752 results about "Spectroscopic detection" patented technology

The invention discloses an on-line detection method for gas in transformer oil based on photoacoustic spectrum self-correction, and relates to the technical field of spectrum detection and power equipment state monitoring, and the method comprises the following steps: S1, emitting modulation laser with a specific wavelength to a gas sample released by the transformer oil through a laser, and exciting gas molecules to generate photoacoustic signals; and S2, detecting the photoacoustic signal by using a photoacoustic sensor, converting the signal into an electric signal, and outputting the electric signal. According to the online detection method for the gas in the transformer oil, the correction coefficient is adjusted in real time through a self-correction algorithm, errors caused by light path changes and sensor aging are effectively compensated, the precision and stability of long-term detection are remarkably improved, and the detection accuracy is improved by combining a gas spectrum database and a mode recognition algorithm. According to the method, accurate qualitative and quantitative analysis of various gases is realized, the problem of cross sensitivity of multiple components is solved, and the method also has temperature and pressure compensation functions and can automatically adapt to environmental changes.

A multispectral combined method for online detection of slurry components in a mineral processing process, relating to the technical field of spectrum detection. The multispectral combined method comprises: collecting slurry samples having a gradient distribution of moisture content to serve as test samples, and using an NIR system to acquire near-infrared spectrum data of the test samples; performing spectral preprocessing on the near-infrared spectrum data, so as to reduce the interference of spectral noise on subsequent modeling, and establishing an NIR regression model for slurry moisture content; using an LIBS system to acquire plasma spectrum data of the test samples, and establishing an LIBS regression model for slurry concentration; substituting the NIR regression model for slurry moisture content into the LIBS regression model for slurry concentration, and optimizing an algorithm to realize model correction and compensation; and establishing a quantitative analysis model for slurry element content to realize LIBS and NIR multispectral combination. The multispectral combined method can effectively improve the online detection precision of slurry components in a mineral processing process and improve the accuracy of a regression model.

The invention discloses a multispectral pollution analysis method and system for a photovoltaic cleaning unmanned aerial vehicle, and belongs to the technical field of spectrum detection.The multispectral pollution analysis method comprises the steps that a multispectral image is obtained, dark current-radiation-atmosphere-shadow full-link preprocessing is carried out, multiband weighted threshold segmentation and morphological post-processing are constructed, and a pollution area is extracted; establishing a self-learning pollution spectral feature library, and identifying pollution types by using cosine similarity; generating a pollution degree distribution diagram in combination with the pollution type-efficiency attenuation mapping table; and when the overall efficiency loss exceeds a preset value, planning a three-dimensional track based on a cluster priority score and an ant colony-genetic fusion algorithm, and returning an image to perform closed-loop verification and complementary cleaning after the unmanned aerial vehicle performs cleaning. According to the invention, the pollution identification precision, the efficiency evaluation accuracy and the cleaning intelligence level are significantly improved, and the method can be widely applied to unattended operation and maintenance of the photovoltaic power station.

The invention discloses a marine plankton hyperspectral imaging detection system, relates to the technical field of spectrum detection, and is used for solving the problem of poor spectrum classification and recognition in a water body environment. According to the method, the hyperspectral image and the environmental disturbance parameters are synchronously acquired, and the disturbance mapping sequence is constructed, so that accurate alignment between the image and disturbance is realized. A disturbance contribution weight matrix is constructed based on a dominant wave band, pixel-level spectrum stripping is carried out, a plankton purification spectrum is extracted, the spectrum purity and the recognition accuracy are improved, and a spectrum abnormal drift region is precisely recognized in combination with derivative spectrum change and image texture features; a coupling relation between the drift region and background disturbance is further established, a dynamic interference factor map is generated, and identification model parameters are dynamically adjusted, so that the identification stability and classification accuracy of the system in a complex interference environment are improved, and the method is suitable for multi-scene marine ecological monitoring.

