291results about How to "Avoid accuracy" patented technology

The invention relates to the technical field of television image communication, in particular to a user information input method and system in an intelligent television all-in-one machine. The method comprises the following steps: collecting a user image, carrying out white balance correction and focusing processing, generating a moving object focusing image, carrying out identification and attention tendency analysis on a character in the focusing image, obtaining character tendency data, analyzing a historical interaction image, identifying an interaction mode and constructing a user intention prediction model, and obtaining a user intention prediction result. And when the tendency data shows that the user preferences the television content, intention drilling and auxiliary adjustment are performed on the current image based on the prediction model, predicted user input information is generated, logic conflicts in the predicted information are detected, feedback optimization is performed, and final user input information is output. According to the invention, a more accurate and more flexible user information input method is realized.

The invention relates to the technical field of artificial intelligence, and provides a search method and device, electronic equipment and a readable storage medium. The method comprises the following steps: acquiring a search term for searching; matching the search terms through a preset database to obtain an initial matching result; obtaining a target search term according to the search term and the initial matching result, and performing semantic extension on the target search term to obtain at least one extended search term; searching by utilizing a target search term and at least one extended search term to obtain a first search result corresponding to the target search term and a second search result corresponding to the at least one extended search term; and determining a target search result corresponding to the search term according to the first search result and the second search result. Through initial semantic matching, semantic extension and comprehensive analysis, a more accurate and comprehensive search result meeting the search intention of the user can be provided for the user.

The invention relates to the field of elevator door change gear detection, in particular to an elevator door change gear detection device, which solves the problem that a door change gear can be automatically replaced while the elevator door change gear detection device is suitable for simultaneous detection of various door change gears with different sizes, and comprises a cabinet body and a driving motor, and an output shaft is fixedly installed at the output end of the driving motor, a plurality of driving wheels are fixedly installed on the outer wall of the output shaft, and the driving wheels are installed at equal intervals. According to the device, the function of automatically adjusting the height of the change gear seat can be achieved, the device can be conveniently suitable for door change gears with different sizes and diameters, the device can conveniently detect the door change gears with different sizes at the same time, a replacement box of the device can achieve automatic replacement when the door change gears descend after detection is completed, and the detection efficiency is improved. Manual operation is not needed, and the detection efficiency of the device can be improved on the premise of ensuring safety.

The embodiment of the invention discloses a big language model training method and device, computer equipment and a storage medium, and belongs to the technical field of computers. According to the method, a first abstract text and a second abstract text are introduced in the training process of a large language model, more learnable information is provided for model training, meanwhile, due to the fact that the first abstract text and the second abstract text contain different information amounts, and the first abstract text contains correct statements and error statements, the learnable information is more learnable. Compared with the prior art, the two different abstract texts of the same sample text are subjected to comparative learning, and correct statements and wrong statements in the first abstract text are learned in a differentiated manner, so that the problems of model overfitting, inaccurate generation and the like caused by single abstract text are avoided, the generalization performance of the model is improved, and the accuracy of the model is also improved.

The invention provides a method for actively detecting the dosage of lime in lime stabilized soil for traffic infrastructure, and relates to the technical field of lime detection. The rapid detection method mainly comprises the following steps: preparing a plurality of test reagents, respectively adding a plurality of groups of lime stabilized soil containing different lime doses into an ammonium chloride solution to form a mixed solution, titrating the mixed solution by using a titrating solution, and detecting the conductivity of the solution, drawing a relation image of the solution conductivity and the dosage of the titrating solution, determining the dosage of the titrating solution when the conductivity is lowest, establishing a function relation between the lime dosage and the dosage of the titrating solution when the conductivity is lowest, repeating the steps and calculating the dosage of the lime in the to-be-detected lime stabilized soil in combination with the function relation. The invention overcomes the defects in the prior art, provides a new method for detecting the lime dosage of the lime-stabilized soil, and can quickly and accurately measure the lime dosage through the change of the conductivity in the solution and the characterization of the reaction process, thereby further improving the working efficiency.

