366results about How to "Realize intelligence" patented technology

The invention provides a water plant raw water and clear water lifting pump station joint optimization energy-saving dispatching method and system for solving the problems that traditional pump station dispatching depends on artificial experience, global optimization is lacked, and energy waste is serious. Comprising the steps that a flow-lift and flow-efficiency relation model is established, and a variable frequency pump deduces a performance formula under any frequency based on the similarity law; in the first-stage optimization scheduling, the optimal flow of a water intake pumping station and the optimal water storage level of a clean water tank in each time period are determined by adopting a dynamic programming algorithm and taking the minimum total work of the system as a target, and the conditions of flow balance, water level constraint and the like are met; and in the second-stage optimization scheduling, the genetic algorithm is adopted to optimize the combination and operation frequency of the water pumps in each time period by taking the minimum total power of the pump set as a target, and a flow and lift deviation penalty term is introduced. According to the method, water taking, water storage and water supply whole-process collaborative optimization is achieved, the energy saving rate exceeds 10%, the operation cost is reduced, the method adapts to dynamic changes of the water source tide level and the water demand, and the dispatching intelligent level is improved.

The invention provides a business workflow dynamic arrangement and optimization method based on a large model agent, and the method comprises the steps: (1) analyzing the features and operation logic of a multi-element business workflow, and defining a business workflow description language; and (2) decomposing a complex business process construction process, and providing a layered process modeling system to guide a large model agent to construct a workflow model. And (3) constructing a task execution queue based on the task dependency relationship, and dynamically executing and monitoring the workflow. And (4) according to the execution log of the business workflow, discovering the bottleneck, redundancy and abnormity of the workflow model by adopting a process mining algorithm, and proposing a process improvement and optimization strategy. And (5) constructing a collaboration framework of a plurality of large model agents, and realizing dynamic arrangement, monitoring and optimization of the business workflow. According to the method, the defects that the current business workflow construction depends on experience of designers, and effectiveness and function requirements are difficult to guarantee are overcome; the defect that the business workflow is difficult to adapt to dynamic demand changes is overcome.

The invention discloses an autonomous evolution type 5G protocol fuzzy test system based on a large language model, and the system comprises a protocol extraction unit which employs the large language model to analyze a 5G protocol specification document, and extracts structured protocol knowledge elements containing a message format, state machine logic and parameter constraints; the vulnerability analysis unit generates a potential vulnerability description list through big language model reasoning based on the knowledge elements; the test strategy generation unit drives a large language model to generate a targeted test case based on protocol knowledge, vulnerability description and historical test knowledge in the dynamic test knowledge base; the test execution unit executes the use case and captures a result; and feeding back an analysis result of the internalization unit, extracting a causal rule, generating new test knowledge and feeding back the new test knowledge to the knowledge base. According to the system disclosed by the invention, test targets and resources can be autonomously scheduled according to continuous updating of the knowledge base, so that the test process has an iterative optimization capability, and full-process automation and intelligentization of 5G protocol fuzzy testing are realized.

The invention discloses a Linux-oriented vulnerability repair verification method and system and a medium. The method comprises the steps of creating a test application form for a CVE vulnerability patch in a task management system, preparing a test environment for CVE vulnerability repair verification as well as a required test table, a software source and a test strategy file, and calling a tool interface to automatically trigger an assembly line; the assembly line executes the test suite in the test environment based on the test table, the software source and the test strategy file and collects an execution state, and if the execution state is failure, automatic retry can be carried out on the CVE vulnerability based on manual triggering; and finally, generating a report file, writing a verification result for the test application form in the task management system, and if the verification result is that verification is passed, issuing a service pack of the CVE vulnerability. The invention aims to realize efficient, traceable and extensible Linux vulnerability repair verification, realize full automation and intelligence of the vulnerability verification process, and improve the accuracy, traceability and expandability of verification.

The application discloses a method for monitoring and controlling corrosion environment of an underwater concrete structure in a brackish water area, and the method comprises the following steps: laying a monitoring system, monitoring the concentration of chloride ions, analyzing data of the distribution of the concentration of chloride ions, dividing the area according to the concentration of chloride ions, adjusting an impressed current, and giving a warning of the corrosion environment; the brackish water area is divided into a constant saltwater area, a constant freshwater area and a brackish water interface change area by continuously collecting data of the concentration of chloride ions and constructing a concentration field and a gradient field model, so that the risk degree of the corrosion environment can be directly reflected, and the cathodic protection parameters can be dynamically adjusted according to the real-time corrected chloride ion concentration field model, thereby realizing the intelligent monitoring, early warning and control of the corrosion environment of the underwater concrete structure in the brackish water area.

