9063results about "Material resistance" patented technology

The invention relates to the technical field of sensor detection, and discloses a detection method and device based on a multi-mode gas sensor, and the method comprises the following steps: carrying out blending processing on a metal oxide semiconductor and a conductive material to obtain a bimodal nano composite material, and creating a multi-mode gas detection module, the preprocessed multi-mode signal data is acquired and obtained; acquiring and analyzing data of the temperature sensor and the humidity sensor to obtain environmental factor compensation parameters; performing adaptive calibration processing on the preprocessed multi-modal signal data according to the environmental factor compensation parameters to obtain calibrated multi-modal signal data; constructing a multi-input neural network model based on the calibrated multi-modal signal data, and training to obtain a gas recognition model; multi-mode signals collected and calibrated in real time are analyzed and judged based on the gas recognition model, gas type and concentration information is obtained, and high-precision and high-reliability gas detection is achieved.

The invention provides a soil fertility quality analysis method and system based on corn planting cultivated land, and relates to the technical field of soil quality analysis and evaluation.The soil fertility quality analysis method comprises the steps that a visible-near infrared spectrum image of a soil sample is collected, reflectivity data of a key wave band is extracted from the spectrum image, and a soil health index and a nutrient balance index are calculated; calculating a soil fertility quality comprehensive score for comprehensively evaluating the soil fertility according to the soil health index, the nutrient balance index and the soil moisture content; comparing the comprehensive score of the soil fertility quality with a preset threshold value, and evaluating the soil fertility; a machine learning model is introduced, historical soil data is trained and predicted, a quality analysis model is constructed based on a random forest algorithm, the trained quality analysis model is put into use, and new data is continuously learned to dynamically adjust and update, so that the soil detection process is simplified, and the soil fertility change can be monitored in real time. And agricultural managers are helped to make scientific decisions.

The invention relates to the field of water quality pollution traceability, in particular to a water quality pollution traceability analysis method and system based on an intelligent unmanned ship. The method comprises the following steps: acquiring a multi-mode network monitoring parameter of a real-time position based on a multi-mode communication module, performing a dynamic multi-mode network intelligent switching decision, and constructing an intelligent multi-mode network switching strategy; real-time water area multi-dimensional water quality monitoring parameters of the intelligent unmanned ship are obtained according to the multi-dimensional water quality sensor, abnormal pollution parameter change detection is carried out, and abnormal change pollution parameters are marked; performing reverse water quality spatial change analysis and gradient descent iterative traceability calculation on the abnormal change pollution parameters to generate a potential pollution diffusion path; and performing intelligent traceability cruise according to the potential pollution diffusion path, and tracking and positioning the polluted water source to obtain a polluted water source point. According to the invention, efficient and accurate water quality pollution traceability is realized.

The invention relates to the technical field of concrete detection, in particular to a dynamic detection and analysis method and system for early performance of ultra-high performance concrete. According to the technical scheme, the method comprises the steps of establishing a raw material characteristic spectrum library based on multi-physics field coupling, constructing a dynamic detection array based on a time sequence, developing a multi-modal data fusion algorithm, establishing a nonlinear coupling effect decomposition model and implementing dynamic parameter inversion. According to the method, a technical chain of four-dimensional monitoring network-multi-physics field coupling analysis-cross-scale prediction-adaptive regulation and control is constructed, so that dynamic accurate detection and intelligent regulation and control of the early performance of the ultra-high performance concrete are realized, and the technical bottlenecks of a traditional method in the aspects of parameter coupling, cross-scale association and real-time regulation and control are solved; the early performance prediction precision and the maintenance efficiency are remarkably improved, the cracking risk is reduced, and reliable technical support is provided for application of the ultra-high performance concrete in major engineering.