The invention discloses a PC board surface intelligent flaw recognition device, and relates to the technical field of PC board flaw recognition devices.The PC board surface intelligent flaw recognition device comprises a bottom plate base, a cover plate, an auxiliary cavity, a flaw recognition visual device and a wavy PC board, the cover plate is fixedly connected to the bottom plate base, and the auxiliary cavity and the flaw recognition visual device are both fixedly connected to the cover plate; the wave PC board is located on a conveying belt on the bottom plate seat, and the multi-application type driving assembly, the stable identification auxiliary assembly and the effective identification processing assembly are further included. Through the design of the stable identification auxiliary assembly, it can be effectively guaranteed that the wave PC board is in a state parallel to a defect identification visual device before defect identification is conducted; therefore, the situation that in actual detection, due to the fact that the placing position of the wave PC board is not parallel to the flaw recognition visual device, local irradiation of the to-be-detected wave PC board is insufficient, and the flaw detection accuracy is affected is avoided, the detection accuracy is improved, the misjudgment and missed judgment risks are reduced, and the integrity of image data is effectively guaranteed.

The invention relates to the technical field of data processing, and discloses a method for determining the reliability of a compressed gas energy storage underground gas storage under the action of an earthquake. Comprising the steps that earthquake influence parameters are combined into a parameter set, the effective state of an earthquake event is recognized, a three-dimensional model of the underground gas storage is constructed, simulation parameter bits are marked, comprehensive reliable parameters are obtained, the comprehensive reliable parameters are imported into the simulation parameter bits, a gas storage simulation model is generated, and the reliability level of the underground gas storage is determined. Compared with the prior art, the method has the advantages that the analysis threshold of reliability determination can be improved, the workload of reliability analysis can be reduced, and the acquired comprehensive reliable parameters can be subjected to analog simulation processing in combination with the gas storage simulation model, so that the negative influence degree of an earthquake event on the underground gas storage can be truly and accurately analyzed; the problems of high burden and inaccurate calculation caused by analysis and calculation after real-time monitoring through multiple sensors in the prior art are avoided.

The invention relates to the technical field of artificial intelligence, and provides an occupied port detection method and device, equipment, a storage medium and a product. The method comprises the steps of obtaining a to-be-detected image; inputting the to-be-detected image into the target detection model to obtain a port position detection result; based on the port position detection result, determining a currently occupied port of the optical cable cross connecting cabinet to be subjected to quality inspection; the target detection model is obtained by pre-training an initial model constructed based on a YOLO-EF algorithm based on a preset loss function, a sample detection image and a sample port position detection result; the sample port position detection result is used for adjusting model parameters of the initial model, so that the preset loss function conforms to a preset threshold value. Through the above mode, a semantic segmentation model does not need to be adopted, the problems of low detection efficiency and low accuracy of the semantic segmentation model can be avoided, accurate detection of the ports occupied by the optical cable cross connecting cabinet is realized by using the deep learning model, and improvement of the quality inspection accuracy of the optical cable cross connecting cabinet is facilitated.

The invention discloses a method and device for predicting the sealing performance of an electrical penetration assembly and a storage medium, and the method comprises the steps: obtaining the structure attribute information of a target electrical penetration assembly in response to a prediction signal of the sealing performance of the target electrical penetration assembly, external environment attribute information of the target electrical penetration assembly at different moments and gas attribute information of gas in a barrel of the target electrical penetration assembly at different moments are collected in real time, and the gas attribute information comprises gas temperature and gas pressure of the gas in the barrel of the target electrical penetration assembly at different moments; based on the gas temperature, judging whether the target electrical penetration assembly meets a preset condition of sealing performance monitoring or not; and if the target electrical penetration assembly meets the preset condition, predicting the sealing performance of the target electrical penetration assembly based on the structure attribute information, the external environment attribute information and the gas attribute information.

