4024 results about "Optical imaging" patented technology

An intelligent traffic management device for optimizing traffic flow at one or more intersections using reinforcement learning, comprising: a central control unit housed in a weatherproof enclosure and mounted on a structural support near an intersection; a sensor interface operatively connected to a variety of multimodal sensors, including at least radar-based vehicle detectors, inductive loop sensors embedded in the road surface, infrared pedestrian detection detectors, and high-resolution optical imaging modules; a powerful embedded computing unit consisting of a multi-core processor and a GPU configured for on-device inference; a reinforcement learning engine embedded in the computing unit, comprising a deep reinforcement learning model trained to map environmental states defined by traffic-related sensor inputs to optimized action policies for traffic light control; a signal actuation module electrically connected to traffic signal controllers, with action policies outputting signal phase durations and transitions in real time; a communications module supporting wireless connectivity and configured for device-to-device communication and cloud synchronization; a policy synchronization module configured to perform federated learning-based updates of model parameters by exchanging gradient weights or distilled traffic state vectors with neighboring intelligent traffic management devices deployed in a traffic network; where the reinforcement learning engine continuously observes traffic state vectors consisting of vehicle counts, average speeds, queue lengths, and pedestrian activity, and dynamically updates the policy to maximize cumulative traffic throughput and minimize average delay.

The invention belongs to the technical field of optical precision measurement, and particularly relates to a wafer defect detection system based on dual-channel optical imaging. According to the invention, dark field scattering and diffraction phase microscopy are combined as two optical imaging channels; optical paths of the two imaging modes are compatible and synchronized; through optical system calibration and optimization, high-precision acquisition and alignment of multi-modal images are realized; calibrating the sensitivity and resolution of the system by using a standard sample to ensure that the detection performance meets a preset requirement; carrying out dual-channel synchronous imaging on the wafer sample to be detected, and respectively obtaining a dark field scattering image and a diffraction phase image; carrying out conjoint analysis on the multi-modal data through an image algorithm, extracting size, depth and structure information of defects, and generating a high-precision defect detection report; the system specifically comprises a dark field scattering imaging module, a diffraction phase microscopic imaging module and an image processing unit. According to the invention, the defect of a single imaging mode can be effectively overcome, and the detection precision and robustness of the system are remarkably improved.

The invention discloses an AOI optical scheme automatic optimization method based on reinforcement learning, and belongs to the technical field of automatic optical detection. According to the method, a reinforcement learning technology is applied to automatic adjustment of optical schemes in a machine vision system, wafer images under different optical schemes are collected by using an AOI system, and scoring is performed by using a plurality of semantic segmentation models; constructing and training a non-reference image quality evaluation network, evaluating the optical imaging quality in real time, and designing a reward function on the basis; by using the Actor-Critic algorithm, the intelligent agent can autonomously learn an optimal parameter adjustment strategy, quickly adapt to different scenes, realize dynamic optimization of light source parameters and remarkably improve image quality, and an efficient and intelligent solution is provided for efficient application of a machine vision system in a complex industrial environment.

The invention provides an optical imaging satellite task scheduling method based on a hybrid heuristic memetic evolution algorithm, solves the problem of how to accurately and efficiently obtain satellite images, belongs to the engineering field, and is based on a constructed satellite data set, a task data set, a satellite dynamics model, a task decision model and constraint conditions, takes maximizing the satellite task completion benefit value as an objective function, and constructs a satellite scheduling decision model; constructs a hybrid heuristic memetic evolution algorithm: obtains an initial observation path solution set through clustering processing and a constraint check model; inputs the initial solution into the satellite scheduling decision model to obtain a total benefit value of the initial solution; adopts a neighborhood search algorithm to obtain a feasible solution and a total benefit value of the initial solution, and obtains the quality of the feasible solution from the total benefit value difference; combines a simulated annealing algorithm and an ant colony evolution algorithm to search, and obtains an optimal solution for optical imaging satellite task scheduling after a preset stop condition is met; the invention realizes accurate and efficient acquisition of satellite images.

