12322 results about "Fully automated" patented technology

The invention discloses an automatic parameter adjustment test method for an electromagnetic angular displacement sensor, and the method comprises the steps: injecting a standard angle signal into a to-be-tested sensor, and collecting an output response signal; calculating a deviation value of the sensor parameter based on the output response signal and the standard angle signal, and judging whether the deviation value exceeds a preset threshold value or not; if yes, based on the deviation value, a control instruction used for compensation is generated through a self-adaptive control algorithm, and the mechanical zero position of the to-be-detected sensor or the relative position of an internal electromechanical conversion element is adjusted; based on the adjusted output response signal, the above steps are repeatedly executed, and sensor parameters are iteratively updated; and when the deviation value is lower than a preset threshold value, judging that the output precision meets a preset requirement, storing the current parameter, and completing the parameter adjustment process of the to-be-detected sensor. By constructing a closed-loop control flow of'detection-analysis-adjustment-verification 'and an adaptive control algorithm, full-automatic, high-precision and high-efficiency calibration of the zero position, sensitivity and excitation signal parameters of the electromagnetic angular displacement sensor is realized.

The invention discloses an AI low-code development component automatic generation method based on a knowledge graph, and relates to the technical field of AI low-code development, and the method comprises the following specific steps: constructing an AI development knowledge graph: constructing a knowledge graph containing a five-layer structure, collecting and preprocessing multi-source data, and extracting various entities and association relationships, so as to obtain an AI development knowledge graph; constructing an ontology structure, importing the ontology structure into a database, and forming a final knowledge graph through manual auditing and machine reasoning optimization; according to the method, the multi-dimensional AI development knowledge graph is constructed, user requirements are analyzed in combination with the optimized natural language processing model, the component configuration scheme is generated by introducing the multi-level reasoning mechanism, and finally the standardized low-code component is automatically generated, so that full-automatic conversion from the user requirements to the low-code component is realized, and the user experience is improved. The defect that an existing low-code platform depends on manual component configuration is overcome, the development period is greatly shortened, and the development cost and the technical threshold are reduced.

The invention discloses a spraying robot trajectory planning method based on depth camera scanning. The method comprises the steps that wall surface boundary polygon data, an initial spraying stroke set and a spraying dosage model parameter set are obtained; calculating a predicted coating thickness field, and performing difference calculation on the predicted coating thickness field and a preset target thickness to generate a thickness error field; performing connected domain clustering on the thickness error field to generate topological thickness error regions, and determining region type labels for the topological thickness error regions one by one; calling a matched editing operator from a discrete stroke editing operator library, performing geometric constraint verification, and generating a candidate editing scheme; and evaluating the candidate editing schemes based on a preset comprehensive scoring function, updating the initial spraying stroke set by using the scheme with the optimal score, obtaining an optimized spraying stroke set, and converting the optimized spraying stroke set into a robot control instruction. According to the method, the problem that global coverage and local thickness uniformity cannot be considered in traditional geometric planning is solved, and high-quality full-automatic spraying is achieved.

The invention discloses a high-precision full-automatic slitting system which comprises a transferring device, a slitting device and a slitting device. The feeding device is used for storing the molded connecting piece and feeding the molded connecting piece to the transferring device; the rough cutting device comprises a rough cutting mechanism and a material pulling mechanism, the transferring device is suitable for transferring the molded connecting piece into the rough cutting device, and the material pulling mechanism is suitable for clamping and pulling the molded connecting piece; the material receiving device is suitable for receiving the separated single-row products; the accurate cutting device comprises a positioning table and an accurate cutting mechanism; the transfer table is used for transferring the precisely cut products; the circulation device is suitable for sequentially carrying the products from the positioning table to the fine cutting mechanism and the transfer table; the carrying device comprises a first carrying mechanism and a second carrying mechanism, the first carrying mechanism is suitable for carrying the products to the positioning table from the material receiving device, and the second carrying mechanism is suitable for carrying the products away from the transfer table; and the discharging device is used for receiving the products carried by the second carrying mechanism. By the adoption of the structure, automatic and efficient slitting of products can be achieved.