The invention discloses a transient electromagnetic three-dimensional dike leakage hidden danger detection method based on unmanned aerial vehicle carrying, and the method comprises the steps: S1, scanning a detection region range, obtaining dike terrain remote sensing image and point cloud image data, and setting a flight path of an unmanned aerial vehicle according to a preset detection region range; s2, performing task flight, and transmitting transient electromagnetic pulse signals with different frequencies to the underground of the dike through a transmitting coil according to a transmitting current frequency range; s3, a receiving coil is used for synchronously collecting secondary electromagnetic response signals generated by underground medium induction, discretization sampling is conducted on the collected signals according to the sampling time interval, and a sampling data sequence is obtained; s4, constructing a three-dimensional resistivity model of the dike underground medium through a three-dimensional inversion algorithm; and S5, through the constructed three-dimensional resistivity model, multi-dimensional features of the leakage hidden danger are extracted, and an area with the leakage hidden danger in the dike is identified. The leakage hidden danger area can be rapidly identified, and the detection efficiency and precision are improved.

The invention discloses a silver paste coating conductive uniformity test system and a test method, particularly relates to the technical field of silver paste coating conductive test, and is used for solving the problem that the silver paste coating conductive uniformity test is inaccurate. Through a high-precision pressure sensor and a camera device, contact state data of a probe are monitored in real time at each measuring point, a contact state matrix is generated to support accurate correction of contact resistance, after collected data are subjected to standardization processing, a support vector regression model is used for capturing a nonlinear relation, and the accuracy of the contact resistance is improved. The method comprises the following steps: optimizing a compensation model through cross validation and parameter tuning, setting an optimal pressure range to stabilize a contact condition and smoothly process data, correcting time deviation by adopting a multi-channel data acquisition and distributed sampling synchronization algorithm, correcting an error in combination with a compensation coefficient, and finally calculating a conductivity uniformity index through a resistance data matrix. Heat map classification evaluation is generated, a low-degree uniform region is repaired, and the consistency and reliability of a conductive uniformity test are remarkably improved.

The invention relates to the technical field of water pollution detection, in particular to a water quality pollution multi-dimensional analysis system which comprises the following steps: synchronously measuring an ultraviolet-visible absorption spectrum of a water sample to be detected and scattered light intensity in an orthogonal direction, and deducting spectrum baseline interference caused by suspended particulate matters in the water sample through a correction algorithm; the interferents in the water sample are selectively converted and degraded by applying a programmed potential to the inflowing water sample to be detected; the reverse pulse is periodically applied, so that the online regeneration function of the electrode is realized; analyzing the spectral data by adopting a multivariate correction algorithm, and calculating the concentration of the target pollutant; the calculation residual error of the multivariate correction algorithm is analyzed, new interference and system performance drift of current measurement are diagnosed, and a corresponding system state code is generated; and responding to the system state code, automatically starting and carrying out state checking and multi-point calibration on the instrument, and using a calibration result to update the analysis model. Through multi-dimensional perception and closed-loop operation, accuracy and reliability of water quality monitoring are guaranteed.

The present invention relates to the technical field of bioenvironmental science. Provided are an auxiliary chlorophyll content prediction method and system for a few-shot water body. The method comprises: acquiring related data of a water body; preprocessing the data to obtain an ideal data set; calculating an average impact value, and performing dimension reduction operation processing on the ideal data set; setting a hybrid training set and a test set, and setting a weight and a sample update coefficient for each sample; combining the data set and a weight vector, training a basic weak regression model, and continuously updating sample weights; continuously and repeatedly establishing models, storing and recording each weak regression model, and finally selecting a regression model having the best effect as a strong regression model; and inputting a test sample into the strong regression model, so as to obtain a predicted chlorophyll value of the test sample. In the present invention, the correlation between a water environment impact factor and chlorophyll and the correlation between different water environments are used to establish, for a chlorophyll prediction process, a chlorophyll prediction model having a low cost and a high generalized performance.

