602results about How to "Reduce time consumption" patented technology

The invention relates to the technical field of computers, and discloses a heterogeneous acceleration system, method and device, a computing device and a storage medium, the heterogeneous acceleration system comprises a host end, a plurality of heterogeneous acceleration clusters and a storage device used for storing target data, and the host end is used for sending an acceleration computing request to the heterogeneous acceleration clusters; when any target heterogeneous acceleration device in the heterogeneous acceleration cluster receives an acceleration calculation request, responding to the acceleration calculation request, adopting a preset direct transmission mode, directly reading the target data from the storage device, and performing corresponding calculation processing on the target data to obtain an acceleration calculation result; writing the acceleration calculation result into the target cache device; and the host side directly accesses the target cache device to obtain an acceleration calculation result. The transmission path of the target data is shortened, and the time consumption of the target data in the transmission process is reduced, so that the data transmission delay of the target heterogeneous acceleration equipment is reduced, and a foundation is laid for improving the performance of computing equipment.

The invention relates to the technical field of electric power facility fault detection, and discloses an electric power facility multispectral remote sensing inspection and fault diagnosis method, and the method comprises the steps: carrying a multispectral remote sensing device through an unmanned plane platform to obtain multispectral image data of an electric power facility, and carrying out the preprocessing to extract spectral features; and constructing a spectral feature analysis model to evaluate the health condition of the electric power facility, constructing a fault diagnosis model in combination with historical fault data, and determining the fault type and position. In order to optimize the fault diagnosis process, fault diagnosis is modeled as a Markov decision process, and the accuracy and efficiency of fault diagnosis are improved by defining a state space, an action space, a reward function and an output strategy and continuously optimizing decision actions by using a reinforcement learning algorithm. According to the invention, intelligent and automatic inspection and fault diagnosis of the electric power facility are realized, powerful technical support is provided for safe and stable operation of the electric power facility, and the method has wide application prospect and important practical value.

The invention relates to the technical field of image sensor design, and particularly discloses an SAR-SS type ADC circuit and module based on adjacent pixel prediction. The SAR-SS type ADC circuit comprises a signal input part, a gain amplifier, a sampling and holding and voltage lifting part, a prediction control part, an SAR-ADC part, an SS-ADC part and a data processing part. According to the invention, the number of ADCs is reduced by adopting a mode of sharing the ADCs in multiple columns; meanwhile, 11-bit quantization is decomposed into 5-bit division quantization through an SAR-ADC part and 6-bit fine quantization through an SS-ADC part, and a prediction control part is additionally arranged to judge whether 5-bit coarse quantization needs to be carried out or not, so that unnecessary time consumption and power consumption of the 5-bit coarse quantization are reduced. According to the invention, the problem that the total number of ADCs is too large due to the fact that one column is matched with one traditional column-level ADC is solved.

The invention discloses a rapid assessment method and system for shock resistance toughness of main and aftershocks based on a cycle-Transform network, and the method comprises the steps: building a finite element model of a building structure, inputting a plurality of groups of earthquake accelerations of main and aftershocks into the model, and obtaining a database comprising a plurality of groups of accelerations and corresponding structure displacement responses; building a loop-Transform neural network, and carrying out the training and optimization of the loop-Transform neural network; inputting the main shock and aftershock sequence into the optimized cycle-Transform neural network, predicting the displacement response of the structure under the double amplitude modulation main shock and aftershock sequence, then obtaining the building damage probability corresponding to different earthquake intensities under the main shock and aftershock situation by using maximum likelihood estimation, evaluating the corresponding damage index, calculating the recovery time, and finally obtaining the building damage probability corresponding to the different earthquake intensities under the main shock and aftershock situation. A function recovery curve of the structure is predicted, and shock resistance toughness evaluation is completed. According to the method, the precision of structure accumulated damage prediction under the aftershock effect is improved, and the calculation complexity and time consumption of toughness evaluation under the main and aftershock earthquake scene are remarkably reduced.

