199results about How to "Reduce human intervention" patented technology

The invention relates to the technical field of unmanned aerial vehicle inspection, and discloses a power transmission line unmanned aerial vehicle inspection task intelligent allocation collaborative planning method based on a genetic algorithm. The method comprises the following steps: firstly, collecting and analyzing basic information of a power transmission line, an unmanned aerial vehicle, a surrounding environment and weather, and establishing a space model of unmanned aerial vehicle inspection by using a grid method; based on the collected information, establishing a mathematical model to allocate inspection tasks of the unmanned aerial vehicle; a genetic algorithm is used for coding and optimizing a routing inspection path, meanwhile, a fitness function is designed to comprehensively consider multiple factors of a search effect, and quantization, weight distribution and optimization selection are carried out; and an optimal solution is found through iterative optimization, and intelligent distribution and collaborative planning of unmanned aerial vehicle inspection tasks are realized, so that the requirements of regional inspection are met. According to the technical scheme, the flight threat degree under different meteorological conditions can be quantitatively evaluated by considering the wind speed, rainfall and visibility, and the flight plan is adjusted according to the flight threat degree.

The invention discloses a screening efficiency online monitoring method, device and system based on a vibrating screen, and relates to the technical field of vibrating screen efficiency monitoring, and the screening efficiency online monitoring method comprises the following steps: collecting working parameter data of the vibrating screen in real time through a sensor arranged on the vibrating screen; the accuracy and stability of screening efficiency are improved by monitoring key parameters such as humidity, particle size distribution and vibration frequency in real time and combining a screening effect model and a dynamic correction algorithm. The system automatically adjusts equipment parameters, equipment overload or screen damage is avoided, the material passing rate is optimized, and production losses are reduced. Meanwhile, manual intervention is reduced through an automatic control mechanism, the automation level of a production line is improved, human errors are reduced, the equipment fault and shutdown time is shortened, the production efficiency is improved, and the service life of the equipment is prolonged.

The invention belongs to the technical field of geophysical exploration. The invention provides an inversion method and system based on transient electromagnetic and ground penetrating radar data collaborative correction, and the method comprises the steps: converting the preprocessed ground penetrating radar data into a format of transient electromagnetic detection data, or converting the preprocessed transient electromagnetic detection data into the format of the ground penetrating radar data; performing weighted summation on the ground penetrating radar data and the transient electromagnetic detection data after format conversion to obtain fusion data; performing three-dimensional joint inversion according to the fused data to obtain a final three-dimensional joint inversion result; according to the method, collaborative detection of different depths of the detection area is realized, a brand new underground structure detection interpretation scheme is provided through intelligent data preprocessing, intelligent correction and three-dimensional joint inversion technologies, and comprehensive, efficient and high-precision interpretation of the underground structure is realized.

The invention discloses a PCB surface defect detection method and system, an electronic device and a medium, and relates to the technical field of defect detection, the connection condition caused by excessive tin soldering of a tin bridge or adjacent welding spots can be automatically identified by judging the connection state between the welding spots, an overall detection instruction is triggered, early detection is facilitated, connectivity defects are avoided, and the detection efficiency is improved. And the welding spot connection reliability is improved. The image is divided into a plurality of image blocks, the texture difference data of each image block is obtained, the texture abnormal state of the surface of the PCB can be finely analyzed by calculating the texture deviation coefficient, the subtle texture change in different areas can be identified by the block analysis method, and surface defects such as scratches and bubbles on the surface of the PCB can be accurately detected. And in combination with the texture deviation coefficient and the geometric features of the welding spots, unified normalization fitting is performed on the defect features to generate the defect recognition index, so that the defect features of different types can be captured, and the robustness and accuracy of the model can be improved.

The invention discloses a system and a method based on laboratory process intelligent management, and relates to the technical field of intelligent management. The system comprises an experiment task classification and sorting module, a historical data analysis and task duration prediction module, an overlapping time period analysis and intelligent scheduling module and a real-time monitoring and task progress adjustment module. The experiment task classification and sorting module is responsible for acquiring an initial experiment task list and carrying out task classification and sorting; the historical data analysis and task duration prediction module predicts the total duration of the experiment task by using historical data and provides accurate task duration prediction; time overlapping between the overlapping time period analysis and intelligent scheduling module processing tasks is carried out, and the task execution sequence and the equipment use time are intelligently adjusted; and the real-time monitoring and task progress adjusting module tracks the task execution condition in real time, analyzes the actual and predicted deviation and carries out necessary progress adjustment.

