1692 results about "Design data" patented technology

The invention relates to a building design scheme multi-objective optimization comparison and selection method and device, equipment and a medium. The method comprises the steps of generating a multi-dimensional design parameter set by obtaining building information model data and parameterized design data; performing multi-dimensional target analysis and evaluation by using a multi-field joint simulation platform to generate a multi-dimensional evaluation index; a dynamic multi-objective optimization model is constructed through a dynamic weight adaptive algorithm in combination with project stage demands and user interaction data; carrying out iterative optimization by adopting an improved non-dominated sorting genetic algorithm to obtain an optimized design scheme gene sequence result, and introducing a spatial topology connectivity constraint to generate a Pareto optimal solution set; and according to the Pareto optimal solution set, generating an optimization scheme through user weight adjustment and scheme screening. According to the method, the optimal design scheme set meeting the project requirements can be quickly and efficiently generated and screened out, the project stage requirements and user preferences are met, and the design efficiency and the scheme quality are improved.

The invention relates to the technical field of digital quality management, in particular to a light-weight glass bottle quality digital traceability method and system. The method comprises the following steps: acquiring glass bottle design data, and constructing a lightweight glass bottle model; detecting the structural strength of the bottle body based on the lightweight glass bottle model; carrying out bottle body surface defect detection based on the bottle body structural strength to generate bottle body surface defect data; performing defect tracing based on the bottle body surface defect data to obtain bottle body production defect process data; carrying out wall thickness non-uniformity anomaly detection based on the structural strength of the bottle body to obtain wall thickness non-uniformity data; the alignment offset of the mold core and the mold cavity is evaluated based on the wall thickness non-uniformity data; and carrying out positioning pin fracture detection according to the alignment offset of the mold core and the mold cavity to obtain positioning pin fracture data. The glass bottle production process is optimized based on the digital quality management technology, and the quality recognition rate, the abnormal response speed and the production process transparency are effectively improved.

The invention provides a while-drilling formation pressure early warning method and device based on model prediction, equipment and a medium, and relates to the technical field of low-carbon mining, and the method comprises the steps: in a pre-drilling stage, based on seismic data, adjacent well historical data and design data, analyzing and generating prediction risk data of a target monitoring well; in the drilling process, actual formation pressure data are calculated in real time by using drilling data collected for a target monitoring well in real time, and the actual formation pressure data are compared with the predicted risk data; in the drilling stage, a pressure safety window is depicted based on the predicted risk data, the cycle equivalent density of the target monitoring well calculated in real time is compared with the safety window, and the drilling safety risk is recognized and analyzed; and after drilling is finished, summarizing the predicted risk data, the actual formation pressure data and the drilling safety risk, and updating and iterating the model algorithm through the summarized data. The method has the effect of improving the accuracy of formation pressure early warning while drilling in the petroleum drilling process.

The invention discloses a multi-modal knowledge-based automotive body innovative design system, which comprises a multi-modal data fusion module, a multi-modal data fusion module, a multi-modal data fusion module, a multi-modal data fusion module and a multi-modal data fusion module, wherein the multi-modal data fusion module is used for receiving text data, picture data, a three-dimensional CAD (Computer Aided Design) model file and an engineering symbol expression from an automotive body design process and is used for carrying out feature extraction and semantic alignment on input data of four modals; generating a unified semantic vector representation; the cross-modal knowledge mining and graph construction module is used for extracting multi-level entities and relationships from the unified semantic vector and constructing a dynamically weighted multi-modal knowledge graph; the large-model-driven multi-hop collaborative reasoning module is used for analyzing the multi-modal design requirement of a user, carrying out multi-hop reasoning on a knowledge graph, and outputting design parameter recommendation and an interpretable reasoning chain. The method aims at breaking through the limitation of an existing design system in the aspects of multi-modal processing and shallow semantic understanding, and deep fusion and intelligent application of multi-source heterogeneous design data are achieved.