The invention relates to a 3D printing sand mold cleaning device which is characterized by comprising an automatic sand cleaning room, a roller shutter door arranged at an inlet of the sand cleaning room, an automatic transfer trolley used for bearing and transferring a sand mold, a sand cleaning mechanism, an air supply system and a control unit. The sand cleaning mechanism comprises a plurality of sand cleaning actuators and a driving mechanism used for driving the sand cleaning actuators to do linear movement independently. An automatic sensing device is arranged on each sand cleaning actuator and is used for detecting the distance between the automatic sensing device and the surface of the sand mold in real time in the moving process; the control unit is in signal connection with the driving mechanism, the automatic induction device and the air supply system. The invention further relates to a sand cleaning method for the 3D printing sand mold. According to the scheme, the problem that a traditional automatic sand cleaning device cannot treat sand molds with complex inner cavities, deep cavities or special-shaped structures can be solved.

The invention discloses a data processing method and system for credential equipment, and belongs to the field of data processing in the information technology application innovation industry, and the method comprises the steps: a multi-source data fusion and intelligent analysis module is used for fusing the operation state, business and security log data of the credential equipment, and carrying out the fault prediction and performance bottleneck positioning through a deep learning model; the data security processing module adopts homomorphic encryption and proxy re-encryption technologies to ensure that data is processed and securely shared in an encryption state; the self-adaptive dynamic load balancing module dynamically allocates tasks and resources by monitoring and predicting equipment load in real time; the cross-platform data interaction and co-processing module constructs a unified framework to realize data adaptation and task collaboration between different operating systems and hardware architecture equipment; and the block chain and federated learning collaboration module realizes security joint modeling and privacy protection of data based on the block chain and federated learning. According to the method, the operation efficiency, the safety, the cooperation capability and the resource utilization rate of the credential equipment group are comprehensively improved.

This utility model discloses a yam slicer that is easy to clean, including a protective cover with a protective door on the front side. A yam body is installed inside the protective cover, and a slicing blade is located on the right side of the yam body. A connecting bolt is located inside the protective cover, and a guide structure is located on the outside of the connecting bolt. A support frame is installed at the bottom of the protective cover, and a drive motor is installed inside the support frame. A guide rod is connected to the left end of the drive motor, and a driven plate is located at the left end of the guide seat. A cleaning frame is located on the upper side of the support frame, and a cleaning rack is located at the inner end of the cleaning frame. This easy-to-clean yam slicer improves slicing efficiency by cleaning the yam slices and yam sap adhering to the yam slicer blade. Simultaneously, the yam is guided by a horizontal movement, avoiding manual pushing and achieving intelligent operation of the yam slicer.

The utility model discloses a kind of test equipment for pneumatic control valve or actuator in the field of pneumatic actuator detection, including valve displacement measuring instrument and control cabinet;Control cabinet is delivered to pneumatic control valve or actuator and measures the pressure of compressed air, valve displacement measuring instrument measures the displacement of pneumatic control valve or actuator;The controller of control cabinet transmits pressure and displacement data to PC host computer by Ethernet, and PC host computer generates the detection report of pneumatic control valve or actuator.The utility model can improve the detection quality and efficiency of pneumatic actuator, improve the production efficiency of pneumatic actuator production enterprise, meet the increasing delivery requirement, solve the problem of low efficiency of factory inspection, stroke etc. rely on visual inspection, realize the digitization and intelligentization of production final inspection.

The invention discloses a low-altitude economic unmanned aerial vehicle motor operation detection method and system, and relates to the technical field of unmanned aerial vehicle motors. According to the method, original parameters of the unmanned aerial vehicle motor are collected, a voltage balance equation of the motor is formed according to the original parameters, and after the voltage balance equation is simplified, torque constants are identified in real time by using a recursive least square algorithm so as to output a torque constant sequence with a timestamp; secondly, calculating and quantifying the support degree of each torque constant for degradation hypothesis through a probability density ratio so as to output an accurate early warning result, quantifying a historical stress event into a magnetic flux loss value through a stress damage accumulation model, and calculating and obtaining a degradation amplitude according to a degradation amplitude self-adaptive adjustment formula; and the detection sensitivity is dynamically adjusted according to the accumulated demagnetization degree of the unmanned aerial vehicle, the early warning capability for a high-risk motor is improved, excessive alarm of a low-risk motor is avoided, and precision and intelligence of predictive maintenance are realized.

