276 results about "System transformation" patented technology

The invention discloses a vehicle-mounted Beidou positioning deviation self-calibration system fused with inertial navigation information, and relates to the technical field of navigation and positioning. The method is used for solving the problems of positioning deviation accumulation and signal failure in a complex environment. The system realizes space-time alignment of inertial navigation and Beidou observation data through timestamp interpolation and coordinate system conversion, and constructs a multi-source synchronous data stream. A difference value between an inertial navigation calculation speed and a Beidou Doppler speed is analyzed based on a vehicle incomplete constraint model, and a weight factor is generated in combination with a confidence threshold to suppress abnormal observation. A geometric matching error is calculated through a high-precision lane map curvature and a vehicle steering angle, and candidate tracks are screened to generate transverse calibration parameters. The noise covariance is dynamically adjusted through a tight coupling filtering algorithm, the mode is switched to a lane constraint calibration mode when a Beidou signal is interrupted, inertial navigation errors are compensated through error boundary constraint, and stable output is achieved. Multi-source data deep fusion and adaptive robust calibration are realized, and system robustness and positioning continuity are improved.

A method and apparatus for robot joint angle generation, and a robot system. The method for robot joint angle generation comprises: acquiring, in a standard form, a DH parameter set of a robot requiring a solution, a base coordinate system transformation matrix between the robot requiring a solution and a standard robot, and a joint angle transformation relationship between the robot requiring a solution and the standard robot; on the basis of the base coordinate system transformation matrix, converting an end pose of the robot requiring a solution into a standard end pose; on the basis of the DH parameter set in the standard form of the robot requiring a solution and the standard end pose, performing an inverse kinematics calculation to obtain, in a standard form, a joint angle of the robot requiring a solution; and, on the basis of the joint angle transformation relationship between the robot requiring a solution and the standard robot and the joint angle in the standard form of the robot requiring a solution, obtaining the actual joint angle of the robot requiring a solution.

The invention discloses a robot joint control method and system based on motion capture equipment, and belongs to the technical field of robot control. An existing robot joint control scheme lacks an effective man-machine cooperation and natural interaction mechanism, so that the flexibility of a robot is poor, and the intention of an operator cannot be naturally expressed. According to the robot joint control method based on the motion capture equipment, by constructing a motion capture module, a data processing module, a coordinate system transformation module and a solution optimization module, rotating posture data, collected by the motion capture equipment, of human body joints are converted into target joint control information needed by execution of a robot; the robot joint control based on the motion capture equipment is realized, so that the human motion can be efficiently and accurately mapped to the robot, the robot is good in flexibility, sudden motion or complex cooperative operation can be effectively processed, the intention of an operator can be naturally expressed, and man-machine cooperation and natural interaction are realized.

The invention discloses an interferometer error calibration method and device and a computer readable storage medium, and belongs to the technical field of measurement equipment.The method comprises the steps that measurement data collected when an interferometer moves on the x / y axis of a motion table is obtained, and x / y axis compensation amount is generated through calculation processing; meanwhile, a coordinate system transformation matrix is established and optimized by using data of a marking plate arranged on a motion table, and x-axis and y-axis non-orthogonal parameters are obtained. And then the compensation amount and the non-orthogonal parameters are input into a preset kinematic model, and the accurate position of the motion platform under the global coordinate system is calculated in real time. And when a preset updating condition is met, dynamically updating the error compensation value of the interferometer through the deviation between the actual position detected by the visual system and the calculated position. Reflector surface type error compensation and non-orthogonal parameter correction are fused, and high-precision error compensation calibration of the interferometer is achieved.

The invention relates to an optimization configuration method, equipment and medium for a network-following construction type series-parallel system considering uncertainty, and the method comprises the steps: constructing a converter optimization configuration model by taking the minimum number of reconstruction times as an optimization target and taking the robust stability of the series-parallel system as a constraint condition; the optimized configuration process of the series-parallel system comprises the following steps: S1, segmenting the current series-parallel system into equivalent network following / network constructing subsystems, respectively calculating a generalized short-circuit ratio, determining a critical value of small interference stability of a corresponding nominal system, and solving a generalized short-circuit ratio and a robust stability margin of critical robustness of a subsynchronous frequency band based on a small gain theorem; s2, judging whether constraint conditions are met or not, if yes, ending the current optimization process, and otherwise, turning to S3; and S3, identifying the weakest feed-in point in the current series-parallel system by adopting a participation factor method, transforming the station corresponding to the weakest feed-in point into network construction type control, and turning to S1. Compared with the prior art, the input cost in the system transformation process is reduced on the basis of ensuring the robust stability of the system.