The invention discloses a multi-beam backscattering intensity jump correction method, which takes a multi-beam measurement strip as a unit, automatically detects backscattering intensity jump generated by factors such as equipment parameter setting through a Gaussian weighting function, and selects a moving window to perform difference compensation by using a weighted average value. And carrying out iterative detection on the repaired intensity data and repairing the jump point until the jump point converges to 0. An example calculation result shows that the method can effectively detect and repair the intensity jump in the multi-beam strip, improve the processing efficiency and quality of the backscattering intensity data of the multi-beam strip, and improve the analysis accuracy of the submarine landform of the multi-beam intensity data.

The invention discloses a transparent logistics supply chain tracing management system fused with a block chain technology. The transparent logistics supply chain tracing management system comprises a data acquisition module, a block chain storage module, an intelligent contract module, a user interface module and a data analysis module, the data acquisition module is responsible for collecting real-time data of each link of a supply chain and transmitting the data to the block chain storage module; the block chain storage module uses SHA-256 and ECDSA algorithms to ensure the security and authenticity of the data; according to the method, the blockchain technology is utilized, data of all links of the supply chain is subjected to chaining storage, the data are open, transparent and non-tampering, and the credibility of the data is enhanced; through an SHA-256 Hash algorithm and an ECDSA signature algorithm, the security and integrity of the data in the transmission and storage process are ensured, and the data are prevented from being tampered or forged; and transactions and operations in the supply chain are automatically executed through the intelligent contract module according to a preset rule, so that human intervention is reduced, and the automation level and the operation efficiency of the system are improved.

The invention relates to the technical field of equipment control, in particular to a self-adaptive switching method and system of a current transformer. The method comprises the following steps: collecting primary side parameters and secondary side parameters of a current transformer to obtain primary side collection parameters of the current transformer and secondary side collection parameters of the current transformer; performing current transformer state segmentation initialization according to the current transformer primary side acquisition parameters and the current transformer secondary side acquisition parameters so as to generate a current transformer operation state classification result; switching result judgment is conducted on the current transformers according to the current transformer operation state classification result, and when the current transformer operation state classification result is a current transformer critical state section, parallel buffering is conducted on the current transformers, and critical current transformer switching data are generated. According to the invention, through accurate state classification, a dynamic switching mechanism, time sequence optimization and visual display, the switching sensitivity and stability of the current transformer are improved.

The invention relates to a tree painting projection data collection and analysis system and method, and the system comprises a data collection module, a data preprocessing module, a feature extraction module, a quantitative analysis module, a classification and prediction module, and a result evaluation module. The modules cooperate with each other to realize standardized processing, feature extraction, quantitative analysis, intelligent classification and prediction and result evaluation of data. According to the method, the holographic theory and the Ama pothole theory are combined, the drawing features are finely analyzed through the cross-modal comparative learning and graph neural architecture search combined algorithm, a scientific and objective psychological data acquisition and analysis method is provided, the diagnosis sensitivity and specificity are improved, a powerful tool is provided for clinical psychological assessment, and the method is suitable for clinical psychological assessment. The method has important clinical and research values, and has wide application prospects in the fields of psychological problem screening, social psychological services, judicial, public security, marriage matching, talent selection and the like.

The invention relates to the technical field of big data, in particular to an intelligent service association method based on data consanguinity, which comprises the following steps of: 1, acquiring and forming metadata; tracking and collecting a service activity link to obtain a data consanguinity and a metadata consanguinity; 2, generating a business log; step 3, collecting a business log, and establishing a business atlas based on metadata consanguinity; step 4, defining a service triggering rule, a service decision point and a response rule based on the service atlas; and 5, monitoring the data change in real time, mapping the data change into the associated service map according to a service triggering rule, and carrying out service early warning prompt or associated information change display. According to the invention, automatic tracking and intelligent management of the project business process can be realized, and the utilization rate of enterprise data and the enterprise management efficiency are improved.

The invention discloses a power grid technical improvement and maintenance optimization method and system based on fault prediction, and relates to the technical field of power grid technical improvement and maintenance optimization, and the method comprises the following steps: monitoring equipment state data in real time; acquiring historical fault data of the power grid equipment; establishing an equipment attenuation model according to the historical fault data of the power grid equipment, and generating an equipment aging coefficient according to the established equipment attenuation model; according to the equipment state data and the equipment aging coefficient, a relation between the equipment state data and power grid equipment historical fault data and power grid technical improvement fault prediction is captured based on machine learning, a power grid technical improvement fault prediction model is constructed, and a power grid technical improvement fault prediction coefficient is generated; and performing fault prediction on the power grid technical improvement equipment according to the power grid technical improvement fault prediction coefficient. Through fault prediction, the problem that potential faults cannot be found in advance by fully utilizing operation data and state information of equipment is solved.

