18 results about "Aerosol scattering" patented technology

The invention provides a three-dimensional scanning wind measurement laser radar system for an offshore rocket platform, which comprises a three-dimensional scanning laser radar, a shipborne attitude compensation module, a data processing module and a protective cover, and is characterized in that the three-dimensional scanning laser radar is used for emitting laser pulses and receiving original detection signals which are scattered by aerosol and penetrate through the protective cover; correcting the direction of the scanning head according to the attitude compensation signal, and outputting scanning track correction data; the shipborne attitude compensation module monitors the attitude change of the platform and generates a compensation signal to counteract the shaking influence; after the data processing module preprocesses the original signal, atmosphere three-dimensional wind field data is calculated in combination with scanning track correction data; the protective cover isolates tail flame heat radiation, strong light and seawater erosion and is used for guaranteeing detection stability; based on an offshore rocket platform scene, platform shaking is offset through shipborne attitude compensation, tail flame and seawater interference is isolated through a protective cover, the atmospheric three-dimensional wind field is calculated in combination with data processing, and the high-precision wind measurement requirement in the marine environment can be effectively met.

The invention relates to the technical field of atmospheric environment monitoring and optical detection, in particular to an aerosol vertical profile correction method and device for aerosol scattering coefficient and laser radar combined observation, and the method comprises the steps: S1, collecting echoes according to an integral window, and obtaining distance correction echoes; s2, collecting a height scattering coefficient greater than or equal to 2, and aligning the height scattering coefficient with a distance correction echo grid / time; s3, background deduction, resolution matching and invalid height elimination are carried out to obtain preprocessed echoes; s4, generating an initial scattering coefficient profile; s5, identifying layered boundary division layer intervals; s6, establishing a correction factor model for each layer, adding overlap compensation to the near earth, and introducing a system constant; s7, taking the consistency of the total height of the theoretical echo and the preprocessed echo as a target, taking the consistency of multi-height scattering coefficients as a constraint, and carrying out joint solving to obtain correction factor distribution; and S8, outputting a correction profile, boundary information and a parameter set. According to the method, system constants and overlap compensation are solved by preprocessing echo layering scale gradient correction factors through combination of full-height consistency and two-height actual measurement constraints, and a correction profile is stabilized.

The invention relates to the technical field of accident early warning, in particular to a dangerous chemical leakage accident prediction method and system, and the method comprises the steps: carrying out the region division and multi-point data collection; identifying a first temporary region when the concentration exceeds the threshold; screening a second temporary area according to temperature and light intensity changes; extracting an abnormal concerned area by spatio-temporal features; comparing the reflective area to correct the abnormal area; dynamically adjusting the threshold value based on the distribution and concentration; and triggering an alarm based on the new threshold. According to the invention, through cooperative application of various indexes such as organic matter concentration, temperature, aerosol scattering light intensity and local highly reflective surface area, accurate identification and dynamic tracking of the whole process of dangerous chemical leakage are realized. The method effectively solves the problems of delay of emergency response and low disposal efficiency caused by delayed early-stage identification of leakage and reduction of early-warning precision due to monitoring response lag and static identification mechanism.

The application discloses a method for inverting marine aerosol optical depth by using spaceborne lidar noise, belongs to the technical field of laser remote sensing, and is used for quantitatively inverting aerosol optical depth. Under the premise that system hardware parameters of the spaceborne lidar and total background noise data detected by the spaceborne lidar, environmental parameters of a corresponding region and moment are given, a noise model of solar radiation items corresponding to water surface white froth diffuse reflection and water surface specular reflection, a water-leaving noise model (a noise model of solar radiation items of water body backscattering), and an atmospheric noise model (a noise model of solar radiation items of Rayleigh scattering of atmospheric molecules and Mie scattering of aerosol particles) are respectively constructed. Water surface noise, water-leaving noise and atmospheric Rayleigh scattering noise are removed from total noise rate of the atmosphere top detected by the lidar, and aerosol scattering noise results are obtained. Finally, marine aerosol optical depth of a satellite transit region and moment is quantitatively inverted by using the aerosol scattering noise results and the aerosol scattering noise model.