The invention relates to the technical field of signal acquisition, and discloses a signal acquisition method and system for an MEMS gas sensor array, and the method comprises the steps: carrying out the analog-to-digital conversion and temperature and humidity compensation of resistance value signals synchronously acquired by a plurality of sensing units in the MEMS gas sensor array, and obtaining a compensated response matrix; performing fast Fourier transform and dynamic feature extraction to obtain a frequency domain feature matrix of each sensing unit; performing sensing unit crosstalk coefficient calculation and response component decoupling to obtain a decoupling feature vector; carrying out Hilbert transform and adsorption-desorption characteristic extraction to obtain a gas sensitive characteristic sequence; inputting a self-adaptive power spectrum analysis model to carry out cross sensitivity identification processing to obtain a target gas response component; according to the method, the accuracy of target gas detection and concentration quantitative analysis is improved.

The invention relates to the technical field of gas detection, and discloses a gas detection method and device based on an MEMS gas sensor array. The method comprises the following steps: performing grouping and detection data acquisition on a plurality of MEMS gas sensors according to target gas types to obtain an original detection data set; performing curve fitting and feature extraction to obtain a feature parameter set, and constructing a sensor array feature model; correcting the original detection data set to obtain standardized response data; extracting a plurality of response characteristic quantities and inputting the response characteristic quantities into an unknown input observer for residual calculation and signal abnormal point identification to obtain abnormal response data; performing piecewise linear regression and dynamic calibration to obtain a target detection data set; and inputting the target detection data set into the sensor network model for array deployment optimization to obtain an array deployment optimization scheme. The adaptive deployment optimization of the sensor array is realized, and the space coverage efficiency of the detection network is improved.

The invention provides a method for measuring the conductivity and the inner diameter of a pipeline based on sweep frequency eddy current. The method comprises the following steps: establishing an eddy current detection device, designing an absolute eddy current detection coil, placing the coil in a metal pipeline, arranging the coil and the pipeline coaxially, introducing alternating current to excite an alternating magnetic field, and inducing eddy current on the surface and the near surface of the pipeline; establishing a metal pipeline eddy current analysis theoretical model, setting coil geometric parameters, and calculating an analysis expression of coil impedance changing along with excitation frequency; calculating the peak frequency and the corresponding phase value of the impedance phase of the coil in a frequency sweep mode, respectively changing the conductivity and the inner diameter of the pipeline, extracting the corresponding peak frequency and phase value, and constructing an inner diameter relation model based on quadratic curve fitting and a conductivity relation model based on power function fitting; and inverting the inner diameter and the conductivity of the metal pipeline by combining a coil impedance sweep frequency phase measurement result. The method can be used for simultaneously measuring the conductivity and the inner diameter of the pipeline, and is suitable for nondestructive testing and performance evaluation of the metal pipeline.

The invention discloses an electronic nose device which comprises a shell, a detection assembly, an air curtain cover and a power assembly. The shell is provided with an air inlet channel and an air outlet channel surrounding the periphery of the air inlet channel. The detection assembly is arranged in the air inlet channel and is used for qualitatively and quantitatively detecting the components of the passing to-be-detected gas. The air curtain cover is installed on the shell, an air inlet of the air curtain cover communicates with the air inlet channel, and an air outlet surrounds the air inlet and communicates with the air outlet channel. The power assembly is divided into two parts, one part is located in the air outlet channel and used for sucking in external air, the external air is exhausted through an air outlet of the air curtain cover, and a hollow cylindrical or conical air curtain is formed. And the other part is positioned in the air inlet channel and is responsible for introducing the to-be-detected gas wrapped by the air curtain into the air inlet channel from the front of the air outlet of the air curtain cover. The electronic nose device can effectively improve the detection efficiency of the to-be-detected gas, ensures that the detection process is quicker and more accurate, and meets the practical requirements of adjustable orientation and more accurate positioning for gas detection in practical application.