The invention discloses a work order auditing management method and system based on a large language model and a medium. The method comprises the steps of receiving input and correspondingly matching a work order auditing rule; based on the matched work order auditing rule, analyzing and processing the input through a large language model NLP, and converting the input into a natural language rule; carrying out synonym and antonym conversion on input white words, and carrying out equal rule conversion on converted words based on a corpus word library; performing rule text and code conversion on the converted natural language rule; and carding the processed rules into SQL statements which can be identified by the system according to the fields and the judger rule base. Updating the rule knowledge base; and writing the processed SQL statements which can be identified by the program into a rule knowledge base. According to the method, non-technical personnel can adjust and modify the work order information verification rule by using a natural language by using a large language model technology, so that the intelligent level of a work order system is enhanced, the development cost of the system is reduced, the auditing efficiency of a work order process system is improved, and the method has relatively good practicability.

The invention discloses an optical cable early warning method, system and device and a storage medium, and the method comprises the steps: obtaining monitoring data, and predicting a risk event and a risk point according to the monitoring data and a trained cross-modal large model; the monitoring data comprises any one or more of vibration data, image data or audio data; detecting a fault point and a fault event of the optical cable by using an optical time domain reflectometer; and if the risk point is matched with the fault point, evaluating a risk level according to the risk event and the fault event, and performing early warning according to the risk level. The embodiment of the invention can quickly and accurately monitor and early warn the optical cable, and can be widely applied to the technical field of optical cable transmission.

The invention relates to the technical field of carbon emission data accounting management systems, in particular to a carbon emission data accounting management system based on a block chain technology. According to the technical scheme, the carbon emission data accounting management system based on the block chain technology comprises a carbon emission accounting module; compared with a traditional carbon emission data accounting management system which often depends on manual accounting, not only is large in workload and tedious in process, but also errors are prone to occurring, so that the accuracy and efficiency of data accounting are low, and meanwhile, due to the fact that a traditional system lacks an efficient data tracing and tamper-proof mechanism, the authenticity of carbon emission data is difficult to guarantee, and the data accounting efficiency is low. According to the carbon emission data accounting management system, the authenticity of a data source is ensured by arranging a plurality of groups of intelligent acquisition equipment; the authenticity in the data storage and circulation process is ensured by utilizing the non-tampering property of the block chain; automation of data accounting is realized through the smart contract, human intervention is reduced, and accuracy of data accounting is improved.

According to the ship ballast water dynamic adjustment method, device and equipment and the storage medium, the water level data set, the attitude data set and the water pressure data set are obtained through the sensor, then whether the ship is in the balance state or not is determined according to the water level data set and the attitude data set, and when the ship is in the non-balance state, the ship ballast water dynamic adjustment is performed. If yes, determining a water volume adjustment scheme through a ballast water allocation optimization model; and then, according to the water volume adjustment scheme, a water pump operation instruction and a valve opening and closing instruction are generated, so that the ship recovers the balance state. According to the invention, the response time of ballast water regulation can be obviously shortened, and the flexibility and operation efficiency of the system are improved; the intelligent central control unit can be utilized to realize automatic operation, human intervention is reduced, and the operation precision is improved; and a ballast water allocation scheme can be flexibly adjusted to cope with the change of the ship state in real time.

The invention relates to the technical field of HVAC system modeling and simulation, and discloses a HVAC model parameter identification method based on a GPS-PSO algorithm. The method comprises the following steps: determining key parameters that affect the accuracy of a HVAC model based on expert knowledge and association rules; performing sensitivity analysis on the key parameters, and sorting them from high to low according to the sensitivity, to construct a parameter set of the HVAC model to be identified; collecting actual operation data related to the parameter set of the HVAC model to be identified, and performing preprocessing; dividing the preprocessed actual operation data into a calibration data set and a verification data set according to a preset ratio; based on the calibration data set, taking the normalized mean error as the optimization target, and performing parameter identification using a GPS-PSO two-stage optimization algorithm; and using the verification data set to verify the effectiveness of parameter identification, thereby improving the efficiency and accuracy of HVAC model parameter identification.