The invention relates to the technical field of pipeline quality detection, and discloses building pipeline quality detection equipment, which comprises a base, and further comprises a fixed disc fixedly mounted at the top of the base; the rotating disc is rotationally mounted in the center of the top of the fixed disc; the L-shaped frame is fixedly mounted at the top of the base; the detection assembly is mounted at the top of the rotary table and used for detecting the building pipeline; the sealing assembly is arranged on the L-shaped frame and the base, and the sealing assembly is used for sealing the detection assembly. According to the invention, pressure resistance and crack damage detection can be synchronously carried out on the building pipeline, the situations of inaccurate detection and troublesome detection are avoided, in addition, the building pipeline with air leakage can be marked by a brush, and the disassembled pipeline with unqualified pressure resistance can directly fall onto the fixed disc, so that the detection result of the building pipeline is clear and visual, and the detection efficiency is improved. And the use effect of the equipment is improved.

The invention discloses a machine tool cutter space pose on-machine measurement device and a measurement method thereof, and the device comprises a calibration module which is installed at one side of a cutter handle of a cutter; a frequency-modulated continuous wave laser interference system and a galvanometer are installed on a vibration isolation workbench of the machine tool, light beams emitted by the frequency-modulated continuous wave laser interference system achieve conversion of a set angle through the galvanometer so as to cover the calibration module, and a space positioning algorithm is adopted to fit the plane where the target ball is located. And obtaining a deviation value between the mass center and the normal vector in two measurement results before and after machining, and taking the deviation value as the tool space pose error before and after machining of the machine tool, so that rapid and high-precision direct measurement of the tool space pose error is realized. The method has the advantages of being large in measurement range, high in measurement precision, simple in structure and low in cost, and the defect that in an existing method, the position and pose errors of the tool are indirectly calculated through an error model is overcome.

The invention provides an operation and maintenance data analysis and optimization system and method based on a deep neural network, and relates to the technical field of intelligent operation and maintenance management, and the method comprises the steps: constructing a high-latitude sparse matrix according to preprocessed first data and second data, and employing a low-rank matrix to decompose the high-latitude sparse matrix, extracting potential low-dimensional features in the first data and the second data according to low-rank matrix decomposition, performing weighted fusion on the potential low-dimensional features, and forming a comprehensive feature vector according to the weighted fusion; introducing an equipment life cycle stage identification mechanism, constructing a fault prediction model, and training the fault prediction model according to the comprehensive feature vector to obtain a trained fault prediction model; and introducing a multi-stage transfer learning mechanism, and carrying out knowledge transfer on the trained fault prediction model to obtain a fault prediction model after knowledge transfer. The problems of feature sparsity in high-dimensional data and data drift in an equipment life cycle are solved through low-dimensional feature extraction and transfer learning.

The invention relates to an automatic feeding positioning mechanism and an automatic feeding method, the automatic feeding positioning mechanism comprises a material loading assembly vehicle, the top of the material loading assembly vehicle is provided with a tray, and the tray is fixedly provided with a plurality of stator placing seats; the positioning frame is used for being fixedly arranged at the feeding station, and a containing space used for longitudinally passing through the material carrying assembly truck is formed in the positioning frame; the tray is borne and transversely limited by the top of the positioning frame; the detection assembly is arranged on the positioning frame and is used for sending out a signal after the tray is detected to reach the target position; and the jacking driving assembly is arranged on the positioning frame, the top of the jacking driving assembly makes contact with the bottom of the tray, and the jacking driving assembly vertically pushes the tray to ascend to the grabbing position after receiving the signal. Through cooperation of the material loading assembly vehicle, the box body positioning frame, the light sensor and the jacking driving assembly, the accuracy of feeding and discharging operation each time is ensured, and the problem that in the related technology, positioning is not accurate in the automatic feeding and discharging process of the stator iron core is solved.