The invention provides a wafer bonding device and a wafer bonding method, and relates to the technical field of semiconductor processing. The wafer bonding device comprises a carrying seat, a driving structure arranged on the carrying seat, and a target chuck and a bearing chuck which are arranged along the Z direction, at least one of the target chuck and the bearing chuck is in transmission connection with the driving structure, and the driving structure is configured to be capable of driving the target chuck and the bearing chuck to relatively move along the X-Y direction and the Z direction; a plurality of notches are formed in the edge of the target chuck; the carrying base is provided with a plurality of visual systems, the visual systems are located on the side, away from the bearing chuck, of the target chuck, the axial direction of the visual systems is consistent with the Z direction, the visual systems correspond to the notches one to one, and the visual systems are configured to shoot images, corresponding to the notches, of the wafers loaded on the target chuck and the bearing chuck. The wafer bonding device is good in wafer bonding quality, high in yield, small in size and small in occupied space.

The invention discloses an RPA-based full-automatic all-electricity invoice issuing method and system. The method comprises the following steps: constructing an RPA system: creating an RPA user, creating a business process, and defining a process rule; data acquisition and preprocessing: capturing basic transaction data, and performing data preprocessing on the captured data; invoicing and intelligent inspection: logging in a full-electricity invoice service platform, filling and submitting data information in an invoicing interface, and verifying various contents of an invoice; invoice circulation and signing determination: sending the issued full-electricity invoice to the user, and monitoring the invoice signing condition; and storage and filing management: uploading the issued all-electricity invoice to a management system. According to the invention, by introducing the RPA technology, the full-automatic processing of the full-electricity invoices from data acquisition and issuing to circulation and archiving is realized, the time consumption of manual operation is greatly reduced, and the invoice issuing efficiency is improved compared with the traditional manual or semi-automatic process.

The invention provides a computing power scheduling method and device for model training, a computer storage medium and electronic equipment, and relates to the technical field of computers. Comprising the following steps: in response to a received training task request for a to-be-trained model, dividing the to-be-trained model into a plurality of first model subtasks; aiming at the target model subtask, determining a heterogeneous computing power unit of a target resource type corresponding to the target model subtask from a heterogeneous computing power architecture according to a pre-configured computing power mapping table; the computing power mapping table comprises a one-to-one correspondence relationship between each computing task and the heterogeneous computing power unit of the corresponding resource type; and determining a target heterogeneous computing power unit from heterogeneous computing power units of the target resource type of each computing node in the heterogeneous computing power architecture, and allocating the target model subtask to the target heterogeneous computing power unit, so as to execute the target model subtask based on the target heterogeneous computing power unit. The method can improve the model training efficiency and the accuracy of the model prediction result.

The invention discloses a device for disassembling and assembling a memory bank and a using method of the device. The device for disassembling and assembling the memory bank comprises a fixing base, a disassembling assembly and a pressing assembly, the disassembling assembly is installed in the vertical direction of the fixing base, the pressing assembly is installed in the horizontal direction of the fixing base, the disassembling assembly is used for disassembling or placing the memory bank, and the pressing assembly is used for pressing the memory bank. The fixing base is in transmission connection with an external mechanical arm, and the mechanical arm is used for controlling and switching the disassembling assembly or the pressing assembly to work. The disassembling assembly and the pressing assembly are integrated and are responsible for disassembling and assembling the memory bank, switching and control of the disassembling assembly and the pressing assembly are achieved through the mechanical arm on the fixing base, the operation process is greatly simplified through the integrated design, rapid disassembling and assembling of the memory bank can be achieved without additional tools or adapter cards, and the working efficiency is improved.