The invention relates to the technical field of artificial intelligence, in particular to a display screen integrated bidding document generation method and device, intelligent equipment and a storage medium. The method is applied to the intelligent equipment, and comprises the following steps: obtaining a project demand of a display screen; according to the project demand, constructing a prompt word; inputting the cue words into a large language model, guiding the large language model to perform reasoning based on the project requirements through the cue words, and generating a bidding document draft of the display screen; calling a bidding document template; and generating a target bidding document of the display screen according to the bidding document draft and the bidding document template. By adopting the scheme of the invention, the display screen bidding document can be intelligently generated, and the bidding document generation efficiency and the demand matching degree are improved.

The invention belongs to the technical field of semiconductor manufacturing and testing, and discloses a matching evaluation method, system and device of a WAT testing machine and a storage medium. The method comprises the following steps: acquiring test data of a target and a reference machine, generating comparability conditions based on information such as products and stations to perform data alignment and preprocessing, and outputting an alignment data set and a quality index; calculating a multi-dimensional feature vector including distribution, risk, trend and wafer spatial features for each test item based on the alignment data; the feature vector and the alignment quality index are fused, a difference score is calculated, and evaluation is carried out in combination with a self-adaptive threshold value dynamically generated based on historical data and parameter importance; and finally, outputting a difference parameter list and an evaluation result, simultaneously introducing an AI model to carry out comprehensive judgment, and continuously optimizing through a feedback closed loop. Through the method, automation, quantification and intelligentization of machine matching evaluation are realized, and evaluation efficiency, consistency and accuracy are remarkably improved.

The application provides a baseband radio frequency signal data feedback processing method based on vector modulation, which first receives a baseband signal data set transmitted by a target radio frequency link in a preset frequency band, which contains multiple signal frame original modulation parameters and corresponding radio frequency feedback signal waveforms, then calculates feedback error indicators composed of phase offset, amplitude distortion and spectral leakage factor according to the radio frequency feedback signal waveforms, quantizes the modulation error, analyzes the feedback signal waveforms in the time-frequency domain, extracts error feature vectors, inputs the pre-trained model for cross-frame correlation learning, generates a dynamic adjustment parameter sequence containing time sequence dependence, and finally constructs a closed-loop feedback control link based on the dynamic adjustment parameter sequence and the original modulation parameters, so as to realize accurate processing and optimized control of the baseband radio frequency signal and effectively improve the signal transmission performance.

This application belongs to the field of data acquisition technology, and particularly relates to a multi-protocol intelligent data acquisition method, system, device, and medium for energy storage power stations. The method includes: acquiring actual message data from energy storage power station devices based on an initial acquisition frequency; identifying the protocol type of the actual message data based on a pre-stored protocol feature library and a hybrid matching algorithm; adjusting the initial acquisition frequency in real time according to the protocol type and the real-time data volume; generating parsing instructions based on the protocol type and its corresponding parsing strategy template; parsing the message data according to the parsing instructions to extract valid data; and preprocessing the parsed valid data to obtain target data. This application improves the efficiency of data acquisition in energy storage power stations.

The application relates to the technical field of plastic intelligent manufacturing, and discloses a machine vision driven plastic master batch feeding and cleaning parameter intelligent regulation and control system. The system comprises the following: an image acquisition and feature extraction module which, based on the equipment running state, identifies and extracts elements such as feeding speed and cleaning flow, maps to a preset parameter field and establishes an associated identifier, and forms a standardized feeding and cleaning data unit. A parameter matching and regulation rule generation module searches a database to match regulation rule conditions, calculates a parameter regulation complexity factor, compares parameters with constraint values, and generates a single parameter matching state judgment. A multi-working-condition correlation modeling module finds different working-condition shared entities, calculates a cross-working-condition correlation closeness index, and constructs a multi-working-condition correlation graph. An abnormal state identification and parameter correction module combines the associated working-condition judgment to calculate a risk score and generates a comprehensive regulation risk prompt. The system realizes intelligent regulation and control and abnormal identification of plastic master batch feeding and cleaning parameters.