The invention discloses a water quality heavy metal real-time detection method and system based on multi-source data fusion, and relates to the technical field of water quality detection.The water quality heavy metal real-time detection method comprises the steps that spectral data and electrochemical data of a water quality sample are obtained, feature analysis is conducted based on the spectral data, a spectral heavy metal detection model is constructed, and a spectral detection result is obtained; performing feature analysis based on the electrochemical data, and constructing an electrochemical heavy metal detection model to obtain an electrochemical detection result; and performing multi-source data fusion according to the spectrum detection result and the electrochemical detection result to obtain a water quality heavy metal detection result. By collecting spectral data and electrochemical data, the limitation of a single detection method is overcome, and the stability and reliability of the model are improved; by establishing a multi-level anomaly detection and processing mechanism and formulating corresponding processing strategies for different levels, the intelligent management of the detection process is realized, and the accuracy and credibility of the detection result are improved.

The invention provides a food heavy metal pollution detection system based on plasma emission spectrum analysis, and aims to realize rapid and accurate detection of heavy metal elements in a food sample. The system comprises a sample processing module, an excitation module, a spectrum detection module, a signal processing module, a data analysis module and an output module. The sample processing module converts a food sample into an aerosol or steam state. The spectrum detection module is used for extracting spectrum characteristic information of heavy metal elements. And the signal processing module adopts an AI-driven spectrum denoising algorithm to remove background noise and interference signals. And the data analysis module calculates the concentration of each element based on the characteristic peak intensity and generates heavy metal pollution data. And the output module is used for visually displaying the detection result. According to the method, complex sample pretreatment steps are reduced, the detection efficiency and sensitivity are improved, and the method is suitable for food safety detection scenes and particularly has remarkable advantages in field rapid detection application of agricultural products, drinking water and processed food.

The invention discloses a coal quality online detection multispectral analysis system and analysis method, and belongs to the technical field of coal quality detection. Comprising a detection table, a crushing barrel, a supporting frame, a spectrum detector and a conveying belt are installed at the top end of the detection table, the conveying belt is driven by a second motor, and a flattening assembly, a collecting guide plate, a collecting box and a smoothing assembly are arranged at the top of the conveying belt. Through cooperation of the crushing cylinder and the flattening assembly, coal samples can be conveyed to the conveying belt after being crushed, the coal samples are automatically flattened and concentrated so that the coal samples can be conveyed into a spectrum detector to be subjected to spectrum analysis through a laser head, automatic operation is achieved in the whole process, rapidness and convenience are achieved, the detection efficiency is high, manual participation is not needed, and the labor intensity of workers is reduced. Meanwhile, through cooperation of the collecting box, the collecting guide plate and the smoothing assembly, the detected coal samples can be collected and stored in a targeted mode, and waste of coal resources is avoided.

The invention relates to the technical field of spectrum detection, in particular to a method for detecting the content of trace elements in quartz sand. The method comprises the following steps: acquiring spectral data of a quartz sand solution with gradient change of concentration; in each concentration spectrum, calculating an overlapping index according to the position and peak height difference of a spectrum peak and a previous spectrum peak, and screening abnormal spectrum peaks; analyzing the cross interference of the abnormal spectrum peak and the previous spectrum peak to obtain a distortion representation degree; obtaining the deviation influence degree according to the deviation of the abnormal spectrum peaks influenced by the silicon peaks among different concentrations, obtaining the concentration change interference degree according to the deviation amplitude variation trend of the distortion representation degree in the continuous concentration spectrum data in the ordered concentration, and correcting the spectrum data of the abnormal spectrum peaks to detect the content of the trace elements. According to the method, the spectrum data deviation of the quartz sand under the gradient concentration change is dynamically analyzed and quantified, so that the interference of the silicon element on the trace elements is eliminated, and the accuracy and reliability of the detection result of the content detection of the trace elements in the quartz sand are improved.

The invention belongs to the technical field of terahertz detection, and discloses a terahertz metamaterial enhanced spectrum detection system. Comprising the following steps: constructing a metamaterial enhancement factor tensor matrix according to the interaction between terahertz waves and a metamaterial; performing local field enhancement and surface plasma resonance optimization on the target sample based on the metamaterial enhancement factor tensor matrix to obtain a feature enhancement spectroscopy mapping function; constructing a multi-dimensional detection feature space based on a feature enhancement spectroscopy mapping function; a spectral signal enhancement topology network is formed based on the multi-dimensional detection feature space; enhancing the topological network based on the spectral signal, and generating an enhanced spectral feature discrimination function; obtaining a high-precision terahertz spectrum detection result based on the enhanced spectrum characteristic discrimination function; according to the invention, internal correlation between spectral characteristics can be mined, and comprehensive description of sample information is enhanced, so that high-precision terahertz spectrum detection is realized.

