54results about How to "Detailed analysis" patented technology

The embodiment of the invention relates to the technical field of visual inspection, and discloses a surface defect detection method based on machine vision, which comprises the following steps: performing parameter analysis on an image quality parameter corresponding to a casting surface image to determine an image accuracy index of the casting surface image; if the image precision index of the casting surface image is not less than a precision index threshold; if the area characteristic parameters are smaller than a preset area standard characteristic threshold value, defect detection is conducted on the corresponding casting area image, and if the area characteristic parameters are not smaller than the preset area standard characteristic threshold value, the corresponding casting area image is marked as a to-be-detected defect image; and comparing the regional defect parameter with a surface defect standard index preset in a casting detection library. According to the surface defect detection method based on machine vision in the embodiment of the invention, the casting surface image is divided into a plurality of areas, and feature extraction is performed on each area, so that the surface condition of the casting can be analyzed more meticulously, and the detection accuracy is improved.

The invention relates to the technical field of signal denoising, in particular to a Beidou navigation satellite observation data purification method under a complex electromagnetic background. The method comprises the following steps: acquiring satellite observation station position data and satellite position data; satellite signal acquisition is carried out on the satellite observation stations according to the satellite observation station position data and the satellite position data, and satellite observation station receiving signals are obtained; multi-angle initial signal discretization is carried out on satellite observation station receiving signals, and an initial satellite observation comprehensive signal discrete diagram is generated. According to the invention, through systematic interference identification, signal purification, multi-angle processing and automatic precision optimization, the identification capability and filtering efficiency of interference signals are improved, so that the problem of electromagnetic interference to Beidou navigation satellite signals under a complex electromagnetic background is weakened, the flexibility of site selection of the Beidou navigation satellite continuous observation station is improved, and the accuracy of site selection of the Beidou navigation satellite continuous observation station is improved. And the precision and stability of positioning, navigation and time service are improved.

The invention relates to the technical field of motion monitoring, in particular to a running posture monitoring method based on an image recognition technology, which comprises the following steps: deploying cameras at different angles, synchronously recording whole body actions of a user during running, extracting a joint angle change sequence, and constructing a running three-dimensional action model. According to the method, the consistency and the difference of the actions are recognized by comparing the amplitude and the speed of the joint movement, so that the detection of the action defects is facilitated, and the stability and the deviation of the gait can be quantitatively evaluated by analyzing the foot landing angle and the stride change; analysis of the motion change frequency and amplitude allows coaches and athletes to adjust and optimize gaits in a targeted manner in the training process, the risk of sports injury is reduced, and through continuous simulation and motion symmetry evaluation, recognition of sports defects and adjustment of the camera angle and shooting speed, the training effect of the coaches and the athletes is improved. And the data capture and analysis process in the training process is more efficient and targeted.

The invention discloses a combustion chemical reaction kinetic data processing method and system for an ADN-based liquid propellant, and belongs to the technical field of data processing. According to the method, firstly, key information in the combustion process can be comprehensively captured by obtaining a combustion chemical reaction kinetic vector and an element state linkage vector; structured semantic mapping is carried out on the primitive state linkage vector to obtain a reaction state structured vector and a strategy association demand vector, which is helpful for accurate classification and positioning of combustion reaction related information. And the integration confidence weights of the first data and the second data are determined, so that the association degree of the element reaction data and the visual association labels under different integration strategies can be quantified, and the analysis of the combustion process is more scientific and meticulous. The finally determined visual monitoring result can visually present the characteristics of the element reaction data under different strategies, and clear and accurate data support is provided for deeply understanding the combustion mechanism of the ADN-based liquid propellant, optimizing the performance of the propellant and ensuring safe use.

The invention relates to the technical field of optical fiber communication, in particular to an optical fiber optical frequency transmission field optical fiber link noise simulation method and system, and the method comprises the steps: dividing laser generated by a laser into reference light and simulation light; modulating the analog light, performing field optical fiber transmission, and performing optical frequency processing on the analog light and the reference light to obtain a radio frequency signal; performing phase processing on the radio frequency signal to obtain continuous phase information and frequency conversion data; the method comprises the following steps: constructing an optical fiber optical frequency transmission field optical fiber noise simulation model, converting phase information and frequency conversion data into voltage data by using the noise simulation model, setting a modulation depth parameter according to the voltage data, performing modulation according to the modulation depth parameter, and adjusting the length of a laboratory winding optical fiber according to a modulation result to realize noise simulation. According to the method, different types and different magnitudes of field optical fiber link noise can be simulated.

