radiation source; building a simulated gas cloud cluster environment, obtaining configuration parameters in real time, and performing classified collection on the configuration parameters to construct a four-dimensional parameter space; acquiring infrared thermal imaging data corresponding to the simulated gas cloud cluster environment, and associating the infrared thermal imaging data with the four-dimensional parameter space to form a structured sample set; sharing the structured sample set by using a dual-channel 3D-CNN to extract radiation intensity features and cloud cluster morphological features, and splicing the radiation intensity features and the cloud cluster morphological features to obtain a fusion feature vector; non-linear mapping based on deep learning is carried out on the fusion feature vector to output a concentration prediction value; and introducing an atmospheric transmission correction factor to correct the concentration predicted value so as to obtain a concentration accurate value. The method has the effect of improving the accuracy of gas leakage concentration calibration.

The invention provides an underwater robot sealing state evaluation method, and relates to the technical field of information, and the method comprises the steps: collecting depth change data and water pressure gradient fluctuation information during the operation of an underwater robot, carrying out the high-frequency sampling of the position of a sealing joint, obtaining the change trend of environment parameters around a sealing surface, and calculating the sealing state of the underwater robot; obtaining a preliminary environment dynamic distribution result; performing filtering and feature extraction on the water pressure gradient fluctuation data according to the preliminary environment dynamic distribution result to obtain dynamic response data of the stress state of the sealing surface, and analyzing the water pressure fluctuation frequency and fluctuation amplitude to determine periodic features of gap deformation of the sealing surface; generating a dynamic strategy adjustment instruction according to the abnormal state distribution of the sealing joint, and obtaining operation parameter configuration after the adjustment instruction is executed; and synchronously transmitting the adjusted operation parameter configuration and the sealing joint state monitoring data to an underwater robot control system, and updating the operation load distribution of the sealing joint in real time to obtain optimized equipment operation state data.

The invention relates to the field of fusion devices, and discloses an acceptance inspection method and device for a cold shield device, the cold shield device comprises a plurality of cold shield sectors, each cold shield sector comprises an outer panel, an inner panel and a connecting assembly, the outer panel is provided with a half window, and the half windows between partial adjacent two of the plurality of outer panels are arranged adjacently; the method comprises the following steps: mounting a plurality of window fixing plates on a test bracket; the half window of the outer panel is installed on the window fixing plate in a matched mode, and the half window, the inner panel and the connecting assembly are assembled to form a cold screen sector; and scanning the cold shield sector to obtain measurement data, comparing the measurement data with theoretical data of the theoretical model of the cold shield sector to obtain a comparison result, and determining whether the cold shield sector is qualified or not according to the comparison result. According to the invention, the supporting and stress states during real assembly can be simulated for the assembly of the cold shield fan section, and the quality control of the cold shield fan section in the manufacturing and acceptance handover process can be realized.

The invention discloses a pipe network large circulation system for a direct drinking water pipeline, which is combined with five functional modules, namely an intelligent monitoring module, a water leakage monitoring module, a pressure adjusting module, a health assessment module and an intelligent operation and maintenance module to form a set of integrated pipe network management system based on multi-source perception, intelligent analysis and visual decision. Compared with the prior art, the system has the advantages that the accuracy of pipeline abnormity identification, the positioning efficiency of a water leakage problem, the response timeliness of pressure regulation and the scientificity of health assessment are remarkably optimized, and meanwhile, data-driven pipe network full-life-cycle management is realized through an intelligent operation and maintenance means. On the whole, the system has remarkable technical progress and application value in the aspects of improving the intelligent level of an urban water supply system, guaranteeing water supply safety and operation economy and the like.

The invention discloses an intelligent monitoring and positioning method and device for oil pipeline leakage. The method comprises the steps that optical fiber temperature and vibration signals are collected; constructing a deep convolutional neural network fusion model based on the optical fiber temperature and the vibration signal; and collecting real-time optical fiber temperature and vibration signals, inputting the real-time optical fiber temperature and vibration signals into the deep convolutional neural network fusion model for identification, performing pipeline leakage state identification according to an output classification result, and performing leakage point positioning according to an output regression result. According to the intelligent oil pipeline leakage monitoring and positioning method and process based on the distributed optical fiber temperature and vibration sensor, the leakage state of the pipeline can be intelligently predicted, the accurate leakage position can be given, and a decision is provided for a pipeline operator to take timely pipeline maintenance measures.

The invention discloses a dam leakage channel detection and danger elimination quality evaluation method based on transient electromagnetism, and relates to the technical field of earth and rockfill dam danger elimination and reinforcement. The method comprises the following steps: A, leakage channel detection: A1, data acquisition: performing data acquisition on a dam by adopting pull-type small loop transient electromagnetic equipment to obtain original electromagnetic signal data; a2, forward modeling: performing forward modeling on the acquired data, and calculating a theoretical attenuation curve and apparent resistivity distribution by considering special boundary conditions of the dam; and A3, carrying out inversion calculation. According to the method, leakage signals can be accurately captured based on the high sensitivity of a transient electromagnetic method to a low-resistance body, the used pull-type small-loop transient electromagnetic equipment is convenient to operate, a dam can be comprehensively covered by combining reasonable measurement point arrangement, forward modeling and inversion calculation can comprehensively consider various factors, the position and depth of a leakage area are determined, and the detection accuracy is improved. Compared with a traditional method, the method has obvious advantages in detection depth and accuracy.