653results about How to "Avoid uncertainty" patented technology

The invention discloses an energy storage lithium battery life degradation prediction method and system, and the method comprises the steps: obtaining and preprocessing lithium battery operation data, constructing a time sequence, carrying out the normalization processing, and dividing a training set and a test set; based on the normalized data, constructing a multi-head self-attention mechanism MSA module with masks, capturing multiple features in the input data through different time windows, and extracting an important feature set through a feature fusion method after screening; based on the important feature set, key hyper-parameters are preliminarily set, and an MSA-LSTM comprehensive prediction model is constructed and used for processing time sequence data and predicting the service life of the battery; an artificial bee colony algorithm is adopted to optimize hyper-parameters of the MSA-LSTM comprehensive prediction model; and training the optimized MSA-LSTM comprehensive prediction model by using the training set, verifying and evaluating the prediction performance by using the test set, predicting unknown data by using the MSA-LSTM comprehensive prediction model, and calculating the remaining service life RUL of the energy storage lithium battery. And safety accidents caused by battery faults are prevented.

The invention provides a multi-core heterogeneous system-oriented startup deployment and cooperative processing method, which comprises the following steps of: when the system runs, obtaining startup codes after a master core and a slave core are electrified, respectively obtaining mirror image files of Linux and RTOS (Real Time Operating System) on the basis of synchronous running and storage partition, and running the mirror image files on the master core and the slave core after moving the mirror image files; and after the heterogeneous operating system is loaded, generating an interrupt signal based on inter-core interrupt and a corresponding register through a CLINT module in the main core, and realizing data communication between the main core and each slave core based on the interrupt signal and the shared memory. By means of the method, after the system is powered on, the multiple cores can synchronously run the starting codes, and time delay and uncertainty possibly caused by one-by-one starting of the single cores are avoided; communication and data transmission among multiple cores are realized through interruption and memory sharing, the synchronism and consistency of data are ensured, and misjudgment and decision errors caused by data delay and inconsistency are avoided, so that the real-time performance of the system is remarkably improved.

The invention discloses an active power distribution network two-stage island division method and system considering flexible resource support. The method comprises the following steps: establishing a first resource allocation model considering energy storage and controllable load, the first resource allocation model comprises energy storage battery charging and discharging upper and lower limit constraints, an energy storage battery degradation cost model, a controllable load model and a controllable load related user protocol; obtaining parameter data of a target power distribution system, wherein the parameter data comprises a line parameter, a load level, a load level, a network topology connection relationship, a system operation voltage level and branch current limitation, a system fault position, a reference voltage and a reference power initial value; and according to the parameter data, establishing a mathematical model for two-stage island power supply recovery based on a first resource allocation model. The method for solving the island is simple and convenient, the island recovery amount can achieve the optimal recovery effect, meanwhile, the search time is greatly shortened, the solving efficiency is higher, and the rapid power supply recovery capacity of the power distribution network is improved.

The invention discloses a quantitative scientific research project screening method based on patent situation analysis, and the method comprises the steps: obtaining patent data, and carrying out the vectorization of a patent text through a pre-trained Chine-BERT model; the method comprises the following steps: performing dimension reduction processing on patent text feature vectors by using a UMAP algorithm, performing clustering analysis on the feature vectors after dimension reduction by using a K-Means + + algorithm, identifying professional technical themes and technical effect themes, merging documents of the same clustering category into a text unit, calculating the importance of each word by using a TF-IDF algorithm, and extracting the feature vectors of the patent text by using the TF-IDF algorithm. Extracting a theme keyword of each cluster; and a technology-effect matrix is constructed based on a clustering result, and a quantitative screening result of the scientific research project is obtained through calculation of a technology life cycle, technology innovation evaluation and market competitiveness evaluation. The objective of the invention is to provide a comprehensive and efficient scientific research project screening method through an advanced semantic understanding patent clustering method, and help to rapidly screen scientific research projects.