The invention discloses an AI-AD intelligent machine design method and system based on a learning-generation mode. The method comprises the following steps: S1, enabling an AI-AD intelligent mechanical design system to understand design knowledge at first; s2, compiling a workflow with low codes; s3, compiling a Prompt strategy of the design Agent and a called knowledge base; s4, repeating the steps S1 to S3, and compiling various agents needing to complete various specific design functions; s5, according to the designed various agents, a multi-agent self-organizing framework is utilized, and product creation type design is completed; and S6, according to the generated design result, generating a VBA file and storing the VBA file in the cloud. And S7, the SW establishes a conversation with the agent through a back-end API of the agent, timely reads a VBA code of the cloud for modeling, and outputs a model. According to the invention, a system structure of knowledge processing, cloud data storage, SolidWorks-based secondary development modeling and a human-computer interface module is constructed, Agents are enabled to learn at first, then design is created, and a 3D model meeting user requirements is generated, so that the current situation that knowledge engineering has extremely high requirements for practitioners' admission threshold can be reduced.

The invention provides an ultraviolet disinfection device for producing nursing pads, which relates to the technical field of ultraviolet disinfection, and comprises a disinfection box, wherein a central column is fixed at the inner center of the disinfection box, a feeding inlet is opened on one side of the disinfection box, and a feeding outlet is opened on the other side of the disinfection box, and a conveyor belt is arranged outside the feeding inlet and the feeding outlet of the disinfection box, a nursing pad body is placed on the surface of the conveyor belt, and a pushing assembly is arranged on the top of the conveyor belt on one side of the feeding outlet. Compared with the prior art, the nursing pad for feeding inlet is clamped by a translation assembly and a clamping assembly, and is transformed from a planar shape to a vertical shape, and circulates around the annular disinfection box, and the two sides of the nursing pad are irradiated by ultraviolet lamp columns on the inner wall of the disinfection box and the outer wall of the central column to improve the disinfection effect, and then the nursing pad is sent out from one side of the feeding outlet. The overall process is efficient, with less human intervention, and is suitable for cyclic disinfection in a production workshop.

The integrated forming welding device comprises a fixed base, a top plate is arranged at the top end of the fixed base, a first vertical plate is fixedly installed on one side of the top end of the fixed base, and a second vertical plate is fixedly installed on the other side of the top end of the fixed base; a lifting mechanism is fixedly mounted at the top end of the fixed base, a connecting table is mounted at the top end of the lifting mechanism, a clamping mechanism is fixedly mounted at the top end of the connecting table, and welding mechanisms are fixedly mounted at the top end of one side of the first vertical plate and the top end of one side of the second vertical plate correspondingly. When products placed on the connecting table are different in thickness, the lifting air cylinder pushes the connecting table from the bottom, the placing height of the products is adjusted, a welding head makes contact with the surfaces of the products conveniently for welding machining, the traditional mode that welding is conducted after the height of the welding head is adjusted is replaced, and the welding efficiency of the welding device is improved.

The invention discloses a wafer classification method and device for a wafer rapid heating process, and the method comprises the steps: obtaining a plurality of types of wafers, carrying out the heating for a period of time, obtaining temperature change data, building a data set, enabling the temperature change data to comprise radiance, a temperature value after heating, and a temperature difference value with resolution in a heating process, training a support vector machine based on the data set; and heating the wafers needing to be classified for the same time, inputting the obtained temperature change data into the trained support vector machine to obtain the wafer category, and implementing a rapid heating process according to the obtained wafer category. According to the method, the classification accuracy and the production efficiency in the rapid wafer heating process are remarkably improved, the production cost is reduced, the consistency and the quality of products are improved, and the method has wide application prospects in the field of semiconductor manufacturing.

The invention discloses an error detection device for electric energy meter metering, and relates to the technical field of electric energy meter calibration, the error detection device comprises a calibration instrument body, a wire and a connector, the calibration instrument body is provided with interfaces at equal intervals, the wire is connected with the connector, and the connector is matched with the interfaces. The calibration instrument further comprises a centralized access mechanism, an opening and closing regulation and control mechanism and a locking control mechanism, the centralized access mechanism, the opening and closing regulation and control mechanism and the locking control mechanism are all arranged on the calibration instrument body, through the arrangement of the centralized access mechanism, the movable sleeve can be pushed in a centralized mode through the elastic reset effect of an elastic telescopic column on a push plate, and the calibration instrument is convenient to operate. The connector is inserted into the interface, so that rapid and automatic insertion of the connector and the interface is realized, the connector is accessed in a centralized manner and managed in a unified manner, human intervention is reduced, a worker does not need to independently operate an electric wire and the connector one by one, errors caused by misoperation or negligence are reduced, and the accuracy of metering error detection and verification data of the electric energy meter is improved.