The invention provides an unmanned aerial vehicle full-band countering method and system based on acousto-optic-electric composite detection. According to the invention, through synchronous cooperative detection of sound wave sensing, optical imaging and electromagnetic spectrum analysis, a composite detection signal is generated; based on the relevance between the acoustic characteristic frequency band and the electromagnetic control frequency band, extracting the working mode characteristics of the unmanned aerial vehicle and generating dynamic interference parameters; generating a synchronous interference instruction according to the time domain modulation characteristic of the dynamic interference parameter; in combination with abnormal noise distribution characteristics captured by the acoustic module and flight path offset identified by the optical module, power distribution and frequency band coverage of the interference instruction are corrected in real time, and optimized interference parameters are generated; and finally, a dynamic interference map is generated through overlapping frequency spectrum fusion of the dynamic interference parameters and the optimized interference parameters, accurate cooperative suppression is realized, full-band real-time accurate suppression of navigation, communication and power control signals of the target unmanned aerial vehicle is realized, and the countering efficiency in a complex scene is remarkably improved.

The invention discloses a PCB detection method and device based on multi-modal fusion and an adaptive algorithm, and relates to the field of electronic manufacturing detection. The method comprises the following steps: acquiring optical imaging data by using an optical imaging unit, acquiring tomography data by using an X-ray unit, and acquiring three-dimensional point cloud data by using a laser unit; collecting a reference signal, and updating detection parameters of the optical imaging unit, the X-ray unit and the laser unit; performing feature level fusion to obtain multi-modal fusion data; and inputting the multi-modal fusion data into a detection model, and performing defect comparison in combination with a historical database to obtain a defect detection result of the PCB. According to the method, optical imaging, X-ray penetration and laser three-dimensional modeling technologies are combined, and full-dimensional defect detection of the surface, the interior and the three-dimensional structure of the PCB is covered, so that the defect accuracy is improved. Meanwhile, a traditional fixed parameter detection mode is broken through through a self-adaptive intelligent algorithm, dynamic parameter optimization and multi-scene self-adaption are achieved, and the detection efficiency is effectively improved.

The invention discloses an acoustic-optical imaging semantic fusion detection method for underwater defects of a hydraulic structure, and the method comprises the steps: obtaining underwater acoustic and optical images of the hydraulic structure at the same time through underwater acoustic-optical imaging sensing for the underwater defects of the hydraulic structure; and on the basis, acoustic semantic features in the acoustic image are extracted through a semantic feature extraction module, optical image features in the optical image are processed by taking the acoustic semantic features as guidance, and a defect detection result is obtained when an underwater defect target exists in the image, so that underwater defect sound-light imaging semantic fusion detection is realized. The technology is suitable for health monitoring of various dam system hydraulic structures, and operation safety and water safety of hydraulic engineering are guaranteed.

The invention provides an evidence obtaining method and system based on image processing, and the method comprises the following steps: S1, generating a pixel-level depth-of-field distribution diagram of an input image through a multi-scale encoder-decoder network, employing an edge perception optimization layer in a decoding stage, and improving the depth-of-field boundary precision through minimizing a local gradient consistency loss function; s2, performing depth-of-field rationality verification based on an optical imaging physical model, and triggering a first-level tampering alarm by calculating a defocusing fuzzy radius and a gradient direction of a selected region when a difference between the defocusing gradient directions of a target region and a background region exceeds a preset threshold value; and S3, dynamically positioning a key pixel region, identifying a depth-of-field mutation boundary by using an edge detector, calculating by combining local texture complexity, screening a pixel set of which the entropy value is higher than a threshold value and which is located at the mutation boundary, correlating metadata to verify the rationality of the physical size and the spatial position of an object, and eliminating false detection caused by perspective transformation.