The invention discloses a tunable excited Raman spectrum microimaging method and device, and belongs to the field of spectrum detection and optical imaging. The device comprises a broadband adjustable wavelength light source, a high-resolution wavelength scanning module, a stimulated Raman signal excitation module and a stimulated Raman signal detection module. The stimulated Raman signal excitation and imaging module is used for focusing the two beams of narrow-band femtosecond pulse light which are overlapped in time and space on a sample and exciting a stimulated Raman signal, and meanwhile, moving the sample to realize spot scanning microscopic imaging; and the stimulated Raman signal detection module is used for converting the stimulated Raman scattering signal into an electric signal, demodulating the electric signal by using a lock-in amplifier, and recording spectral information by using a data acquisition card. According to the invention, the broadband tunable characteristic of the optical parametric amplifier is utilized to tune the pump light to the wavelength region of the sample absorption peak length so as to realize electron pre-resonance stimulated Raman; and a balance detection technology is combined at a detection end, so that high-sensitivity, high-resolution and high-signal-to-noise-ratio detection of stimulated Raman signals is realized.

The invention relates to the field of optical detection, in particular to spectrum detection equipment for measuring the thickness of a coating film, and the spectrum detection equipment comprises a feeding unit which comprises an erecting assembly; the erecting assembly is used for placing a to-be-detected coating optical element, a turntable in the feeding unit can transfer the coating optical element to the position of the measuring unit, and two spectrum detectors in the measuring unit can measure the coating thickness of two surfaces of the coating optical element at the same time; compared with an existing measuring device, the designed spectrograph coating thickness measuring device has the advantages that firstly, the coating thicknesses on the two surfaces of a coating optical element can be measured at the same time at a time in the aspect of efficiency, the efficiency is doubled, and the spectrograph coating thickness measuring device is suitable for large-batch coating thickness measuring tasks; in the aspect of accuracy, when the coating thicknesses on the two surfaces of the coating optical element are measured at the same time, the coating optical element does not need to be taken out, turned over and then fed, the problem of turn-over errors is avoided, and the coating thickness of each surface is accurately measured.

The invention provides an optical image and LIBS detection area registration method and device, a medium and a program product, and the method comprises the steps: collecting an optical image, three-dimensional shape data and spectrum detection data of a to-be-detected sample, and building a sample space coordinate system based on the optical image and the three-dimensional shape data, the spectrum detection data is collected from a preset spectrum detection area on the surface of the to-be-detected sample; establishing a mapping relation between optical image pixel coordinates and LIBS laser focus coordinates in the sample space coordinate system; extracting image features of the optical image and spectral features of the spectral detection data, and fusing and updating the mapping relation based on the image features and the spectral features to obtain a registration result of the optical image and the spectral detection area; and performing superposition display on the optical image and the spectrum detection result aligned based on the registration result in a visual interface. According to the method, the influence caused by mechanical positioning errors, manual calibration deviations and sample morphology differences is effectively reduced, and the registration precision and robustness are improved.

The invention relates to the technical field of soil pollution detection, in particular to a soil pollution real-time detection and analysis method and system based on spectral analysis, and the system comprises a soil pollution detection platform, a soil database, a regional pollution division unit, a sample check analysis unit, a regional identification analysis unit, a pollution diffusion analysis unit and a display response unit. Analysis is carried out from two points of an unmanned aerial vehicle hyperspectral technology and a sample collection and detection technology, namely, regional pollution division feedback analysis is carried out on a spectral feature image to judge whether a heavy metal pollution area exists in a target soil area or not and the pollution degree condition, and regional pollution matching check analysis is carried out on sample parameters to judge whether the target soil area has a heavy metal pollution area or not. According to the method, the unmanned aerial vehicle hyperspectral detection can be checked and fed back through sample experiment detection, and whether the two types of detection are consistent or not can be visually known through an information feedback display mode, so that the availability of a detection result is ensured.