The present invention relates to the field of non-standard automation technology, in particular to an end cap rotary cutting assembly system and method for an injection-molded bottle body, comprising an injection molding machine, an injection molding transfer mechanism, a conveying mechanism, a first positioning mechanism, a first clamping mechanism, a rotary cutting mechanism, a second positioning mechanism, a second clamping mechanism and an end cap assembly mechanism, wherein the injection molding machine is used for bottle body injection molding, the injection molding transfer mechanism comprises an injection molding material picking component and an injection molding conveying component, the injection molding material picking component is used for grabbing the injection-molded bottle body on the injection molding machine and placing it on the injection molding conveying component, the injection molding conveying component is used for conveying the bottle body toward the conveying mechanism, the conveying mechanism is used for bottle body conveying, the first positioning mechanism is used for positioning the bottle body on the conveying mechanism, the first clamping mechanism is used for clamping the positioned bottle body and conveying it toward the rotary cutting mechanism, and the rotary cutting mechanism is used for ring cutting at the port on the bottle body; the present invention realizes full-chain automated operation from injection molding to end cap assembly through integrated and automated design.

The invention relates to the technical field of radiation dose calculation, in particular to a radiation dose calculation method and device based on a V-Net network. The method comprises the following steps: acquiring a CT image and light beam flux information for a focus area of a patient to be treated, wherein the light beam flux information represents parameter information of a light beam for performing radiotherapy on the patient to be treated; and on the basis of the CT image and the beam flux information, through a pre-trained V-Net network, performing radiotherapy dose calculation for a focus area of a patient to be treated, and generating a dose distribution diagram. According to the method, the dose distribution diagram can be automatically generated, human intervention is reduced, and the clinical working efficiency and the adaptability of a treatment plan are improved. Moreover, the pre-trained V-Net network can effectively capture features in the CT image, the calculation speed is greatly improved, the precision of the generated dose distribution diagram is equivalent to the calculation precision of the Monte Carlo method, and both the speed and the precision are taken into account.

The invention provides a self-adaptive operation and maintenance quality monitoring and management method, which comprises the following steps that: monitoring indexes are dynamically adjusted according to real-time data and business requirements so as to ensure the flexibility and adaptability of monitoring, and the monitoring indexes comprise monitoring frequency; the method comprises the following steps: acquiring a quality data set on line through data, wherein the quality data set comprises quality information data of a dimension service object, system service environment data, fault abnormal data and key element index data; analyzing the quality data set, detecting abnormity by adopting a high-dimensional algorithm, and triggering early warning if a detected abnormal value exceeds an abnormal threshold value; performing nonlinear mapping on the current actual operation data and the performance index reference value, and triggering a dynamic adjustment mechanism service to deal with abnormity; and the system calculates a quality problem score according to the operation and maintenance performance, and gives a qualified result according to the quality problem score. According to the invention, by optimizing resource configuration, the operation and maintenance quality is ensured to be matched with service requirements, and finally higher-level service quality and management effect are realized.

The invention provides an aspect emotion tetrad extraction method and device, equipment and a medium, and the method comprises the steps: carrying out part-of-speech analysis and dependency description on a text based on a user comment data set, automatically extracting aspect words based on an extraction rule, and classifying the aspect words according to a classification rule to obtain a preset number of aspect category dictionaries; a dictionary containing calling preset aspect categories is constructed, a cue word of detailed task description information is set, and the detailed task description information comprises an execution process of a large language model extraction aspect emotion tetrad task and tetrad extraction logic; and inputting the cue word and the comment data set to be extracted into the large language model, automatically calling the aspect category dictionary according to the form of the cue word, and injecting the aspect category dictionary into the large language model to realize extraction of the emotion tetrad in the user comment. According to the method and the device, the emotional tetrad in the user comments can be efficiently and more accurately extracted by the large language model, the human intervention is reduced, and the universality and the applicability of the model are improved.