The invention relates to the technical field of underground power tunnel design data processing, in particular to an automatic reinforcement design method based on an instantiation reference algorithm, which comprises the following steps: constructing a multi-level parameterized model, orthogonally classifying structure types and shapes, and associating geometric features, mechanical attributes and reinforcement rules for each type of structure to form a structured database. A geometric boundary of the special-shaped structure is defined by adopting a B spline curve or an NURBS curved surface, and dynamic association with a reinforcement rule base is achieved through a topological relation mapping module. The instantiation reference algorithm calls a reinforcement template library according to load conditions, and optimizes the diameter, spacing and reinforcement ratio of reinforcements in combination with an elastic mechanics principle to generate an initial scheme. And generating a standard drawing and a synchronous statistical table through a CAD conversion model. According to the method, diversified special-shaped structure reinforcement design is supported, and a whole-process closed loop of parametric modeling, dynamic rule expansion and construction data delivery is realized.

The invention discloses an automobile wire harness process rule automatic matching method based on a knowledge graph, and the method comprises the following steps: collecting wire harness design data, and carrying out the standardization processing; analyzing the process rule base, extracting key attribute fields and generating a process rule metadata set; semantic modeling and structured fusion are carried out, and a process knowledge graph is constructed; performing semantic association analysis, causal constraint fusion and feasibility judgment processing by utilizing a semantic retrieval enhancement module; carrying out provable retrieval, risk assessment and conflict resolution based on the candidate process rule set; converting the target process rule set into a process instruction, and driving a design system to perform synchronous updating and rule labeling; and updating the process knowledge graph based on system feedback data, and outputting an optimized process verification report and updating a design version. The method is based on the knowledge graph and the semantic causal fusion technology, intelligent matching of the wire harness process rules is achieved, and the method has the advantages of being high in matching precision, high in interpretability and capable of achieving self-adaptive optimization.

The present invention provides a method for producing a dental restoration for preferably at least a part of at least one tooth. The method comprises the step of obtaining design data, wherein the design data includes acquired data and preliminary design data of the dental restoration. The method further comprises the step of modifying the preliminary design data before at least one manufacturing step to obtain modified design data and producing the dental restoration based on the modified design data.

The invention provides an acquisition and analysis method and system for 3D printing tool clamp data based on big data, and relates to the technical field of 3D printing and intelligent manufacturing, and the method comprises the steps: obtaining a clamp historical design scheme, machining parameters and sensor data, carrying out the feature extraction and data cleaning, and forming structured data; then, the design intention is analyzed based on a BERT-CNN model, and a clamp applicability classification database is constructed in combination with the classification model; and then, generating a lightweight clamp structure by adopting a generative adversarial network and topological optimization, and optimizing the topological structure of the lightweight clamp structure through an optimization model. Thirdly, simulation analysis is carried out, stress, deformation and thermal stress are evaluated, errors are optimized based on simulation parameters, and optimized clamp design data are obtained; and finally, the clamp is manufactured, stress data are collected in real time, and machining process parameters are optimized through dynamic analysis. According to the method, clamp design and manufacturing are optimized through data driving, and design efficiency and clamp performance are improved.

The invention relates to the technical field of mechanical engineering, in particular to a three-dimensional simulation design method and system based on an elevator structure. The method comprises the following steps that an elevator structure drawing is obtained; a three-dimensional elevator assembly is constructed according to the elevator structure drawing; lift car static load simulation is conducted according to the three-dimensional elevator assembly, and lift car static load data are obtained; detecting the structural strength of the lift car based on the lift car static load data; evaluating welding defects based on the structural strength of the lift car, and generating welding defect data; identifying a weld weak area according to the welding defect data; determining the abrasion loss of the car structure based on the weld weak area; according to the lift car structure abrasion loss, the lift car bottom plate fracture risk is predicted; carrying out welding optimization design based on the fracture risk of the bottom plate of the lift car to obtain welding optimization design data; and traction and traction simulation is conducted according to the three-dimensional elevator assembly, and traction and traction data are obtained. Based on the mechanical engineering technology, the safety and stability of the elevator structure are improved, and the design precision and efficiency are remarkably improved.

The invention relates to the technical field of quality inspection, in particular to a complex steel structure construction quality detection method and system based on three-dimensional laser scanning, and the method comprises the steps: obtaining three-dimensional laser scanning data and corresponding design data of a steel member in a machining quality detection stage, a virtual pre-assembly stage and an on-site actual assembly stage of the steel member; preprocessing the obtained three-dimensional laser scanning data to obtain point cloud data corresponding to a real object, constructing the obtained design data into a BIM model and converting the BIM model into point cloud data corresponding to the model, carrying out point cloud registration on the two parts of data through a registration algorithm, obtaining an error between the two parts of data through comparison, and obtaining the point cloud data of the real object according to the obtained error information. And determining the actual quality of the steel member.