The invention discloses a system and a method for automatically collecting metadata for a heterogeneous data source, the system and the method for efficiently collecting the metadata for the heterogeneous data source are constructed through a full-automation, unification and intelligentization technical path, and the system and the method have the advantages of comprehensiveness, automation, intelligentization and real-time performance, that is, the system and the method are not limited to a certain type of data sources any more. Comprehensive support for multiple types of data sources is realized through a unified framework; an end-to-end automatic process is constructed, and manual intervention is not needed from source discovery to metadata extraction and storage; natural language processing and machine learning technologies are fused, so that an acquisition result has business semantic comprehension and classification capabilities; through an event-driven dynamic monitoring and incremental updating mechanism, high consistency of metadata and source data is realized.

The invention provides a sole pressing machine for shoemaking and a shoe sole pressing method. The sole pressing machine comprises a rack, a left and right edge pressing device, a front and back tightening device, a pressing rod device and a jacking mechanism, and a working platform is arranged on the lower portion of the rack; the jacking mechanism is arranged on the working platform, and the left and right edge pressing device is arranged above the jacking mechanism and connected with the movable end of the jacking mechanism. The front-back tightening device and the pressing rod device are both arranged above the left-right edge pressing device, and the upper end of the front-back tightening device and the upper end of the pressing rod device are both connected with the rack. The automatic shoe taking and placing device has the advantages that in the open state, the front end and the rear end of the left-right edge pressing device are not blocked by the front lacing mechanism and the rear lacing mechanism, meanwhile, the enough distance can be kept between the left-right edge pressing device and the front-rear lacing device, automatic taking and placing operation on shoes can be conveniently achieved by means of a mechanical arm and the like, manual shoe taking and placing are not needed, and the labor intensity of workers is reduced. And full-automatic production of sole pressing operation can be realized, so that the production efficiency is improved.

The invention provides a PLC-based biomass gasification industrial steam full-automatic intelligent control system and method. The system comprises a data acquisition module, a modeling identification module, a multi-objective optimization module, a rolling prediction control module, a coordination execution module, a self-adaptive correction module and an abnormal fault tolerance and safety control module. The system collects operation data of a feeding system, a gasification furnace, a boiler, a steam-water system and an environmental protection system in real time through a PLC platform, a dynamic coupling model of a combustion side, a steam-water side and an environmental protection side is established, and a multi-target constraint optimization model with stable steam pressure, up-to-standard emission and minimum energy consumption as targets is constructed. According to the invention, unattended operation of the biomass gasification industrial steam system is realized, the system has the advantages of high control precision, low energy consumption, stable emission and strong fault-tolerant capability, and the intelligence and safety of the industrial steam system are obviously improved.

The invention relates to a full-automatic assembling machine for vehicle hooks. The full-automatic assembling machine comprises a rotary table mechanism, a first feeding mechanism, a second feeding mechanism, a third feeding mechanism, a pressing mechanism and a discharging mechanism. The pressing mechanism comprises a pressing assembly and a detection assembly; the detection assembly comprises a detection rod, a sliding table, a weighing sensor and a sliding table driving part; one end of the weighing sensor is connected with the detection rod, and the other end of the weighing sensor is connected with the sliding table through a floating connector. The full-automatic assembling machine for the vehicle hook has the following advantages that the downward pressing assembly conducts downward pressing to enable the pressing block, the clamping block with the elastic piece and the hook body to form a complete hook; the detection rod is used for simulating a rod piece clamped into the hook on the sun shield, and the weighing sensor is used for detecting the pressure of the detection rod entering the hook body and the pulling force of the detection rod separating from the hook body, so that whether the function of the hook product is normal or not is judged through the pressure and the pulling force.

The invention discloses a method and device for automatically generating a Java method unit test case based on AI, and the method comprises the steps: building a structured annotation specification, carrying out the automatic traversal and intelligent analysis of a Java project, extracting a method signature, a parameter type and a parameter constraint condition, constructing a test data generation model, and carrying out the automatic generation of the test case. The model is transmitted to an AI service to analyze business logic and boundary conditions, test case codes are generated, test cases are optimized and integrated to a project test directory, finally, code areas with insufficient coverage are identified through coverage rate analysis, a test completion strategy is generated, and iterative perfection of the test cases is completed. The technical problems that in the prior art, project-level automatic test case generation cannot be achieved, the generated test case cannot fully cover business logic and boundary conditions, and context relation understanding is lacked are solved, full-automatic project-level test generation is achieved, and the test efficiency and quality are improved.