The invention discloses a risk assessment method and device, a computer readable storage medium and electronic equipment. The method relates to the field of artificial intelligence, and comprises the following steps: obtaining target data of N users, the target data comprising user data and credit data of the users; the N users are clustered according to the target data of the N users through a target clustering algorithm, M user clusters are obtained, and an initial clustering center set of the target clustering algorithm is determined based on an eagle optimization algorithm; and for each user cluster, evaluating the credit risk of the first user in the user cluster to obtain a risk evaluation result, and determining the risk evaluation result as a risk evaluation result corresponding to each user in the user cluster. Through the credit risk assessment method and device, the problem that the accuracy of credit risk assessment is affected due to poor clustering accuracy caused by randomly determining the initial clustering center of the clustering algorithm when the credit risk of the user is assessed based on the clustering algorithm in the related technology is solved.

The invention relates to an intelligent monitoring and decision-making system for a soil pollution remediation process, and the system comprises a data collection layer which is used for collecting and uploading the data of a pollution remediation site; the data processing layer is used for receiving, cleaning, storing and managing data of a pollution remediation site; the analysis and decision-making layer is used for carrying out intelligent analysis such as pollution diffusion prediction, equipment state monitoring and restoration progress optimization on the data; and the user interface layer is used for remote monitoring, dynamic operation and information feedback of pollution remediation data and equipment states. According to the system, through cooperative work of the data acquisition layer, the data processing layer, the analysis and decision-making layer and the user interface layer, intelligent management and scientific decision-making of the soil pollution remediation process are achieved. The system collects on-site key data in real time through the Internet of Things, provides real-time monitoring, automatic control and decision support for pollution remediation projects by combining big data analysis and machine learning technologies, and ensures that the remediation process is efficient, low-carbon and safe.

The utility model relates to a multi-face grinding device for neodymium iron boron magnet machining, which comprises a workbench, a transmission mechanism is arranged on the workbench, and a feeding mechanism, a first grinding mechanism, a turnover mechanism, a second grinding mechanism, a drying mechanism and a discharging mechanism are arranged on the transmission mechanism. The feeding mechanism is used for conveying the neodymium-iron-boron magnet to the conveying mechanism. The first grinding mechanism is used for grinding the left face and the right face of the neodymium-iron-boron magnet on the conveying mechanism. The overturning mechanism is used for overturning the polished neodymium-iron-boron magnet by 90 degrees; the second grinding mechanism is used for grinding the two surfaces of the overturned neodymium-iron-boron magnet; the drying mechanism is used for drying the polished neodymium-iron-boron magnet; the discharging mechanism is used for removing the dried neodymium-iron-boron magnet from the conveying mechanism; the full-process automatic treatment from raw material feeding to finished product discharging is realized, the production efficiency is greatly improved, and the consistency and the quality stability of products are ensured.

The invention discloses a wafer flatness measuring device and method, and particularly relates to the technical field of semiconductors, the wafer flatness measuring device comprises a first main body and a second main body, the first main body is internally provided with a moving mechanism and a measuring mechanism, the second main body is internally provided with a feeding device, and the moving mechanism is provided with a fixing mechanism. Through the arrangement of the plugging plate, the plugging plug, the sealing plate and other structures, air flow in the negative pressure hole corresponding to the adsorption groove which is not covered by the to-be-tested wafer can normally flow, the plugging plate and the plugging plug in the corresponding valve body can continue to move downwards, and the plugging plug can be inserted into the sealing plate to realize sealing and sleeving; the negative pressure air flow cannot continue to circulate, impurities in the air are prevented from entering the negative pressure cavity through the negative pressure hole under the action of the suction force, the influence of dust accumulation on the normal work of the external air supply device and the negative pressure suction cup is avoided, the warping phenomenon of the wafer to be measured in the measurement process caused by the reduction of the suction force is avoided, and the measurement precision is improved.

The ceramic rod screening device for the wafer resistor comprises a rack, a control module, a driving component, a screening component and a removing component are arranged on the rack, a feeding platform is arranged on the rack, the screening component comprises a fixing chuck fixedly arranged on the feeding platform, a mounting groove is formed in the fixing chuck, and the mounting groove is communicated with the feeding platform. A mounting groove is formed in the fixed chuck, a lower fluted disc is fixed in the mounting groove, an upper fluted disc connected with a driving part is arranged on the lower fluted disc, a feeding port is formed in the fixed chuck, a first outlet for discharging wafer resistors with small diameters is formed in one end, close to the feeding port, of the lower fluted disc, and a second outlet for discharging qualified wafer resistors is formed in the other end of the lower fluted disc; v-shaped grooves which are evenly distributed in the circumferential direction are formed in the edge of the upper fluted disc, a third outlet is formed in the center of the upper fluted disc, and the V-shaped grooves are used for removing wafer resistors with large diameters to the third outlet for discharging.