The invention relates to a hot-rolled wire rod for a 2060MPa bridge cable and a manufacturing method of the hot-rolled wire rod, after C-Si-Mn-Cr-V-Nb component is rolled and spun into a wire rod, the wire rod is subjected to online molten salt strong isothermal treatment, so that the wire rod is cooled at a cooling speed of greater than or equal to 34 DEG C / s, and enters a sorbite phase region from an austenite state to form a structure mainly comprising fine lamellar spacing sorbite, and isothermal treatment is carried out; and finally, through roller way slow cooling, the hot-rolled wire rod with a microscopic structure mainly comprising tempered sorbite and the balance being a mixed structure composed of ferrite and microspheroidized carbide is prepared, a deteriorated structure influencing the performance of a wire rod finished product in the production process can be effectively controlled, stable production is achieved, and the strength and plasticity matching of the wire rod is improved. The tensile strength is 1440-1490 MPa, the percentage reduction of area is 42%-46%, and the method is suitable for efficient and stable production and manufacturing of the 2060 MPa bridge cable.

The invention relates to an aerodynamic force-thermal-structure multi-field coupling intelligent prediction method for a high-speed aircraft, and belongs to the technical field of high-speed aircraft design. According to the flight path of the aircraft, sample parameters used for calculating aerodynamic force and aerodynamic heat states are extracted; modeling the aircraft, and carrying out analog calculation to obtain an aerodynamic force and aerodynamic heat data set; calculating an aircraft temperature field along the trajectory; training the aerodynamic force data set to obtain an aerodynamic force prediction model; calculating structural stress displacement field data of the aircraft model; extracting concerned aircraft feature point corresponding data from the aerodynamic data set, the aircraft temperature field and the structural stress displacement field data of the aircraft model to obtain a feature point data set; training the feature point data set to obtain an accurate prediction result; according to the method, after artificial intelligence algorithm offline learning modeling is carried out on the aerodynamic force-heat-structure coupling data of analog simulation, the flight path is input, and the data, changing along the flight path, of the feature point data of the output aircraft is rapidly predicted.

The invention discloses an intelligent scheduling method based on port bulk cargo transfer. The method comprises the steps of S1, obtaining related information of bulk cargos to be transferred and related information of transport vehicles; s2, matching transport vehicles of corresponding types; s3, calculating a transfer train number; s4, calculating the number of transport vehicles; when the number of the transport vehicles is one, executing the step S5; when the number of the transport vehicles is two or more than two, executing the step S6; s5, generating transfer scheduling planning information according to the loading position of the bulk cargo to be transferred and the departure position of the corresponding transport vehicle; s6, determining the departure sequence of the transport vehicles: for the first departure transport vehicle, calculating corresponding transfer scheduling planning information based on the step S5; and for the second transport vehicle and the subsequent departure transport vehicle, corresponding transfer scheduling planning information is generated according to the transfer scheduling planning information of the previous transport vehicle. According to the invention, the accuracy, orderliness and collaboration of bulk cargo transfer scheduling can be improved.

The invention discloses a motor stator short circuit ring automatic assembly device, and relates to the technical field of short circuit ring assembly.The motor stator short circuit ring automatic assembly device comprises a control machine table, a controller is installed on the upper surface of the control machine table, a supply conveying belt is installed on the front side face of the controller, and a feeding air cylinder is installed at the conveying end of the supply conveying belt; an assembling assembly is installed on the rear side of the feeding air cylinder, an interval distribution mechanism is arranged on the surface of the supply conveying belt, a damage prevention and centering mechanism is arranged in the assembling assembly, oil liquid is driven to be sprayed out through pressure, then it is ensured that lubricating oil is evenly distributed between a mold and a base by ingeniously using suction force generated by counter-acting force, and a thin oil film is formed; the high-efficiency boundary lubrication effect is achieved, firstly, through continuous and uniform oil film lubrication, direct contact friction between the die and the stator short circuit ring assembly part in the pressing process is effectively reduced, in addition, due to the existence of an oil film, the friction coefficient between contact surfaces is greatly reduced, and material deformation and displacement caused by friction are reduced.