The application relates to the technical field of network threat detection, and discloses a network threat detection and response system based on deep learning. The system comprises a collection module, a statistical module and an instruction generation module. The collection module is used for collecting standardized data sets from a plurality of preset security areas. The statistical module is used for statistically calculating attack equivalent cumulative values, defense strength indexes and asset attack exposure degrees based on the standardized data sets. The instruction generation module is used for calculating a threat comprehensive score according to the attack equivalent cumulative values, the asset attack exposure degrees and the defense strength indexes, and generating blocking instructions, isolation instructions and flow limiting instructions according to the threat comprehensive score. The application can automatically generate an access control strategy according to an attack chain analysis result and execute the access control strategy, thereby forming a complete closed loop from threat detection to strategy optimization, and improving the synergy, accuracy and real-time performance of network security operation.

The application belongs to the technical field of teaching practical training scene simulation control, and specifically discloses a teaching practical training scene simulation control method based on PLC technology, which comprises the following steps: constructing a fault mode library containing low, medium and high levels, randomly distributing faults from the low fault level, loading a simulation scene, collecting fault identification response time and adjustment operation sequence, verifying diagnosis accuracy and evaluating fault recovery degree after executing the sequence, generating a practical operation qualification degree according to different conditions, then judging promotion and dynamically adjusting the fault level according to the qualification degree, and generating a student comprehensive ability evaluation report based on the qualification degrees in the previous iterations; the application constructs a fault mode library containing low, medium and high fault levels based on historical power operation data, and dynamically adjusts the fault level to be distributed subsequently according to the practical operation qualification degree, thereby overcoming the defects of static preset fault situations, and realizing a personalized and gradual skill upgrading path.

The invention provides a pet self-adaptive feeding recommendation method and system based on AI image analysis, and the method comprises the steps: firstly monitoring food images of a feeding disc of feeding equipment at the moment of food discharge stopping and pet feeding leaving, obtaining a food state image set of the feeding disc, carrying out the AI image analysis of the food state image set of the feeding disc, and obtaining a food state image set of the feeding disc; feeding time and food intake information are extracted, a pet food intake data set is formed, the pet food intake data set is input into a pre-trained feeding demand prediction model, and the next hunger time and food intake prediction result of the pet is obtained through fitting analysis. Self-adaptive feeding recommendation information containing recommended feeding time and recommended feeding amount is generated according to the next hunger time and food intake prediction result of the pet, and finally the self-adaptive feeding recommendation information is pushed to an associated mobile terminal for a user to check and decide whether to execute feeding operation or not. Personalized, intelligent and precise management of pet feeding is realized.

The application discloses a cross-cultural communication non-verbal media emotion recognition interaction system, which comprises a non-verbal media data acquisition module, a non-verbal emotion feature extraction module, a non-verbal emotion recognition model construction module, a cross-cultural feature weight parameter self-adaptive acquisition module and an emotion intelligent interaction module. The application relates to the technical field of data processing, in particular to a cross-cultural communication non-verbal media emotion recognition interaction system, which proposes a hierarchical collaborative design of a general non-verbal emotion recognition model and a cross-cultural feature weight parameter self-adaptive acquisition module, can significantly improve the accuracy of non-verbal emotion recognition in a cross-cultural scene, improves the recognition accuracy of the model by designing a three-dimensional structured model input tensor, a customized emotion feature reinforcement filter and an emotion fluctuation extraction pooling operation, and improves the accuracy of cross-cultural non-verbal emotion recognition by adopting a stage-by-stage position updating strategy in a predation stage and combining a dynamic dimension exchange mechanism to improve and optimize the algorithm.

This invention relates to the field of fluid machinery testing technology, and in particular to a performance testing system shared by circulating pumps and submersible pumps. The system includes a data acquisition and control unit, a drive unit, a load adjustment unit, and an intelligent control and analysis server, configured to perform: startup and intelligent identification, digital twin model construction and test planning, adaptive basic performance sampling, boundary performance exploration, real-time safety monitoring and prediction, synchronous acquisition of multi-source heterogeneous information, and digital profile generation and model training. Before physical testing begins, this invention pre-calculates key feature points under all operating conditions through numerical simulation. Based on these pre-calculated key points, the system can automatically generate a dynamic test sequence that balances safety and efficiency, enabling subsequent real-world testing to be targeted and precise, capturing the core performance framework of the pump with the fewest possible tests, greatly improving the scientific rigor and efficiency of the testing.