The invention discloses an SNP (Single Nucleotide Polymorphism) molecular marker related to the testis size character of Hu sheep as well as a screening method and application of the SNP molecular marker, and belongs to the fields of genetic breeding and molecular biology. The marker is located in an intron region of a Hu sheep chromosome 3 LRRIQ1 gene and is remarkably related to the Hu sheep testis size character, and the accuracy and reliability of the SNP molecular marker are ensured through a scientific and rigorous screening method; according to the marker, Hu sheep individuals related to testis size characters can be rapidly and accurately screened out, the breeding efficiency and accuracy are improved, the breeding process is accelerated, the breeding cost is reduced, and the economic benefits are improved; the genetic diversity is protected, the accuracy of seminal fluid quality evaluation is improved, a powerful tool is provided for Hu sheep breeding work, and important basic data is also provided for researching a genetic mechanism of testis development and functions; the method can also be used as an auxiliary diagnosis tool to assist in identifying potential genetic defects or disease risks and promote progress and development of the breeding technology.

The invention discloses a multi-modal traffic flow prediction method based on multi-source data feature fusion. The method comprises the following steps: acquiring traffic data; dividing a training set and a test set according to the traffic data; constructing a traffic prediction model, and training the traffic prediction model by adopting the training set; verifying the traffic prediction model by using the test set; the traffic prediction model comprises a cloud image encoder used for carrying out feature extraction on cloud image data to obtain cloud image features; the space-time encoder is used for performing feature extraction on the space-time data to obtain space-time features; the fusion module is used for fusing the cloud image features and the spatial-temporal features to obtain fusion features; and carrying out addition operation on the cloud picture features, the spatial-temporal features and the fusion features, and inputting into a spatial-temporal decoder for prediction to obtain a final prediction result. According to the method, multi-azimuth and multi-dimensional information is fused, redundant information in the spatial-temporal feature extraction process is simplified, efficient and high-precision prediction is achieved, and the method can be widely applied to the technical field of traffic flow prediction.

The invention relates to an urban park physical examination evaluation system construction method based on a machine learning algorithm. The method comprises the following steps: S1) selecting an evaluation index set; s2) taking a park system, an urban comprehensive park, an urban community park and an urban micro-greenbelt collaborative group as evaluation scales, and selecting evaluation indexes from the evaluation index set; s3) acquiring specific data of evaluation indexes to form an index data set; s4) screening repeated indexes with complex collinear features in all index data sets by using a variance expansion coefficient; s5) clustering by using a K-medoids clustering algorithm, and S6) based on an SHAP machine learning algorithm, performing full sample analysis and outputting the importance degree of the index factors, and constructing an urban park physical examination assessment system based on the importance degree of the index factors.According to the method, subjectivity and uncertainty of a traditional assessment method can be avoided, the assessment efficiency is improved, and rapid updating can be performed.

The invention discloses an SSR (Simple Sequence Repeat) core primer combination and a kit for identifying a tea tree variety 'swan gooses 12' and application of the SSR core primer combination and the kit. According to the invention, three pairs of SSR core primers are screened by using an SSR fluorescence labeling detection technology, and the three pairs of SSR core primers can rapidly identify and detect the 'Yangou 12' from other tea tree varieties. The SSR core primer combination disclosed by the invention can be used for identifying the variety of the swan goose 12, the uncertainty of identification based on external morphological characteristics is overcome, the result is reliable and visual, the detection efficiency is high, the operation is simple and convenient, and meanwhile, the popularization, utilization and protection of the variety of the swan goose 12 are also facilitated.