The invention discloses a group behavior recognition method based on dynamic and static characteristics and multiple interactive networks, and relates to the technical field of computer vision, comprising the following steps: preprocessing original video data and skeleton node data to obtain dynamic and static characteristics of participants; multi-level character features are obtained by extracting coarse-grained key character information and restoring fine-grained character information; the method comprises the following steps of: obtaining a complex space-time interaction feature by applying a Space-Transform and a Temporal-Transform, and obtaining the complex space-time interaction feature by applying the Space-Transform and the Temporal-Transform; predicting an identification result through data fusion; dynamic features are utilized to supplement static features, and group behaviors of participants are comprehensively and meticulously analyzed; in order to emphasize the key figure information, the key figure information is used as a consistency constraint to guide the focus of the space-time interaction network, and the recognition capability of the model on the space-time dynamic state of the key figure is enhanced.

The present invention discloses a road quality intelligent evaluation method and system based on the Smooth Road Index. The method comprises: obtaining collected data of urban roads to be evaluated; dividing the urban roads to be evaluated into different evaluation units; obtaining health status indicators according to the collected data, and calculating the Smooth Road Index corresponding to different evaluation units according to the health status indicators, wherein the health status indicators at least include road damage parameters and bump impact parameters; dividing according to the Smooth Road Index corresponding to different evaluation units to obtain at least a multi-color evaluation map; and outputting the at least multi-color evaluation map. By implementing the method of the present invention, the scientificity and accuracy of road health evaluation can be improved, and the defects of traditional evaluation methods in terms of low coverage frequency and untimely update can be effectively compensated.

The invention discloses a dental CBCT three-dimensional tooth rapid labeling method based on an SAM large model. According to the method, an improved SAM network is utilized to distinguish teeth from periodontal membrane and alveolar bone in a CBCT image, and the method comprises the following specific steps: stage 1, conversion and processing from tooth data to trainable data; stage 2, constructing an improved SAM network model; stage 3, training a network model; and a fourth stage of tooth labeling and three-dimensional visualization based on CBCT data. According to the invention, the Lora fine tuning technology is used to help the SAM network adapt to the image characteristics of the medical image data set, so that the defect that the SAM network is only trained on a natural image originally is overcome. In addition, a CNN bypass network is adopted to make full use of spatial information in a three-dimensional slice and help capture edge information in the slice. And finally, a previous prediction result is ingeniously utilized to help to generate a target box prompt to give full play to a prompt mechanism in the SAM network. According to the method, a better tooth labeling effect can be obtained when the same small amount of labels are used for training.

The invention relates to the technical field of WiFi data processing, in particular to a method for identifying a wireless camera based on WiFi signals, which comprises the following steps: acquiring WiFi round-scan signals, decoding the WiFi round-scan signals to obtain scanning data, performing feature extraction on the scanning data to obtain scanning feature data, comparing the scanning feature data with a plurality of preset thresholds, and if the scanning feature data is compared with the plurality of preset thresholds, identifying the wireless camera based on the WiFi signals. And obtaining the target wireless camera according to the comparison result, uploading the scanning feature data to a server for data analysis, and obtaining the target wireless camera according to the data analysis result. Compared with the prior art, the method has the advantages that the scanning feature data of the WiFi round-scan signal is obtained by decoding and feature extraction of the WiFi round-scan signal, so that the hidden wireless camera can be identified by using the data transmission features reflected by the scanning feature data.

The invention provides a six-axis linkage motion platform, and belongs to the technical field of scanning electron microscopes. The X-axis linear motion mechanism comprises an X-axis linear motion structure arranged on a base; the Y-axis linear motion mechanism is arranged on the base and is used for enabling the portal frame to move in the Y direction; the Z-axis linear motion structure is arranged on the portal frame; the R-axis rotating structure is arranged on the X-axis linear motion structure and is used for enabling the sample to rotate by 360 degrees; the T-axis tilting and swinging structure is arranged on the Z-axis linear motion structure and is used for enabling the electron gun assembly to swing; and the A-axis linear motion mechanism is arranged on the T-axis tilting and swinging structure and used for providing linear motion of the electron gun assembly in the A-axis direction. The X-axis, the Y-axis, the Z-axis, the A-axis, the T-axis and the R-axis are arranged, adjustment of movement in six directions can be achieved, slicing treatment is not needed when large-size samples are observed, and precious samples are prevented from being damaged.

