36results about How to "Address diversity" patented technology

The invention discloses a test question data generation method, electronic equipment, a storage medium and electronic equipment, and relates to the field of large model technology and text data processing. The method comprises the steps that in response to a first input instruction acting on an operation interface, a target document corresponding to the input instruction is displayed on the operation interface, and the target document comprises multi-modal data; in response to a conversion instruction acting on the operation interface, displaying target text data corresponding to the conversion instruction on the operation interface; in response to a second input instruction acting on the operation interface, a generation condition corresponding to the second input instruction is displayed on the operation interface, and the generation condition comprises at least one of a target type, a target difficulty level and a target dimension; and in response to a generation instruction acting on the operation interface, displaying the target test question data on the operation interface. The technical problem of low efficiency and diversity of test question data generation in related technologies is solved.

The invention belongs to the field of non-intrusive load monitoring, and discloses a household electricity consumption analysis method based on non-intrusive load monitoring and related equipment, firstly, non-intrusive monitoring is realized by using household total electricity meter data instead of a single equipment electricity meter, and the complexity and cost of household electricity consumption data collection are reduced; secondly, an unsupervised learning method is adopted to cluster the power load state data, data does not need to be marked in advance, and different load events are automatically identified and classified, so that the problems of load type diversity and high identification difficulty are effectively solved, and the accuracy and efficiency of load event detection are improved; in combination with a depth-first search algorithm and load event constraint conditions, fine search is carried out on load event labels, an undetermined event sequence set is generated, the logicality and continuity of event sequences are enhanced, electricity utilization behavior analysis of the electric equipment is deeper and finer, home users can better understand and optimize own electricity utilization modes, and the user experience is improved. And energy conservation, emission reduction and efficient utilization of energy are promoted.

The invention discloses a sewage treatment process optimization method and device based on deep learning, and the method comprises the steps: carrying out the sample generation based on a generative adversarial network algorithm of hybrid differential privacy, and employing a reverse feature refinement strategy to adjust the data features in the sample generation process; performing feature extraction by adopting a full-connection neural network based on an adaptive wolf pack optimization algorithm; adopting a self-encoding neural network based on mask enhancement to selectively hide partial features of input data in an input layer by adopting a random mask to perform data compression and reconstruction so as to realize feature dimension reduction; and adopting a random forest algorithm based on model capacity self-adaptive pruning to perform classification prediction on the data after feature dimension reduction to obtain a classification result of the sewage treatment degree. According to the method, the sewage treatment process is integrally optimized and improved, the sewage treatment process can be monitored and dynamically optimized in real time after improvement, the sewage treatment efficiency is improved, the sewage treatment effect is improved, and it is ensured that the sewage treatment process meets the environmental protection standard.

The invention relates to a cross-department enterprise credit information knowledge graph multi-dimensional fusion method, which comprises the following steps: collecting multi-dimensional data in enterprise credit information knowledge graphs of two different departments, and indexing the multi-dimensional data; performing feature extraction on the indexed multi-dimensional data in the two departments to respectively obtain multi-dimensional data embedding representations in the source knowledge graph and the target knowledge graph; calculating a similarity value matrix of multi-dimensional data embedding representation of each entity in the source knowledge graph and the target knowledge graph; fusing the similarity value matrixes of the corresponding entity pairs between the source knowledge graph and the target knowledge graph to obtain a fusion similarity representation vector of each entity pair; inputting the fusion similarity representation vector of each entity pair into a multi-layer perceptron to obtain a final similarity score of each entity pair; and performing alignment fusion based on the entity pair with the highest final similarity score to obtain a cross-department enterprise credit information fusion knowledge graph.

The invention relates to a geothermal recharge water multi-effect treatment system, which comprises a desanding and filtering unit, a water supply unit, a water supply unit and a water supply unit, wherein the desanding and filtering unit is used for discharging impurity particles in geothermal water; the water inlet and the water outlet are located on the two sides of the tank body, the spiral pipe is located in the tank body, can rotate and enables impurity particles to be separated from water, and the drain outlet is located at the bottom of the tank body and used for discharging the impurity particles. The high-frequency electric field generating unit is located on the inner wall of the tank body and used for removing old scales in geothermal water and inhibiting generation of new scales, and a middle electrostatic field formed by the high-frequency electric field generating unit is parallel to the direction of the water inlet; the ultrasonic degassing unit is positioned on the inner wall of the tank body and is used for removing dissolved oxygen in geothermal water; and the ultraviolet sterilization unit is positioned in the water outlet. Compared with the prior art, the device has the advantages of integrating the functions of sand removal, scale removal and prevention, sterilization, degassing and the like.