The invention discloses a machine learning optimization method of a low-frequency sound absorption structure based on three-dimensional printing, and belongs to the technical field of artificial intelligence acoustics, the low-frequency sound absorption structure is prepared from a photosensitive resin material through photocuring three-dimensional printing, and comprises a side seam, an extension cavity, a circular through hole, a resonance cavity, a first partition plate, a second partition plate and a third partition plate, the method has good expansibility and can be adjusted according to different noise control requirements; through a machine learning optimization method, structure parameters can be quickly adjusted to cope with a noise control task on the premise of ensuring a small size, so that a remarkable sound absorption effect is obtained at a specific low-frequency band; according to the method, a machine learning method based on a multi-layer perceptron and a genetic algorithm is adopted, geometric parameters of the low-frequency sound absorption structure are optimized, simulation calculation is carried out by using a commercial finite element solver COMSOL Multiphysics, and the sound absorption performance of the structure is further verified and optimized.

The invention discloses a welding seam defect detection method and system based on WGOA-HHO improved YOLOv8, and relates to the technical field of deep learning, and the method comprises the following steps: receiving a welding seam image data set, employing a Canny edge detection algorithm to carry out the preprocessing of the welding seam image data set, and obtaining a preprocessed welding seam image data set; the preprocessed weld seam image data set is input into a pre-established YOLOv8 weld seam defect detection model for training, and based on a WGOA-HHO optimization algorithm, an Improved-YOLOv8 model is obtained through output; and acquiring a to-be-detected welding seam image, inputting the to-be-detected welding seam image into the Improved-YOLOv8 model, and outputting to obtain a welding seam defect detection result image.

The invention provides a credit management method and related equipment based on multi-temporal satellite remote sensing, and the method comprises the steps: determining a to-be-analyzed land parcel in response to a credit management instruction; acquiring a multi-temporal satellite remote sensing image of the land parcel to be analyzed; analyzing the multi-temporal satellite remote sensing image by using a preset image analysis system to obtain a normalized difference vegetation index (NDVI) sequence of the land parcel to be analyzed; determining crop species of the to-be-analyzed plot according to the NDVI sequence of the to-be-analyzed plot; inputting the NDVI sequence into a pre-constructed yield analysis model to obtain a crop yield prediction result of the crop variety; and carrying out credit granting on the credit granting object to which the to-be-analyzed land parcel belongs according to the crop yield prediction result of the crop type. By applying the method provided by the embodiment of the invention, the credit can be accurately granted to the customer.

The invention discloses an electronic plant air conditioner control method for setting PID parameters based on a fuzzy algorithm. The method comprises the steps that a design scheme is preliminarily determined according to plant design indexes, and a schematic diagram of a control system is planned; establishing a mathematical model; carrying out PLC control program design and configuration programming; designing a fuzzy controller; fuzzy design of input and output variables; defining an input and output membership function; establishing a fuzzy control table and rules; designing a system fuzzy reasoning algorithm; setting defuzzification output; designing a Simulink system control block diagram, and establishing a real-time control working space; and the communication between the MATLAB and the PLC is realized. According to the method, the control experience of a person is summarized into a group of conditional statements described qualitatively by utilizing a fuzzy logic function of Matlab software, and the conditional statements are quantified by utilizing a fuzzy set theory, so that the controller can accept the experience of the person, simulate an operation strategy of the person and overcome uncertain factors of the person, and the system has higher reliability.

The invention relates to the technical field of hemostatic clips, in particular to a chuck mechanism and a hemostatic clip. Aiming at the technical problem that the existing hemostatic clip has defects, the invention provides the chuck mechanism and the hemostatic clip, the structure of a clamping piece is improved, a three-way integrated hole is formed in the tail part of the clamping piece, and the integrated hole is matched and connected with a ball head of a metal wire, so that the clamping and closing of the clamping piece are controlled; and the mutual influence of the clamping and closing operation and the separation operation of the clamping pieces in the operation can be avoided by combining the control of the metal wire and the separation control between the metal wire and the clamping pieces. And moreover, through the design of the multi-stage locking part, the clamping piece can be locked under different clamping degrees, so that the clamping requirements under different conditions are met, and more excellent practicability and operation convenience are achieved.