The invention relates to the field of image processing, in particular to an automobile part defect detection method and system based on image recognition, and the method comprises the steps: obtaining a part surface image, matching the part surface image with a standard contour to determine an optimal position, and carrying out the proportional adjustment of the standard part contour based on the optimal matching position, calculating burr coefficients under different proportions to form a burr coefficient sequence; taking any burr coefficient in the burr coefficient sequence as a target value, traversing the target value from large to small, setting a traversal stop condition, and finishing traversal in response to the stop condition reaching a minimum value; and obtaining the standard part contour of the adjustment proportion corresponding to the minimum value of the stop condition as a burr range, calculating a defect evaluation value according to the burr range, and determining that the automobile part has defects when the defect evaluation is greater than a defect threshold value. According to the invention, proportion adjustment is carried out on the contour of the standard part through the optimal matching position, the burr range after proportion adjustment is obtained, and the burr detection accuracy is improved.

This invention provides a method, apparatus, electronic device, and readable storage medium for processing electricity consumption data. The method includes clustering users based on a first frozen electricity consumption to obtain first cluster centers for electricity consumption patterns; determining a target electricity consumption cycle based on the changing trend of the first frozen electricity consumption; clustering users based on a second frozen electricity consumption to obtain second cluster centers; and comparing the first and second cluster centers to obtain an analysis result of the user's electricity consumption habits. Thus, this invention, without excessively increasing sampling pressure, obtains a more detailed analysis of electricity consumption behavior through a broader dimensional analysis of the first frozen electricity consumption, thereby providing a more scientific and reliable theoretical support for distribution network management and adjustments.

The utility model relates to a new energy commercial vehicle resolver signal detection circuit comprising a filter circuit comprising a first filter unit and a second filter unit, and the output end of the second filter unit outputs the positive differential output and the negative differential output of a resolver signal to a decoding chip; the differential circuit comprises a buffer amplification unit and a third filtering unit, the input end of the buffer amplification unit is connected with the second output end of the first filtering unit, the output end of the buffer amplification unit is connected with the input end of the third filtering unit, and the output end of the third filtering unit outputs a decoding signal; and the micro-control unit is connected with the output end of the third filtering unit, and the micro-control unit is used for judging the fault type of the rotary transformer in combination with the information of the decoding chip. According to the utility model, through combination of multi-stage filtering, differential signal processing and the micro-control unit, the stability of a rotary transformer signal can be effectively improved, and faults can be accurately diagnosed.

The utility model discloses a sewage outlet water quality monitoring device based on full spectrum, comprising a water sample processing mechanism, the water sample processing mechanism comprises a water sample collection device and a pretreatment device, the water sample collection device collects a water sample of a sewage outlet, and the pretreatment device pretreats the collected water sample; a light source that generates a light beam covering a full spectral range; the optical system is arranged opposite to the light source, and the optical system guides the light beam generated by the light source to the pretreated water sample and collects a spectrum reflected, scattered or transmitted by the water sample; the spectrograph is used for receiving a spectral signal after the light beam passes through the water sample and converting the spectral signal into a digital signal; the wireless communication module is connected with the spectrograph and used for sending the digital signals to a cloud server, and the cloud server receives the digital signals and analyzes the digital signals to extract water quality parameter information.

The invention discloses a circuit breaker mechanical state monitoring data cleaning method, and relates to the technical field of data cleaning. The invention discloses a method for cleaning mechanical state monitoring data of a circuit breaker. The method comprises the following steps of: 1, establishing a data cleaning model by utilizing an EMD algorithm; 2, acquiring and processing real-time monitoring data; 3, decomposing all monitoring data one by one; step 4, clustering all monitoring data decomposition results; and step 5, removing noise point data outside the data set. According to the method, the problem that the fault diagnosis of the circuit breaker is inaccurate due to the fact that noise and loss easily exist in the monitoring data obtained in the prior art is solved, the cleaned data are cleaner and tidier, the characteristics of the circuit breaker state data monitored in real time are better extracted, the data quality is effectively improved, and the fault diagnosis accuracy is improved. It is ensured that the operation state of the circuit breaker is better reflected by the data reserved after data cleaning, and the accuracy of fault diagnosis of the circuit breaker is improved.