The invention discloses a single cell subtype sample generation method, system, device and medium, and relates to the technical field of single cell subtype sample generation, the method comprises the following steps: obtaining a plurality of omics data; the omics data comprises a single cell genome, transcriptome sequencing expression data, clinical metadata and cell type annotation data; learning a meta-path graph of single-cell RNA sequencing data and clinical metadata through graph network data conversion, and learning representation of nodes and edges on the meta-path graph; a self-adaptive condition graph diffusion convolution model ACGDC model is constructed; inputting representations of nodes and edges into an adaptive condition graph diffusion convolution model through a graph network data conversion module, and sampling new single cell sample seeds in a Gaussian distribution space; decoding the single cell sample seeds to generate a new single cell subtype sample through a condition control sample generation method; according to the method, various high-quality single cell subtype samples can be efficiently generated.

The invention discloses an emergency communication system and method, and belongs to the field of emergency communication. The emergency communication method comprises the following steps of: acquiring a link performance parameter of a satellite communication link associated with an adjacent station node; based on the state information and the satellite communication link state of the local station node, executing at least one of the following scheduling operations on the service data: determining a first transmission performance index for transmitting data through the satellite communication link of the local station node, determining a first transmission performance index of a composite path from a wireless ad hoc network to the adjacent station node based on the state information, determining a second transmission performance index of a composite path from the wireless ad hoc network to the adjacent station node and transmitting data through a satellite communication link of the adjacent station node based on the state information, and selecting a forwarding path according to a comparison result of the first transmission performance index and the second transmission performance index; or, when the flow of the data to be transmitted meets the preset bandwidth aggregation condition, dividing the data to be transmitted into the first data part and the second data part.

The invention relates to the technical field of anti-fraud early warning, and discloses a cross-industry anti-fraud early warning method and system based on big data, and the method comprises the following steps: collecting first comprehensive information and logistics information of n continuous time points including a current time point and a previous time point; generating first two-dimensional structure data based on the first comprehensive information, and generating second two-dimensional structure data based on the logistics information; inputting the collected first comprehensive information into a risk assessment model, and outputting a risk assessment report; and the judgment result is decoded and notified to consumers and related supervision departments. The system has the beneficial effects that the logistics information of each logistics company of a plurality of countries is re-integrated, and then anti-fraud early warning is performed through the integrated information, so that the problems of data diversity and consistency caused by multi-channel logistics tracking and transportation delay are solved, and real-time monitoring and anomaly detection of the logistics state are ensured.

The invention discloses a power transformation equipment fault early warning system and method fused with defect detection, and relates to the technical field of fault early warning, and the method comprises the steps: obtaining a plurality of operation modes of power transformation equipment, carrying out the mode switching, and collecting a plurality of pieces of real-time operation data; through defect extraction, outputting a plurality of groups of defect feature vectors; carrying out fault event identification according to the multiple groups of defect feature vectors, outputting a matched fault event, and respectively calculating a plurality of corresponding risk indexes; and fusing the plurality of risk indexes, and generating a fault early warning signal according to the fused risk indexes to carry out fault early warning. The technical problems that an existing power transformation equipment fault early warning method only detects a single operation mode or specific defects, and fault early warning is poor in comprehensiveness and accuracy are solved, the real-time operation data under the multiple operation modes are fused, defect extraction and fault event recognition are carried out, and the fault early warning accuracy is improved. And the comprehensiveness and accuracy of fault early warning are improved.

This invention belongs to the field of underwater robots, specifically an in-situ filtration and preservation device for an underwater sampling robot. The inlet and outlet trays are sealed together. A filter membrane and sand core are located on the open side of the outlet tray's inner cavity. A preservative sealant cap is sealed within the inlet tray's inner cavity, and a filter chamber cover is located between the preservative sealant cap and the filter membrane. The inner cavity of the inlet tray is divided into a relatively independent preservative chamber and a seawater chamber by the preservative sealant cap and the filter chamber cover. A preservative sealant plug is installed inside the filter chamber cover. One end of the filter's suction connector is connected to the inlet tray, and the other end is fixed to a filter suction port fixing component. A one-way valve is installed between the filter suction connector and the filter suction port fixing component. This invention achieves in-situ filtration in the deep sea and automatically injects biological sample fixative for sample preservation after in-situ filtration, solving the problem of the impact of changes in environmental parameters such as temperature and pressure on the diversity and gene expression of planktonic microbial communities after deep-sea samples reach the sea surface.