The invention relates to the field of ocean energy development and utilization, in particular to a tidal current energy array field site selection method based on a three-dimensional high-precision numerical model, which comprises the following steps: (1) a macroscopic site selection method; (2) a microscopic site selection method; (3) establishing a high-precision layered three-dimensional numerical model; (4) a tidal current energy resource refined evaluation method; analyzing a model calculation result, analyzing tidal current properties such as a large tide rising and falling moment, a small tide rising and falling moment, tidal current stability, energy flow density, theoretical reserve of tidal current energy resources, single-width energy flow flux and the like of a target sea area, and presenting an evaluation result through a visualization technology so as to guide a laying mode of a tidal current energy unit; compared with a traditional two-dimensional or simplified three-dimensional model, the evaluation precision is greatly improved. The tidal current characteristics at different water depths can be meticulously simulated, so that tidal current energy resource assessment is more comprehensive and accurate.

The invention discloses an improved sliding-mode active-disturbance-rejection control method for a two-stage energy storage converter, and the method comprises the steps: firstly, building a mathematical model of the energy storage converter in a three-phase static coordinate system, converting the mathematical model into a d-q rotating coordinate system, converting the mathematical model into a second-order active-disturbance-rejection normal form on the basis, and then carrying out the design of a super-spiral expansion state observer. In order to reduce system buffeting, a discontinuous switching item sign function in the super-spiral expansion state observer is replaced by a hyperbola function; secondly, a variable gain function which can change in real time along with observation errors is designed to replace the linear gain of ST-ESO, so that the disturbance observation capability is improved; and then, a superhelix integral terminal sliding mode is introduced as a feedback controller, so that the control precision and the convergence speed of the system are improved, and the robustness of the system is better improved.

The invention relates to the technical field of data processing, in particular to a coating equipment fault real-time early warning method, which comprises the following steps of: acquiring pressure data and vibration data, acquiring instability of each pressure data according to surrounding data of each pressure data, and determining whether each pressure data is unstable or not according to the instability of each pressure data. Obtaining a characteristic value of each piece of pressure data, obtaining the optimal degree of each clustering result according to the characteristic value of each piece of pressure data and the correlation of the abnormal degree of each piece of pressure data in each clustering result, obtaining the optimal number of midpoints, obtaining the optimal clustering result, and obtaining the optimal clustering result according to the optimal clustering result. The final anomaly degree of each piece of pressure data is obtained, then the fault of the coating equipment is judged, and the anomaly detection accuracy is improved.

The invention relates to a valve sealing performance detection system and method, and belongs to the technical field of valve detection. The problems that traditional valve detection is limited to sealing performance detection in a closed state, and monitoring on abnormal changes of pressure, temperature and flow parameters in detection is insufficient are solved. Comprising a valve installation module, a sealing performance evaluation module, a safety monitoring module and a control and display module. The control and display module determines the acquisition evaluation value and the acquisition frequency of the acquisition parameters according to the valve pressure and the opening range, so that the pertinence and the effectiveness of data acquisition are greatly improved; the sealing performance evaluation module establishes a pressure curve, a flow curve and a temperature curve by analyzing various parameters, and analyzes the pressure curve, the flow curve and the temperature curve to obtain a valve sealing value, so as to accurately judge the sealing performance of the valve; the safety monitoring module can deeply analyze the curve to calculate an alarm evaluation value, compares the alarm evaluation value with a preset threshold value, and gives an alarm for abnormal conditions of pressure, temperature and flow in time, so that the safety of the detection process is guaranteed.

The invention belongs to the field of aircraft control, and particularly relates to a helicopter adaptive command filtering backstepping tracking control law design method, which comprises the following steps: firstly, decomposing a helicopter kinetic model into a plurality of strict feedback systems with uncertainty, and then designing a controller by using a backstepping method; a hybrid command filter is adopted to solve the problem of calculation explosion of backstepping, and a filtering compensation mechanism is introduced. In addition, an uncertain part in the model is approximated by adopting a neural network, and network parameters are updated online by adopting an adaptive law. And finally, designing a Lyapunov function to prove the effectiveness of the method.