The invention, which belongs to the technical field of intelligent breeding equipment, discloses an underwater bionic robotic fish school cooperative breeding environment dynamic monitoring and regulation system comprising a bionic robotic fish body core module, a group cooperative control core module and an intelligent regulation core module. The bionic robotic fish module simulates a real fish swimming mode and carries various water quality sensors to autonomously cruise, so that interference to cultured fishes is reduced; the group cooperation module utilizes a cluster intelligent algorithm and an underwater acoustic communication technology to realize coordinated movement of multiple robotic fishes and full coverage of a monitoring area; the intelligent adjusting module is based on an abnormal detection algorithm, and integrates a miniature oxygenation device, a pH adjusting device and the like to achieve precise regulation and control of the local environment. By the adoption of the system, dynamic sensing and active regulation and control of the culture environment are achieved, a bionic monitoring regulation and control solution is provided for modern aquaculture through intelligent cooperation of the robot fish school and the management system, and the system has the important value of improving the culture efficiency and improving the growth environment.

The invention provides a composite nanofiber membrane applied to detection of a C4F7N gas decomposition component C3F6, a preparation method of the composite nanofiber membrane and a sensing device. The composite nanofiber membrane comprises a polymer nanofiber substrate and a metal organic framework dispersed in the polymer nanofiber substrate, the metal organic framework is MIL-101 (M), and M represents a metal element and comprises at least one of Cr, Cu and lanthanide series metal elements; the surface of the interdigital electrode is coated with the composite nanofiber membrane, and the composite nanofiber membrane serves as a sensing device and is used for detecting C3F6 gas. The sensor disclosed by the embodiment of the invention can generate response within 25s, still has certain sensitivity (which is 3% or above) to 10ppm of C3F6 gas, and meets the requirements on high sensitivity and quick response in detection of a C4F7N gas decomposition product C3F6.

The invention relates to the technical field of intelligent detection, and discloses a water pollutant concentration intelligent detection system and a detection method thereof, and the water pollutant concentration intelligent detection method comprises the following steps: obtaining optical data, chemical data, electrical data, environmental data and biological data; performing normalization and standardization processing on the obtained data through edge calculation; performing feature extraction on the acquired data; splicing the features to obtain a fused feature; the fusion features are input into a multi-layer perceptron for water pollutant concentration prediction; the diffusion conditions of pollutants at different time points in the future are predicted through a fluid mechanics formula; inputting the fusion features into a decision tree model, and judging the instant influence of the water pollutants on the cultured organisms; the breeding environment parameters are adjusted through instant influence. According to the method, through edge calculation, behaviors of aquatic organisms are combined, and the diffusion trend of water pollutants is predicted, so that more accurate water quality monitoring is realized.

The invention discloses a soil health and microbiological analysis intelligent environment monitoring device, and relates to the technical field of soil monitoring, the device comprises the following components: an outer shell, a sensor assembly, a microflora interaction monitoring sensor group, a data acquisition and transmission module, a power supply module, a microprocessor, a control unit and a data analysis module; signal molecule concentration change data and predatory relationship visual data are combined through the data analysis module, deep analysis is carried out by using bioinformatics and mathematical modeling means, and a multi-dimensional regulation network hidden in a microbial community can be comprehensively revealed; according to the soil health assessment device, the interaction relationship between the soil ecological system and the soil ecological system is analyzed accurately, the influence of the interaction relationship on key ecological functions such as material circulation and energy flow in the soil ecological system is analyzed accurately, the device can generate a detailed soil health assessment report based on the analysis results, agricultural scientific researchers, planting farmers and environmental protection monitoring departments can assess the soil health condition accurately, and the soil health assessment efficiency is improved. And targeted soil management measures are taken.

A hydrogen gas sensor with a substrate and a zinc oxide nanostructured thin film deposited on the substrate, wherein the zinc oxide nanostructured thin film has a lattice structure with a weight ratio of low binding energy O2− ions to medium binding energy oxygen vacancies in a range of 0.1 to 1.0, and a method of fabricating a gas sensor by thermally oxidizing a metal thin film under low oxygen partial pressure. Various combinations of embodiments of the hydrogen gas sensor and the method of fabricating the gas sensor are provided.