The invention discloses a test system and method suitable for a carrier rocket test launching process, and belongs to the technical field of carrier rocket software. The system comprises a binding data reading module, a test transmitting process organization module, a test transmitting operation execution module, a user-defined operation interface module, a network execution interface module and the like. Through a universal data processing mode and communication interface operation among a plurality of modules, software generalization is realized, and the system is easy to expand so as to adapt to differences of launch vehicle test launch task requirements.

The invention provides a watermark recognition method and device, electronic equipment and a readable storage medium. The method comprises the steps of obtaining a to-be-recognized image; and inputting the to-be-recognized image into a pre-trained watermark recognition model to enable the watermark recognition model to calculate the contribution probability of each image position in the to-be-recognized image to the watermark classification result, determining the output probability of each watermark type included in the to-be-recognized image, and outputting the watermark recognition result in the to-be-recognized image. Therefore, wrong recognition of the watermark in the complex to-be-recognized image can be avoided, and the watermark recognition accuracy of the watermark recognition model can be improved; meanwhile, a plurality of synthesized sample watermark images carrying automatically labeled watermark type labels and watermark mask labels are adopted to train the watermark classification model, so that the problems of training sample richness and few samples are solved, and the accuracy of the trained watermark recognition model on watermark recognition is further improved.

The invention discloses an industrial printed circuit board image defect detection method based on deep learning, which specifically designs a small data set expansion scheme to enhance data diversity. The method comprises the following steps: designing an early stage of a depth separable convolution reconstruction parameterization module to construct a backbone network, designing a non-adjacent window filling block improved multi-head self-attention module to construct a lightweight neural network Transform architecture to construct the backbone network, and designing a small target step length output improved module to construct a target detection head; a defect detection model capable of positioning an industrial printed circuit board image is designed, a small target detection strategy is designed, and the small target defect learning speed and precision of the model are improved; and a label duplicate removal scheme and an adaptive defect screening scheme are designed, so that the accuracy of model prediction is improved. According to the invention, the feature learning ability of an image with a small detection target can be improved, and the defect detection performance of an industrial printed circuit board image can be effectively improved.

This invention discloses a method, apparatus, and computer device for dynamically displaying a circular progress bar on an Android device, relating to the field of Android development and application technology. The method involves initializing the inner and outer circle styles of the circular progress bar, first drawing the inner and outer circle views of the progress bar, and then, when the user sets or updates the actual value of the progress bar, invoking an Android-side attribute animation method. Within a preset animation duration, the progress bar gradually returns to various interval values ​​within the animation execution parameter value range, starting from the minimum interval value and increasing upwards. After each interval value is returned, the outer circle's rotation endpoint angle is updated and calculated based on that interval value. Then, based on the updated calculation result of the outer circle's rotation endpoint angle, the outer circle view is redrawn using an Android-side continuous drawing method, resulting in a dynamically displayed circular progress bar on the Android device. This allows for dynamic display of progress bar text prompts based on the current progress, meeting the needs of dynamic visualization.

The invention discloses a corn growth monitoring method and system combining a remote sensing technology and image recognition, and relates to the technical field of corn growth monitoring. An unmanned aerial vehicle is carried with a visible light sensor and a multispectral sensor, and obtains a color RGB image and a multiband image of a to-be-recognized area; the color RGB image and the multi-band image are preprocessed; dividing sub-regions according to the preprocessed color RGB image; identifying a corn variety type in each sub-region, and selecting a corresponding growth cycle judgment model; and inputting the preprocessed multi-band image of each sub-region into the corresponding growth period judgment model, and determining the growth period of the corn in each sub-region. By combining the remote sensing technology and the image recognition technology, the problem of diversity of corn varieties in the region is solved, and the corn growth monitoring efficiency and accuracy are improved.