The present application discloses an image threshold segmentation method, system, device and storage medium for display screen defect detection, which realizes efficient, accurate and robust defect detection, helps to improve the image segmentation effect, and can accurately segment the defective area of ​​the image, so as to facilitate the analysis of the defective image. The method of the present application includes: acquiring the initial image displayed on the display screen by a camera; downsampling the initial image to obtain a downsampled image, which is a partial image of the initial image; expanding and filling the edge of the downsampled image to obtain an extended image; pre-processing and filtering the extended image to obtain a filtered image; dynamically generating a selection window according to a window selection strategy, and selecting a target image on the filtered image through the selection window.

The invention discloses a chicken primordial germ cell transfection method which comprises the following transfection steps: S1, separating chicken primordial germ cells, and culturing the chicken primordial germ cells in a culture medium in groups, S2, mixing pPB-GFP transposon plasmids and transposase plasmids mPB according to a ratio of 3.5: 1, S3, diluting the plasmids by using opti-MEN, diluting a transfection reagent by using opti-MEN, and carrying out transfection by using opti-MEN. According to the method, the transfection operation of the chicken primordial germ cells is carried out by setting culture media with different serum addition amounts and different serum addition times, so that the influence of different serum addition amounts and different serum addition times on the transfection efficiency of the chicken primordial germ cells can be known; and then the increase and decrease of the fluorescence brightness in the transfected chicken primordial germ cells are recorded, and the growth condition of the transfected chicken primordial germ cells is known, so that the most suitable culture medium can be selected, the serum adding condition can be optimized, and more efficient transfection of the chicken primordial germ cells can be realized.

The invention discloses a GAN-based phase coherent image generation method, and relates to the technical field of image processing. The method comprises the following steps: firstly, constructing a PCGNet network comprising a preprocessing module, an image generation module and a phase correction module, designing a generator loss function and setting a discriminator; the method comprises the following steps: acquiring a source image, preprocessing the source image, and inputting the preprocessed source image into a PCGNet network, wherein the preprocessing comprises Gaussian blur and shallow feature extraction; carrying out three times of down-sampling and up-sampling processing on the preprocessed feature map, and carrying out frequency domain processing through a phase correction module to optimize phase coherence; the generator integrates pixel-level, perception, confrontation and phase loss functions to form a total loss function, and a Real-ESRGAN discriminator is adopted to provide pixel-level feedback; and evaluating the image phase difference based on an optical transfer function (OTF). The method can eliminate the influence of the phase information of the imaging target, the evaluation result is only related to the imaging system, and the phase coherence image can be effectively generated and evaluated.

This invention belongs to the field of intelligent transportation technology, specifically relating to a traffic situation analysis system based on holographic intersections. It includes edge devices, a data access module, an intersection modeling unit, a data analysis module, a data storage module, and an anomaly backtracking module. The edge devices collect cross-sectional flow, speed, queue length, vehicle trajectory, and traffic signal control data; the data access module receives this information. The intersection modeling unit constructs a detailed 3D digital model including lanes, stop lines, zebra crossings, and other elements. The data analysis module calculates multiple situation indicators such as intersection overflow degree, traffic imbalance index, and congestion degree based on traffic data and the model. The data storage module stores traffic data, the model, and records of anomalies exceeding thresholds. The anomaly backtracking module can trace back to the state before the anomaly occurred based on the anomaly records, supporting the retrieval of monitoring videos, trajectory data, and the situation results at the corresponding time, assisting in the analysis of the causes of the anomalies.

The present invention discloses a minicomputer performance optimization method and system based on dynamic regulation, which specifically relates to the field of dynamic regulation, including S1: dividing time feature text, S2: obtaining key text, S3: preprocessing key text, S4: analyzing key text, S5: comprehensive analysis, S6: optimizing performance, S7: human-computer interaction. Through the division of time feature text, a first performance key text and a second performance key text are obtained, and the key text is preprocessed to obtain keyword groups corresponding to the key texts, so as to obtain a first performance evaluation value and a second performance evaluation value through a minicomputer performance intelligent analysis model; based on the first performance keyword group and the second performance keyword group, a comprehensive performance text output value is obtained, and a comprehensive performance evaluation analysis model is constructed to obtain a comprehensive performance evaluation value, so that in the minicomputer optimization process, different optimization effects can be achieved according to the comprehensive performance evaluation value.