The invention discloses an underground pipe network construction drawing generation and verification method and system based on image recognition, relates to the technical field of construction drawing verification analysis, and solves the technical problem that in the verification process, detection of pipe network element integrity and space conflicts is not comprehensive and efficient enough. According to the method, extracted pipe network element data is compared with original design data element by element, verification is carried out from element types, number, attributes and other dimensions, whether a construction drawing is complete or not can be rapidly and accurately judged, missing or wrong elements can be found in time, and a minimum rectangular bounding box and a three-dimensional projection overlapping judgment algorithm are utilized to judge whether the construction drawing is complete or not. According to the method, the space conflicts among the pipe network elements can be efficiently detected, the conflict detection efficiency and accuracy are improved, the overlapped elements are classified according to the elastic modulus of the element material, the hard and non-hard overlapped elements are subjected to targeted analysis, whether design conflicts exist or not can be judged, and a more scientific basis is provided for design optimization.

The invention discloses a robot operation object positioning method and system, and relates to the image processing related technical field, and the method comprises the steps: building a three-dimensional point cloud data set based on laser scanning and design data, and enabling the three-dimensional point cloud data set to be marked with key features; activating a positioning camera of the robot, executing operation scene image acquisition, and establishing a scene image; carrying out contour matching identification on the RGB image according to the workpiece features, establishing a matching identification result, and calling a mapping depth image; executing search matching of the key features, and establishing a search matching result; local point cloud region fusion matching is executed, and a spatial registration result is established; and resolving attitude parameters of the target workpiece in the three-dimensional point cloud data set, and completing positioning based on a resolving result. The technical problems of poor adaptability and insufficient positioning precision of robot operation object positioning in a complex environment in the prior art are solved, and the technical effects of realizing high-precision positioning of the operation object and improving the positioning real-time performance and reliability are achieved.

The invention provides a mechanical correction optimization method and device for steel structure welding and electronic equipment, and relates to the technical field of steel structure welding.The mechanical correction optimization method for steel structure welding comprises the steps that a steel structure deformation model is obtained through preset simulation software according to obtained design data and welding parameters of a steel structure; based on the steel structure deformation model, a mechanical correction model of the steel structure is established according to the obtained mechanical correction process data; and the mechanical correction model is optimized through mechanical correction simulation, optimized mechanical correction process data are obtained, and the optimized mechanical correction process data are used for conducting mechanical correction on the welded steel structure. According to the method, the mechanical correction process data are optimized through modeling, then the correction process is controlled according to the optimized mechanical correction process data, welding residual stress and deformation are effectively reduced, the alignment precision and the overall performance of a welded joint are improved, and therefore the welding quality is improved.

The invention discloses a gas compressor blade mean camber line design method, a gas compressor blade, a gas compressor and an aero-engine, and the method comprises the steps: S1, obtaining known design data, including an inlet blade angle theta in, an outlet blade angle theta out, a mean camber line starting point coordinate, a mean camber line end point abscissa, and turning angles delta theta 1, delta theta 2 and delta theta 4 of a first section arc, a second section arc and a fourth section arc, and abscissas of all tangency points; and S2, each section of arc is calculated through a geometric analysis method, a mean camber line is constructed after circle center coordinates, arc radiuses and tangent point coordinates of each section of arc are calculated, and the mean camber line is formed by sequentially and tangentially connecting four sections of arcs according to the sequence of convex, concave, convex and concave. The gas compressor blade mean camber line design method is good in adaptability and multiple in controllable point in the high Mach number state; therefore, the requirements of an advanced compressor are met; design parameters are greatly reduced, the optimizing period is greatly shortened, the adjusting efficiency is high, and the time is short.

The invention relates to the field of artificial intelligence, in particular to an intelligent standard knowledge retrieval system based on an AI large model, which comprises a standard knowledge management database, a multi-source acquisition preprocessing module, a semantic understanding and indexing module, an intelligent retrieval engine module, a knowledge enhancement module, a user interaction feedback module, a security control module and a deployment expansion module. The standard knowledge management database is used for storing standard knowledge design data, real-time retrieval data and feedback data and constructing a dynamically updated standard knowledge resource pool; through the multi-source standard knowledge acquisition and preprocessing module, multi-channel objective standard data can be integrated and dynamically updated, and the problem of knowledge fragmentation is solved; and through the semantic understanding and indexing module, industry professional semantic accurate matching is realized, the limitation of traditional keyword retrieval is broken through, and the accuracy and efficiency of standard knowledge retrieval are remarkably improved.