The invention provides a polarization modulation coupling time control phase locking high-temperature noise suppression in-situ Raman method and device, and relates to the technical field of spectrum detection. The method comprises the following steps: exciting pulse linear polarization laser to irradiate a sample to obtain Raman scattering light; a parallel vibration component (P) and a vertical vibration component (S) are obtained, and original spectral data containing polarization information and residual high-temperature noise are collected by adopting an ISCCD detector synchronously triggered by gating. Background noise is removed and a parallel vibration component (P) is extracted through polarization differential processing in combination with adaptive filtering (dynamically adjusting parameters according to signal distribution) and principal component analysis (PCA); and finally, performing signal-to-noise ratio optimization on the pure component by applying a phase locking algorithm to finally obtain a Raman spectrum result with a high signal-to-noise ratio. According to the invention, the in-situ Raman spectrum of the material within the temperature range of room temperature to 3000 DEG C can be measured, and the detection of weak signals is more sensitive.

The invention relates to an airglow layer gravity wave spectrum temperature imaging system and a two-dimensional temperature field point-surface fusion inversion method. The airglow layer gravity wave spectrum temperature imaging system comprises a fine spectrum detection subsystem, a rotation temperature spectrum measurement subsystem and a large-view-field gravity wave imaging subsystem. The three subsystems are respectively provided with three progressively-increased field angles and carry out synchronous detection, a detection area and a detection target are organically cooperated, image and data processing is carried out in the later period, and the fine spectrum detection subsystem and the rotating temperature spectrum measurement subsystem carry out cooperative calibration, so that high-precision inversion of the atmospheric temperature can be realized. And the linear relation between the airglow radiation intensity and the atmospheric temperature is obtained. A small, medium and large field-of-view collaborative observation mode is adopted, and through a point-surface fusion detection method and a data inversion algorithm, a linear relationship between high-accuracy airglow radiation intensity constructed by single-point detection and atmospheric temperature is expanded and fused to an airglow radiation field with a horizontal two-dimensional resolution capability; therefore, the temperature field with the same detection precision and the horizontal two-dimensional resolution capability is obtained.

The invention relates to the technical field of grading gangue selection of coal gangue, in particular to a grading gangue selection method of coal gangue, which comprises the following steps: acquiring mineral texture data through a multispectral imaging device, analyzing the spatial distribution of aluminum and silicon elements in combination with an X-ray diffractometer, and generating a three-dimensional component map through spatial registration and fusion with infrared heat value data; impurities are dynamically removed through sulfur element spectrum detection, and the air pressure and the material flow of winnowing equipment are adjusted by matching roasting process parameters; components of the sorted waste are analyzed through an X-ray fluorescence spectrometer, particle size data are obtained through a laser particle analyzer, a genetic algorithm is input to iteratively optimize detection channel combination and sampling density, a resource distribution instruction is generated, and equipment parameter correction is fed back. According to the method, aluminum-silicon ratio critical value accurate identification, sorting parameter dynamic adaptation and waste recycling path optimization are realized, and the problem of overburning caused by insufficient quantitative analysis of element distribution in the prior art is solved.

The invention relates to the technical field of spectrum detection, in particular to a Raman spectrum-based rice oil detection method, which comprises the following steps: extracting main and auxiliary peaks to construct a peak group structure, performing sliding comparison to output a conformity region, identifying jump to remove an abnormal signal, calibrating a peak position to generate a correction structure, and performing homing numbering to complete a detection scheme. According to the method, the feature matching rule is constructed by combining the peak position spacing, the intensity ratio and the wavenumber index, the recognition precision of the multi-peak structure in the spectrum is enhanced, non-continuous response signals are recognized and eliminated through derivative change trend and proportion deviation constraint, and the accuracy of stable response extraction is improved. Dynamic calibration and position adjustment of peak positions are realized by utilizing an offset trend sequence, the consistency of a peak group structure in an overall direction and the continuity of a local structure are ensured, a numbering system and structure attribution division is completed after homing sorting, and the integrity of feature expression in a complex sample and the orderliness and reliability of spectral data processing are improved.

