25results about How to "Non-destructive testing" patented technology

The invention relates to the technical field of image processing, in particular to a bamboo shoot quality detection method and system based on a hyperspectral image and a medium, and the method comprises the following steps: acquiring a first hyperspectral image acquired from a target bamboo shoot; obtaining K characteristic wave bands of a target bamboo shoot, extracting K first spectral images in one-to-one correspondence with the K characteristic wave bands from the first hyperspectral image, and respectively determining reflectivity matrixes of the K first spectral images; determining the spectral deviation degree corresponding to the first spectral image based on the reflectivity matrix, and determining the quality of the target bamboo shoot based on the spectral deviation degree of each first spectral image; the method can realize lossless and efficient detection of bamboo shoot quality.

The invention belongs to the technical field of agricultural food detection, and particularly relates to a method for rapidly detecting the fatty acid content of Beijing ducks based on a near infrared spectrum technology, which comprises the following steps: selecting a sample and pre-treating the sample; collecting sample data by using a standardized collection method; removing abnormal samples; performing spectral data correction; standard normal variable transformation is used to eliminate baseline drift and random errors in the spectral data; dividing the data set into a training set and a test set according to a proportion of 7: 3 by using a sample set division method based on a joint X-Y distance; constructing an optimized extreme learning machine model, and training the optimized extreme learning machine model based on the training set; constructing an evaluation model, and verifying the detection effect of the optimized extreme learning machine model based on the test set; rapid detection of the fatty acid content of the Beijing duck is realized. The defects that an existing method is long in consumed time and lagged in detection result, and dangerous solvents need to be used are effectively overcome.

The invention relates to the technical field of signal processing and fault diagnosis, and the method comprises the steps: collecting a flame chemiluminescence signal, and carrying out the adaptive filtering noise reduction processing; comprehensive combustion characteristic information is obtained by using an improved intrinsic orthogonal decomposition method and a high-order mode; developing a real-time synchronous compression transformation algorithm to perform time-frequency analysis on the data, and updating energy distribution in real time; sensor data are combined, multi-parameter conjoint analysis is conducted, combustion state evaluation is obtained, flame images are obtained from different angles through a plurality of high-speed cameras, the three-dimensional flame form is reconstructed through the computer vision technology, and fault detection information is provided; and a fault prediction model is constructed, and early warning of combustion faults is realized. The method realizes lossless and rapid detection of oscillation combustion faults, retains rich information of flame images, reflects the overall pulsation characteristics of flames, improves the detection speed and accuracy, and makes up for the disadvantage of low frequency resolution of a traditional time-frequency analysis method.

The invention discloses a method and a device for rapid in-situ monitoring of sodium precipitation at a negative electrode side of a soft-package sodium-ion battery. According to the method, the on-line nondestructive monitoring of the negative electrode sodium precipitation is realized by monitoring the pressure change of the sodium ion battery cell in the charging and discharging process. A first-order differential curve and a second-order differential curve of the pressure of the battery cell are obtained and analyzed by measuring and recording the pressure curve of the battery cell in the charging process on line, and when the change rate of the pressure of the battery cell exceeds a set threshold value and the second-order differential curve of the pressure is always larger than 0 under the high SOC, the second-order differential curve can serve as an external indication signal for judging sodium precipitation of the negative electrode. According to the technical scheme, the occurrence of the sodium separation reaction of the negative electrode can be efficiently and sensitively detected without any modification or damage to the target sodium ion battery cell. The method provides a simple and effective lossless online monitoring means which is easy to integrate and popularize for effectively defining the safe use condition of the sodium ion battery cell and monitoring and predicting the healthy operation condition of the sodium ion battery.

The invention discloses a multi-layer glass layer thickness detection system and method based on a single-row non-uniform microlens array, and belongs to the technical field of glass quality detection, and the system comprises a collimation laser light source module, a light beam splitting module, a focusing module, a signal acquisition module and a data processing module; wherein the collimation laser light source module comprises a light source with a tail fiber and a collimation lens for carrying out collimation processing on a light beam; the light beam splitting module comprises a light splitting plate or a light splitting cube positioned above the tested multi-layer glass; the focusing module comprises single-row non-uniformly distributed microlens arrays which are respectively positioned on two sides of the light beam splitting module; the signal acquisition module comprises linear array cameras which are respectively matched with the two microlens arrays in the focusing module; and the data processing module is configured to process multi-beam spot data acquired by the two linear array cameras by using a one-dimensional centroid method. The method can be used for rapidly, accurately and nondestructively detecting the thickness of each layer of medium of the multi-layer glass and judging whether the layer thickness of the multi-layer glass meets the standard or not.