The invention relates to the technical field of hydrological detection, and discloses a water quality detection equipment calibration system based on artificial intelligence assistance, which comprises a data preprocessing module, a drift identification module, a model comparison module, a self-adaptive calibration module and a feedback updating module. According to the water quality detection equipment calibration system based on artificial intelligence assistance provided by the invention, the aspects of data processing precision, drifting identification capability, calibration response efficiency and model adaptability are remarkably improved. Through cooperative work of multiple modules, the system can realize full-process intelligent operation from original data acquisition to calibration execution to model self-updating, the human intervention frequency is reduced, and the stability and accuracy of long-term operation of equipment are improved.

The invention discloses a soil salinity inversion method, system and device based on multi-mode remote sensing data fusion and a storage medium, and is applied to the technical field of soil quality monitoring, and the method comprises the steps: obtaining radar and optical remote sensing data of a to-be-inverted region of soil salinity, and carrying out the conductivity measurement, and taking the obtained data as an inversion index of the soil salinity; obtaining multi-modal remote sensing features based on radar and optical remote sensing data fusion, optimizing a remote sensing feature combination by combining the radar and optical remote sensing data and based on a random forest algorithm and utilizing a recursive feature elimination method, and performing model performance evaluation on the remote sensing feature combination by adopting cross validation to obtain an optimal remote sensing feature combination; and based on the optimal remote sensing feature combination, constructing and training a soil conductivity prediction model based on a random forest algorithm, and inputting to-be-measured data to the conductivity prediction model after hyper-parameter adjustment to complete soil salinity inversion. According to the method, more accurate inversion of the soil salinity under the interaction influence of a complex environment and human factors is realized.

The invention discloses a natural gas odorant concentration intelligent detection device suitable for remote monitoring, and belongs to the field of natural gas safety monitoring, and the natural gas odorant concentration intelligent detection device comprises an odorant concentration sensor array used for detecting original concentration data of a natural gas odorant; the cross validation module is used for carrying out fusion processing on the original concentration data corresponding to the various sensors respectively to obtain calibrated odorant concentration detection data; the pipeline monitoring module is used for obtaining pipeline operation data; the communication module is connected with the cross validation module, the pipeline monitoring module and the remote monitoring module; the remote monitoring module is used for determining an odorant concentration predicted value based on integrated multiple models according to the original concentration data and the pipeline operation data corresponding to the multiple sensors respectively; and obtaining a final odorant concentration confirmation result according to the calibrated odorant concentration detection data and the odorant concentration predicted value. According to the invention, high-precision, real-time and reliable remote intelligent monitoring of the concentration of the natural gas odorant is realized.

The invention relates to the technical field of circuit boards, and discloses a circuit board interlayer connection detection method, device and equipment, and the method comprises the steps: carrying out the electrical characteristic parameter measurement of a multilayer flexible circuit board, and obtaining the characteristic parameter data of the circuit board; designing and arranging a multi-test-point detection structure on the multi-layer flexible circuit board, and performing signal excitation to obtain test point position information; applying a differential excitation signal, and collecting a differential response waveform between the test points to obtain a time domain reflection signal feature; impedance spectrum conversion and parameter extraction are carried out on the time domain reflection signal features, and an interlayer connection impedance distribution diagram is obtained; and establishing an interlayer connection defect characteristic model aiming at nickel-based alloy wire fracture, interface cracking and liquid metal fiber felt delamination in various bending states by utilizing the interlayer connection impedance distribution diagram, so that accurate classification of defect types and severity is realized, and interlayer connection faults and surface welding quality problems can be distinguished; and the misjudgment rate is greatly reduced.

The invention provides a silk-screen printing conductive substance uniformity detection method and system, and relates to the technical field of electronic material manufacturing and detection.The method comprises the steps that a conductive pattern image is acquired through an image acquisition device, surface topography feature data is obtained through phase profilometry processing, and the surface resistance value measured by a four-probe array is combined; establishing a resistance-density data pair, calculating a resistance change rate and a difference coefficient, generating a conductive uniformity quantitative index value, and identifying a conductive performance deviation region based on the conductive uniformity quantitative index value so as to optimize printing process parameters. The uniformity of the conductive substance can be accurately detected, and the accuracy of printing quality control is improved.