The application relates to the field of micro-electro-mechanical systems, and specifically discloses a micro-cantilever beam deformation correction method and system for MEMS sensor output errors, which comprises the following steps: exciting a composite vibration mode of a micro-cantilever beam through a multi-mode active excitation signal, collecting a dynamic response signal and identifying a deformation state parameter by using a deep learning model, generating laser micro-processing parameters based on the identification result to perform selective material removal or annealing treatment, establishing a deformation trend prediction model to perform pre-compensation adjustment, and ensuring the correction effect through a closed-loop verification mechanism; the system comprises a multi-mode active excitation control module, a dynamic response collection and processing module, a deformation identification and state evaluation module, a laser micro-processing control module, a deformation trend prediction and pre-compensation module, a correction effect verification and iterative control module, and a system integration and data management module. The application solves the problem of sensor errors caused by physical deformation of a micro-cantilever beam, and significantly improves the precision and long-term stability of a MEMS sensor.

The application provides a method and device for removing odor, a food storage device, a storage medium and a program product. The method is applied to a food storage device, which comprises a storage cavity and an odor removal module. The method comprises the following steps: determining the related parameters of food in the storage cavity; wherein the related parameters comprise the height of the food in the storage cavity and / or the weight of the food; determining the storage duration of the food based on the change degree of the related parameters of the food; in the case that the change degree represents a decrease or no change and the storage duration is greater than a first preset value, determining the odor removal duration of the food based on the related parameters of the food and the storage duration; and controlling the odor removal module to perform an odor removal operation on the storage cavity within the odor removal duration to reduce the odor substances in the storage cavity.

The invention discloses a waterworks intelligent dosing optimization system and method based on data driving, and belongs to the technical field of water treatment, and the system comprises a historical data intelligent clustering module which obtains and preprocesses historical operation data, employs a minimum distance clustering algorithm to automatically generate a clustering center representing a typical working condition, and sends the clustering center to a cloud server; calculating a corresponding expert recommended dosage, and constructing an expert experience knowledge base; the real-time parameter dynamic matching module is used for acquiring real-time operation parameters, performing window processing, performing Euclidean distance matching on the real-time operation parameters and a clustering center in a knowledge base, and finding out a reference dosage corresponding to the most similar working condition; and the dosage optimization decision module is used for performing feedback correction on the reference dosage according to the comparison relationship between the real-time effluent quality and the standard value, and generating a final dosage instruction under the constraint of the minimum dosage. According to the invention, accurate and dynamic control of the dosage is realized, and the medicament consumption is obviously reduced on the premise of ensuring the stability of the effluent quality.

The invention discloses a search agent training method and device and a storage medium, and the method comprises the steps: collecting a current state vector under the condition that a search agent carries out the key sign search of any sample cardiovascular three-dimensional diagram; inputting the current state vector into a search agent, and outputting an action instruction through the search agent; the observation window is controlled to execute the action instruction, an experience tuple is collected and stored in an experience playback pool, and the experience tuple comprises the current state vector, the action instruction, the instant reward value and a next moment state vector; and performing iterative training on the search agent based on an experience tuple stored in the experience playback pool, so that the trained search agent can output an action instruction sequence enabling the observation window to quickly cover a key sign area according to the state vector.

The invention discloses a full-intelligent steel wire rope detection system which comprises a rack, a mobile platform, an inclination angle adjusting mechanism, a detection probe assembly, an automatic code spraying device, an encoder assembly, a central control platform and a remote center, the mobile platform is installed on the rack and comprises a first power mechanism and a mobile seat, and the detection probe assembly is hinged to the mobile seat through a first hinge shaft; the inclination angle adjusting mechanism is hinged to the detection probe assembly through a second hinge shaft and hinged to the movable base through a third hinge shaft. The automatic code spraying device is mounted on the moving seat; the encoder assembly is installed on the moving base and makes contact with the steel wire rope. The central control platform is connected with a remote center through a wireless transmission module. The steel wire rope is magnetized through the detection probe assembly, the leakage magnetic field outside the steel wire rope is detected, the inclination angle of the detection probe assembly is flexibly adjusted through the inclination angle adjusting mechanism, and automation and intellectualization of the detection process are achieved through cooperative work of the central control platform and the remote center.