The utility model relates to the technical field of detection equipment, and provides multi-spectral detection equipment for defects in industrial places, which comprises a three-axis cradle head bracket, the detector outer shell is rotationally connected with the three-axis holder bracket, and the position adjustment of the detector outer shell is controlled by the three-axis holder bracket; the visible light lens I, the visible light lens II, the infrared lens and the ultraviolet lens are mounted on the detector outer shell, and lenses of the four lenses are positioned on the same side surface of the detector outer shell; and the visible light lens I, the visible light lens II, the infrared lens and the ultraviolet lens are distributed in a crossed manner. According to the technical scheme, visible light pictures and infrared or ultraviolet pictures under the same field angle can be collected, the four lenses are distributed in a crossed mode, coordinate transformation of the pictures can be achieved conveniently, information result fusion of visible light detection and infrared or ultraviolet detection is achieved, and the detection accuracy is improved. And the detection accuracy and reliability of industrial place defects and the like can be improved.

The invention relates to the technical field of spectrum detection, and discloses a quality control method for traditional Chinese medicine capsules, which comprises the following steps: continuously scanning by using a micro light spot probe during capsule movement to obtain a spatial spectrum response sequence; performing adjacent micro-area differential operation on the sequence, and filtering a shell background and retaining a particle scattering signal by utilizing a microstructure difference between a capsule shell continuous film and a powder content discrete accumulation; according to the method, a traditional path of a shell standard model is established, through a spatial frequency domain decoupling mechanism, reference errors caused by batch drifting of shell physical attributes are avoided, and the detection sensitivity of trace component fluctuation and foreign matter mixing is improved.

The invention discloses a visible light hyperspectral measurement method based on multispectral sensing, and belongs to the technical field of spectrum detection. According to the method, visible light eight-channel data is collected through a multispectral sensor, after optical crosstalk correction and filtering preprocessing, key principal components are reserved through PCA dimension reduction, a multispectral and hyperspectral mapping model is constructed through an SVR algorithm, and finally the hyperspectral reflectivity is reconstructed through PCA inverse transformation. The problems that traditional hyperspectral equipment is high in cost and poor in portability are solved, low-cost and high-precision visible light hyperspectral measurement is achieved, and the device and the method can be widely applied to food freshness detection, agricultural product quality evaluation and other scenes.

The invention relates to the field of cavity ring-down, in particular to a cavity ring-down spectrum detection system and method, and the system comprises a detection unit, a gas path system, a constant temperature control unit and a control and processing unit. The gas path system can be used for filling inert protective gas into the ring-down cavity and maintaining a micro-positive pressure state in a non-measurement period of the detection system, so that external pollutants and water vapor are effectively prevented from invading, and lens pollution and internal adsorption are reduced; the constant-temperature control unit is used for carrying out overall temperature control on the ring-down cavity and the gas path system and inhibiting signal drift caused by water molecule adsorption / desorption; and the gas path system adopts a low-adsorption material, a dead-cavity-free structure and a low-leakage sealing joint, so that the memory effect and the leakage risk are further reduced. The invention also provides a corresponding detection method which comprises the steps of micro-positive pressure maintenance, constant temperature control, strong purification, sample measurement and the like. According to the system and the method, the measurement precision and the stability are remarkably improved, the maintenance frequency and the startup purging time are reduced, and the maintenance requirement is reduced.

The invention discloses a material quality detection system, method, medium and equipment, the material quality detection system comprises a feeding module, a conveying module, a spectrum detection module, a visual detection module, a sorting module and an information management module, the spectrum detection module is arranged at the downstream of the conveying module; comprising a camera obscura, a visible near-infrared spectrometer, a plurality of optical fiber probes, a plurality of first light sources, a plurality of second light sources, a laser distance measuring sensor and an adjustable rack, and the adjustable rack is arranged on the inner wall of the camera obscura and located above a conveying module. The information management module controls the adjustable rack to move so as to drive the multiple optical fiber probes, the multiple first light sources and the laser distance measuring sensor on the adjustable rack to move, and the multiple second light sources are arranged in the camera obscura and located below the conveying module. By arranging the spectrum detection module with the adjustable rack, optical signals of materials can be received from multiple angles, and multi-mode detection such as diffuse reflection, slow transmission and transmission is achieved.