The invention discloses an aircraft component self-adaptive in-place method, device and equipment and a medium. The aircraft component self-adaptive in-position method comprises the following steps: acquiring an aircraft component ball socket image; based on the target detection model, detecting an aircraft component ball socket image to obtain a target ball socket joint image, and performing image preprocessing on the target ball socket joint image to obtain a ball socket joint circle center pixel coordinate; according to the initial positioning coordinates of the ball head and the ball socket, the pixel coordinates of the circle center of the ball socket joint and the coordinate system transformation matrix, the ball head feeding amount of the positioner is calculated; and controlling the positioner ball head to completely enter the ball socket according to the feeding amount of the positioner ball head and the force-position hybrid control model. According to the technical scheme, the ball head can be automatically guided to be accurately inserted into the ball socket in the racking process of the large aircraft component, manual intervention is not needed, the safety is high, the racking efficiency is improved, and damage to the component can be avoided.

The invention provides an inspection-oriented structure three-dimensional model data optimization method, which comprises the following steps of: analyzing assembly body model data generated by a three-dimensional design platform, and extracting an original data set containing a BREP topological structure, PMI labeling information and a hierarchical relationship; dynamically removing welding nodes, process auxiliary lines and non-geometric attribute data; performing multi-precision curved surface reconstruction on the BREP entity; grid fusion optimization based on material attributes is implemented, triangular patches of the same material are combined, and a vertex index table is reconstructed; constructing a lightweight assembly relation tree, and converting the spatial poses of the parts into a relative coordinate system transformation matrix; generating a lightweight metadata file containing measurable geometric parameters; and outputting a JT format lightweight model which accords with the ISO 14306 standard. According to the technical scheme, on the premise that the model states before and after lightweight processing are consistent, the data size of the model can be reduced, reduction of the overall data size of the three-dimensional model is promoted, and the opening and loading speed of the called model is greatly increased.

The invention relates to a clamping control method of a movable mechanical arm. The clamping control method is used for solving the problem of collaborative optimization of stability and precision in clamping operation. According to the method, a motion coupling factor and a contact force gradient mode length are calculated in real time through a dynamic coordination module, base-world coordinate system conversion is combined to realize bidirectional constraint of chassis speed and mechanical arm torque, instability caused by sudden load change is inhibited, a time-varying sliding mode surface and an anti-buffeting control law are adopted for sliding mode control, and the stability of a mechanical arm is improved. Dynamic boundary layer thickness and adaptive gain are introduced, control parameters are further optimized through a double-delay depth deterministic strategy gradient, and a multi-target reward function is designed. According to the method, the robustness of the system is remarkably improved through closed-loop optimization, and the stability and precision of the movable mechanical arm in the clamping operation are improved.

The invention relates to the field of transformer bank operation optimization methods, in particular to a transformer bank operation state evaluation and optimization method considering cooling system transformation, which comprises the following steps of: S1, determining a mathematical mapping relationship among the number of cooling fans, the rotating speed type of the fans, the load rate and an operation temperature drop value of an oil-immersed self-cooling transformer; establishing a transformer cooling system transformation efficacy model; s2, determining unknown parameters in the transformation efficacy model of the transformer cooling system according to the field operation data; s3, generating load rate data of the transformers in a future planning period according to the historical load rate data of the transformers; establishing a mathematical relationship between the operating temperature and the aging factor of the transformer to obtain a transformer operating state evaluation method considering the transformation influence of the cooling system; and S4, on the basis of S1, S2 and S3, forming a transformer bank cooling system transformation scheme optimization decision-making method considering the cost constraint so as to determine a cooling system transformation scheme of each transformer. According to the invention, an accurate optimization scheme can be obtained.