The invention relates to a stochastic optimization method for capacity configuration of an off-grid wind and light storage system. The method comprises the following steps: constructing a system mathematical model by considering equipment constraint and power balance; considering the uncertainty of wind speed and illumination intensity and performing probability distribution fitting by using a parameter estimation method; constructing a stochastic optimization algorithm by using an expected value model and a Monte Carlo method; a non-dominated sorting genetic algorithm is used for carrying out multi-objective optimization calculation on economic benefits and carbon emission; a new method for evaluating the permeability of renewable energy sources is provided by combining a Monte Carlo method definition, and investment decision suggestions are given by taking the new method as an index. The problem that the renewable energy source permeability of the off-grid energy system with uncertainty lacks specific quantification is solved. According to the method, the uncertainty of renewable energy sources is considered, compared with a deterministic method, the method has higher robustness, and the system uncertainty caused by volatility is effectively solved.

The utility model provides a pile foundation concrete pouring over-pouring height measuring device which comprises an installation frame, a winding drum mechanism arranged on the installation frame, a coil spring arranged in the winding drum mechanism, a measuring rope with one end fixed and wound on the winding drum mechanism and a fixing piece connected with a reinforcement cage. The fixed part is arranged on the mounting frame, the floating ball mechanism is movably connected to the fixed part and connected with the other end of the measuring rope, the ratchet wheel is fixedly connected to the winding drum mechanism, and the alarm mechanism is arranged on the mounting frame and used for being matched with the ratchet wheel. The pile hole concrete surface ascends to push the floating ball mechanism to ascend, and then under the action of the coil spring, the winding drum measuring rope is driven to be shortened, the winding drum mechanism and the ratchet wheel are driven to rotate, so that the alarm mechanism matched with the ratchet wheel sends out a signal to remind constructors of the concrete pouring condition, and accurate control over the over-pouring height is achieved. Tediousness and uncertainty of manual judgment are avoided, and construction efficiency and construction quality of the pile foundation are effectively improved.

The invention relates to a blue film depoling linkage synchronization method, device and equipment and a storage medium, and the method comprises the steps: obtaining the ejection height of an ejector pin, the target position of the ejector pin, the force of the ejector pin and the target position of a suction nozzle based on all attributes of a chip and the characteristics of a blue film; acquiring image information to obtain initial position coordinates of the ejector pin and the suction nozzle; planning a moving route and a time driving sequence in the same preset time, driving the ejector pin and the suction nozzle to move, and when it is monitored that the ejector pin moves to the ejector pin target position, deviation exists between the current position of the suction nozzle and the planned position in the moving route of the suction nozzle, adjusting the speed curve of the suction nozzle according to the deviation of the suction nozzle; and when it is detected that the ejector pin reaches the ejector pin jacking height and the suction nozzle moves to the suction nozzle target position, a suction instruction operation is sent to the vacuum generator, and the suction force is adjusted until the chip is separated from the blue film, so that the purposes of achieving accurate, efficient and linkage synchronous operation in the blue film core removal process and improving the overall production efficiency of chip core removal are achieved.

The invention discloses a signal data real-time acquisition, storage and transmission device applied to a hydrophone, and the device comprises a plurality of sound wave receivers disposed on a measurement platform to form a matrix layout; receiving sound wave signals of different underwater paths, and performing electric signal conversion; analyzing the received sound wave signal, extracting signal data of the sound wave, and calculating the arrival angle of the sound wave signal; calculating the position of a target signal source, determining main signals in different paths, and correcting the main signals; the corrected signal data is transmitted to a storage device for segmented storage; according to the invention, the plurality of receivers are deployed on the measurement platform to form the matrix layout, and the position of the target signal source is calculated, so that the main signals received by the receivers are determined, the multipath effect caused by water body boundary reflection is eliminated, the main signals are corrected, the quality and accuracy of the signals are improved, and the measurement accuracy is improved. And accurate transmission and storage of underwater signals are ensured, so that the performance of the hydrophone system in a complex underwater environment is ensured.