The invention belongs to the technical field of automatic focusing, and particularly relates to a dynamic focusing method based on an industrial measurement system. Comprising the following steps: S1, fixing a target on a measured target, and aligning a lens of an industrial measurement system with the measured target to obtain an image data set of the measured target; s2, sequentially inputting the detected target images into a target acquisition network to obtain a target image data set; s3, correspondingly calculating the working distance of the target relative to the camera based on the prediction frame of each target image; s4, all the target images are subjected to denoising and illumination normalization processing, and a processed target image data set is obtained; s5, predicting the predicted defocus distance of each processed target image by using a deep regression network; s6, performing static adjustment on the lens to obtain a clear first frame of target image; and S7, dynamically adjusting the lens according to the motion state of the target to be measured and the working distance of the target relative to the camera. The invention has the capability of dynamic focusing.

The invention discloses a long text intelligent output reference system, which relates to the technical field of intelligent text processing, and comprises a long text processing module, a reference demand analysis module, a reference extraction module, an optimization module and a reference output module, the long text processing module is used for receiving multiple formats of long texts and converting the long texts into internal formats, determining a core theme field and a sentence structure relationship through vocabulary statistics, syntactic analysis and semantic recognition and constructing a semantic map, and providing a text analysis basis for subsequent reference; according to the method, the long text reference efficiency and accuracy are remarkably improved, the time consumption of manual retrieval and screening is reduced through automatic processing of long text data, meanwhile, the professionality and correlation of reference content are ensured through deep analysis of the text content, the system can understand the reference requirement of a user, and the user experience is improved. And the demands are converted into accurate screening conditions, so that reference contents highly matched with the user demands are provided.

The invention discloses an unmanned aerial vehicle image multi-crop plot identification and productivity prediction method based on DeeplabV3 +, and the method comprises the steps: obtaining an unmanned aerial vehicle image of a research region, and carrying out the splicing processing of the image; preprocessing and labeling the images, and dividing the images into a training set and a verification set; training, verifying and testing the improved DeeplabV < 3 + > deep learning network model by using the data set to obtain a final unmanned aerial vehicle image plot recognition and crop classification model based on DeeplabV < 3 + >; carrying out land parcel identification and crop classification on the preprocessed to-be-detected image by using the trained land parcel identification and crop classification model, and carrying out splicing processing; and the spliced prediction segmentation map is further processed by using envi and ArcGis software to obtain a productivity prediction map of various crops. According to the invention, the dependence on manual field investigation is reduced, the method is less limited by topographic factors, the method is faster and more accurate, and the efficiency of agricultural asset checking is improved.

The invention discloses a television intelligent maintenance decision-making method, and the method comprises the following steps: obtaining historical work order information which at least comprises a television type, a fault description, a fault reason, a maintenance scheme, a maintenance category and used spare parts; constructing an intelligent fault library containing standard faults according to the historical work order information; establishing a knowledge graph according to the historical work order information and the intelligent fault database; acquiring new work order information, performing fault matching with the intelligent fault library according to fault information in the new work order information, and performing maintenance scheme recommendation according to the matched fault based on the knowledge graph; the invention also discloses a television intelligent maintenance decision-making system and a computer program. The intelligent, automatic and personalized television maintenance process can be realized, the quality and efficiency of the maintenance service can be greatly improved, the operation cost can be reduced, and the high-quality and reliable maintenance experience can be provided for the user.

The invention provides a progressive multi-level detail monomer reconstruction method for a real-scene three-dimensional building model, and relates to the field of inclined model monomer reconstruction, and the method comprises the steps: sequentially constructing an LOD0-level vector element model, an LOD1.0-level building white model, an LOD2.0-level building white model and an LOD2.0-level building standard model through DEM data and DSM raster data converted from the real-scene three-dimensional model, and constructing a model of the LOD0-level vector element model, the LOD1.0-level building white model, the LOD2.0-level building white model and the LOD2.0-level building standard model; progressive multi-level detail monomer reconstruction of the live-action three-dimensional model is completed, building monomer reconstruction is carried out in a full-automatic mode, manual intervention is not needed, the monomer reconstruction cost is greatly reduced, and the live-action three-dimensional building monomer reconstruction efficiency is improved.