The invention belongs to the technical field of robot welding, and discloses a welding spot positioning method for an underground diaphragm wall reinforcement cage, which is used for positioning a welding spot between a transverse bar and profile steel, and comprises the following steps: establishing a three-dimensional coordinate system, and obtaining a three-dimensional point cloud data set of the transverse bar and the profile steel, processing the three-dimensional point cloud data set to form a first point set, determining a starting point coordinate of a center line of the connection section according to the first point set, processing the three-dimensional point cloud data set to form a second point set, determining an end point coordinate of the center line of the connection section according to the second point set, and determining the end point coordinate of the center line of the connection section according to the starting point coordinate and the end point coordinate of the center line of the connection section. And determining starting point coordinates and terminal point coordinates of a welding seam between the connecting section and the profile steel. By means of the arrangement, the welding spot positioning method for the underground diaphragm wall reinforcement cage can achieve accurate positioning of the welding spot position, and the welding quality and the operation efficiency can be improved easily.

The utility model discloses a hydraulic oil pump coupling coaxiality adjusting device, and relates to the technical field of coaxiality adjustment. Comprising a hydraulic oil pump base, an oil pump arranged at one end of the hydraulic oil pump base, a motor base arranged at the other end of the hydraulic oil pump base, a driving motor installed on the motor base, and a coupler connected with the output end of the driving motor and a connecting shaft of the oil pump. The throw measuring assembly is arranged on the coupler and used for measuring the radial and axial throw of the coupler, and the coaxiality adjusting assembly is used for adjusting the transverse and longitudinal positions of the motor base so as to adjust the coaxiality of the coupler. When the motor base is transversely adjusted, according to data measured by the radial dial indicator and the axial dial indicator at the position of the coupler, the first dial indicator is adopted to accurately monitor the movement condition of the motor base while the transverse adjusting jack is used for adjustment, inaccurate adjustment and repeated adjustment are avoided, and the coaxiality deviation of the coupler of the pressure oil pump is small after adjustment is completed.

The invention relates to the technical field of financial data analysis, and discloses a fraud gang identification method and system based on a knowledge graph. The method comprises the following steps: extracting financial transaction entities in equipment fingerprint data and transaction data generated in a financial transaction process and a relationship between the financial transaction entities based on an entity identification technology and a relationship extraction technology, and constructing a financial transaction knowledge graph; and carrying out financial transaction feature analysis on the financial transaction knowledge graph based on a graph analysis technology, identifying target nodes with an association relationship, and determining a financial fraud gang. On the basis of the knowledge graph constructed by utilizing the equipment fingerprint data and the transaction data, the graph analysis technology is adopted, the incidence relation between entities in the financial data can be comprehensively analyzed, potential fraud gangs are identified, and the problem that the fraud gangs in different financial fields cannot be identified is solved. And the hidden association and behavior pattern are difficult to capture by a single data feature, so that the accuracy of cross-domain financial fraud gang identification is improved.

The invention relates to the field of data processing, in particular to a heat exchange station equipment operation information acquisition and generation method based on big data analysis, which comprises the following steps: periodically detecting a temperature reference value of each target heating user to obtain an average temperature reference value and a temperature difference value; a temperature analysis mode is determined according to the average temperature reference value and the temperature difference value, and the temperature analysis mode comprises the steps that detection is conducted on temperature fluctuation values in a preset fluctuation detection range, and whether compensation analysis is conducted on the temperature reference values of all the target heating users or not is determined according to the distribution state of all the types of users; determining a setting mode of an early warning time period according to the heating effect trend and the temperature difference value; and if the equipment state is under the heat exchange early warning condition, equipment state early warning is carried out, and the equipment operation information processing efficiency in the equipment operation maintenance process is improved.

The invention relates to the technical field of fire fighting, in particular to an AIOT-based fire-fighting facility health situation detection and analysis system. Comprising an acquisition layer, a transmission layer, a data layer, a support layer and an application layer. The acquisition layer uses a detection integration device to detect fire-fighting equipment and sends detection data to the transmission layer, the transmission layer transmits the data to the data layer, the data layer transmits the data to the supporting layer, the supporting layer transmits the data to the application layer, and finally the application layer generates an evaluation report. The acquisition layer consists of a smoke / temperature monitoring sensor, a wind pressure monitoring sensor, an illumination / noise monitoring sensor, a distance / slope measurement sensor or detector and an edge computing gateway, and a detection integrated device with a replaceable acquisition head is used for acquiring the data; the system working platform is divided into six layers; the potential safety hazard rate of a single fire-fighting facility and the potential safety hazard rate of the fire-fighting facilities of a social unit (having n fire-fighting facilities) can be calculated through related formulas according to detection data, and then evaluation is carried out.