The invention relates to the technical field of smartphone surface defect detection, and discloses a smartphone defect detection method and system, and the method comprises the steps: firstly collecting defect detection image data through multi-dimensional optical imaging, and dividing the defect detection image data into a plurality of detection sub-regions; extracting surface defect features based on a texture enhancement technology, and extracting defect difference indexes in combination with pixel distribution and spatial correlation; then, the regularity of defect modes is analyzed and evaluated through multi-scale decomposition, the defect fluctuation amplitude is dynamically analyzed and evaluated through a sequential sequence, and the stability of defect difference indexes is judged by integrating the regularity and the fluctuation amplitude; and finally, comparing the stable defect difference index with reference data, and determining a detection result. According to the method, through multi-dimensional imaging, multi-scale analysis and dynamic evaluation, the recognition precision and reliability of complex surface defects are improved, the method is suitable for surface detection of smart phones of different materials and structures, and the high-quality detection requirement in large-scale production is met.

The invention belongs to the technical field of physiological parameter measurement and testing, and discloses a multi-mode optical non-contact health monitoring system and method. The system comprises a sensing measurement module, a data synchronous acquisition module, a micro-motion stabilization and correction module, a three-dimensional trajectory reconstruction module, a multi-modal data processing module and a physiological index calculation module. Optical imaging data are processed preferentially through a U-Net network and then fused with video micro-motion features, and the problem of multi-modal data coupling interference in a traditional method is solved. A mathematical mapping relation between blood flow parameters and physiological indexes is established through a diffusion optical spectrum mapping network, the segmented blood flow parameters are mapped to initial physiological indexes, and the time lag problem of single-modal data is solved through time sequence features extracted through a time sequence feature fusion network. And the weights of the time sequence characteristics and the preliminary physiological indexes are dynamically adjusted through a space-time attention mechanism, so that the robustness in a complex environment is enhanced, and the prediction precision and stability of a non-contact health monitoring system are improved.

The invention discloses an on-line detection method and system for etching quality of a laser perovskite cell, and the method comprises the steps: employing a double-camera alternate working mode, installing high-resolution CCD camera assemblies at two sides of a laser processing head in an X direction, eliminating the shielding of a motion direction, carrying out the scribing quality analysis through combining the submicron optical imaging of the CCD camera assemblies with an image processing algorithm, and carrying out the detection of the etching quality of the laser perovskite cell. According to the method, local adaptive threshold segmentation is put forward, an Otsu method is used for adaptively calculating a binarization threshold, a morphological opening operation is used for removing irrelevant information, an edge searching logic algorithm is used for searching two edges of a scribed line, finally, the two edges and a center line are fitted, and scribed line quality analysis is carried out through the three lines. And real-time power adjustment, position calibration and defect position marking are carried out by detecting the scribing quality, the calculation speed of the high-resolution optical detection system is high, detection can be carried out while machining is carried out, and machining-detection-correction closed-loop control is achieved.

The invention discloses a nondestructive testing device for a steel profile and a testing method of the nondestructive testing device. According to the method disclosed by the invention, the ultrasonic technology is combined with optical imaging, so that synchronous detection of surface and internal defects can be completed at one time. Ultrasonic waves penetrate through the interior of the steel profile, and hidden defects such as cracks and air holes are accurately recognized; the optical camera module captures visible problems such as surface scratches and corrosion in real time. The integrated detection mode avoids the tedious process of step-by-step operation required by a traditional method, for example, magnetic powder detection of surface defects and ultrasonic scanning of an internal structure are not needed, the detection period is greatly shortened, and the method is especially suitable for steel structure buildings, bridge engineering and other scenes with high requirements for detection efficiency and has good application prospects. The full-process automatic design effectively reduces the influence of human intervention, and ensures the scanning continuity of the detection area; the intelligent algorithm automatically analyzes the ultrasonic echo signal and the optical image data, and judges the defect level according to the preset standard, thereby avoiding subjective misjudgment of manual visual inspection.