The present invention relates to the technical field of motor heat dissipation, and specifically to a phase change heat dissipation method and system for a propulsion motor. The invention analyzes the data distribution of multiple curve segments in the temperature curve of each position, obtains the degree of fluctuation of each curve segment, and obtains the local heat dissipation degree of each curve segment corresponding to each position; screens out abnormal heat dissipation curve segments; obtains the overall heat dissipation degree of each position according to the time characteristics of the abnormal heat dissipation curve segments corresponding to each position, and the distribution of the local heat dissipation degree; obtains multiple heat dissipation similar position groups according to the difference in the overall heat dissipation degree between adjacent positions; obtains the flow rate control coefficient of each position at each moment, regulates the initial output power of the flow rate control device, and obtains the corresponding regulated output power; assists the propulsion motor in phase change heat dissipation. The present invention assists the phase change structure in more effective motor heat dissipation by appropriately adjusting the flow rate control device of the cooling liquid corresponding to each position.

The invention discloses a method and device for determining the influence mode of a hump-type modified surface on heat transfer characteristics, and the method comprises the steps: obtaining the initial geometric information and material attribute information of a target hump-type modified surface in response to a determination signal of the influence mode of the target hump-type modified surface on the heat transfer characteristics; based on the initial geometric information and the material attribute information, constructing a three-dimensional finite element model, and controlling the three-dimensional finite element model to respectively carry out main convective heat transfer tests and main critical heat flux density tests under different main heat transfer surface areas, controlling the three-dimensional finite element model to perform secondary convective heat transfer tests and secondary critical heat flux density tests under different secondary heat transfer surface areas; based on the main convective heat transfer test result, the main critical heat flux density test result, the secondary convective heat transfer test result and the secondary critical heat flux density test result, the influence of the surface area of the target hump type modified surface on the heat transfer characteristic of the modified surface is determined.

The utility model discloses an endoscopic surgery positioning device which comprises an endoscope body, the endoscope body comprises a display panel, and the display panel is provided with a first connecting line and a second connecting line which are connected with an endoscopic probe and a point positioning device used for positioning the position of the endoscopic probe in the body. The endoscope body further comprises a fixing base and a connecting handle used for connecting the fixing base and the display panel, and a control panel used for controlling the endoscopic probe and the point location positioning device is arranged at the joint of the connecting handle and the display panel. The endoscopic probe can be used for observing local focuses inside a human body and clearly positioning the position of the endoscopic probe in the human body, so that an operation can be conveniently and externally assisted.

The invention discloses a giant panda activity area division method and system based on big data, and the method comprises the steps: constructing a geographic weighting model according to the local features of giant panda inhabiting space, then determining potential spatial distribution according to the maximum entropy principle and known position and environment data, simulating the pheromone influence in the potential spatial distribution through an ant colony algorithm, and obtaining the giant panda activity area. The method comprises the following steps: obtaining a predicted moving path through a hidden Markov chain, clustering the predicted moving path, obtaining activity intensity distribution by using a Kriging interpolation method, dividing regions, considering climate influence in each season to generate a division strategy set, selecting a division strategy with optimal ecological protectiveness and panda adaptability from the set, and carrying out clustering on the selected division strategy. The method serves as a final scheme for giant panda activity area division. According to the method, multi-source data and multiple algorithms are integrated, the accuracy and scientificity of giant panda activity area division are improved, protection and ecological research of giant panda activity areas are assisted, and meanwhile good interpretability is achieved.

The invention discloses a human motion posture correction method, system and device based on an unmanned aerial vehicle and a medium, and the method comprises the steps: obtaining a load training scheme of a user through clustering analysis, and determining a posture guidance scheme; judging whether the user is in a normal movement mode or not when the user moves; if not, reminding the user to pause the exercise; if yes, shooting a continuous frame video stream in the motion of the user; dividing the video stream according to the minimum action unit to obtain an image, extracting user contour features and calculating ambiguity, and performing deblurring to obtain a target contour so as to extract key points of a user skeleton; and according to the ideal coordinates and the actual coordinates of the skeleton key points, calculating a joint angle deviation in the motion attitude of the image frame so as to calculate a target angle deviation of the continuous motion attitude of the user in the minimum motion unit, and updating a load training scheme and an optimized attitude guidance scheme of the user. The training plan of the user can be dynamically adjusted, the load bearing scheme of the user is scientifically guided, posture correction is carried out, and the training effect is improved.