The utility model discloses an efficient intelligent phosphorite flotation cell which comprises a flotation cell body, a plurality of partition plates are arranged in the flotation cell body to divide the flotation cell body into a plurality of cell bodies, a stirring device is arranged in each cell body, grooves for foam to flow out are formed in the top ends of the two sides of the flotation cell body, and a laser foam breaker is arranged at one end of each groove. The aeration holes of the air distributor are improved, bubbles are generated more sufficiently, capturing of hydrophobic mineral particles is facilitated, the flotation effect is better, and the flotation efficiency is higher. An infrared liquid level instrument installed on a phosphorite flotation tank body is in linkage with an air distributor installed at the bottom end of a flotation machine stirring paddle, the height of a foam layer is detected through infrared liquid level scanning, when the foam layer is too high, the air distributor automatically reduces the inflation amount and reduces generation of bubbles, and when the foam layer is too low, the air distributor automatically increases the inflation amount and increases generation of bubbles. And intelligentization and automation of the equipment are realized. And the laser bubbles are adopted, so that the bubbles can be broken more quickly and thoroughly, and the water consumption is also reduced.

This application relates to an automotive seat system and an automobile, including a seat, a sensor module, a control module, and an airbag system, which are connected sequentially. The sensor module includes acceleration sensors and pressure sensors, with at least two acceleration sensors and at least two pressure sensors distributed inside the seat. The airbag system includes airbags and a pneumatic actuator, with at least two airbags distributed inside the seat. The airbags are connected to the pneumatic actuator, which inflates or deflates the airbags. The sensor module and the control module are respectively connected to an on-board electronic terminal. The sensor module transmits collected sensor data to the on-board electronic terminal, and the control module receives control signals generated by the on-board electronic terminal and outputs the control signals to the pneumatic actuator. The seat can adaptively adjust its shape and support strength, achieving intelligent adjustment of seat comfort.

This application provides a third-party monitoring method for road transport safety management, including: a monitoring platform determining the status of a vehicle entering or exiting an assigned electronic fence based on vehicle satellite positioning data, and generating a regional alarm when a vehicle crosses the boundary or violates speed limits; executing a verification and processing procedure for various alarms generated by the monitoring platform, including platform alarms and proactive safety alarms, supporting enterprise users to appeal the verification results and subsequent review; marking the status of vehicles in special states such as being out of service, under maintenance, scrapped, or suspended from monitoring, and providing abnormal movement records and offline duration statistics queries; pushing announcement documents to subordinate enterprises or initiating safety inspection tasks, and requiring enterprises to submit reading receipts or inspection responses; generating statistical reports on daily, weekly, monthly, and yearly cycles, and supporting scheduled automatic or instant push to designated email addresses.

The invention discloses a geothermal heat supply system integrating electricity price response and a heat storage scheduling strategy, belongs to the technical field of geothermal heat supply, and can solve the problems that an existing single geothermal heat supply system is low in efficiency and poor in stability. The system comprises a deep geothermal well; a photo-thermal module; the temperature commutator comprises an inlet end and a plurality of outlet ends; the deep geothermal well and the photo-thermal module are both communicated with the inlet end; the temperature reverser is used for detecting the temperature of the heat exchange fluid at the inlet end and controlling the outflow direction of the heat exchange fluid according to the temperature; the heat storage module comprises a heat storage heating unit and a heat storage water supply unit which are connected to different outlet ends of the temperature reverser, and the heat storage temperature of the heat storage heating unit is higher than that of the heat storage water supply unit; and the control module is used for controlling the deep geothermal well and the photo-thermal module to store heat to the heat storage module in the valley electricity period of the heat consumption valley period and controlling the heat storage module to release heat to the user side in the peak electricity period of the heat consumption peak period. The device is used for geothermal heat supply.

This invention discloses an installation and positioning device for precast cylindrical bridge piers, comprising four positioning parts assembled together to form a positioning cavity for the precast cylindrical bridge pier. Each positioning part consists of a positioning device, an adjustment device, and a lifting device. The positioning device is mounted on the lifting device and consists of a base plate, a first telescopic device, a second telescopic device, a sleeve, and a laser positioning system. The first and second telescopic devices are mounted on the base plate to drive the sleeve to move radially along the precast cylindrical bridge pier. The laser positioning system is mounted on the side wall of the sleeve. The adjustment device consists of an electric track mechanism and a miniature camera. The electric track mechanism and the miniature camera are mounted on the inner wall of the sleeve, with the miniature camera mounted below the electric track mechanism.