The invention relates to the technical field of atmosphere image degradation simulation, in particular to an image degradation simulation method for atmosphere turbulence space-time blurring and aerosol multiple scattering, and the method comprises the steps: obtaining an atmosphere turbulence data set, and generating a three-dimensional space-time refractive index fluctuation field; constructing an atmospheric turbulence influence operator, and respectively constructing a real-time turbulence influence operator and an atmospheric turbulence influence distortion operator; constructing a multi-scattering influence operator, obtaining aerosol scattering parameters, and simulating a multi-scattering process through Monte Carlo ray tracing; fusing the atmospheric turbulence influence operator and the multiple scattering influence operator to form a composite atmospheric degradation model; and inputting the clear image into the composite atmospheric degradation model, and outputting a degraded image. According to the method, the Monte Carlo multiple scattering simulation and the dynamic turbulence operator are fused, the complex atmosphere comprehensive degradation effect can be efficiently and vividly reproduced, and continuous degradation processing of the video frame can be carried out due to the fact that the turbulence operator has space-time continuity.

The invention provides a method for selecting calibration height layers of satellite-borne laser radars with different wavelengths, and relates to the field of atmospheric remote sensing. On the basis of SAGE III / ISS and reanalysis data, optical parameters of a stratosphere blue light wave band are accurately calculated by combining wavelength conversion and data fusion; comprising the following implementation steps: step 1), selecting SAGE III / ISS data and preprocessing the data; 2) correcting the refractive index of the aerosol, and carrying out stratosphere scattering calculation; 3) establishing a stratosphere aerosol optical parameter wavelength conversion model; step 4), calculating a stratosphere blue light aerosol backscattering coefficient and an atmospheric molecule backscattering coefficient; step 5), data space-time matching fusion; and step 6), calculating an aerosol scattering ratio and selecting a calibration height.

The application discloses an aerosol scattering measurement device and method, which comprises an aerosol scattering cavity, a plurality of light sources, a motor, a photodetector bracket, and a photodetector. The aerosol scattering cavity is a hollow cylindrical cavity enclosed by an upper cover plate, a lower bottom plate and a cavity. The upper cover plate and the lower bottom plate are respectively provided with aerosol inflow holes and outflow holes. The light sources are lasers of different wave bands, and the exit ends of the lasers are connected to the laser input hole positions of the cavity. The side surface of the cavity is provided with a plurality of detection holes, and each detection hole is provided with an optical attenuation sheet. The photodetector bracket is arranged outside the cavity of the aerosol scattering cavity, the motor drives the photodetector bracket to rotate, and drives the photodetector to collect scattering signals of each detection hole corresponding to each wave band laser. The application can automatically measure scattering signals of multiple angles in a range of 360 degrees, and realize in-situ measurement and accurate identification of scattering signals in aerosol optical properties.

The invention discloses an aerosol scattering measurement device and a use method thereof, and belongs to the field of light scattering measurement, the aerosol scattering measurement device comprises an aerosol scattering cylinder, the top and the bottom of the aerosol scattering cylinder are fixedly connected with a top cover and a bottom cover respectively, and a measurement assembly is arranged outside the aerosol scattering cylinder. An aerosol circulation assembly is arranged in the aerosol scattering cylinder and comprises an input pipe which is fixedly connected to the interior of the top cover, and the axis of the input pipe coincides with the axis of the top cover; by arranging the rotatable arc-shaped detection mechanism and the modularized arc-shaped sleeve plate and utilizing a single photoelectric detector to be matched with a precise gear transmission system, full-automatic and multi-angle scanning measurement of scattered light signals is realized, the use number of detectors is remarkably reduced, and the device cost and complexity are greatly reduced; moreover, the angle measurement range is effectively expanded, and an angle scattering distribution diagram with higher spatial resolution is obtained.