The invention discloses a brain-computer interface implantation accuracy judgment method based on combination of images and electroencephalogram signals, and belongs to the field of biological cross scientific research. By combining an image processing technology and fine electroencephalogram signal analysis, the accuracy of electrode implantation is evaluated from two independent and complementary angles. Compared with a traditional method depending on postoperative histological analysis, the method has the advantages that multiple real-time feedback mechanisms are provided, and the accuracy and reliability of electrode positioning in an operation are remarkably improved. The technical innovation not only shortens the operation time and reduces the operation risk, but also improves the success rate of the whole operation process. Through real-time image and signal analysis, an operation team can adjust an operation strategy in real time, an electrode implantation path is optimized, and it is ensured that an electrode accurately reaches a target brain area. Besides, the delay and uncertainty of relying on postoperative slice analysis are avoided, so that the correctness of the electrode position can be confirmed during the operation, and the overall safety and effect of the brain-computer interface operation are enhanced.

The invention provides a tight oil reservoir fluid occurrence type identification method and system based on nuclear magnetic resonance, and belongs to the technical field of petroleum geology exploration and development. The method comprises the following steps: on the basis of comparison between a nuclear magnetic resonance T2 relaxation time cumulative distribution curve of a tight oil reservoir sample and a high-pressure mercury injection pore throat diameter cumulative distribution curve, dividing pore throat types, and converting T2 relaxation time into pore throat diameters; judging occurrence fluids in different types of pore throats through a nuclear magnetic resonance spectrum to obtain fluid occurrence types corresponding to different signal domain ranges, and calculating the relative fluid content of each fluid occurrence type; and based on the signal domain range of each fluid occurrence type of the plurality of samples, establishing a nuclear magnetic resonance fluid occurrence type identification chart, and defining an identification standard of each fluid occurrence type. According to the method, the pore size distribution of the T2 relaxation time is combined with the nuclear magnetic resonance spectrum, the pore size range corresponding to the fluid occurrence type is determined, and the relative content of the fluid is calculated through the signal intensity of each signal domain, so that the accuracy is higher.

The invention relates to the technical field of logistics management, in particular to a cross-border logistics demand prediction method and system, which can provide accurate and reliable prediction results and decision support for cross-border logistics enterprises. The method comprises the following steps: acquiring a destination cargo demand influence parameter set and a delivery place cargo supply influence parameter set; respectively performing feature analysis on the destination cargo demand influence parameter set and the shipping place cargo supply influence parameter set to obtain a destination cargo demand feature index and a shipping place cargo supply feature index; comparing the destination cargo demand characteristic index with the shipping place cargo supply characteristic index, extracting a minimum characteristic index, and marking the minimum characteristic index as a logistics demand characteristic index; obtaining the real-time cross-border transportation cost and the historical same-period cargo transportation characteristic quantity corresponding to the logistics demand characteristic index; and inputting the logistics demand characteristic index and the real-time cross-border transportation cost into a pre-constructed cross-border logistics demand influence analysis model as input.

The invention relates to the field of water quality detection, and discloses an automatic detection method and system based on local raw water quality, and the method comprises the steps: monitoring and collecting current water quality parameters in a water sample, and transmitting the collected current water quality parameters to a data processing center for processing and characteristic analysis; the current water quality parameters are combined with historical water quality parameters obtained from a database to analyze the change trend and the specific fluctuation condition of the water quality state, the current water quality health condition is evaluated through the calculated water quality health condition evaluation coefficient, then the water quality health condition is detected, and the abnormal condition of the water quality health condition is fed back. According to the method, the water quality condition is monitored and fed back in real time according to the water quality condition monitoring coefficient, the water quality condition adjusting process is monitored and fed back in real time, the water quality abnormal problem can be detected, an early warning signal can be sent out, errors and uncertainty in the manual sampling process are avoided, and therefore the timeliness and detection efficiency of water quality management are improved.