The embodiment of the invention discloses a multi-modal analysis and diagnosis model based on combination of multi-source data fusion and a large model, and belongs to the technical field of large models, and the model comprises a scene model module which is used for calling different function modules according to different tasks and scenes; the industry large model module is used for establishing different industry large models according to different industry requirements; the task execution module is used for calling different task models and function applications according to different task requirements; the matching tool module is used for providing tools or engines according to task requirements; the data knowledge module is used for establishing various databases and storing different data in the corresponding databases in a classified mode, diversified and fragmented AI application requirements can be rapidly met, the development cost and time can be reduced, the development efficiency can be improved, information and value in the data can be fully mined, and the development efficiency can be improved. And the influence caused by insufficiency or inaccuracy of the annotated data can be avoided.

The invention provides a foundation treatment process, and relates to the technical field of foundation treatment. The foundation treatment process specifically comprises the following steps: S1, geological survey and three-dimensional modeling; s2, establishing a micro-seismic monitoring system; s3, applying a self-healing material; s4, construction of a rotary drilling rig; s5, performing real-time construction monitoring and adjustment; s6, detecting the hole forming quality of the pile foundation; s7, concrete is poured, and a self-healing material is injected; and S8, geological treatment and acceptance after construction. Safety and accuracy of the construction process can be guaranteed by monitoring changes of underground rock strata and karst caves in real time, the construction quality of each pile foundation is guaranteed through data analysis and dynamic adjustment of a construction scheme, self-repairing of the material can be achieved through the fungus self-healing cement-based material, durability and stability of the pile foundations are enhanced, and the construction quality of the pile foundations is improved. The long-term effect of foundation treatment is improved, the later maintenance cost is reduced, the pile foundation construction quality under the complex karst geological condition can be ensured, the construction efficiency is improved, the cost is reduced, and the engineering safety and stability are ensured.

The invention discloses a commercial vehicle air filter element service life early warning method, system and equipment and a medium, mainly relates to the technical field of air filter elements, and aims to solve the problems that an existing scheme is large in operation load, air filter residual information of multiple vehicles cannot be uniformly acquired, a reference value is utilized, and the service life of the air filter elements is not influenced. The air quality correction factor is relatively high in cost or the accuracy cannot be ensured. Comprising the following steps: uploading whole vehicle operation state data to a cloud; reading the running state data of the whole vehicle from the cloud by using a hive tool; obtaining an air filter pressure mean value of the air filter pressure values every day, and writing the air filter pressure mean value into a preset database; when the average value of the air filter pressure stored in the preset database exceeds a preset number of days, fitting to obtain a change trend of the average value of the air filter pressure based on the average value of the air filter pressure stored in the preset database; determining the time when the average air filter pressure in the change trend is greater than a preset air filter pressure threshold value, and further determining the remaining time.

The invention discloses a polishing cloth trepanning device and method, and relates to the technical field of polishing machines, the polishing cloth trepanning device comprises a bracket and an adjusting seat, the bracket is provided with a first cutter body, a cloth pressing body and an expansion body, the bracket is installed from the outlet end of a liquid guide hole of a polishing disc, the first cutter body is used for cutting the polishing cloth at the outlet end of the liquid guide hole, and the cloth pressing body is used for pressing the cloth at the outlet end of the liquid guide hole. The cloth pressing body is used for pressing the cutting edge of the polishing cloth into the liquid guide hole and abutting against the inner wall of the outlet end of the liquid guide hole. The adjusting seat is arranged from the inlet end of the liquid guide hole, and the adjusting seat is matched with the expansion body, so that the expansion body is tightly supported on the inner wall of the liquid guide hole after being matched, and the bracket is fixed in the liquid guide hole. According to the polishing cloth tapping device, accurate finishing and fixing of the polishing cloth at the position of the liquid guide hole are achieved, and the problems that the polishing cloth is degummed and a wafer is scratched due to improper manual finishing are effectively avoided.