The invention relates to a lacustrine facies shale conductive model considering organic matter influence and a saturability evaluation method, and belongs to the technical field of unconventional oil and gas reservoir oiliness evaluation, and the method comprises the following steps: 1) representing fluid information in a shale sample based on a pressure-maintaining closed sample and a two-dimensional nuclear magnetic resonance technology; 2) according to the organic carbon content and the clay content of the shale, dividing the lithology type of the lacustrine facies shale, and analyzing the relation between different lithology resistivity values and the porosity of free water and bound water; 3) selecting a siltstone interlayer sample, and inversely calculating a cementation index and a saturation index of the inorganic pore conductive network; 4) establishing a lacustrine facies shale parallel conductive model, and calibrating rock-electricity parameters according to lithology; 5, a lithology discrimination chart, a TOC prediction model, a bound water content prediction model and an effective porosity calculation model are established, and the oil saturation is explained according to different lithologies in combination with the lacustrine facies shale parallel conduction model.According to the method, accurate shale reservoir fluid information is provided, and a brand new thought is provided for rock electrical parameter calibration.

The invention discloses a bridge pier stud crack automatic detection system based on a wall-climbing robot, and relates to the technical field of crack detection, and the system realizes closed-loop operation from accurate crack detection to intelligent repair through a crack detection module and a repair material intelligent spraying detection module. The crack detection module uses a multispectral imaging device, a thermal imaging camera and a laser scanning technology, can collect a multispectral difference value G (x, y), surface temperature distribution T (x, y) and a depth matrix D (x, y) of a crack area, extracts a crack boundary B (x, y) through a high-precision algorithm, and calculates a crack volume Vc. And the repairing material intelligent spraying detection module dynamically calculates the volume Vm of the repairing material according to the volume of the crack, and the SLAM technology is utilized to optimize the spraying path and parameters, so that uniform coverage and efficient utilization of the repairing material are ensured. The system greatly improves the precision of crack detection and repair, and avoids material waste and repair omission.

The invention relates to the technical field of tin-containing copper alloy manufacturing, in particular to a method, system and equipment for detecting the oxygen content of copper alloy melts.The method comprises the steps that resistivity data of the copper alloy melts.The temperature data of the copper alloy melts.The resistivity data of the copper alloy melts.The temperature data of the copper alloy melts.The resistivity data of the copper alloy meltsare acquired in real time; the resistivity data are corrected based on the temperature data, and standardized resistivity irrelevant to the temperature is obtained; a correlation model of the resistivity and the oxygen content is established according to the linear influence relation of oxygen impurities in the copper alloy melt on the resistivity, a real-time oxygen content value is output based on the standardized resistivity, and an oxygen content fluctuation trend is generated; and according to the real-time oxygen content value and the oxygen content fluctuation trend, the oxygen content tolerance threshold value of the copper alloy melt is dynamically adjusted based on the oxygen sensitivity requirements of different alloying stages. By means of the method, the problems that in a traditional oxygen content detection method, due to the fact that temperature distribution is uneven, alloy element interaction and solidification behaviors are not systematically modeled, the detection precision is low, and microstructure control fails are effectively solved.

The invention discloses a conductivity measurement compensation method and system based on temperature field distribution modeling, and the method comprises the following steps: 1), building a to-be-measured medium temperature field model which is used for describing the temperature distribution in a medium; 2) establishing a conductivity temperature compensation model; 3) coupling the temperature field model and the conductivity temperature compensation model, and establishing a conductivity measurement compensation equation; 4) solving the conductivity measurement compensation equation to obtain compensated conductivity distribution; and 5) receiving data of the temperature sensor in real time, dynamically updating boundary conditions and initial conditions of the temperature field model, inputting temperature field distribution obtained by calculation into the conductivity compensation model, and compensating a conductivity measurement result in real time. According to the method, the influence of the temperature change on the conductivity is more accurately compensated by simulating the temperature distribution of the medium, the method adapts to the environment condition of rapid change, and the measurement precision of the conductivity can be obviously improved in the scene of large temperature gradient or rapid change.