The invention belongs to the technical field of detection of defects in small holes, and discloses a method and a system for detecting the quality of a perforated workpiece. The detection method comprises the steps that laser penetrates through a small hole of a workpiece to be detected to form a diffraction image, and the diffraction image is a multi-layer circular bright ring; projecting the diffraction image to an imaging unit; the imaging unit transmits the diffraction image to the processing unit; the processing unit extracts a hot spot central region of the diffraction image, performs polar coordinate system transformation on the original diffraction image according to sub-pixel points of the hot spot central region to obtain a horizontal stripe image, and extracts center line sub-pixel coordinates of the horizontal stripe image; the extracted center line sub-pixel coordinates are converted back to original Cartesian image coordinates to obtain the trajectory center line of each layer of circular ring, and the actual circle center, the actual roundness and the actual diameter of the circular ring are calculated according to the trajectory center line of each layer of circular ring; and the analysis unit analyzes the actual circle center, the actual roundness and the actual diameter to obtain defect information of the workpiece to be detected. According to the invention, tiny defects can be efficiently and accurately detected.

The invention discloses an intelligent scheduling method and system for improving quality and efficiency of a pumped storage power station, and the method comprises the steps: extracting a power grid load and a new energy output typical day scene based on power grid source load characteristics and new energy output characteristics, and determining a typical operation scene and an operation mode of the pumped storage power station; establishing a scheduling model which takes quality improvement and efficiency improvement as an optimization objective function and takes power generation and pumping power of the pumped storage power station as decision variables; and according to the equivalent load typical historical scene and the prediction scene, an intelligent evolutionary algorithm is adopted to optimize the power generation and pumping scheduling process of the pumped storage power station, and a scheduling scheme capable of improving quality and efficiency is compiled. According to the method, the operation scene of the pumped storage power station can be accurately extracted, the new energy grid-connected impact can be reduced while considerable economic benefits are brought, and technical support is provided for promoting new energy development and utilization and power system transformation.

The invention discloses a coordinate system transformation fusion filtering tracking method and system for a dual-base-station radar, and relates to the technical field of radar target tracking. The method comprises the following steps: firstly, establishing a state and observation equation, and determining an initial state of a target based on prior information under Cartesian coordinates; then, obtaining a target motion state through one-step prediction, generating a sigma point by utilizing U transformation, and calculating a mean value and a covariance for constructing state space prediction; thirdly, fusing the measurement data and the prediction data by using a Kalman filter to obtain optimal state estimation and a covariance matrix; and finally, converting the updated state estimation back to the Cartesian coordinate system based on U transformation, and circulating the process until the tracking is finished. According to the method, the nonlinear filtering problem in the updating process can be avoided, and the tracking robustness and precision are improved.

The invention provides a method for quickly converting coordinate formats of mineral resource reserve databases in batches and related equipment. The method comprises the following steps: firstly, reading a mining area number and a registration classification number in a row coordinate record, and a character string in a mining area or mine range coordinate field and a character string in a calculation coordinate field from a coordinate management table; secondly, independently storing block coordinates in the two character strings by utilizing two one-dimensional arrays, and independently storing initial positions and inflection points of the block coordinates by utilizing two two-dimensional arrays; and finally, according to the information in the four arrays, in combination with an encoding rule of the character string, reading block coordinates from the corresponding arrays in sequence, forming a coordinate pair format, and writing the coordinate pair format into a corresponding text file, so that forward conversion from the coordinate string to the coordinate pair is realized. In addition, reverse conversion of coordinate pairs to coordinate strings is also provided. According to the invention, the coordinate pair data meeting the coordinate system transformation format requirement can be quickly realized and provided.

The invention relates to a sweeper path planning method, system and device suitable for a complex environment and a medium. The method comprises the steps that a global map of a sweeping area is acquired, feature vertexes are determined to decompose the global map, and a structural sub-area and a special sub-area are generated; determining a starting point of the structure sub-region according to the feature vertex, and generating a first path covering the structure sub-region by adopting an internal spiral method based on the starting point; determining a non-linear constraint region of the special sub-region, converting the non-linear constraint region based on coordinate system transformation, and generating a second path of the special sub-region; and determining a starting point and a target point of any path, connecting the starting point and the target point based on an improved path search algorithm, and generating a target path of the cleaning area. Therefore, according to the invention, through accurate path planning and dynamic adaptability optimization, the path planning level and the completion quality of the sweeping operation are improved, so that the sweeping vehicle can adapt to the actual scene of a complex environment, and the application range is greatly expanded.

The invention discloses an information system existing interface-based AI large language model interaction method, which comprises the following steps of: constructing an interface operation feature set according to an information system operation log; identifying a service intention category and a function granularity level corresponding to the interface, and generating an interface function granularity identification table; constructing an action rule chain according to the interface service intention category and the function granularity level; performing field consistency calibration in combination with a field time sequence identifier, a stage identifier and a trigger point identifier to form standardized intermediate JSON data; according to the standardized intermediate JSON data, generating cue words including field operation instructions, business semantic instructions and time sequence background instructions; model request sending, model output result analysis and consistency verification are carried out through an existing API interface, and system state updating information is recorded. According to the method, the system transformation cost is reduced, the accuracy of interface semantic expression is improved, and an enforceable and extensible technical path is provided for intelligent upgrading of a traditional information system.