The invention discloses an ultrasonic enhanced tactile sensor system, a sensor and a sensing method. The tactile sensor system comprises a multi-mode sensing unit and a processing unit. The multi-mode sensing unit integrates an ultrasonic module and a visual tactile sensing module, ultrasonic acoustic impedance matching and optical imaging transmission are achieved through an acousto-optic matching structure, and ultrasonic echo signals and tactile deformation images can be synchronously collected. In the processing unit, an event triggering module detects a contact event based on a tactile image and generates a switching signal, and a self-adaptive processing module dynamically controls an ultrasonic mode, distance measurement during non-contact, and switching to object internal imaging or material property identification during contact according to the switching signal. And the three-level fusion processing module outputs a multi-modal sensing result through signal-level synchronous acquisition, feature-level cross-modal fusion and decision-level task switching. According to the system, multi-dimensional perception of proximity sense, surface texture and deep information is realized, and the pre-judgment and accurate operation capability of the robot in a complex scene is improved.

The invention provides wafer detection equipment and a wafer detection method, which are used for solving the problem of how to improve the wafer detection efficiency. The wafer detection equipment comprises a double-sided detection unit, the double-sided detection unit comprises a scanning carrying platform, a front optical imaging module and a back optical imaging module, and the scanning carrying platform can linearly move along a first direction; the front optical imaging module and the back optical imaging module are respectively arranged on two opposite sides of the scanning stage and are respectively provided with a back bright field light source and a back dark field light source; when the scanning stage moves along the positive direction of the first direction, the front bright field light source and the back bright field light source are synchronously turned on, and the front optical imaging module and the back optical imaging module respectively generate bright field images of the front and back of the wafer; and when the scanning stage moves along the negative direction of the first direction, the front and back dark field light sources are synchronously turned on, and the front optical imaging module and the back optical imaging module respectively generate dark field images of the front and back of the wafer.

The invention relates to the technical field of chip optical detection, and discloses a high-precision defect detection method and system for a semiconductor chip. Initial detection data are obtained through laser scattering and photo-thermal microscopic detection, key visual features are extracted and converted into a multi-dimensional visual feature matrix, and the multi-dimensional visual feature matrix is used for detecting the defects of the semiconductor chip; according to the method, a fuzzy sensing area is positioned and potential defects are identified by using a map clustering algorithm, adaptive analysis of a supplementary visual angle is carried out and supplementary detection data is generated, and finally defect identification is carried out through the supplementary data and popularity information to obtain a chip defect result. The method effectively improves the precision and reliability of defect detection, especially has obvious advantages in recognition of complex and fuzzy regions, and solves the problem of insufficient precision of single-path optical imaging detection in the prior art.

The invention provides an optical imaging lens. The optical imaging lens comprises a lens barrel, a lens group and a spacing element group, and the lens group and the spacing element group are arranged in the lens barrel. The six lenses are sequentially a first lens with negative focal power, a second lens with positive focal power, a third lens with positive focal power, a fourth lens with negative focal power, a fifth lens with positive focal power and a sixth lens with negative focal power from the object side to the image side along the optical axis of the optical imaging lens; the following conditions are satisfied: 1.00 lt; cT5 / EP45 / N5lt; 1.75, 1.75; f4 / (EP34 + CP4) is greater than or equal to-2.05 and less than or equal to-1.35; and (D5m-d4s) / CP5 is more than or equal to 3.59 and less than or equal to 5.60. According to the invention, the problem that the size of the lens is increased due to the fact that a six-piece optical imaging lens in the prior art meets the performance requirement, and thus discretization is caused is solved.

The invention provides an optical imaging lens. The optical imaging lens comprises a lens barrel, a lens group and a spacing assembly, wherein the lens group and the spacing assembly are accommodated in the lens barrel; the lens group comprises a first lens with negative focal power, a second lens with positive focal power, a third lens with negative focal power, a fourth lens with positive focal power and a fifth lens with negative focal power which are sequentially arranged from the object side to the image side along the optical axis. The sixth lens has positive focal power; the seventh lens has negative focal power; the spacing assembly comprises a second spacing element which is arranged between the second lens and the third lens and is in contact with the image side surface of the second lens, and a third spacing element which is arranged on the image side of the third lens and is in contact with the image side surface of the third lens; the optical imaging lens satisfies the following conditions: 7.69 mm < = f * tan (HFOV) < = 9.27 mm, and 33.65 < EP23 / T23 < 59.35.