The invention discloses a multi-task visual perception tomato maturity detection method which comprises the following steps: constructing an observation model according to position distribution information of tomato fruits; processing actual position information and scanning position information of the tomatoes by using a volume Kalman filter, and calculating a covariance matrix of tomato position coordinates and a covariance matrix of obstacle position coordinates; calculating a volume point according to the covariance matrix of the tomato position coordinates and the covariance matrix of the obstacle position coordinates, and obtaining coordinate information of the tomato position after visual perception; performing state volume point propagation to obtain an estimated value of the tomato position; and fuzzy control is utilized to take the matching degree of the actual variance and the theoretical variance of the residual error of the lycopene content as an input quantity and a noise regulation factor in the process of measuring the tomato hardness as an output quantity, and the input quantity is taken as a final positioning result after visual fusion filtering. The tomato maturity can be effectively, intelligently and nondestructively detected, and the method has good robustness and superiority.

This invention discloses a contactless chip testing system. The platform includes a PC, a data parsing / forwarding module, a source signal excitation module, a gating array, and a chip slot under test. The platform allows for simultaneous multi-selection via a PC's visual interface, enabling automated integrated testing of resistance, capacitance, package integrity, voltage, and overall power consumption between any chip pins. Compared to traditional mechanical probe-based contact testing systems, this invention is more compact. Furthermore, it employs an automatically gating physical path switching method, resulting in a higher switching rate and more efficient package testing.

The present application relates to a kind of biological base micro needle sensor-based crop health nondestructive testing method, belong to agricultural information technology and biosensor field.The method is intelligently analyzed to crop surface microstructure by convolutional neural network, realize the accurate arrangement of microneedle array and customized nondestructive adaptation.Microneedle multimodal sensing unit can synchronously real-time acquisition crop internal multidimensional physiological parameters, and signal quality is improved using adaptive filtering and standardization processing.Combined with multivariate anomaly detection algorithm of self-supervised and contrast learning, health status is unsupervised clustering and early abnormal screening, and environmental and management information is fused, realize whole plant multiscale health evaluation, abnormal risk distribution analysis and dynamic traceability.System can intelligently output differentiated farm work suggestions, realize the high accuracy, nondestructive, real-time monitoring and intelligent management of crop health.

The application discloses a kind of detection system of quick nondestructive testing fabric density, including size comparison module, platform module, image acquisition module, processing module;Platform module is fixed to be detected object and cooperates size comparison module to form the object to be detected that can be used for real-time detection, image acquisition module acquires corresponding image information and real-time backup storage data according to operator target detection position, and the original data after backup is transferred to processing module, and processing module calculates the fabric density of the object to be detected in specified range according to the space layer conversion of fiber, the application further discloses a kind of detection method of application detection system.Relative to prior art, the technical scheme of the present application has the advantages of being convenient, real-time and traceable, etc.The application not only has the advantages of being fast and convenient and not damaging the fabric, but also the data can be traced back and reproduced well, and has important application prospects in the field of textile fiber detection.

The invention provides a device and a method for on-line detection of boric acid in a primary loop coolant of a nuclear power station. The device comprises a cavity enhancement module, a sample cell, a Raman scattering light collection module and a spectrometer module, the cavity enhancement module comprises a laser, a first spherical mirror and a second spherical mirror; the first spherical mirror and the second spherical mirror are oppositely arranged, and an enhancement cavity is formed between the two; laser emitted by the laser device enters the first spherical mirror, and the incident laser is reflected for multiple times in the first spherical mirror and the second spherical mirror and is converged at a focus position; the sample cell is arranged at the central position of the enhancement cavity, and the laser passes through a to-be-detected solution in the sample cell to generate Raman scattering light; the spectrograph module comprises a slit and a spectrograph; and the light converged by the second converging and collimating lens passes through the slit and enters the spectrometer. By using the method, the boric acid ion concentration in the nuclear power plant primary loop coolant can be rapidly detected in situ without an auxiliary reagent and generating waste liquid.