The invention discloses a surrounding rock dynamic response calculation and evaluation method under hard rock tunnel blasting excavation. The calculation method comprises the following steps: S1, obtaining tunnel design data and geological section information; s2, acquiring physical and mechanical parameters; s3, blasting parameters are obtained; s4, constructing a three-dimensional hard rock tunnel blasting excavation grid model according to the tunnel design data and the geological section information obtained in the step S1; s5, importing the three-dimensional tunnel blasting excavation grid model, blasting parameters and physical and mechanical parameters into finite difference software; s6, analyzing and calculating the three-dimensional tunnel blasting excavation grid model through a dynamic calculation module built in finite difference software to obtain surrounding rock dynamic response data under blasting excavation; and S7, comparing and analyzing the dynamic response data of the surrounding rock under blasting excavation with a safety evaluation threshold value. According to the method, the comprehensiveness and the accuracy of tunnel surrounding rock dynamic response evaluation under blasting excavation are improved aiming at the defects of an existing method and actual application requirements.

The invention relates to the technical field of transformer simulation, in particular to a simulation system and method for a temperature rise field of a dry-type transformer. The method comprises the following steps: acquiring geometric parameters of an iron core lamination of the dry-type transformer to be simulated, spatial arrangement information of a winding and a positioning relation of an insulating component to form structural design data; the method comprises the following steps: constructing three-dimensional geometric modeling data based on structural design data, importing the three-dimensional geometric modeling data into a finite element electromagnetic simulation platform, setting a power-on condition of an excitation winding, and applying rated current or voltage, so as to obtain local magnetic flux density distribution data at each iron core lamination position in a whole operation period. According to the method, on the basis of three-dimensional structure data, three physical processes of an electromagnetic field, a thermal field and a fluid field are fused, a high-precision local heat source model and a dynamic temperature rise prediction model are constructed, and geometry-material-boundary all-parameter modeling is achieved from the whole structure of an iron core lamination, a winding and an insulation assembly.

The invention relates to the technical field of data processing, in particular to a product package online design display method and system. The method comprises the following steps of obtaining packaging target product data and determining the outer contour of a product, reconstructing a simulation to-be-packaged product frame, obtaining a packaging leakproofness requirement and estimating a packaging use scene, generating packaging process constraint data, analyzing entity packaging constraints, and fusing the packaging constraint data to support packaging process simulation. The method comprises the following steps: generating simulated product packaging data, constructing a packaging demand reverse environment field according to a leakproofness demand, carrying out leakproofness re-measurement on the simulated product packaging data, generating packaging design leakproofness data, carrying out packaging backtracking optimization through the data, finally obtaining qualified product packaging design data, and carrying out online visual display. According to the invention, efficient and intelligent product package online design and display are realized.

The invention provides a helicopter flight parameter prediction method, system and device and a storage medium, and belongs to the field of helicopter performance prediction.The method comprises the steps that a helicopter and engine integrated performance model set is established; acquiring historical data including flight parameters of a helicopter, operation parameters of an engine and environmental parameters under different flight conditions and states; fitting undetermined coefficients of the helicopter and engine integrated performance model group by combining historical data with specific design data of a helicopter and an engine to obtain model coefficients conforming to specific helicopter and engine models; representing a to-be-predicted flight mission as a flight mission profile containing input parameters, substituting the input parameters of the flight mission profile into the helicopter and engine integrated performance model group with the determined coefficients, and solving the model to obtain predicted flight parameters. According to the method, reliable prediction of flight parameters of the helicopter in different flight environments can be realized, and a basis is provided for engine design, modification and use optimization.