The invention provides a transformer insulating oil fire smoke detection device, which comprises a dual-light-path smoke detector (1) comprising a light source module (2), a first receiver module (3) and a second receiver module (4); wherein the light source module (2) is configured to emit at least two detection light beams with different wavelengths; the first receiver module (3) and the second receiver module (4) are arranged to receive scattered light signals generated after the detection light beams are scattered by the aerosol to be detected at different scattering angles; and the signal acquisition and processing system is used for acquiring electric signals output by the first receiver module (3) and the second receiver module (4), calculating power ratios of corresponding scattered light under different wavelengths based on the electric signals, and identifying aerosol types according to the power ratios. The invention further discloses a corresponding method. According to the invention, the accuracy of transformer insulating oil fire smoke detection can be improved.

This invention discloses a method and system for improving the alarm reliability of smoke detectors. The method includes the following steps: S1, setting a background update threshold, an alarm threshold, and an aerosol type threshold. S2, initializing the background value of the smoke detector. S3, periodically updating the detection value. S4, periodically updating the long-cycle background value. S5, updating the short-cycle background value using a threshold method. S6, identifying the aerosol type. S7, alarming for fire smoke. S8, alarming for interfering substances. This invention separates the background value for calculating the aerosol scattered light power ratio from the background value for alarm decision, referring to them as the short-cycle background value and the long-cycle background value, respectively. Different background value update mechanisms are used to adapt to the influence of rapidly changing and slowly changing factors, respectively. Compared to existing methods that rely on the same background value to calculate the aerosol scattered light power ratio and alarm decision, this method can calculate the aerosol scattered light power ratio more accurately.

The invention discloses an all-sky imager aerosol optical parameter inversion algorithm constructed based on machine learning, and belongs to the field of meteorological observation. According to the method, an iterative threshold segmentation method and threshold self-optimization are used, a clear sky extraction quantitative standard is established for the first time, and the problems of manual dependence and poor consistency are solved; according to the method, an equal zenith angle scanning mode is simulated, multi-dimensional feature extraction is carried out from a sky area picture, aerosol scattering information reflecting multi-angle and multi-position information related to an aerosol scattering phase function and multi-angle information of total brightness is obtained, and key support is provided for SSA inversion; according to the method, an integrated regression model is constructed by taking the multi-dimensional features as input and AOD and SSA as output, a spatial difference and time difference matching sample is set, synchronous output is realized, a sample standard is defined, and efficiency and precision are greatly improved. The method is applied to the fields of atmosphere remote sensing, climate mode research, air quality evaluation and the like.

The invention provides an accurate ceilometer comparison and measurement method, and belongs to the technical field of ceilometers, the method comprises the steps: building an aerosol scattering feature discrimination matrix, removing an aerosol layer, reserving a real cloud layer signal, employing a cloud layer boundary Bayesian inference algorithm based on maximum likelihood estimation to obtain the posterior probability distribution of cloud base height, and carrying out the comparison and measurement of the cloud base height. Constructing a double-layer game optimization model to improve the cloud layer recognition precision and minimize the data registration error, calculating the cloud layer movement speed by adopting a cloud layer motion vector estimation algorithm, carrying out space-time interpolation correction, and calculating a correlation coefficient and a linear regression slope to judge the comparison qualification. And increment deviation analysis is carried out on all maximum cloud height values to judge full-scale performance, so that the technical problem that the comparison accuracy is reduced due to space-time mismatching of observation data of a reference instrument and a tested instrument caused by dynamic movement of the cloud layer is solved.

The application discloses a machine learning-based all-sky imager aerosol optical parameter inversion algorithm and belongs to the meteorological observation field.The application uses an iterative threshold segmentation method, optimizes a threshold automatically, first constructs a clear sky extraction quantitative standard, and solves the problems of artificial dependence and poor consistency.The application simulates an equal zenith angle scanning mode, performs multi-dimensional feature extraction from a sky area picture, obtains scattering information of aerosols which reflects multi-angle, multi-position information related to an aerosol scattering phase function and multi-angle information of total brightness, and provides key support for SSA inversion.The application sets up a regression model with multi-dimensional features as input and AOD and SSA as output, sets spatial difference and time difference matching samples, realizes synchronous output, makes the sample standard clear, and greatly improves efficiency and precision.The application is applied to the fields of atmospheric remote sensing, climate model research and air quality assessment.