The present application discloses a method for detecting the moisture content of Daqu during storage, comprising the following steps: obtaining a Daqu sample to be tested; measuring the temperature and humidity in the storage bin where the Daqu sample to be tested is located; calculating the moisture content of the Daqu sample to be tested according to the temperature and humidity in the storage bin where the Daqu sample to be tested is located and a pre-constructed standard curve; wherein the standard curve is a curve obtained according to the temperature and humidity in the storage bin where the Daqu sample is located during storage and the actual moisture content of the Daqu sample. By adopting this method, the moisture content of Daqu can be detected quickly and non-destructively during storage, so that the moisture change of Daqu can be monitored online and in real time during storage, the fermentation quality of Daqu can be monitored, and the efficiency and stability of production can be improved, which is of great significance to the automation and intelligence of Daqu production.

The invention provides a method for detecting a straight fluted tap through polarization imaging based on deep learning. Comprising the following steps: S1, collecting multi-polarization angle images of the straight fluted tap under different shooting azimuth angles by using a polarization camera, and forming a data set; and de-noising the image, enhancing the contrast ratio and performing matching calibration by using an RDN neural network to obtain a polarization degree image and a polarization angle image. S2, marking images of the training set and the verification set, including abrasion, defect areas and features of the screw tap, training Mask R-CNN based on an ImageNet pre-training model, analyzing training indexes, and selecting an optimal weight file; and S3, the Mask R-CNN model detects defect and wear information in the test set and segments key features. And S4, performing mask extraction on the segmented image, performing calibration measurement by using the segmented mask, and calculating the size. And S5, detecting and screening unqualified products. According to the invention, an efficient, accurate and reliable solution can be provided for detecting the straight fluted taps in the manufacturing industry.

The present invention discloses a fusion spectrum detection method for the quality of minced meat gel under ultrasonic treatment, comprising: preparing a minced meat sample after ultrasonic treatment; determining the gel strength of the minced meat sample; obtaining the spectral information of the minced meat sample, and pre-processing the spectral information to obtain the spectral information after pre-processing; constructing a prediction model for the initial minced meat gel quality, inputting the gel strength of the minced meat sample and the spectral information after pre-processing into the prediction model for the initial minced meat gel quality, and obtaining the prediction model for the minced meat gel quality; inputting the minced meat sample to be predicted into the prediction model for the minced meat gel quality, and obtaining the detection result of the minced meat gel quality. The present invention effectively captures the close relationship between the minced meat gel strength and the near-infrared-Raman fusion spectrum, and finally realizes the non-destructive, rapid and accurate detection of the minced meat gel quality.

The present application relates to a kind of surface enhanced raman nanoparticles and fentanyl substance detection method, belong to the field of drug safety detection.The surface enhanced raman nanoparticles is noble metal nanoparticle, the noble metal nanoparticle is preferably gold nanobiscake.The fentanyl substance detection method uses the surface enhanced raman nanoparticles of the present application to carry out raman detection.The surface enhanced raman nanoparticles and fentanyl substance detection method can quickly, non-destructively detect trace fentanyl substance in the sample to be measured, and has very good application prospect in public safety detection.

The invention provides a fish meat quality detection method and system. The fish meat quality detection method comprises the following steps: determining key indexes influencing the fish meat quality; then obtaining a first fish meat sample, obtaining target map data according to the first fish meat sample, and establishing a plurality of index detection models based on the target map data and the key indexes; and finally, obtaining to-be-detected fish meat, and obtaining the fish meat quality of the to-be-detected fish meat according to each index detection model and the to-be-detected fish meat. According to the method, the fish quality is detected by using the map data, the accuracy and precision of model detection are improved, and rapid nondestructive detection of the fish quality is realized.

The present application relates to the technical field of signal processing and fault diagnosis, the method comprises, collecting flame chemiluminescence signal, and carrying out adaptive filtering noise reduction processing;Using improved intrinsic orthogonal decomposition method and high order mode, obtaining comprehensive combustion characteristic information;Developing real-time synchronous compression transform algorithm to carry out time-frequency analysis to data, and updating energy distribution in real time;Combining sensor data, carrying out multi-parameter joint analysis, obtaining combustion state evaluation, using multiple high-speed cameras to obtain flame image from different angles, reconstructing three-dimensional flame morphology through computer vision technology, providing fault detection information;Building fault prediction model, realizing early warning of combustion fault.The method realizes nondestructive and rapid detection of oscillating combustion fault, retains rich information of flame image, reflects overall pulsation characteristics of flame, improves detection speed and accuracy, and makes up for the shortcoming of low frequency resolution of traditional time-frequency analysis method.