The invention discloses a reticulocyte recognition and grading system based on a blood smear, and particularly relates to the field of medical cell morphology examination, and the system comprises an image acquisition module, a staining normalization module, an instance segmentation module, an erythrocyte classification module, a reticulocyte grading module and a statistics output module. The image acquisition module adopts an automatic microscope platform to continuously scan the blood smear under a 100-time visual field, acquires a high-quality bright field channel image through an automatic focusing technology, and monitors image definition, contrast and illumination uniformity; the statistical output module is used for calculating the proportion and bluish violet intensity statistics of reticulocytes of each level, and generating a visual quality control result and a diagnostic report; according to the invention, full-automatic processing from samples to reports is realized, interpretability and high classification precision are both considered, subjective difference and omission ratio of manual microscopic examination are significantly reduced, and efficiency and consistency of clinical detection are improved.

The invention discloses a bonding full-automatic detection system and method based on image recognition, and belongs to the technical field of semiconductor packaging quality detection.The bonding area image is collected through a multi-angle visual sensor, bonding points are recognized and positioned, coordinates, sizes and arc heights of the bonding points are recorded, and a node network model is constructed according to a spatial distribution structure; selecting an initial node in the model to set a reference, transmitting reference values in sequence along a preset path, judging whether the reference is updated or not by each node by comparing a measured value with a received value, and recording a deviation state at the same time; in the process, the reference adjustment amplitude is recorded in real time, the accumulated adjustment amount of each path is calculated, abnormal transmission paths are identified, and deviation node density is counted to mark abnormal areas; and finally, according to the number of the abnormal paths and the area of the abnormal region, carrying out bonding quality judgment, automatically calculating the marking position of an unqualified product, and executing laser marking.

A full-automatic packaging scheduling method based on a multi-objective optimization algorithm, which method relates to the technical field of intelligent production scheduling in packaging workshops. The method comprises: on the basis of work orders to be packaged of a production line, extracting production data of the production line, and initializing parameters; constructing a multi-objective optimization model of the packaging production line; to address the problems of premature convergence and susceptibility to local optima in an INSGA-II algorithm, using the INSGA-II algorithm to improve an initialization method, crossover and mutation strategies and crossover and mutation factors, and performing solving on the basis of objective functions such as minimizing the maximum makespan, minimizing the maximum energy consumption and minimizing the total machine load, so as to generate an optimized scheduling scheme; and starting packaging operations on the basis of the generated optimized scheduling scheme. The method can increase the unit-time production capacity of a production line, and effectively solve the problems in packaging production scheduling, thereby reducing the production costs of enterprises and improving the packaging production efficiency.

The invention belongs to the technical field of strip mine step line automatic extraction, and discloses a strip mine step line automatic extraction algorithm based on double RANSAC optimization shape detection, and the method comprises the steps: introducing a block processing strategy, and controlling the scale of each sub-point cloud through dividing sub-regions; samples are randomly extracted from the disordered point cloud according to plane sample data, shapes are extracted through probability selection and connection of the multiple samples, and finally optimization and storage of the shapes are completed; and setting a normal vector threshold value, a point set number threshold value and a point cloud density threshold value so as to effectively filter out an inclined plane, a curved surface and a residual point set and reserve a target shape area. According to the invention, full-automatic extraction of the step line is realized by using the point cloud data, and the extraction can be completed within half a workday. And large subjective errors exist in manual extraction, the precision and efficiency of the extraction result can be greatly improved by utilizing a computer technology based on the high-precision point cloud data, the labor and time cost is reduced, and the engineering benefit and the economic benefit are remarkable.