The invention provides an efficient crack detection and intelligent risk assessment system, belongs to the technical field of structural health monitoring, and is particularly suitable for crack detection in buildings, bridges, tunnels and industrial equipment. According to the system, comprehensive detection on the surface and the interior of a crack is realized by combining an optical imaging sensor, a laser scanning sensor and an ultrasonic sensor through a multi-mode sensor fusion technology. The system comprises a data acquisition unit, a data processing unit, a multi-modal data fusion module, a three-dimensional modeling module and an intelligent decision support module. Through an adaptive learning algorithm and a deep learning technology, the system can dynamically optimize a detection model and provide a high-precision detection result. Meanwhile, the system supports three-dimensional reconstruction and visual display of the crack, carries out real-time assessment on the crack risk through an intelligent decision support module, automatically generates a health assessment report and gives out an early warning. Compared with traditional manual detection, the system has the advantages that the comprehensiveness, the automation degree and the efficiency of detection are greatly improved, and the system is suitable for structural health monitoring in various complex scenes.

The invention discloses a snapshot type hyperspectral imaging industrial online sorting system which comprises a support assembly, an optical imaging assembly and a motion control assembly. The bracket assembly consists of a bottom plate, and an adjustable bracket and a fixed bracket which are fixed on the bottom plate; the optical imaging assembly comprises a lighting unit, an imaging objective lens and a snapshot type hyperspectral camera, and can synchronously obtain space image information of a measured object and spectral information of a continuous wave band in a single exposure process; the motion control assembly realizes automatic transmission of the measured object through the transmission platform; the data processing module is integrated with an image preprocessing unit, a spectral analysis unit and a spectral database, and is used for end-to-end closed-loop control from original hyperspectral data generation to sorting decision making; the system adopts a metasurface light splitting structure to realize real-time decoding, performs material or category identification by using a pre-trained classification model, and finally automatically generates a sorting decision signal according to an identification result to drive a motion control assembly to complete sorting operation.

The invention discloses an optical imaging and coding hole technology fused optical imaging system and method, and aims to integrate scattered polarization components in a reflected light signal into coding light field data with clear layers by constructing a polarization coding modulation system, so as to highlight a coupling relationship among optical elements. A refocusing sequence and a focal plane chromatography technology are adopted, spatial geometric information and light intensity distribution characteristics of different depth layers are fully excavated, and a three-dimensional distribution rule of surface topography is disclosed; wavefront correction and deformable mirror control technologies are introduced, imaging parameters of an optical system are adjusted in a self-adaptive mode, and the application range of measurement precision is expanded; light intensity modulation analysis and phase unwrapping window processing are combined, the change trend of the surface curvature is depicted, and key feature points of morphology measurement are grasped; finally, multi-dimensional and multi-level optical measurement information is fused, three-dimensional measurement output with rich content and reliable precision is formed, and comprehensive and high-quality measurement technology resources can be provided for application scenes such as precision optical detection and surface quality evaluation.

In accordance with at least one aspect of this disclosure, there is provided an imaging agent, a including dye compound conjugated to an antigen specific targeting vector which can be particularly advantageous because their behavior in vivo can contribute to superior optical imaging properties, for example, by significantly increasing the target-to-background ratio of imaged tissues, leading to higher resolution imaging, and ultimately providing for better recognition of malignant tissue for resection and margin assessment and improved visualization during minimal invasive laparoscopic surgery, for example. A method of imaging tumor cells in a subject, can include, administering an imaging effective amount of an imaging agent according at least one embodiment of the invention; 2-4 hours after administration of the imaging agent, irradiating a region in the subject in which tumor cells are expected to be found with at a wavelength absorbed by the imaging agent; and detecting a signal from the imaging agent, thereby imaging the tumor cells, wherein the target-to-background ratio 2-4 hours after administration is from about 2.75 to about 15.