The invention relates to the technical field of numerical control machining, in particular to a five-axis drilling numerical control machine tool based on visual positioning and a machining method, and the five-axis drilling numerical control machine tool comprises a machine tool body, a numerical control system, a contact type measuring head, a visual system and a calculation control unit. Coordinates of at least three non-collinear reference features on a workpiece in a machine tool coordinate system are automatically collected through a contact type measuring head, the deviation between the workpiece coordinate system and the machine tool coordinate system is automatically calculated through a coordinate system transformation algorithm, and after the workpiece coordinate system is established, a visual system is moved to the position above each programming hole site to shoot actual marks, and the workpiece coordinate system is calculated. According to the method, actual hole center coordinates are extracted through image recognition and compared with theoretical coordinates, and finally, deviation calculation and machining decision are carried out by integrating measuring head data, visual images, numerical control programs and tolerance parameters, so that through the automatic process integrating measurement, recognition, comparison and decision making, the machining precision is improved, and the machining precision is improved. The technical problems of manual errors and lack of verification before processing are effectively solved.

The invention discloses an automatic detection method for three-dimensional information of a segment steel mold. The automatic detection method comprises the following steps: S1, constructing a detection device and a system; s2, establishing a movable axis coordinate system Q; S3, calibrating a coordinate system relation; s4, confirming a coordinate system transformation relation between the structured light 3D camera and the tracker; s5, the optical tracker identifies and captures the position information of the self-luminous tracker; s6, a teaching detection step: enabling the structured light 3D camera to collect 3D point cloud information of the detection area; s7, a system automatic detection step; and S8, collecting the point cloud data of all the detection areas, and converting the point cloud data into an optical tracker coordinate system to obtain global point cloud data of the segment steel mold. And according to the global point cloud data of the segment steel mold, analyzing vertex position information, line segment position information and plane position information of the detection area, and according to an analysis result, outputting a detection report of the segment steel mold. Three-dimensional information of the inner cavity of the large-size steel mold is automatically collected and detected, and field installation and maintenance are facilitated.

The invention provides a comprehensive anomaly recognition and fault-tolerant control method based on current sensor fault modeling, offset coordinate system transformation, a full-order sliding-mode observer and current space vector error projection, which comprises an innovative algorithm for accurately modeling and classifying various typical faults and carrying out fault detection and positioning by using the models. Based on a current sensor fault detection strategy of an offset coordinate system, through specific Clark transformation and coordinate offset, in combination with current residual amplitude reconstruction and hysteresis comparison, a reconstruction error is obtained through reconstruction of a current space vector error and projection, a sliding mode surface is formed by the reconstruction error and a measurement error, and accurate reconstruction of fault phase current is achieved. According to the method, various fault types and positions thereof can be accurately identified, the faults can be more accurately positioned, and the accuracy of fault detection is improved. When the current sensor breaks down, fault phase current can be effectively reconstructed, stable operation of the system is guaranteed, and better dynamic performance and control precision are achieved.

The invention provides a robot fault data generation method and system based on sample simulation transfer learning, and the method comprises the steps: evaluating the similarity between experiment action curves of two robots through KL divergence based on source domain data and target domain data, selecting a next action most likely to enable the motion response curves of the two robots to be similar for each current pose; a system transformation network is constructed and trained, fault sample currents obtained by an experimental robot are all converted into fault samples of a target robot based on the trained system transformation network, and a virtual fault data set of a target domain is generated to train a fault diagnosis algorithm. Aiming at the difficulty that a fault sample cannot be prepared for a deployed normal fault-free robot in the field of industrial robots, sample data can be obtained for a robot which is in service but has no fault sample by utilizing abundant healthy samples, so that any fault diagnosis algorithm is supported.