The invention discloses a guided-mode resonance refractive index detection device and method based on a longitudinal gradient grating structure, and belongs to the technical field of optical sensing and imaging spectrum detection, the guided-mode resonance refractive index detection device comprises a light source, an optical isolator, a polarization controller, a collimation beam expander, a guided-mode resonance sensing chip, an image detector and a signal processing unit which are connected in sequence; the guided-mode resonance sensing chip is of a transmission type structure, the top of the guided-mode resonance sensing chip is provided with a strip-shaped nano structure which is consistent in period but longitudinally gradually changed, and an image detector is arranged below the guided-mode resonance sensing chip and used for receiving a transmission light signal penetrating through the guided-mode resonance sensing chip, generating a transmission light image and transmitting the transmission light image to the signal processing unit; and the signal processing unit is used for analyzing the transmitted light image and inverting the refractive index of the medium to be measured according to the structure mapping model. According to the invention, the longitudinal structure gradual change characteristic is introduced into the guided-mode resonance chip, so that the spatial distribution control of the monochromatic light resonance response position is realized, and finally the imaging refractive index sensing without an optical splitter is realized.

The invention discloses an intelligent developing active packaging film thickness uniformity detection method and system, and relates to the field of film thickness uniformity detection.The intelligent developing active packaging film thickness uniformity detection method comprises the steps that a terahertz time-domain spectrum detection device is arranged, and area scanning is conducted on a to-be-detected developing active packaging film; network edge nodes are set, and data acquisition, data preprocessing and film thickness uniformity judgment are processed step by step; based on a convolutional neural network algorithm, preliminarily confirming the film thickness of the developing active packaging film; environment data are collected, and the film thickness of the color developing active packaging film is corrected through an environment error compensation algorithm; analyzing the influence of different film thicknesses of the developing active packaging films on the data of the terahertz time-domain spectroscopy instrument, and performing feedback correction on the film thicknesses of the developing active packaging films; and carrying out uniformity evaluation on the to-be-detected developing active packaging film area. The method has the advantages that non-contact detection is adopted, the efficiency of detecting the film thickness uniformity of the developing active packaging film is effectively improved, and the error influence caused by the film thickness and the environment is avoided.

The invention provides Fourier transform spectrum equipment based on phase regulation and control and a spectrum detection method, and relates to the technical field of spectrum measurement. The Fourier transform spectrum equipment comprises a light source module used for providing detection light; the spectroscope is used for splitting the detection light into first scanning light and first reference light; the scanning module is used for introducing phase delay linearly related to the light frequency into the first scanning light to obtain second scanning light, and providing the second scanning light for the sample through the spectroscope; the reference module is used for reflecting the first reference light to obtain second reference light and providing the second reference light for the sample through the spectroscope; the photoelectric detector is used for receiving the second scanning light acted on the sample and the second reference light acted on the sample to obtain a first interference pattern; and the processing module is used for processing the first interference spectrum to obtain a spectrum detection result of the sample.

The invention relates to the technical field of coal-fired boiler control, in particular to a spectrum detection and intelligent diagnosis collaborative coal-fired boiler combustion optimization control system which comprises a spectrum detection module, and combustion flame spectrum information is collected at preset intervals by means of a fiber optic spectrometer. Collected information is transmitted to a data processing unit, and feature parameters related to the content of key substances are obtained through median filtering, wavelet transform preprocessing and PCA and PLS feature extraction. And the intelligent diagnosis module evaluates the combustion condition in the furnace based on a neural network or a support vector machine model and performs early warning in case of abnormality. And the optimization control module adjusts the air volume of the fan and the rotating speed parameter of the coal feeder according to the diagnosis result to optimize combustion. The display module is controlled to display the data through a graphical interface, and manual operation is supported. According to the system, real-time monitoring, accurate diagnosis and intelligent control are achieved, the combustion efficiency is improved, and pollutant emission is reduced.