This invention provides a method for detecting and calculating the austenite content in steel based on a permeability meter, relating to the fields of steel and electromagnetics. Based on the theoretical differences in saturation magnetization of different phases in ferromagnetic materials, this invention establishes a theoretical calculation model and detection method for measuring austenite content using a permeability meter. A standard-prepared sample is placed in a magnetic pole shoe, and the magnetic field strength H corresponding to the maximum permeability of the ferromagnetic material is first measured. μ Then at ≥1.5H μ Under a magnetic field strength of J, the polarization intensity of the magnetic field strength at multiple points was measured at continuous intervals. m Then, based on the saturation magnetization approximation law and derivation law, the saturation magnetization Js is fitted and solved. Finally, the austenite content is determined according to the theoretical calculation model of austenite content. The method described in this invention solves the influence of the constantly changing effective magnetic path length of traditional magnetometers on the measurement results. The method for determining austenite content is simple, has a solid theoretical basis, high measurement accuracy, and strong data repeatability.

The invention relates to a method for detecting the fastness and surface roughness of a nickel-titanium wire for a puncture needle, and belongs to the technical field of nickel-titanium wire detection, and the method comprises the following steps: S1, feeding the nickel-titanium wire onto a workbench through a feeding mechanism on the workbench; s2, a resistance detection mechanism on the workbench electrifies the nickel-titanium wire to detect the resistance of the nickel-titanium wire, a transfer mechanism on the workbench transfers the nickel-titanium wire subjected to resistance detection to roughness detection equipment on the workbench, and the roughness detection equipment detects the surface roughness of the nickel-titanium wire; and S3, discharging the detected nickel-titanium wire from the workbench by a discharging mechanism on the workbench. The method has the effect of rapidly and nondestructively detecting the surface roughness and fastness of the nickel-titanium wire.

A PCB electrical performance testing device comprises a base assembly, a fuzz button assembly and a tail end throwing line, the base assembly comprises an upper base, a lower base and a stud, the upper base is fixed to the lower base through the stud, an installation table is arranged on the inner side of the upper base, an installation hole penetrating through the upper base and the lower base is formed in the bottom face of the installation table, and the fuzz button assembly comprises a fuzz button assembly and a tail end throwing line. The fuzz button combining piece is fixed on the base combining piece through the mounting hole, and the tail end throwing line is arranged below the fuzz button combining piece. Through the structural arrangement of the base assembly and the fuzz button assembly, the functions of data exchange and signal transmission between the testing device and an external structure are achieved, rapid, accurate and damage-free testing of the electrical performance of to-be-tested PCBs of different heights is achieved, the overall structure is simple, the machining technology is mature, and operation is convenient.

The embodiment of the invention provides an anti-counterfeiting master batch for automobile manufacturing and a preparation method and an identification method of the anti-counterfeiting master batch. The anti-counterfeiting master batch comprises carrier resin, an anti-counterfeiting tracking agent and a dispersing agent, the anti-counterfeiting tracking agent comprises at least two metals or compounds thereof, the metals are selected from Mg, Ca, Sr, Ba, Al, Ti, Zr, Hf, Nb, Ta, Mo, W, Mn, Fe, Co, Ni, Cu, Zn, Ga, Ge, Sn, Sb, Bi, Y, La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb and Lu, and the at least two metals or compounds thereof have a selected mass ratio. The technical problem of providing the anti-counterfeiting master batch added into the plastic for automobile manufacturing is solved, and the anti-counterfeiting master batch can realize the use safety of an automobile plastic material and the reliability of anti-counterfeiting tracing.

The invention discloses a non-transparent film thickness measurement method and system based on ultrafast photoacoustic spectroscopy. The method comprises the following steps: (1) superposing a two-dimensional semiconductor film on a non-transparent film; based on a femtosecond laser pumping detection technology, pump light and detection light with different time delays are generated, the pump light and the detection light with different time delays are focused on the surface of the two-dimensional semiconductor film, and a time-resolved ultrafast photoacoustic spectrum reflected by the surface of the two-dimensional semiconductor film is detected; performing background removal processing on the time-resolved ultrafast photoacoustic spectrum to obtain picosecond sound wave pulse echo signals under different time delays; and extracting a time delay t corresponding to an echo moment in the picosecond sound wave pulse echo signal, and calculating the thickness d of the non-transparent film according to a formula d = vt / 2 in combination with a sound wave transmission speed v in the non-transparent film. The method has the technical advantages of high spatial resolution, rapidness and no damage.