The invention relates to the technical field of material pile boundary detection, and particularly discloses an automatic material pile boundary detection system and method for an unattended bucket-wheel stacker-reclaimer. Radar equipment is used for scanning a target material pile to obtain point cloud data of the target material pile, and after coordinate system transformation and filtering processing are carried out on the point cloud data, the target material pile boundary is detected; carrying out local window-based geometric feature extraction on the preprocessed point cloud data by adopting a deep learning algorithm so as to mine local shape information of the target material pile, and carrying out core information-based aggregation analysis on geometric features of the target material pile under each local window; the global shape features and boundary information of the target material pile are captured, and automatic detection of the boundary of the target material pile is achieved through the semantic segmentation technology. By means of the mode, the defects of a traditional radar data processing mode can be overcome, accurate detection of material pile boundary information is achieved, and powerful support is provided for automatic operation of the bucket-wheel stacker reclaimer.

The invention discloses a marker-assisted visual positioning method and system for assisting cooperative management and control of a smart tunnel. The method comprises the following steps: acquiring an image; measuring a marker in the image and calculating a coordinate system transformation matrix; and based on the coordinate system transformation matrix, carrying out spatial positioning on the target vehicle in the image. The system comprises an image acquisition module, a matrix calculation module and a positioning module. According to the invention, space positioning can be realized at a low cost in a scene with poor signals. The method can be widely applied to the field of space positioning.

The invention relates to the field of BIM model visualization, in particular to a BIM design terrain and GIS live-action texture fusion method, BIM design terrain and GIS live-action texture data are processed respectively, when GIS live-action texture data changes, data updating can be achieved only by replacing slice data, and the convenience of data updating is improved; according to the method, the relation between the image slice nodes of the GIS live-action texture data and the space coordinates of the BIM design terrain is established through the coordinate system transformation matrix, so that coordinate transformation between the image slice nodes and the space coordinates of the BIM design terrain is facilitated, the space coordinates of the BIM design terrain correspond to the texture coordinates of the GIS live-action texture data, and finally fusion of the BIM design terrain and the GIS live-action texture data is realized.

The invention provides an interactive multi-model infrared time-sensitive target tracking method fusing image features, aiming at solving the problem that the motion state of a ground target is difficult to determine due to rigid motion generated by an airborne camera influenced by air flow and strong maneuverability of the ground target in infrared target tracking in an air-ground scene. According to the method, under the framework of Kalman filtering, a target detection result is used as a state observer, inter-frame registration is introduced to compensate for errors caused by coordinate system transformation due to shaking of an airborne platform, strong maneuverability of a ground moving target is represented by interactive multiple models, and finally, the moving target is accurately tracked through data association. The tracking method provided by the invention is low in complexity, can well adapt to a complex environment of air-ground imaging, and has important engineering significance, and the tracking precision is not influenced by the precision of a target detection result.

The invention provides a robot anti-collision method and device and a robot control system, and the method comprises the steps: building a workpiece coordinate system, and constructing a robot working space under the workpiece coordinate system; acquiring a first pose of a tool tail end of the robot moving to a target point of a working space of the robot; a second pose is obtained through calculation according to the first pose and a first coordinate system transformation matrix, the second pose is the pose of the tool tail end in a robot base coordinate system, and the first coordinate system transformation matrix is a matrix for coordinate transformation between a workpiece coordinate system and the robot base coordinate system; according to the second pose, a bounding box of each joint connecting rod and a tool of the robot under a robot base coordinate system is calculated, a plurality of base coordinate bounding boxes are obtained, the bounding boxes are minimum cuboids wrapping joint parts, and the joint parts comprise the joint connecting rods and the tools; whether the joint pieces corresponding to the multiple base coordinate bounding boxes collide or not is determined through the separation axis theorem, and the problem that the anti-collision cost is high through the three-dimensional vision technology is solved.

A storage method and platform for three-dimensional motion data belongs to the technical field of motion data storage, and comprises the following steps: segmenting acquired three-dimensional motion data, performing a plurality of cardinal number counting system transformations on the segmented three-dimensional motion data, and synchronously performing modulation of different methods according to cardinal number counts acquired after the transformations. Then, transmission analysis is executed on the modulated segmentation sections, re-segmentation processing is executed on the segmentation sections according to transmission time consumption, simulation section forming is synchronously executed on the re-segmented data sections, aggregation transmission is executed on the data sections, the reliability in the three-dimensional motion data transmission period is improved, and when storage is executed on the three-dimensional motion data, the three-dimensional motion data can be stored and stored in the three-dimensional motion data transmission period, so that the reliability of the three-dimensional motion data transmission period is improved. By performing a benchmark analysis on the form of the three-dimensional motion data to reduce the entire stored area, the synchronized may be suitable for subsequent selection of the three-dimensional motion data.