The invention belongs to the field of hydrogen filling, and relates to an automatic hydrogen filling system for a hydrogenation mother station, which comprises a hydrogen purification device, a plurality of hydrogen compressors, a plurality of filling main pipes, a plurality of branch pipelines, a plurality of emptying pipelines, a plurality of filling hoses and a control system, an outlet of each hydrogen compressor is connected with a compressor outlet pressure gauge and a check valve, each branch pipeline is provided with a branch stop valve, and each emptying pipeline is provided with an emptying adjusting valve. And the control system is in signal connection with the compressor outlet pressure gauge, the branch stop valve, the emptying regulating valve and a long pipe vehicle pressure gauge arranged on the long pipe vehicle, and is used for automatically executing the actions of boosting, depressurizing, filling and stopping filling according to the pressure difference. Compressor pressure, filling header pipe pressure and long pipe vehicle pressure cooperate with one another, full automation and full flow of filling boosting and depressurization are achieved, and the working efficiency is improved.

The invention discloses a method and device for identifying organic matter pores in a shale electron microscope scanning image, and the method comprises the steps: obtaining a shale scanning electron microscope original image, carrying out the manual marking, and generating an original image and mask image data set; performing synchronous data enhancement on the data set and dividing a training set and a verification set; constructing an improved U-Net model containing a multi-scale feature fusion input module, a residual attention module and a wavelet domain feature enhancement center module; training the model by adopting a dynamic mixed loss function and an AdamW optimizer; and verifying the model through an average intersection-to-union ratio, a pore Dice coefficient and a pore error, and identifying the pores of the image to be processed after reaching the standard. The device correspondingly comprises an image acquisition annotation module, a data preprocessing module, a model construction module, a training module, a verification module and a pore recognition module. According to the method, full-automatic identification is realized, the multi-scale pore segmentation precision and the low-porosity sample adaptability are improved, and the efficient characterization requirement of the shale gas reservoir is met.

The invention provides a boiler welding seam full-automatic detection system and method based on machine vision and an ultrasonic phased array, and relates to the technical field of boiler detection.The system comprises a six-axis mechanical arm unit, a multi-degree-of-freedom boiler fixing platform unit and a welding seam type recognition device; the boiler is arranged on the multi-degree-of-freedom boiler fixing platform unit and used for driving the boiler to do vertical motion, inclined motion and rotary motion, the six-axis mechanical arm unit is arranged on one side of the multi-degree-of-freedom boiler fixing platform unit, the welding seam type recognition device is arranged at the tail end of the six-axis mechanical arm unit, and the welding seam type recognition device is arranged on the other side of the multi-degree-of-freedom boiler fixing platform unit. And the six-axis mechanical arm unit is used for driving the welding seam type identification device to move and identifying a circular seam and a longitudinal seam of the boiler. According to the invention, full-process automation of boiler welding seam detection is realized, the detection efficiency and the defect detection rate are improved, the safety risk of manual detection is eliminated, and the detection quality consistency and the industry standardization level are remarkably improved.

The invention discloses an automatic auditing and checking system and method for substation operation safety. The system comprises an automatic data acquisition module, a data semantic fusion analysis module, a dynamic auditing rule generation module, a risk collaborative prediction module, an automatic information pushing module and a visual interaction configuration module. All the modules are connected through an intranet data interface and a system internal communication protocol, aiming at the prominent problems that the auditing process depends on manpower, the information system is split, the system semantics is difficult to understand, the risk identification is not comprehensive, the rule adaptability is poor, the response and push chain is broken and the like commonly existing in the existing substation operation auditing work. The invention provides an automatic auditing and checking system and method for substation operation safety, and aims to construct a full-process closed-loop intelligent auditing platform with semantic comprehension capability, multi-source data fusion capability, risk collaborative prediction capability and dynamic rule evolution capability.

The invention discloses a portable wagon balance full-automatic folding and unfolding and vehicle weighing method, and relates to the technical field of intelligent weighing equipment and automatic control, and the method comprises the following steps: S1, recognizing a license plate, checking vehicle parameters, and assigning AGV trolleys with corresponding axle numbers; s2, enabling the trolleys to carry the wagon balance formation to pre-position at the bottom of the vehicle; s3, accurately aligning the trolley and placing a wagon balance; s4, guiding the vehicle to roll the wagon balance, and acquiring and processing data to obtain axle load and total weight; and S5, after weighing, guiding the vehicle to drive away from the area, recovering the wagon balance by the trolley, and waiting for the system. Vehicle parameters are obtained by means of roadside visual recognition, wagon balance alignment placement and recovery are cooperatively completed in combination with the AGV, manual operation is not needed, multi-axle vehicle weighing can be completed by a single person, single-time operation time is greatly shortened, manual weighing data errors can be reduced, meanwhile, the vehicle parameters are complemented through the laser radar, the AGV adapts to the complex environment, and the working efficiency is improved. Safety is guaranteed through wagon balance self-checking leveling, vehicle speed monitoring and the like, and the system is suitable for multiple scenes.