The invention relates to a battery pole defect detection method and device, computer equipment and a storage medium. The method comprises the following steps: carrying out scratch area detection on an obtained to-be-detected pole image by adopting a trained pole scratch detection model to obtain a scratch area binary image; performing connected domain segmentation on the binary image of the scratch area to generate a scratch area pixel matrix; performing circular ring area detection on a circular ring on the outer side of the pole of the to-be-detected pole image to generate an outer circular ring area pixel matrix; according to the scratch area pixel matrix and the outer circular ring area pixel matrix, determining an overlapping area pixel matrix; and according to pixel values in the overlapped region pixel matrix, determining a region where the penetrability scratch is located in the to-be-detected pole image. According to the invention, the accuracy and efficiency of defect detection of the battery pole can be improved.

The invention discloses an array type focused laser differential interference measurement system, relates to the technical field of fluid mechanics measurement, and aims to solve the problem of how to improve the FLDI measurement efficiency and ensure the measurement precision at the same time. An emission light path generates multiple paths of light splitting pairs by using a diffractive optical element; a multi-path optical fiber array receiving system is arranged at the tail end of the receiving optical path and comprises a plurality of groups of receiving terminals, each group of receiving terminals comprises a three-dimensional coordinate frame, a photoelectric detector and an optical fiber probe, a rigid connecting rod is fixedly connected to a moving part of the three-dimensional coordinate frame, and the optical fiber probe is fixedly connected with the rigid connecting rod; the positions of the rigid connecting rods of the multiple groups of receiving terminals are respectively adjusted, so that the positions of the receiving ends of the multiple optical fiber probes are respectively in one-to-one correspondence with the final imaging focus positions of the multiple paths of light in the receiving light path; the device is simple in structure and ingenious in conception, the measurement efficiency can be remarkably improved, and meanwhile it can be guaranteed that multiple paths of optical signals are respectively and accurately received, so that the measurement accuracy is guaranteed.

The invention relates to the technical field of glucose detection, and discloses a method for detecting glucose in d-ribose fermentation broth, which comprises the following steps: step 1, diluting a d-ribose fermentation broth sample and adjusting the d-ribose fermentation broth sample to a predetermined pH value to form a pretreated sample; 2, removing impurities and concentrating target components through solid-phase extraction to obtain a treated sample; 3, separating the sample by using high performance liquid chromatography, setting a mobile phase, a flow rate and a chromatographic column temperature, and separating to obtain a glucose component; and 4, injecting the separated components into a mass spectrum system on line, and detecting a characteristic ion signal of glucose. The high-sensitivity and accurate detection of glucose in the d-ribose fermentation liquor can be realized by adopting a high-performance liquid chromatography and mass spectrometry combined technology. Through optimized sample pretreatment and mobile phase selection, interference of other carbohydrates on glucose detection is reduced, and accurate determination of glucose concentration is ensured.

The invention belongs to the technical field of SLAM (Simultaneous Localization and Mapping), and discloses a robot vision algorithm for a large visual angle, a storage medium and equipment, and the algorithm comprises the steps: S1, collecting image information, extracting feature information from an image through employing a multi-scale and multi-stage neural network, and repairing a fuzzy region; s2, performing position prediction on the feature points matched with the image based on an IMU sensor, and judging whether the feature points of the next frame are in a prediction range or not; s3, dividing the image into a plurality of regions, calculating the information entropy of each region, and performing grid division according to the size of the information entropy; and S4, providing a new neighbor grid domain grid statistical algorithm to further screen the feature points screened by the IMU sensor. According to the method, the blurred image frame is repaired, so that a large number of image feature points can be accurately extracted in large-view-angle motion, and timeliness and accuracy are improved in accurate matching through improvement.