The invention discloses an electrostatic induction and optical imaging principle-fused online monitoring device and method for wear particles of a water-lubricated bearing, and belongs to the field of state monitoring of mechanical equipment. The device comprises a square insulation detection cavity, a detection electrode array, an electromagnetic shielding shell, a high-speed optical imaging module and a signal processing unit, the square insulation detection cavity is installed in a bearing lubrication water loop. The detection electrode array is fixed to the outer wall of the cavity and used for capturing electrostatic signals generated when the abrasion particles pass through. The electromagnetic shielding shell wraps the detection cavity and is grounded through a wire to eliminate environmental electromagnetic interference. The high-speed optical imaging module integrates a high-magnification microscope lens and a CMOS sensor, is coaxially mounted with the detection cavity, and obtains the morphology characteristics of the wear particles in real time; and the signal processing unit performs multi-modal data fusion analysis on the electrostatic signal and the optical image. Through cooperative detection of electrostatic induction and optical imaging, the monitoring precision and reliability of the wear particles of the water-lubricated bearing are remarkably improved.

The invention provides an optical imaging lens and imaging equipment, and belongs to the technical field of optical imaging. The optical imaging lens comprises a first lens with negative focal power, a second lens with positive focal power, a diaphragm, a third lens with negative focal power, a fourth lens with positive focal power, a fifth lens with positive focal power, a sixth lens with negative focal power, a seventh lens with positive focal power and an eighth lens with negative focal power which are sequentially arranged in the direction of an optical axis. The image side surface of the first lens is a concave surface, the Abbe number of the fourth lens is greater than that of the third lens, the object side surface and the image side surface of the fifth lens are rotationally symmetrical aspheric surfaces, the object side surface of the sixth lens is a concave surface, and the Abbe number of the seventh lens is greater than that of the sixth lens; the object side surface and the image side surface of the eighth lens are rotationally symmetrical aspheric surfaces and are respectively a concave surface and a convex surface, and the optical imaging lens meets set optical parameter conditions. According to the invention, the requirements of miniaturization, large wide angle, large aperture and high imaging quality can be met.

The present invention relates to an in-situ micro-nano impact indentation testing instrument, falling within the technical field of material micromechanical testing. The instrument comprises a nitrogen generation module, an environmental chamber, a high / low temperature loading module, an “optical-infrared” in-situ monitoring module, an “electromagnetic-piezoelectric” coupling impact module, etc. After the nitrogen is introduced into the environmental chamber and the test area is determined by microscopic imaging, the “electromagnetic-piezoelectric” coupling impact module can drive an indenter to indent a specimen. An acoustic emission sensor embedded in the high / low temperature loading module can monitor the surface crack propagation of the specimen. The “optical-infrared” in-situ monitoring module can perform real-time high-speed optical imaging and infrared imaging on the impact indentation process. The present invention can perform micro-nano impact indentation testing on the material at high or low temperatures.

The invention discloses a melamine paper surface defect detection system based on optical detection, and relates to the technical field of industrial optical detection, and the melamine paper surface defect detection system comprises a polarized light signal generation module which employs a high color rendering index white light source to irradiate the surface of melamine paper, obtains a surface reflection light beam array carrying different polarization states, and modulates the surface reflection light beam array into eight groups of independent polarized light signals; the multispectral imaging and registering module inputs eight groups of independent polarized light signals into a free-form surface prism group and performs light splitting to generate a diffuse reflection texture image, a mirror reflection image and a near-infrared perspective image, and constructs a three-channel space registering image matrix; and the light path calibration module is used for extracting defect coordinate data and confidence score based on the pixel-level defect thermodynamic image, and performing light path compensation by adopting a real-time feedback regulation mechanism to obtain a dynamically calibrated stable optical imaging signal.

The invention provides an intrinsic solid-state ion diffusion coefficient test method and device based on optical imaging, and relates to the technical field of solid-state ion test.The method comprises the steps that a test sample is pretreated; carrying out a photoelectric test on the test sample; placing the electrochemical cell in an optical imaging system, connecting the electrochemical cell with an electrical testing system, applying a constant voltage deviating from a steady state to the monodisperse electrode plate, collecting the real-time change condition of the material under the modulation of the constant voltage in real time through an industrial camera, and outputting relational data of optical intensity and time; analyzing the diffusion path through in-situ characterization equipment, and obtaining an ion diffusion path corresponding to the to-be-detected ion battery electrode material particles in combination with dynamic information provided by an optical imaging system; and determining the characteristic time according to the relational data of the optical intensity and the time, and determining the intrinsic solid ion diffusion coefficient corresponding to the test sample by combining the characteristic time and the ion diffusion path corresponding to the to-be-tested ion battery electrode material particles.