The invention relates to the technical field of methane leakage laser detection based on industrial vision, in particular to a methane leakage laser detection method and system based on industrial vision, and the method comprises the following steps: monitoring the intensity of a laser signal, and capturing a signal intensity reduction event when the reduction of the intensity of the laser signal exceeds a preset intensity threshold value; aiming at the signal intensity reduction event, extracting the speed, the amplitude and the fluctuation frequency of signal intensity reduction to obtain laser attenuation mode characteristics; analyzing the color, transparency, form, internal texture, edge and moving track of the object in the laser path area to obtain visual features; associating the laser attenuation mode characteristics with the visual characteristics, and judging whether the signal intensity reduction is caused by target gas absorption or non-target aerosol scattering according to an association result to obtain a judgment result; and outputting corresponding early warning information according to the judgment result. The detection accuracy and reliability can be improved.

This invention provides an accurate cloud height comparison method, belonging to the field of cloud height technology. The invention establishes an aerosol scattering feature discrimination matrix to eliminate the aerosol layer and retain the true cloud signal. It employs a maximum likelihood estimation-based Bayesian inference algorithm for cloud boundaries to obtain the posterior probability distribution of cloud base height. A two-layer game optimization model is constructed to improve cloud identification accuracy and minimize data registration errors. A cloud motion vector estimation algorithm is used to calculate cloud movement speed and perform spatiotemporal interpolation correction. Correlation coefficients and linear regression slopes are calculated to determine the pass / failability of the comparison. Incremental deviation analysis is performed on all maximum cloud height values ​​to determine full-range performance. This invention solves the technical problem of decreased comparison accuracy caused by spatiotemporal mismatch between the observation data of the reference instrument and the tested instrument due to dynamic cloud movement.

A wind observation device includes processing circuitry configured to: acquire a reception signal of each scattered light beam from a conical scanning sensor to repeatedly emit a laser beam toward a wind observation region and to receive scattered light of each laser beam scattered by aerosol present in the wind observation region; shift a frequency of each reception signal having been acquired using a frequency shift amount corresponding to each of a plurality of mutually different wind vectors and to integrate spectra of the plurality of reception signals after the frequency shift for each wind vector; and select a wind vector corresponding to a wind vector in the wind observation region from among the plurality of wind vectors on a basis of the integrated spectrum of the reception signals for each wind vector.

This invention relates to the field of laser ranging technology, and in particular to a method for improving ranging accuracy based on waveform superposition. The steps are as follows: A precise time reference is constructed through synchronous transmission and data acquisition; the number of waveform superpositions is adjusted according to the ranging distance, with fewer superpositions for close distances to ensure real-time performance, and multiple superpositions for long distances to strengthen weak signals and suppress aerosol interference, outputting a high-quality synthetic waveform; dual-threshold target positioning is performed based on the synthetic waveform to accurately identify key sampling points at the leading and trailing edges of the echo; linear time interpolation is performed based on the key sampling points; the distance is calculated using the precise time obtained from the interpolation, and a correction coefficient is used to offset waveform broadening errors, followed by multi-calibration point fitting coefficients to compensate for hardware deviations. Thus, by using waveform superposition and threshold positioning, target misjudgment caused by aerosol scattering is eliminated, and by using interpolation subdivision and coefficient compensation to solve the accuracy reduction caused by echo distortion, the core challenge of ranging in aerosol environments is ultimately overcome.

A wind observation device (3) is configured so as to be provided with: a reception signal acquisition unit (31) that acquires reception signals of scattered light from a conical scanning sensor (1) that repeatedly emits laser light toward a wind observation region and receives scattered light of the laser light scattered by an aerosol present in the wind observation region; and a signal integration unit (32) that uses a frequency shift amount corresponding to each of a plurality of mutually different wind vectors to shift the frequency of each of the received signals acquired by the received signal acquisition unit (31), and integrates the spectrum of the plurality of frequency-shifted received signals with respect to each of the wind vectors. Furthermore, the wind observation device (3) is provided with a wind vector selection unit (33) that selects a wind vector corresponding to the wind vector in the wind observation region from the plurality of wind vectors on the basis of the spectrum of the received signals integrated by the signal integration unit (32) for each wind vector.