The invention relates to the technical field of cable aging diagnosis, in particular to a cable aging diagnosis monitoring method and system. The method comprises the following steps: acquiring cable operation log data and cable internal structure design data, extracting a cable structure distribution condition in combination with an operation log, and evaluating cable operation state data; electric power sudden demand characteristics are identified, and then a non-uniform thermal coupling unbalance state is determined; based on the thermal coupling unbalance and the operation state data, detecting the coupling failure condition of the cable multilayer structure, and further judging the structural integrity damage condition; deducing a load stability disintegration situation according to a structure damage and insulation strength reduction trend; further detecting the decline of the quality of transmitted electric energy, analyzing the increase degree of abnormal voltage fluctuation, and identifying the fatigue trend of the metal material of the cable; through the above cable aging diagnosis, the cable aging diagnosis data is output. According to the cable aging diagnosis method and device, cable aging diagnosis is diagnosed, so that cable aging diagnosis is more accurate and efficient.

The invention relates to the technical field of green low carbon and the technical field of structural design, and discloses a design method and device of a prefabricated composite wall, electronic equipment and a storage medium, and the method comprises the following steps: obtaining mechanical data, construction data and cost data of the prefabricated composite wall; according to the mechanical data and a preset mechanical evaluation model, the flexural capacity of the prefabricated composite wall is generated; according to the construction data and a preset carbon emission evaluation model, the total carbon emission amount of the prefabricated composite wall is generated; according to the cost data and a preset cost evaluation model, the total cost of the prefabricated composite wall is generated; and when the flexural capacity of the prefabricated laminated wall is greater than the flexural capacity demand value, generating a collaborative efficiency coefficient of the design data of the prefabricated laminated wall according to the flexural capacity of the prefabricated laminated wall, the total cost of the prefabricated laminated wall, the total carbon emission amount of the prefabricated laminated wall and a preset collaborative efficiency model. According to the method, the collaborative effect of the prefabricated laminated wall design data can be quantified.

The invention belongs to the field of intelligent manufacturing, and particularly relates to an intelligent scheduling method for collaborative manufacturing of tunnel boring machines, in the method, multi-source heterogeneous data including design data, process data, production data, material data and the like are acquired, and a rich data basis is provided for intelligent scheduling. The data fusion method based on the ontology is adopted, and the problems of semantic heterogeneity and structural heterogeneity of multi-source heterogeneous data are effectively solved. By constructing the tunnel boring machine manufacturing field ontology model, semantic association and sharing of data from different sources are realized, and the availability and understandability of the data are improved. An algorithm combining mixed integer programming and deep reinforcement learning is provided for intelligent scheduling of tunnel boring machine collaborative manufacturing. A robust optimization method is introduced to enhance the robustness of the scheduling scheme, and the influence of uncertain factors such as raw material supply and equipment maintenance in the manufacturing process of the tunnel boring machine is considered.

The present invention discloses a method for predicting the static behavior of a bridge based on dynamic loading, comprising the following steps: establishing a full-bridge structural analysis model according to the design data of the existing bridge; conducting dynamic loading tests on the existing bridge to obtain the bridge dynamic response values; performing sensitivity analysis on each design parameter in the initial structural analysis model to obtain and determine the key design parameters to be corrected that affect the bridge structure; based on the uniform design sampling method, using machine learning intelligent algorithms, constructing training samples of the key design parameters to be corrected and establishing a surrogate prediction model; correcting the initial structural analysis model using the prediction results of machine learning and intelligent algorithms; predicting the static behavior of the bridge based on the corrected structural analysis model; introducing an error analysis method to evaluate the prediction results of the bridge static force. The beneficial effects of the present invention are: reducing the cost of the bridge static load test, reducing the damage to the bridge's own structure, and having high prediction result accuracy.

The invention discloses a generation method of a generative adversarial network for planning a resource design stylized layout, and belongs to the technical field of artificial intelligence and machine learning, and the method comprises the following steps: S1, multi-source data collection: widely collecting a large number of existing planning resource samples; s2, data classification labeling; s3, constructing a generative adversarial network model; s4, performing model training; s5, style migration training; s6, optimizing the model; s7, generating a planning resource scheme; s8, optimizing the scheme; and S9, performing feedback iteration. According to the method, through integrating a technical path of multi-source design data acquisition, deep style feature extraction and generative adversarial network collaborative optimization, full-process automation from user demand input to high-quality planning resource layout generation is realized, and user personalized demands are met through a multi-scheme candidate and interactive adjustment function; and finally, constructing an incremental learning closed loop based on user feedback data, and continuously updating model parameters to adapt to an emerging design trend and an industry specification.