The invention relates to the technical field of government affair informatization, in particular to a government affair knowledge graph construction method and system based on artificial intelligence, and the method comprises the steps: obtaining multiple pieces of multi-source government affair data, carrying out the format unification of the multiple pieces of multi-source government affair data, obtaining multiple unified texts, carrying out the cleaning segmentation of the multiple unified texts, obtaining multiple text segments, and carrying out the segmentation of the multiple text segments; performing subject recognition on the plurality of text segments to obtain a plurality of government affair entities, performing normalized alignment on the plurality of government affair entities to obtain a plurality of unique entities, obtaining a plurality of semantic relationships of the plurality of unique entities, and constructing a triple set by using the plurality of unique entities and the plurality of semantic relationships, and constructing a government affair knowledge graph by utilizing a plurality of triads in the triad set, and automatically generating a rule required by the rule engine by the government affair knowledge graph. The method can solve the problem that intelligent application of government affair knowledge is difficult due to dispersion of multi-source government affair data and low manual integration efficiency.

The utility model relates to the technical field of mobile phone accessories, and discloses a ring card bag support which comprises a silica gel shell. The plastic plate is arranged in the silica gel shell, and at least one magnet is arranged in the plastic plate; the card bag is fixedly connected to the outer wall of the silica gel shell; the arched ring and the card bag are integrally arranged; a groove for accommodating the magnet is formed in the plastic plate, and the magnet comprises an annular magnet and a tail magnet which are arranged in the groove; the outer side of the plastic plate is covered with a protection piece used for fixing the annular magnet and the tail magnet. And the protective sheet is made of a PVC (Polyvinyl Chloride) material. According to the utility model, the arched ring has the functions of a ring and a support, and can prevent slipping and support film watching. The built-in magnet realizes a magnetic attraction function, and is convenient for vehicle-mounted use. The integrated design integrates multiple functions, the burden caused by the fact that a user needs to be equipped with various accessories is avoided, and great convenience and market competitiveness are achieved.

This invention relates to the field of computer vision and image processing technology, specifically to an industrial image anomaly detection method and system based on multi-source feature fusion and synthetic anomaly enhancement. This invention aims to solve the problems of insufficient feature utilization and pixel-level segmentation edge blurring in existing unsupervised industrial image anomaly detection methods. By combining a non-parametric memory prior with a parametric fine-tuning filter network, and introducing a spatial attention mechanism to guide multi-source feature fusion, this method can effectively detect minute defects on industrial surfaces with only normal sample training. The technical solution includes: constructing a frozen multi-scale feature extractor; establishing a non-parametric feature memory; generating a coarse anomaly prior map; designing a multi-source feature parallel encoding network; constructing an attention-guided feature fusion and decoding module; generating synthetic anomaly samples based on a Berlin noise field; performing gradient-truncation hybrid forward propagation; and performing forward inference to obtain anomaly localization results.

A clinical patient nursing system comprises a mattress, the mattress comprises a plurality of air bags arranged on the mattress and further comprises air channels arranged in the mattress and communicated with the air bags, and a bed pan limiting groove is further formed in the axis of the mattress; the bed pan is arranged in the bed pan limiting groove and comprises an air bag body, the air bag body is of an annular structure with an opening in the upper portion, an air bag inner bottom is arranged below the air bag body, the portion, above the air bag inner bottom, in the air bag body is a space for bearing excrement, and an excrement discharging channel is reserved from the interior of the air bag body to the outer side of the air bag body; the bed pan further comprises a channel unit arranged in an inner cavity of the air bag body, and the channel unit communicates the outer side of the air bag body with the space for bearing excrement in the air bag body. The system further comprises nursing equipment, the nursing equipment comprises a pneumatic unit, a first hydraulic unit and a first hot air mechanism, the pneumatic unit is communicated with the gas channels, and the first hydraulic unit and the first hot air mechanism are communicated with the channel unit. The problem of complexity in clinical nursing is solved, and the working efficiency is improved.

The invention relates to the technical field of computer vision, and discloses a cartoon analysis method based on semantic consistency and structural correlation, which is used for cartoon analysis based on semantic consistency and structural correlation. The problems of low cartoon analysis accuracy and the like in the prior art are solved.