The invention discloses a formation resistivity determination method and device for a post-casing transient electromagnetic logging curve, equipment and a medium, and relates to the technical field of oil exploration and development, and the formation resistivity determination method comprises the following steps: obtaining a post-casing electromagnetic logging curve, and carrying out time sequence conversion and data preprocessing to obtain time sequence data; converting the data into frequency domain data by adopting wavelet transform, and performing multi-scale refinement splitting to obtain low-frequency features and high-frequency features; fitting the low-frequency features and the high-frequency features by using a symbol regression method to obtain a nonlinear high-dimensional symbol regression formula for the low-frequency data and a nonlinear high-dimensional symbol regression formula for the high-frequency data, and generating a post-casing electromagnetic logging curve nonlinear fitting formula; the mapping relation between the post-casing transient electromagnetic curve and the formation resistivity is determined through the post-casing electromagnetic logging curve nonlinear fitting formula, the formation resistivity is obtained, the uncertainty of manual selection of model parameters is avoided, the capacity of processing nonlinear problems is improved, and the accuracy and reliability of high-dimensional relation mapping and nonlinear fitting are improved.

The invention provides an engine heat insulation layer defect automatic detection line, and relates to the technical field of engine detection, the engine heat insulation layer defect automatic detection line comprises a marble platform, and the top of the marble platform is provided with a measuring rod fixing welding seat. According to the invention, the position and direction of the monitoring mechanism are adjusted to adapt to different detection requirements, the mechanical arm can accurately position and control the detection tool at the position needing to be detected, errors and uncertainty of manual operation are avoided, and the accuracy and reliability of detection are improved. The mechanical arm also has high flexibility and accuracy, can freely move in a three-dimensional space, and can carry out detection work with high repeatability and long duration time, so that the working efficiency and accuracy are improved, and the detection mechanism has the advantages that the detection mechanism can be used for carrying out nondestructive detection technologies such as ultrasonic wave, laser imaging, thermal imaging and the like; the thermal insulation layer surface is scanned and analyzed to detect and identify surface defects and damage.

The invention provides a capacitance detection method, system and device and a storage medium, and relates to the technical field of capacitance detection. The method comprises the following steps: acquiring a capacitance type and a parameter range of a measured capacitor, and matching with a preset resonance library according to the capacitance type and the parameter range to obtain a target resonance inductance parameter; constructing a target LC resonance test circuit based on the target resonance inductance parameter, the capacitor type and the parameter range, and measuring the tested capacitor based on the target LC resonance test circuit to obtain resonance response data; and analyzing the resonance response data to obtain a capacitance performance index. Through the scheme, the capacitor testing efficiency is improved.

The invention discloses a BIM-based communication pipeline design intelligent optimization system and method, and relates to the technical field of BIM. An initial data set X is constructed, the electromagnetic interference intensity between each pair of pipelines is deduced in combination with an electromagnetic field theory, an interference intensity matrix EMI is finally generated, the relative position of a high-interference pipeline is dynamically adjusted by adopting an optimization algorithm, and the relative position of the high-interference pipeline is optimized. The method comprises the steps of generating a preliminary pipeline layout scheme Xop, applying the preliminary pipeline layout scheme Xop to a BIM model, further combining a spatial constraint Cs to perform verification and fine tuning, calculating a pipeline position optimization evaluation index Ft, and comparing the pipeline position optimization evaluation index Ft with a preset pipeline position optimization execution evaluation threshold Fth, thereby realizing scientific evaluation and decision-making of the scheme optimization effect, and improving the pipeline position optimization efficiency. The problems of insufficient electromagnetic interference influence evaluation, disjunction of an optimization process and spatial constraint and the like are solved in a targeted manner, and electromagnetic interference minimization, path optimization rationalization and space resource utilization maximization of communication pipeline layout are realized.