The invention provides a multi-sensor obstacle avoidance control method and system for a fan blade inspection robot, and the method comprises the steps: carrying out the preliminary target detection through employing an RGB camera, and rapidly obtaining the visual information of a candidate obstacle; performing motion distortion correction and coordinate system transformation on the visual candidate targets by using accurate point cloud data of the laser radar, and performing cross-modal association and threat verification so as to effectively fuse visual semantic information and geometric accuracy of the laser radar and ensure accurate identification and three-dimensional space state acquisition of a threat object; further, state estimation and trajectory prediction are carried out on the verified threat object so as to deal with the uncertainty of a dynamic obstacle motion mode; and finally, accurately evaluating the collision risk based on the predicted trajectory and the planned trajectory of the unmanned aerial vehicle, quickly generating an avoidance decision containing the optimal direction and speed vector, and sending a final rotating speed instruction to an unmanned aerial vehicle motor to realize physical avoidance. In this way, the pre-judgment capability of the system on the potential collision risk is remarkably improved.

Provided are a jamming signal generation method and system. The method includes receiving a synthetic aperture radar (SAR) transmission signal by an SAR, determining a first form and position of a noise patch in a predefined coordinate system, transforming the predefined coordinate system into an SAR image formation plane (IFP) coordinate system, based on a coordinate system transformation function, determining a second form and position transformed from the first form and position of the noise patch in an SAR image using the SAR IFP coordinate system, generating a first reflectivity map model, based on the second form and position of the noise patch, generating a second reflectivity map model by performing two-dimensional fast Fourier transformation on the first reflectivity map model, and generating an SAR jamming signal based on a convolutional product of the second reflectivity map model and a reference signal.

The invention provides a multi-view autonomous cooperative positioning method and system. The method comprises the following steps: determining a plurality of local maps and a plurality of key frame information of an environment where a plurality of agents are located based on a preset synchronous positioning and mapping algorithm; the plurality of intelligent agents are used for acquiring local environment information of multiple viewpoints from different positions and visual angles through carried visual sensors; the multi-view local environment information corresponds to a plurality of local maps and a plurality of key frame information; determining a constraint relationship among the plurality of local maps according to the information of the plurality of key frames, and determining a local map coordinate system transformation matrix according to the constraint relationship; the constraint relation comprises pose constraints of adjacent key frames; and fusing the plurality of local maps according to the local map coordinate system transformation matrix to obtain a global map, and determining global positioning information according to the global map. The method can adapt to a complex environment, and realizes high-precision and high-robustness unmanned aerial vehicle cluster positioning.

The invention discloses a non-intrusive stock data encryption method and device, equipment and a storage medium, and relates to the field of data processing. Performing static analysis on a program in the static analysis engine through a reflection scanning technology, and determining a target field for processing stock data in the database; periodically querying and extracting stock data from the database, and carrying out slicing processing; performing plaintext judgment on the slice data by utilizing a dynamic detection method and a judgment rule; the dynamic detection method is determined based on a coding mode of preorder encryption; and performing transactional encryption processing on the recognized plaintext data according to the target encryption algorithm and the matched target field, and then storing the data back to the database. Target fields are automatically recognized through the reflection scanning technology, accurate plaintext judgment is achieved in combination with dynamic detection and a rule engine, data consistency is guaranteed through transactional encryption processing, and the method has the advantages that stock plaintext data are automatically recognized and encrypted, the system transformation risk is avoided, and the plaintext judgment accuracy is improved.

The invention provides a system, a method and a device for monitoring the operation state of production equipment. The method comprises the following steps: determining total operation time data of the production equipment based on a startup signal; receiving production data pushed by production software corresponding to the production equipment; capturing an interface image of the production software, and generating a production state identifier and actual production time data of the production equipment after image recognition; calculating and generating estimated power consumption data; generating a state data packet with a uniform format and sending the state data packet to the MES subsystem; and outputting an equipment operation state report, an energy efficiency evaluation chart and a historical data query result according to the state data packet. According to the invention, equipment data acquisition is realized in a pure software mode, two modes of API docking and image recognition are supported to be compatible with new and old equipment, comprehensive, real-time and accurate equipment state data are provided for an MES system in combination with intelligent energy consumption estimation and a flexible network transmission strategy, the system reconstruction cost and complexity are significantly reduced, and the system reliability is improved. And the intelligent level of production management is improved.