The invention relates to the technical field of IO-Link electromagnetic flow meters, the IO-Link electromagnetic flow meter comprises an IO-Link electromagnetic flow meter body, a lining pipe is arranged in the IO-Link electromagnetic flow meter body, and the IO-Link electromagnetic flow meter further comprises a primary cleaning unit arranged on the lining pipe and used for filtering liquid introduced into a lining and cleaning the outside of the lining at the same time; the primary cleaning unit comprises a filtering assembly which is concentric with the lining pipe and is used for filtering liquid introduced into the lining pipe and cleaning the end part of the lining pipe; the IO-Link electromagnetic flowmeter solves the problems that in the prior art, when an electromagnetic flowmeter is used for a long time, impurities are attached to the outer portion and the inner portion of a lining pipe, electrode detection is indirectly influenced, and the impurities attached to the surfaces of an electromagnetic winding and an electrode directly influence the detection of the electromagnetic flowmeter. Impurities are comprehensively cleaned when liquid is detected, so that the detection result of the electromagnetic flowmeter is accurate.

The invention discloses a fault stress disturbance physical simulation system and method, and relates to the technical field of oil and gas field development. A physical simulation system for disturbance of a fault stress field comprises a strain calculation module which is used for calculating data of a 3D displacement field, a 3D strain field and a 3D deformation field of an object to be measured in the loading process through three-dimensional reconstruction and a digital image correlation algorithm according to surface feature changes of an image of the object to be measured; and the model optimization module is used for adjusting a digital modeling design method according to the data of the 3D displacement field, the 3D strain field and the 3D deformation field to obtain an optimal modeling method. In addition, the invention further discloses a fault stress field disturbance physical simulation system based on the system. According to the method, the problem of verifying the accuracy of a finite element solution result is solved, the modeling technology is optimized and adjusted, the optimal modeling method is conveniently obtained and popularized and applied to three-dimensional modeling, and therefore the disturbance rule of a fault on ground stress is found out.

The invention relates to an adjustable water gate device for a water conservancy project, and relates to the field of water conservancy projects, and the adjustable water gate device for the water conservancy project comprises a gate chamber used for being mounted to a dam body; the gate is slidably connected to the gate chamber in the height direction, a lifting device used for driving the gate to move up and down is arranged between the dam body and the gate, and a plurality of impurity removal openings are formed in the position, close to the top of the gate, of the gate in the height direction at intervals; the multi-stage opening and closing mechanism is arranged on the gate and used for controlling opening or closing of the single impurity removal opening; and the impurity removing mechanism is arranged on one side of the impurity removing opening and used for intercepting and removing impurities floating on the water surface. The device has the effects that in the process of conveying water resources to the downstream, floating garbage and algae are not prone to being gradually accumulated on the water surface close to one side of the gate, the floating garbage and algae are prevented from being accumulated and fermented for a long time to generate a large amount of unpleasant smell, and pollution to water quality is reduced.

The invention belongs to the technical field of liquid level detection devices, and discloses a liquid level detection device for water treatment tank equipment, which comprises a water treatment tank, a detection head is arranged at the top end of the water treatment tank, a mounting plate is mounted on the outer wall of the detection head, a connecting rod is connected to the bottom end of the detection head, and a cleaning assembly is arranged outside the connecting rod. The bottom end of the connecting rod is fixedly provided with a detection end, the detection end is arranged in the water treatment tank body, the cleaning assembly comprises a cleaning cylinder arranged outside the connecting rod, the cleaning cylinder is arranged below the mounting plate, and the mounting plate and the cleaning cylinder are connected through a moving assembly. A water pump connected with the first connecting pipe is started, so that an external water source is pumped by the water pump to be discharged into the sixth connecting pipe and the second connecting pipe through the first connecting pipe and finally discharged from a spray head to wash the surface of the detection end, and the maintenance steps are simplified and the maintenance efficiency is improved by directly cleaning the interior of the water treatment tank body.