The invention relates to the technical field of automatic monitoring and early warning, in particular to a ground disaster monitoring and early warning system and method based on multi-source fusion, and the system comprises a data collection module, a background service module, a ground disaster early warning module, an early warning release module and a data visualization module. The data acquisition module is used for acquiring GNSS displacement data, sensor data and meteorological product data, and integrating various data for ground disaster monitoring and early warning. Secondly, a ground disaster early warning module capable of flexibly replacing an early warning algorithm model is designed, the module carries out model training by utilizing historical monitoring data, two optimal model files and two optimal parameter files generated by training are used for realizing rapid modeling and carrying out displacement prediction, and if the predicted displacement exceeds a threshold value, the early warning algorithm is executed; if yes, the predicted value and the early warning result are processed into a fixed JSON format and sent to the RabbitMQ to wait for consumption data of the early warning issuing module. And the early warning publishing module splices the notification content and sends the notification content to the contact person according to a mode specified by the configuration information.

The application relates to a fault self-healing control method, device and equipment of a distributed power supply connected to a power distribution network, which comprises the following steps: firstly, obtaining the network frame topology structure of the distributed power supply connected to the power distribution network; then, configuring the power distribution terminal matched with the switch on the network frame topology structure; then, numbering each power distribution terminal and dividing the sub-network and area of the power distribution network according to the number; when the power distribution network is faulty, determining the power-off area and non-power-off area on the communication network architecture of the divided sub-network and area, determining the power supply line for restoring power supply to the non-power-off area on the communication network architecture of the divided sub-network and area, and closing the tie-in switch of the power supply line to restore power supply to the non-power-off area, so as to solve the power distribution network fault self-healing problem under the condition of the line load power supply line diversification and the topology structure complication of the high-permeation connection of the distributed power supply, improve the power supply reliability of the power distribution network, and reduce the power-off loss caused by the power distribution network fault.

The invention is suitable for the technical field of industrial detection, and provides an intelligent industrial detection method and system based on image processing. The method comprises the following steps: performing detection shooting and graying processing on a target process product to generate a target grayscale image; selecting a first standard point, a second standard point and a plurality of detection points; obtaining point position coordinate data of the first standard point, the second standard point and the plurality of detection points, and calculating a plurality of detection proportions and a plurality of detection angles; and carrying out detection analysis, generating an industrial detection result, and carrying out process post-processing. Detection shooting, selection of a first standard point, a second standard point and a plurality of detection points, calculation of a plurality of detection proportions and a plurality of detection angles, and detection analysis and processing of the plurality of detection proportions and the plurality of detection angles can be carried out without comprehensive detection analysis of various characteristics of a product, so that the problems of diversity and complexity of detection are solved, and the detection efficiency is improved. And the calculation amount is greatly reduced, the calculation cost is reduced, and the risks of jamming and collapse can be effectively avoided.

The invention relates to the technical field of satellite navigation positioning, in particular to a navigation multipath signal estimation method based on particle filtering, which combines extended Kalman filtering (EKF) and a genetic algorithm to jointly optimize parameter estimation of particle filtering (PF), and comprises the following steps: firstly, in a PF importance sampling stage, utilizing the EKF algorithm and latest observation information to obtain a sample mean value and a covariance; reasonable suggestion density is provided for particle filtering, and the weight of each particle can be recalculated. And copying and eliminating a particle set by using an improved genetic algorithm in a resampling stage of particle filtering, so as to avoid the problem that the particle filtering is trapped in a local extremum. According to the method provided by the invention, the problems of particle degradation and particle diversity reduction in particle filtering can be solved, and high-precision parameter estimation of the direct signal and the multipath signal is realized, so that the influence of the multipath signal on the navigation signal performance is reduced.

The application discloses a kind of aircraft autopilot perception network training data set construction method and system.The method comprises: determining the scene richness requirement of data set collection;Each individual scene requirement and expected data proportion are refined;Each sample is combined category statistics, determines data volume according to existing data set information and project scene requirement, and is sampled based on Monte Carlo method;Actual scene building and data collection are carried out according to the sampling result.The application is based on manned electric aircraft autopilot neural network training data set scene richness requirement, designs a kind of scene richness building method, combines each scene, determines the sample quantity that needs to be collected, finally collects a large amount of sample data, and overcomes the defect that intelligent driving data set is insufficient for low-altitude flight.

The invention discloses a geologic texture synthesis method based on a GAN network, and the method comprises the steps: obtaining an original geologic texture picture, and carrying out the screening and preprocessing of the original geologic texture picture, and obtaining a geologic texture data set; calculating homogeneity, repeatability and directivity values of each picture sample in the geological texture data set to obtain a sample index range, and performing sample screening on the geological texture data set based on the sample index range to obtain a typical sample data set; and constructing a geologic texture synthesis network model based on a generative adversarial network, and inputting the typical sample data set into the geologic texture synthesis network model to obtain a synthesized geologic texture picture. Through accurate sample screening and an efficient generation algorithm, real geological texture mapping resources can be provided for the field of three-dimensional geological modeling, and researchers are helped to better understand the geological structure and form.