According to the sorting control system of the flow cytometry sorting instrument, liquid drop images are shot through a camera, and liquid drop states are quantitatively evaluated and monitored on the basis of image content information. In order to determine the liquid drop breaking state, a liquid drop image stroboscopic shooting mode is designed to observe the liquid drop state, and the STM32H7 provides a synchronous control signal. When the droplet generation state is stable, the droplet breaking image is close to a stationary state. The stroboscope lamp is controlled to be turned on at different moments in a period, so that different states of liquid drop generation can be observed. The time difference between the detection time and the charging time is quantitatively determined through liquid drop delay control, and accurate delay control over sorting is achieved. And finally, a full-automatic algorithm is adopted to calibrate the liquid drop time delay, the liquid drop time delay is continuously tried to be changed, and when the shooting brightness of the sorted CCD camera under a certain liquid drop time delay is the highest, the time delay is considered to be the current liquid drop time delay, so that full-automatic calibration of the liquid drop time delay is realized.

The invention discloses a rock mass structural surface identification method and system based on adaptive neighborhood and multi-seed-point growth, and relates to the technical field of geotechnical engineering, geological exploration and mining engineering, and the method comprises the steps: carrying out the adaptive non-uniform downsampling of three-dimensional point cloud data based on local feature entropy; retaining key geometric features of the structural surface while compressing the data volume; fusing the normal vector and the local point cloud density to carry out multi-feature classification; an improved region growing algorithm supporting parallel growth of multiple seed points is adopted, and a structural surface is accurately recognized; automatically extracting occurrence, spacing, trace length and roughness parameters of each structural surface; performing full-automatic advantage grouping on the occurrence through a DP-DBSCAN hybrid clustering algorithm; and constructing a three-dimensional discrete fracture network model based on the statistical parameters, and integrating the three-dimensional discrete fracture network model to discrete element software for mechanical response analysis. According to the method, full-process automation of rock mass structural surface recognition is realized, and the processing efficiency, the recognition precision and the engineering practicability are remarkably improved.

The invention relates to the technical field of intelligent inspection of power equipment, and particularly discloses a power transmission line inspection system based on an autonomous correction long-endurance unmanned airship. The system aims to solve the problems of short endurance, small operation radius, single image angle, intermittent operation, leak detection, low precision, poor environmental adaptability and the like caused by dependence on manpower or GPS navigation in the conventional unmanned aerial vehicle inspection. The system comprises an energy supply module, a data acquisition module, an intelligent control module and a communication and data return module. Wherein the energy supply module is integrated with a solar energy collection, storage and intelligent scheduling unit to realize day-and-night continuous energy supply; the intelligent control module adopts an RT-DETR visual algorithm to identify a tower in real time, performs automatic deviation correction by fusing pose information, and accurately tracks a preset track; the data acquisition module supports multi-angle high-definition imaging, and the communication module guarantees real-time data return. And high-precision unmanned inspection with ultra-long endurance, full-automatic and wide-area continuous coverage is integrally realized.

The invention discloses a tidal flat automatic extraction method fused with an irregular hexagonal grid. The method comprises the following steps: step 1, constructing a time sequence remote sensing data set; step 2, establishing a precision verification sample library; step 3, screening spectral indexes; 4, synthesizing an extreme tide level image; 5, generating an irregular hexagonal grid; step 6, carrying out adaptive threshold segmentation; step 7, secondary elimination of confused ground features; step 8, tidal flat range extraction and precision verification; according to the method, based on a time sequence remote sensing image set, pixels at all positions are screened through a specific spectral index maximum value, a new extreme tide level image is formed through combination, spatial heterogeneity of a complex coastal zone is adapted through an irregular hexagonal grid and a bottom-to-top hierarchical merging strategy, local self-adaptive threshold segmentation is achieved in cooperation with a local Otsu algorithm, and a new extreme tide level image is obtained. The optimal grid scale is automatically determined by means of an elbow method, and the confused ground features are secondarily eliminated through the time sequence standard deviation, so that the problem of miscarriage of the confused ground features is effectively solved, and high-precision full-automatic extraction of the tidal flat is realized.