The utility model provides a low-distortion vehicle-mounted optical imaging system and a camera module applying the same, which mainly comprise seven lenses, the first lens has focal power, the second lens has focal power, the object side surface of the second lens is a convex surface, the third lens has negative focal power, the object side surface of the third lens is a concave surface, the image side surface of the third lens is a concave surface, the fourth lens has positive focal power, and the fifth lens has negative focal power. The fifth lens has positive focal power, the object side face of the fifth lens is a convex face, the sixth lens has focal power, the seventh lens has negative focal power, through reasonable matching of the lens shapes and the focal power, the advantages of low distortion, high pixel and high resolution design are achieved, the temperature characteristic is excellent, and the image resolution ratio is high. The object identification capability of the optical system is further improved, and the design requirements of low distortion and high resolution of the optical system are effectively met.

The invention provides a sound wave generator soot blowing test method and system. The method comprises the steps that an experiment platform for simulating the working environment of a low-low-temperature economizer is built, and a test sample and sensing equipment are installed; setting power output parameters including a fixed power level and pulse power modulation parameter, a soot blowing frequency and phase control parameter, a time period and adaptive adjustment parameter, a sound wave frequency and an airflow velocity and vector control parameter; soot blowing operation is carried out, data are collected through sensing equipment, the soot coverage rate and particle information are obtained through an optical imaging sensor, and the pressure intensity generated by sound waves at the position where soot particles are located is obtained through an acoustic sensor array; calculating cleaning efficiency, and performing adjustment and iterative experiment on parameters according to the cleaning efficiency and data feedback; comprehensive optimization of the soot blowing process of the sound wave generator is achieved, the soot blowing effect of the low-low-temperature economizer is improved, then the overall operation efficiency of energy equipment is improved, the service life of the equipment is prolonged, and the requirements for environmental protection and energy saving are met.

The present invention provides an automatic focusing method, an electronic device, and a readable storage medium. The automatic focusing method comprises: using a target detection model to detect a target object in an image frame acquired at an initial focal length by an optical imaging device to be focused, so as to acquire a target object detection result; on the basis of the target object detection result, determining whether a target object is present in the image frame; if yes, determining an actual object distance on the basis of the target object detection result and the initial focal length, and on the basis of the actual object distance and a mapping relationship between the object distance and an optimal imaging focal length, determining the optimal imaging focal length; and if not, using a preset search algorithm to search for a focal length until an image having the highest definition value is found, and using a focal length corresponding to the image having the highest definition value as the optimal imaging focal length. The present invention primarily employs a deep learning-based automatic focusing method, supplemented by an image definition evaluation method. Compared with traditional passive focusing methods, the present invention greatly improves the focusing efficiency. Compared with traditional active focusing methods, the present invention eliminates a need for adding an additional optical ranging component, ensuring that the imaging device has a simple structure and a low cost.

The invention discloses an optical imaging lens, which comprises an imaging lens group, the imaging lens group comprises a lens group and a spacing element group, and the lens group is composed of a first lens, a second lens, a third lens and a fourth lens which are sequentially arranged from an object side to an image side along a first optical axis; the spacing element group comprises a first spacing element and a second spacing element; the optical imaging lens satisfies the following conditions: 6.74 lt; eP12 / T12lt; 12.80 and 31.30 lt, 12.80 and 31.30 CT2 / (T23 + CP2) lt; eP12 is the distance between the first spacing element and the second spacing element in the first optical axis direction, T12 is the spacing distance between the first lens and the second lens on the first optical axis, CT2 is the center thickness of the second lens on the first optical axis, T23 is the spacing distance between the second lens and the third lens on the first optical axis, and CP2 is the maximum thickness of the second spacing element.