The invention relates to the technical field of shale oil casing deformation prediction, in particular to a shale fracturing casing deformation machine learning prediction method based on a mechanism model, and the method comprises the steps: obtaining a target to-be-processed simulation data set meeting an acquisition standard; preprocessing the target to-be-processed simulation data set, correcting each to-be-processed simulation feature set according to a preprocessing result to obtain a target actual simulation data set, and performing initial numerical simulation on each actual simulation feature set, target shale oil well reservoir slip casing variables under different influence factors are determined according to the initial numerical simulation result; obtaining influence factors which cannot be measured actually to obtain a plurality of invisible simulation feature sets, and performing inversion based on each invisible simulation feature set so as to optimize the initial numerical simulation result to obtain an actual numerical simulation result; and performing prediction training and prediction testing on the actual numerical simulation result based on the selected initial prediction standard to optimize the initial prediction standard so as to obtain an actual prediction standard.

The invention is applied to the technical field of photovoltaic modules, and discloses a treading BIPV photovoltaic module based on non-standard floating installation, the treading BIPV photovoltaic module comprises a roof, the upper surface of the roof is fixedly provided with a limiting support column and a central support column, and a voltage regulating support mechanism is arranged between a photovoltaic panel and the limiting support column and between the photovoltaic panel and the central support column. According to the treading BIPV photovoltaic module based on non-standard floating installation, when a person treads a photovoltaic panel or pressure generated by accumulated snow, sundries and the like exists in a pressure adjusting supporting mechanism, a mechanism composed of a fixed pressure bearing table, a movable pressure bearing plate, a communicating column, a communicating groove, a piston cylinder and a piston plate can effectively buffer and disperse the pressure, the pressure is transmitted through the movable pressure bearing plate, and the pressure is effectively reduced; the pressure among the fixed pressure-bearing tables is balanced through the communication columns and the communication grooves, and the piston cylinders and the piston plates can adjust the internal initial pressure state according to the pressure change, so that the local stress of the photovoltaic panel is prevented from being too large, the photovoltaic panel is protected from being damaged, and the service life of the photovoltaic module is prolonged.

The invention relates to a multi-temperature cold chain automatic distribution system and a distribution method. The invention relates to a multi-temperature cold chain automatic distribution method. The method comprises the following steps: S1, loading goods; s2, automatic delivery: carrying out path planning according to the goods information and automatically delivering the goods to a target goods taking place; s3, automatically taking the goods, notifying the client and automatically taking the goods for the client; and S4, traversing all the distribution points and then returning to the distribution station. According to the multi-temperature cold chain automatic distribution method, the goods are sub-packaged in the multiple goods box bodies, and when goods are taken every time, the goods box bodies where the goods are to be taken automatically rotate to the rear portion of the goods taking door, so that automatic goods taking is achieved; only one pick-up door needs to be opened for pick-up each time, loss of a large amount of cold air caused by frequent pick-up in the delivery process can be effectively avoided, fluctuation of the temperature in the box can be reduced, and the energy utilization rate can be increased; meanwhile, an automatic navigation mechanism is carried, full-automatic goods distribution can be achieved, manpower is saved, and the distribution cost is reduced.

The invention relates to the field of electronic equipment tests, in particular to a universal vibration tool and method for an integrated electronic system. Comprising a vibration disc and a plurality of adjusting blocks detachably connected with the vibration disc. The vibration disc is provided with a first through hole used for being connected with the adjusting block and a second through hole used for being connected with the vibration table, the integrated electronic system is connected with the vibration disc through the adjusting block, and installation of integrated electronic systems of different sizes can be met. According to the universal vibration tool, the problem of mounting interface diversification of the comprehensive electronic system in a vibration experiment is fundamentally solved, and the universal vibration disc is matched with the adjusting block, so that rapid adaptation of the comprehensive electronic systems with different sizes and different interface forms is realized, the comprehensive electronic system can be stably mounted on the tool, and the working efficiency is improved. The accuracy and repeatability of the experiment can be improved, and the defects that a traditional tool is single in structure and fixed in installation structure are overcome.