The embodiment of the invention provides a turning and milling combined machining deformation control method and system for a special-shaped part, and is used for the technical field of numerical control machining. The turning and milling combined machining deformation control method for the special-shaped part comprises the steps that structural feature analysis and process association marking are conducted on design data of the special-shaped part to generate a feature association data set, and clamping and process planning are conducted according to a machining constraint database and the feature association data set to generate initial turning and milling combined machining process data; cutting parameter multi-objective optimization solution is carried out on the initial turning-milling combined machining process data to obtain a turning-milling cutting parameter set, and multi-axis linkage analysis and instruction collaborative planning are carried out on the turning-milling cutting parameter set according to the equipment operation feature set to generate a combined machining control instruction set. According to the method, through part key feature recognition and risk marking, combined machining control instructions are generated after layered digital twinning verification in combination with process multi-objective optimization, and the one-time qualified rate of special-shaped part machining and turn-milling combined machining process stability are improved.

A system and a method for generating an optimized power converter design based on one or more multimodal large language models (MLLMs) are disclosed. The system obtains structured design data, one or more user queries, one or more design parameters, and real-time power converter design data. The system performs a similarity matching between one or more embeddings associated with the structured design data, and the one or more user queries and the one or more design parameters to compute an utmost similarity score. The system retrieves one or more similar document chunks. The system processes the one or more user queries and the one or more design parameters to extract one or more parameters. The system determines one or more design workflows based on the one or more parameters. The system executes at least one design workflow. The system visualizes design outcomes, simulation results, and prediction results to a user.

The invention discloses a method for performing product fault root cause analysis based on a knowledge graph, which comprises the following steps: obtaining design data associated with a product, the design data comprising semi-structured data and / or non-structured data; production data associated with the product is obtained, and the production data comprises structured data; performing information extraction on the design data to obtain structured design data; performing knowledge fusion on knowledge generated based on the production data and the structured design data to construct a target knowledge graph; and executing a product fault root cause analysis task based on the target knowledge graph.

The invention discloses a dynamic hydrodynamic modeling and parameter intelligent identification method for sailing of a trailing suction dredger, and relates to the technical field of sailing of trailing suction dredgers. According to the hydrodynamic modeling and parameter intelligent identification method for the sailing dynamic state of the trailing suction hopper dredger, core data covering an operation manual, historical cases, ship design data and all-working-condition sailing data are systematically obtained, so that a comprehensive basis is provided for modeling; an MMG reference model parameter set is constructed in combination with a hydrostatic calculation book, all working condition data are fused to obtain an environment adaptive fusion model, model deviation is corrected through parameter compensation, real-time data are processed at high frequency and the model is dynamically optimized by means of an edge calculation unit, and a sliding window can be adjusted according to error feedback to accelerate convergence. It is ensured that the final model prediction error is smaller than a threshold value, reliable kinematics support is provided for intelligent operation such as ship autonomous collision avoidance and trajectory tracking, and dredging operation safety risks and energy losses are effectively reduced.

The present disclosure relates to an extended reality (XR)-based supervision assisting device, which finds a construction error by comparing a real design object photographed by a camera of the supervision assisting device with building information modelling (BIM) design data, and corrects the BIM design data to fit the real design object when the construction error between the real design object and the BIM design data exceeds a preset error tolerance range, thereby adjusting the BIM design data according to the construction error.

The invention relates to the technical field of photovoltaic modules, in particular to a photovoltaic module control method and device. The method comprises the following steps: obtaining an installation position according to design data of the photovoltaic module, carrying out illumination intensity change measurement, and further evaluating the luminous flux change of the photovoltaic module; on the basis of the luminous flux change data, calculating the generating capacity fluctuation of the photovoltaic module, further performing power quality attenuation evaluation, and extracting power grid transmission voltage fluctuation data; according to the power grid voltage fluctuation and power quality attenuation data, the battery overcharge condition and the battery life attenuation are evaluated, the battery capacity attenuation is further calculated, and the photovoltaic module system efficiency attenuation is evaluated; by analyzing system efficiency attenuation data, photovoltaic module degradation risk early warning is carried out, and risk early warning information is fed back to the terminal in real time; according to the invention, through early warning of power generation of the photovoltaic module, the deterioration prediction of the photovoltaic module is more accurate.