The invention relates to a vehicle queuing and bypassing control method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring front vehicle state information corresponding to at least one front vehicle in a target monitoring range and vehicle driving information of a target vehicle; the target monitoring range is the monitoring range of the target vehicle; determining a target lane where the target vehicle is located and vehicle detour information according to the vehicle driving information; and under the condition that the preceding vehicle state information represents that a target preceding vehicle in a parking waiting state exists in the at least one preceding vehicle, the target vehicle is controlled to perform detouring processing according to the vehicle detouring information. According to the technical scheme provided by the invention, the queuing time of the vehicle can be shortened, the vehicle passing efficiency is improved, and meanwhile, the driving safety can be enhanced.

The invention discloses an intelligent material environment adjusting system for a vacuum pug mill, relates to the technical field of artificial intelligence, and solves the problems that the influence of environmental factors on pug stirring is not considered in the prior art, and the situation that finished pug meets the target requirement due to self-adaptive control over the vacuum pug mill is lacked. The finished product state of pug is poor; and the production efficiency of the vacuum pug mill is relatively low. The method comprises the steps of generating material data according to demand data and generating equipment initial parameters according to the material data; according to the material data, the to-be-finished product data and the environment data, to-be-finished product estimation parameters are generated; equipment adjustment parameters are generated according to the to-be-finished product pre-estimated parameters, the change influence of environmental factors on the to-be-finished product data in a stirrer is considered, the difference between the to-be-finished product data and the finished product data is predicted in real time, materials are added in advance or the equipment parameters are adjusted, and it is ensured that demand data can be obtained on time and according to quality at the minimum cost; and the accuracy and the efficiency of the vacuum pug mill are improved.

The invention discloses a power grid data consanguinity management system, and relates to the technical field of data management, and the system comprises a power grid data acquisition module, a power grid consanguinity data analysis module, a power grid consanguinity data processing module and a local database. According to the method, the blood relationship abnormal correlation coefficient of each data of the power transformation equipment to which the power grid belongs is analyzed, and the abnormal weight factor value of each data is dynamically adjusted, so that the early warning accuracy of the power transformation equipment is improved, and the failure rate of the power transformation equipment is reduced. By analyzing the consanguinity similarity between each piece of outage power transformation equipment which the power grid belongs to and each piece of pre-estimated fault power transformation equipment and each fault type, the predicted outage reason of each piece of outage power transformation equipment which the power grid belongs to and the pre-estimated fault reason of each piece of pre-estimated fault power transformation equipment are quickly determined, so that the maintenance efficiency of the power transformation equipment is improved; and the operation efficiency of the power transformation equipment is improved.

The utility model discloses mixing equipment capable of uniformly mixing for magnesium-calcium brick raw material processing, which comprises a mixing box and a crushing box, the crushing box is arranged above the mixing box, the output end of a large gear is fixedly connected with a first crushing roller, the output end of a small gear is fixedly connected with a second crushing roller, and the output end of the small gear is fixedly connected with a second crushing roller. And one side of the first gear is fixedly connected with a first stirrer, and one side of the second gear is fixedly connected with a second stirrer. Through the arrangement of the first crushing rollers and the second crushing rollers, the number of the second crushing rollers is two, and the three crushing rollers have a synergistic effect, so that large particles and cakes in magnesia-calcium brick raw materials can be effectively crushed into smaller particles, the specific surface area of the raw materials is increased, the mixing effect is improved, and the mixing efficiency is improved. And the crushed raw material particles are easier to uniformly distribute in the mixing process, the contact area between the small particles is increased, and the mixing efficiency is improved, so that the component uniformity of the magnesia-calcium brick product is ensured.