The utility model provides a micro-channel plate heat exchanger performance test system which comprises an upper cover plate, a heat source chip support, a heat source chip, an inlet channel connecting piece, an outlet channel connecting piece and a lower cover plate, and a single heat exchange plate, the heat source chip and the heat source chip support are installed between the upper cover plate and the lower cover plate. The heat source chip is arranged below the heat exchange area of the single heat exchange plate and is positioned in the mounting groove of the heat source chip support; the left and right ends of the upper cover plate and the lower cover plate are respectively and hermetically provided with an inlet channel connecting piece and an outlet channel connecting piece; a pressure sensor and a threaded thermal resistor are arranged near a liquid inlet / outlet of the single heat exchange plate and are used for measuring inlet / outlet pressure and inlet / outlet temperature; the inlet channel connecting piece is connected with a fluid supply pipeline and is provided with a flow sensor. The test system is used for carrying out heat exchange performance measurement on a single plate to ensure that the performance of the single heat exchange plate is improved, so that the whole heat exchanger is optimized.

The invention provides an engineering quantity list processing method and system based on double analysis and correction, and relates to the technical field of data processing, and the method comprises the steps: obtaining an engineering quantity list; carrying out electronic version conversion on the paper version engineering quantity list; extracting a plurality of identification engineering categories of the target engineering quantity list and the identification engineering quantity of each identification engineering category based on a target detection algorithm; extracting an initial text of the target bill of quantity in combination with a Bayesian algorithm; performing semantic analysis on the initial text in combination with a large language model taking dynamic context lexical elements as input data, and outputting a semantic text of a target bill of quantity; aligning each identification project category and each analysis project category to a target entity; comparing the identification work amount and the analysis work amount which belong to the same target entity; and under the condition that the comparison results are consistent, outputting the semantic text as an engineering quantity list processing result, otherwise, marking a comparison difference result in the semantic text. And the compiling efficiency and accuracy of the bill of quantity are improved.

The invention discloses a power grid fault prediction system. The system comprises a sensing terminal module, a data processing module, a data transmission module, a central data center and a power grid monitoring module, wherein the sensing terminal module is used for acquiring power grid parameters and sending the power grid parameters to the data processing module; the data processing module is used for cleaning the power grid parameters, obtaining target power grid data and sending the target power grid data to the data transmission module; the data transmission module is used for performing data encryption on the target power grid data to obtain encrypted data; the central data center is used for storing the received encrypted data and sending the encrypted data to the power grid monitoring module; and the power grid monitoring module is used for obtaining a fault prediction result matched with the target power grid data after receiving the encrypted data. Through the technical scheme of the invention, the power grid fault prediction is realized, and the efficiency of power grid fault prediction work, the safety of power grid data transmission and the accuracy of a fault prediction result are improved.

The present disclosure relates to an autonomous mobile device, a control method and apparatus thereof, and a storage medium, the method comprising: a shooting step of shooting an image of a working environment of the autonomous mobile device; a distance measurement step: obtaining point cloud data of a working environment of the autonomous mobile device; an identification step: inputting the image into an image object identification model for identification to obtain an object in the image and a space range of a detection frame where the object is located; an obtaining step: obtaining the number of the point cloud data in the space range of the detection frame; a judgment step: judging whether the quantity of the point cloud data exceeds a preset quantity threshold value or not; and an object positioning step of calculating the spatial position of the detection frame according to the point cloud data in the spatial range of the detection frame under the condition that the number of the point cloud data exceeds a preset number threshold. Therefore, wrong object recognition or wrong object position judgment can be avoided, the accuracy of obstacle recognition and obstacle avoidance of the autonomous mobile equipment is improved, and thus the intelligent degree of the autonomous mobile equipment is improved.