The utility model relates to strength detection technical field, concretely relates to a water conservancy project reinforcing steel strength detection device, include: base, the two sides of base upper end surface length direction symmetry fixedly connected with two slide ways, the two sides of base upper end surface width direction symmetry fixedly connected with two orifice plates, two the two sides of orifice plate opposite surface all fixedly connected with scale rule. Through the telescoping of first electric telescopic rod in vibration subassembly, realize the approach and the far away of roof and first sliding block, further realize the extrusion fixed of chuck and the one end of reinforcing steel placed in resonance recess, reinforcing steel and resonance recess contact through elastic transmission block, make vibration force transmission to resonance recess, realize the purpose of effectively amplifying to vibration force with the synergistic effect of resonance block and resonance rope, thereby promote the strength and the definition of detection signal, further improve the sensitivity and accuracy of reinforcing steel strength detection, slide realize more positioning reinforcing steel local quality problem.

The invention belongs to the technical field of nuclear reaction, and discloses a nuclear reactor physical numerical simulation method and system based on a CPU / GPU heterogeneous platform, and the method comprises the steps: assuming that each resonance nuclide adopts a subgroup fixed source equation needing to be solved for N times on average; according to subgroup transport calculation, circulation is carried out on each subgroup of each resonance nuclide in a calculation system, for M resonance nuclides, the number of calling times of a characteristic line method transport solver by a subgroup fixed source equation is MN, and characteristic line scanning calculation needs to be carried out for each calling; the MN subgroups are combined together to form a'multi-group 'structure; the multi-group structure is applied to subgroup fixed source transport calculation, feature line scanning is carried out in the whole multi-group structure at the same time, and fixed source flux of all subgroups is solved at the same time; a multi-group grouping calculation method is adopted, it is assumed that the number of energy groups adopted by final multi-group transport calculation is G, and sub-group fixed source calculation of a multi-group structure is conducted through existing multi-group transport variables.

The present invention relates to the technical field of image analysis, and discloses an image analysis device for urine detection, comprising an image acquisition unit, a data processing unit, a data analysis unit, and a result output unit. The present invention can convert a high-definition image of a urine sample from an RGB color space to an HSV color space, and more accurately describe and analyze color features; by creating a hue domain, a saturation domain, and a brightness domain, and based on the comparison of the absolute value of the difference between pixel points and the standard deviation, an abnormality analysis is performed on the high-definition image, and it can accurately determine whether the color of the urine sample is abnormal; the analysis result is presented to a user in an intuitive form, so that the user can quickly obtain and understand the test result, and a method of determining whether the color is abnormal is also used by calculating a color intensity determination value and comparing it with a preset normal urine color range.

The present invention provides a SEM push method, system and device, the method comprising the following steps: obtaining user device information, storing the user device information in a database according to different user device platforms; creating a push task according to the user device information; calling a first platform interface corresponding to the user device to execute the push task; calling a second platform interface corresponding to the user device to obtain push result information of the push task. The SEM push method of the present invention can greatly increase the proportion of push messages reaching devices, achieving push marketing effects.

The present invention discloses a method and system for dividing the activity area of ​​giant pandas based on big data, including: constructing a geographical weighted model according to the local characteristics of the giant panda's habitat space, then determining the potential spatial distribution according to the maximum entropy principle and known location and environmental data, simulating the influence of pheromones in the potential spatial distribution with an ant colony algorithm, deriving a predicted movement path through a hidden Markov chain, clustering the predicted movement path, using the Kriging interpolation method to obtain the activity intensity distribution and divide the area, and in each season, considering the impact of climate to generate a set of division strategies, and selecting the optimal division strategy for ecological protection and giant panda adaptability from the set as the final solution for the division of the giant panda's activity area. The method integrates multi-source data and multiple algorithms, improves the accuracy and scientificity of the division of the giant panda's activity area, helps its protection and ecological research, and has good interpretability.