The invention discloses a method for reducing natural language generation complex SQL through table mode construction and SQL conversion. The method comprises the steps that a database mode is configured in advance, and a request of a user is processed; a database mode is pre-configured. The method comprises the following configuration steps: 1.1, a user configures connection information of a database to obtain a read permission of a target database in the database; and 1.2, reading table mode information from the target database according to the information configured by the user in the step 1.1, randomly reading two records at the same time, naming the two records as data 1 and data 2 respectively, and storing the data 1 and the data 2 in the database as a table mode. The method for processing Query of a user by the system comprises the following steps of: 2.1, retrieving a database mode related to the Query, and retrieving a related table mode from a database; 2.2, retrieving an SQL (Structured Query Language) example related to Query; 2.3, prompt word construction; 2.4, generating an SQL (structured query language) through the LLM model; 2.5, rewriting the SQL; and 2.6, executing the SQL. The method has the characteristics of more accurate complex query, lower maintenance cost and shorter time consumption.

The invention provides a method for optimizing reasoning performance of a neural network model and computing equipment. The method comprises the following steps: carrying out pre-running processing on a directed graph structure of the neural network model; obtaining input data; and sequentially scheduling operators from the operator execution queue to perform reasoning calculation on the input data. The pre-running processing comprises the following steps: sequentially obtaining each operator of each layer from the directed graph structure; judging the type of the operator, wherein the type of the operator comprises a constant operator, a deformation operator, a hardware operator and a user-defined operator except the constant operator, the deformation operator, the hardware operator and the user-defined operator; performing classification processing on the operators according to the types of the operators; and adding the processed operator to an operator execution queue according to a classification processing result. According to the technical scheme, the loading process of the neural network model can be optimized, the time consumed by model reasoning is shortened, and the power consumption of the model is reduced.

The invention relates to a digital manufacturing and construction method for a special-shaped stone veneer in a large venue, and aims to solve the problems of low machining precision, high mounting difficulty, low construction efficiency and the like of special-shaped stone in construction of an outer vertical face and an inner veneer of a building. The method comprises the following steps: firstly, measuring a building special-shaped structure by using a three-dimensional scanner or a BIM (Building Information Modeling) technology to generate a three-dimensional geometric model; based on the model, combining the material characteristics of the stone, and optimizing the geometric shape and size of the stone through a typesetting algorithm; then the optimized data are imported into five-axis CNC numerical control equipment for precise cutting; pre-assembly is conducted after cutting, errors are detected through laser scanning equipment, and adjustment is conducted till the precision requirement is met; and finally, a laser positioning system and a mechanical sensor are combined, a manual construction team manually installs the stone, and it is ensured that the installation precision meets the design requirement. According to the method, the machining and mounting precision of the special-shaped stone is effectively improved, the construction efficiency is improved, and the structural safety and the attractive effect of a building are guaranteed.

According to the agricultural transplanting instrument and method, a cavity is formed in the middle of a bearing plate, a soil sampling cylinder can penetrate through the cavity, two side plates are symmetrically arranged on the two sides of the soil sampling cylinder, a moving frame is slidably arranged at the upper end of the bearing plate, a second motor is fixedly arranged at the upper end of the bearing plate, and a moving seat is arranged in the middle of the moving frame; a driving screw penetrating through the moving seat is arranged at the output end of the second motor, two second lifting air cylinders are symmetrically arranged on the two sides of the moving frame, and first lifting rods connected with the side plates are arranged at the output ends of the second lifting air cylinders. The time consumption in the transplanting process is greatly reduced, more transplanting tasks can be completed in a shorter time, and the agricultural production efficiency is improved.

The invention discloses a CPMPS manufacturing resource servitization reconstruction method and system based on reconstruction opportunity driving, and is applied to the technical field of intelligent manufacturing, and the method comprises the steps: packaging manufacturing resources into a modularized manufacturing resource service directory; determining an optimal reconstruction time point of the modular production system by adopting a reconstruction opportunity triggering strategy; performing manufacturing resource service matching on the modular production system based on the manufacturing resource service directory and the optimal reconstruction time point to obtain a plurality of reconstruction schemes; and selecting an optimal reconstruction scheme from the plurality of reconstruction schemes, and carrying out implementation and simulation verification on the optimal reconstruction scheme.