The invention discloses automatic feeding and punching equipment for injection molded parts, and relates to the field of punching equipment, the automatic feeding and punching equipment comprises a rack, a material taking mechanism, a transfer carrier, a multi-axis manipulator, a punching mold and a feeding mechanism, the material taking mechanism comprises a vibration disc assembly, a three-axis translation module and a first suction assembly, and the first suction assembly is installed on the three-axis translation module; a first suction assembly is arranged on the multi-axis manipulator, the first suction assembly adsorbs and fixes injection molding parts and arranges the injection molding parts on the transfer carrier, a second suction assembly is arranged on the multi-axis manipulator, the second suction assembly adsorbs and fixes the injection molding parts arranged on the transfer carrier, the feeding mechanism comprises a pushing assembly and a guide rail, and the guide rail extends into the punching mold. The material pushing assembly is used for pushing the injection molding part into the punching mold along the guide rail; full-automatic feeding and discharging operation is achieved, multiple products can be synchronously subjected to circulating punching treatment, batch high-speed punching separation is adapted, the product punching efficiency is remarkably improved, the consistency of the appearance and precision of finished products is improved, and complete separation of injection molding products is guaranteed.

The invention discloses a flexible circuit board warping degree non-contact detection method and system, and the method comprises the steps: carrying out the multi-angle scanning of a target flexible circuit board, and obtaining three-dimensional point cloud data; separating a component area and a circuit board substrate area based on a deep learning algorithm, and constructing a circuit board substrate three-dimensional model; a reference reflecting plate is arranged at the bottom of the three-dimensional model, relative spatial position parameters of a reference plane and the detection device are obtained in real time, and a circuit board three-dimensional substrate model is constructed; constructing a self-adaptive coordinate system, and mapping the three-dimensional substrate model of the circuit board into a reference plane coordinate system; curvature parameters of all nodes of the three-dimensional model are calculated through differential geometric analysis, and a curved surface gradient tensor field is constructed; and obtaining a maximum warping amount, a regional warping gradient value and an overall warping degree distribution parameter. The method has the advantages that the warping degree of the circuit board is accurately evaluated through three-dimensional scanning, a deep learning algorithm and differential geometric analysis, and the method has the advantages of high precision, full automation and quick response.

The application discloses a kind of full automatic waste fabric identification sorting control system, it is related to resource reusing technical field, including identification analysis module, the type, color, component and fibre fineness data of waste fabric on the surface of automatic conveying module are acquired and analyzed by identification analysis module, obtain the component composition and its weight distribution of each area of waste fabric, generate data form and send to data module, and sorting action module is controlled by sorting strategy control module to carry out sorting screening;Using machine vision technology and fabric visual identification model determines the type of waste fabric and divides its area, so that different parts of fabric can be detected and identified, improve the component identification precision of fabric;By extracting the color value of different areas and correcting the color value of spectral data in the identification analysis module, the influence of the color on the surface of the fabric on light, especially visible light, is eliminated, making the spectral data closer to the truth, and the analysis result is more accurate.

The invention discloses a high-precision and automatic dental crown generation method. The method comprises seven steps of oral cavity three-dimensional data acquisition, full-mouth tooth semantic segmentation, upper and lower jaw point cloud precise registration, abutment and associated gingiva precise segmentation and trimming, abutment surrounding environment multi-tissue segmentation, neck-edge line secondary precise detection, and dental crown generation and multi-dimensional refinement. The method comprises the steps of oral cavity three-dimensional data acquisition, full-mouth tooth semantic segmentation, upper and lower jaw point cloud precise registration, abutment and associated gingiva precise segmentation and trimming, abutment surrounding environment multi-tissue segmentation, neck-edge line secondary precise detection and dental crown generation. Through combination of deep learning and a point cloud algorithm, high-precision segmentation of teeth and gingiva and precise reduction of an occlusion relationship are realized, an oral anatomical feature library and a clinical repair standard are fused, and through multi-dimensional fine adjustment optimization, a dental crown 3D model which is high in fitting degree, harmonious in occlusion and capable of meeting clinical requirements is generated. The method is full-process automatic, greatly improves efficiency, reduces operation threshold, reduces material waste and diagnosis and treatment cost, remarkably improves repair success rate, and is suitable for various oral repair scenes.