The present invention provides a waterproofing agent mixing uniformity detection device and control device in the production process of artificial boards, wherein the waterproofing agent mixing uniformity detection device comprises a spectrum detection module and a processor; the spectrum detection module is arranged on the artificial board production line and is located after the waterproofing agent adding process, the spectrum detection module detects the artificial board raw material and outputs a spectrum data set to the processor in real time; the processor receives the spectrum data set, and converts the spectrum data collected by each spectrum probe in real time or converts the spectrum data collected by each spectrum probe into two-dimensional data and inputs it into a pre-trained multi-layer convolutional neural network model, obtains the waterproofing agent addition amount detection value of each spectrum probe corresponding to the raw material detection area, and performs uniformity judgment according to the waterproofing agent addition amount detection value of each spectrum probe corresponding to the raw material detection area and outputs the detection result. The analysis efficiency is high, and the waterproofing agent mixing uniformity in the artificial board can be accurately detected online on the production line.

The present invention relates to the fields of materials, optics and environmental detection, and specifically to a silver-coated optical fiber Raman probe and a preparation method and application thereof, wherein methimazole is used as a Raman signal molecule to realize the detection of Cr(VI). The silver-coated optical fiber Raman probe of the present invention realizes ultra-sensitive detection of Cr(VI) and excellent antioxidant performance by functionalization with methimazole. The preparation method of the present invention has simple process, high sensitivity, good repeatability, good stability and good anti-interference. By adopting stannous chloride-assisted solvent thermal method, the morphology control of silver nanoparticles on the end face of the optical fiber and the strong interface adhesion between the optical fiber and the silver nanomaterial are realized. Specifically, the stannous chloride pretreatment process promotes the dense and uniform growth of silver nanoparticles on the end face of the optical fiber on the one hand, and enhances the interface adhesion between the optical fiber and the silver nanoparticles on the other hand. Ultra-sensitive detection of Cr(VI) and excellent antioxidant performance are realized by functionalization with methimazole.

The invention discloses a glass fiber reinforced plastic connecting piece mechanical performance online detection method and device, a medium and a product, and relates to the field of nondestructive detection.The method comprises the steps that a GFRP connecting piece sample is obtained; carrying out mechanical accelerated aging and acoustic emission loading tests with different time lengths on the GFRP connecting piece sample, and acquiring a characteristic acoustic signal by utilizing an acoustic emission sensor; determining the bending strength of each GFRP connecting piece sample after the test; constructing a mechanical strength model of the glass fiber reinforced plastic connecting piece according to the residual mechanical strength and the corresponding characteristic sound signal; acquiring a real-time characteristic acoustic signal of the GFRP connecting piece in a working state by using an acoustic emission sensor; and determining the real-time residual mechanical strength by adopting a glass fiber reinforced plastic connecting piece mechanical strength model according to the real-time characteristic sound signal and the corresponding borne load. The mechanical performance of the GFRP connecting piece can be detected in a lossless, time-saving and real-time manner in the equipment operation process, and the health state is evaluated.

The utility model discloses a farm egg sub-packaging and screening device which comprises a rotating disc, the surface of the rotating disc is fixedly connected with a partition plate, a base is rotationally installed at the bottom of the rotating disc, a conveying roller line is installed on one side above the base, a base plate is installed at the inner bottom of the rotating disc, and a conveying roller is installed on the base. And a lamp holder is mounted on the surface of the base plate in an embedded mode, a bulb is mounted in the lamp holder, one side of the bulb is electrically connected with a photoresistor, and an ultrasonic vibration sensor is mounted on the side wall of the rotating disc. A photoresistor is arranged in the lamp holder, the photoresistor LDR is used for detecting the quality of eggs, light source irradiation is used, high-quality eggs are semitransparent, the yolk outline is clear, poor-quality eggs are poor in light transmission, and therefore the freshness degree of the eggs can be judged easily, and in this way, the eggs are detected through the photoresistor and light source irradiation; and the quality of the eggs is judged according to the LDR reading, so that the eggs are subpackaged and screened according to the quality.