The invention relates to a lake water quality real-time monitoring method and system based on a sensor array. The method comprises the steps that the sensor array is arranged in a target lake, and data acquisition frequency parameters are set; acquiring working parameters of the sensor array in real time, analyzing the working parameters, determining health states of the sensors, and performing adaptive adjustment on the sensors based on the health states of the sensors; collecting water quality monitoring data in real time based on the adjusted sensor array, performing preprocessing and quality control verification on the water quality monitoring data, and constructing a monitoring data set with qualified quality control; and comparing each water quality index in the monitoring data set with qualified quality control with a preset environmental standard limit value, marking a limit value exceeding event, and performing early warning, thereby completing real-time monitoring of the water quality of the target lake. According to the invention, intelligent real-time monitoring, abnormity identification, data quality control and early warning response of lake water quality are realized, and comprehensive technical support is provided for water environment management.

The invention discloses a copper extraction effect analysis method and system, and the method comprises the steps: carrying out the continuous scanning of the surface of a copper sample through an optical sensor, and obtaining the chromaticity change time sequence data in a refining process; and carrying out segmentation processing on the data by utilizing a preset threshold value, and extracting dynamic change trend characteristics and key point locations. And in combination with conductivity and hardness value data recorded by a real-time monitoring system, a polynomial regression model is constructed, and correlation between copper purity and physical characteristics is established. And through historical data calibration and mean filtering optimization, the mapping relation between chromaticity change and copper purity is determined. And finally, according to the optimized chromaticity characteristic value and the calibrated correlation model, calculating the quantitative score of the real-time refining effect, and judging the grading basis of the copper purity. According to the method, the real-time evaluation of the copper purity and the dynamic optimization of the refining process are realized, and the refining efficiency and the product quality are improved.

The invention discloses a Frechet distance-based abnormal inflow traceability method and system for a sewage treatment plant, and the method comprises the steps: carrying out the unit division of the inflow range of the sewage treatment plant through combining land parcel information, pipe network information, convergence conditions, monitoring stations and the like, and analyzing the correlation between total phosphorus and conductivity; arranging a pipe network water quality monitoring micro station, and carding a factory-network-land parcel-source pointer relation library; a sewage treatment plant big data warehouse is constructed, related data are cleaned and treated, and the data are accessed to a pollutant traceability visualization platform; a sewage plant water pollution traceability model is constructed, a water inlet total phosphorus standard exceeding event is selected to carry out traceability research, the traceability model is embedded into a visual platform, and sewage plant total phosphorus concentration standard exceeding traceability visualization is achieved. Compared with the abnormal inflow tracing method of the sewage treatment plant, the large data resource utilization rate can be greatly improved while a large amount of manpower and material resources are saved, and a basis is provided for locking secretly-discharged enterprises, predicting pollution diffusion and environment emergency.

The invention provides a flexible palladium film hydrogen sensor and a preparation method thereof, the flexible palladium film hydrogen sensor is sequentially provided with a flexible substrate, a hydrogen sensitive sensing layer and a contact connection layer from bottom to top, and the contact connection layer is connected with a resistance measurement unit; and the hydrogen-sensitive sensing layer is a palladium or palladium alloy film with a conical micro-nano structure. The palladium or palladium alloy thin film with the conical micro-nano structure provides a hydrogen sensor conical surface micro-nano structure with a high specific surface area for the flexible palladium thin film hydrogen sensor, and the process that hydrogen is adsorbed, dissolved and diffused into the palladium or palladium alloy thin film is accelerated, so that the response speed of the sensor is increased; according to the hydrogen sensor, the flexible substrate is adopted, so that the hydrogen sensor can be conveniently arranged in various narrow spaces, and the applicability of the hydrogen sensor in various scenes is improved.