The invention provides a Bluetooth equipment battery endurance test method, which is characterized in that a Bluetooth signal is sent and / or received through a Bluetooth adapter, a voltage value of a battery is acquired through a power supply monitoring module, and the method comprises the following steps: when a user tests Bluetooth equipment, the Bluetooth signal and the voltage value of the Bluetooth equipment are acquired; determining the device type of the Bluetooth device according to the Bluetooth signal, and determining an operation instruction through the Bluetooth device type; performing power consumption operation on the Bluetooth equipment according to the operation instruction; and determining the endurance of the battery of the Bluetooth equipment according to the Bluetooth signal and the change of the voltage value. The Bluetooth signal and the voltage value are acquired at the same time, so that the cruising ability of the Bluetooth equipment is measured, a real use scene is simulated, the Bluetooth equipment is fully automatically tested, manual operation is not needed in the process, and the test is efficient and accurate.

The invention relates to the technical field of seabed base adjusting platforms, and discloses a seabed base self-adaptive leveling device and method based on shape memory alloy, and the device comprises a seabed base observation platform which is used for bearing instruments and equipment; the leveling supporting legs are uniformly distributed below the seabed-based observation platform and are used for realizing shock isolation and shock absorption and full-automatic and high-reliability leveling after the seabed-based observation platform touches the bottom by utilizing the shape memory effect and the superelasticity of SMA (Shape Memory Alloy); and the universal joint connecting mechanism is used for connecting the leveling support leg with the foot pad so as to adapt to and support slopes with different angles. The shape memory effect and the hyperelasticity of SMA are utilized, under the condition that an external power source and a complex control system are not needed, full-automatic and high-reliability leveling after the platform touches the bottom is achieved, and the technical problems that according to an existing leveling scheme, limitation of different degrees exists in the aspects of structure complexity, environment adaptability, long-term reliability and leveling precision are solved.

The utility model belongs to the field of disc stacking machines, and provides a stock bin type disc stacking machine which comprises a machine frame, a conveying belt, a feeding device and a discharging device. The grabbing mechanism is arranged on the rack and located above the conveying belt, the movable end of the grabbing mechanism is connected with a clamping jaw and a magnetic attraction block which are arranged in a height difference mode, and the grabbing mechanism can drive the clamping jaw and the magnetic attraction block to turn over and change positions. Compared with the prior art, the device has the advantages that by using the clamping jaw and the magnetic attraction block which are arranged in a height difference mode, workpieces of various shapes and sizes can be rapidly and accurately processed, the operation flexibility of the device is greatly improved, and the application range of the device is greatly widened; and meanwhile, by means of coordinated operation among the feeding area, the stacking area and the conveying mechanism, the full-automatic process from workpiece machining to finished product stacking is achieved, the requirement for manual intervention is reduced, the labor cost is reduced, the overall efficiency of a production line is remarkably improved, and meanwhile the workpiece quality is guaranteed.

The invention is suitable for the technical field of powder metallurgy and advanced ceramic material sintering equipment, and provides an integrated flash sintering device for vacuum and a sintering method. The device comprises a power supply module, a high vacuum module, a first servo hydraulic machine, a second servo hydraulic machine, a third servo hydraulic machine, a mold rotation switching module, a vacuum feeding module, a green body pressing module, a demolding and mold cleaning module and a mold transfer module. According to the invention, an integrated gear tray design is adopted to integrate the functions of die installation, graphite paper treatment and green body pressing, and online synchronous cleaning of an electrode and a die is realized through die fixation and a cleaning brush arranged in a cleaning drum; therefore, full-automatic, high-efficiency and high-stability continuous production of flash sintering from powder filling to finished product collection is realized.