The invention relates to the technical field of blood concentration detection by optical means, in particular to a clinical blood concentration detection method. The method comprises the following steps: acquiring the delay responsivity of spectral data to drug concentration and the change complexity of other wavebands except a preset characteristic waveband; further obtaining the interfered change credibility of the drug concentration; according to the morphological characteristics of the spectrum curve corresponding to each drug concentration in the preset characteristic wave band and the distribution difference characteristics of the data points between the corresponding spectrum curve and the preset spectrum curve in the preset characteristic wave band, obtaining the spectrum shape distortion of the spectrum curve corresponding to each drug concentration in the preset characteristic wave band; obtaining the processing beneficial confidence of the spectral data; filtering the spectral data to obtain filtered spectral data; and detecting the blood concentration. According to the method, interference components in spectrum detection are removed, so that the quality of spectrum data and the detection precision of the blood concentration are improved.

The invention provides a quartz enhanced photoacoustic spectrometry detection system environment gas interference correction method which can be applied to the technical field of photoacoustic spectrometry gas detection. The method comprises the following steps: analyzing vibration-translation relaxation time and infrared absorption peak intensity of each gas to be detected; the to-be-detected gas with the vibration-translation relaxation time exceeding the time threshold value and the absorption peak intensity larger than the intensity threshold value is selected as comparison gas; dividing the laser of the comparison gas into a first laser beam and a second laser beam according to a preset proportion; using the first laser beam to excite a sound wave signal and detecting by a quartz tuning fork to generate a tuning fork electric signal; the second laser beam is enhanced and absorbed by a multi-reflection absorption cell and then is detected by a photoelectric detector to generate a light intensity electric signal; establishing a neural network model taking the tuning fork electric signal, the light intensity electric signal and the environment gas component vector as input and taking the to-be-detected gas concentration vector as output; and correcting the concentration of the to-be-detected gas under the interference of the environmental gas in real time through the trained neural network model.

The invention relates to the technical field of unmanned aerial vehicle inspection, and discloses an unmanned aerial vehicle photovoltaic inspection detection algorithm based on dual-light fusion, and the algorithm comprises the steps: obtaining image data; performing internal parameter calibration on the dual-light camera to obtain a camera internal parameter matrix and a distortion coefficient; calibrating image registration related parameters to obtain a homography matrix; establishing a dynamic offset compensation model, and calculating to obtain a pixel offset; obtaining a defect detection result based on a dual-light image defect detection module; based on the camera calibration parameters and the homography matrix, obtaining a registered detection frame coordinate; fusing the dual-light detection results based on an IoU matching algorithm to obtain a fused detection result; according to the method, the precision and reliability of photovoltaic defect detection are remarkably improved, various defect types can be comprehensively detected, and the technical problems that traditional single spectrum detection is large in limitation, the cross-modal registration failure rate is high, and dynamic error compensation is insufficient are effectively solved.

The invention discloses a transformer substation insulator pollution positioning method, device and system fusing a multispectral image and a laser radar point cloud, and belongs to the technical field of power equipment multispectral detection and intelligent operation and maintenance. The method comprises the steps that a multispectral imaging device and a laser radar device are arranged in a measurement area facing the outdoor insulator of the extra-high voltage transformer substation, and the laser radar device is controlled to collect three-dimensional point clouds of the insulator and a surrounding structure of the insulator, controlling the multispectral imaging device to acquire multispectral images of the outer insulation surface of the insulator under a plurality of working wavebands; performing spatial registration on the three-dimensional point cloud and the multispectral image based on a calibration plate and geometric constraints, and mapping multispectral spectral information to point cloud sampling points; by introducing a multispectral three-dimensional point cloud and a virtual cleaning operator and combining multi-view joint optimization under an umbrella skirt structure parameter model, the problem that pollution assessment is unstable and not fine due to a single-view image or a simple intensity threshold value in the prior art is solved; and a reliable quantitative basis is provided for substation insulator electrical risk assessment and intelligent operation and maintenance decision.