71 results about "Stability index" patented technology

The invention discloses a production processing data collaborative management system and method of a curtain wall single aluminum plate, and relates to the technical field of data collaborative management. According to the method, the production processing data and the quality detection data of the curtain wall single aluminum plate are collected, the dynamic time warping algorithm is adopted to analyze the time sequence data change between the working procedures, the time deviation and the performance fluctuation between the working procedures are recognized, then the working procedure coordination index is obtained, and the time synchronism and the efficiency matching degree between the working procedures are measured. And performing classification and regression analysis on the quality index of each processing procedure through a decision tree algorithm to obtain a quality stability index, and identifying and predicting quality fluctuation and abnormal modes in different procedures. And judging whether the sequence and priority of the production processes need to be adjusted or not through comprehensive analysis of the process coordination index and the quality stability index. And time inconsistency, efficiency bottleneck and quality fluctuation in the production process are identified, intelligent optimal scheduling of the production process is realized, and the collaborative management level of the production process is improved.

The invention provides an information system gray release migration method and system, and relates to the field of information system migration, and the method comprises the steps: controlling the gray scale proportion of each module through initializing a gray scale proportion vector, and dynamically shunting user requests; monitoring abnormal and slow response conditions of the system with migration based on the time slice, and generating a system statistical vector; performing weighted statistics and standardization on the statistical vector by using a sliding window to form a system state vector; generating a final system state vector reflecting the real-time operation state of the system in combination with the health state information; and calculating the stability index of each module through the stability discrimination model, dynamically adjusting the gray scale proportion, preferentially transitioning the stable module, and rolling back the gray scale proportion of the unstable module. The system supports automatic adjustment of the gray scale proportion, risk real-time response and multi-architecture compatibility, the risk in the informatization system migration process is remarkably reduced, and the gray scale release efficiency and stability are improved.

The invention relates to the technical field of data processing, in particular to an intelligent monitoring method and system for pipeline sealing performance, and the method comprises the steps: obtaining a pressure data sequence in a pipeline, carrying out the iterative clustering of the pressure data sequence through employing a DIANA algorithm, calculating the stability index of a clustering cluster after the clustering of any time is completed, and calculating the sealing performance of the pipeline. When the stability index is larger than a preset threshold value, iteration is stopped, clustering results are obtained, and the pipeline sealing performance is monitored according to a comparison result of the data size of the minimum clustering cluster in the clustering results and a preset number threshold value. According to the invention, the accuracy of the obtained clustering result can be improved, so that the sealing condition of the pipeline can be accurately monitored.

The invention provides an intelligent layout method, system and device for a land survey control network and a medium, and the method comprises the steps: building a space-time dynamic terrain model based on the obtained measurement data of a construction region; generating a candidate control point set in the construction area according to a preset layout density requirement; based on the space-time dynamic terrain model, performing stability analysis on each candidate control point in the candidate control point set to obtain a stability index of each candidate control point; based on the space-time dynamic terrain model, any two candidate control points in the candidate control point set are used as candidate control point pairs for time sequence intervisibility analysis, and time sequence intervisibility indexes of the candidate control point pairs are obtained; establishing a multi-objective optimization model according to the stability index and the time sequence intervisibility index; and solving the multi-objective optimization model by adopting a multi-objective evolutionary algorithm, and outputting a control network layout scheme set. By adopting the method, the point distribution quality of the control network can be improved.

The invention relates to the technical field of program repair, in particular to an executable invariant and differential signal combined automatic program repair method, which comprises the following steps of: receiving a to-be-repaired program and a test set, and calling a large language model to generate a plurality of candidate patches; forming an entry behavior specification list according to the repair intention description; generating a plurality of executable invariant assertions and injecting the executable invariant assertions into the target function or the calling point, and generating an invariant assertion injection record table; generating a test case covering the boundary condition and the abnormal scene based on the large language model; collecting an execution signal when the candidate patch is operated; converting the patch difference into semantic editing features, calculating an editing stability index, and calculating an overall semantic consistency score of the candidate patches according to the support degree of the standard bar; and calculating an overall comprehensive score of the candidate patches, and outputting an optimal patch according to the overall comprehensive score of the candidate patches. According to the method, the proportion of overfitting patches can be effectively reduced, the patch repairing accuracy is improved, the interpretability is high, and the universality is good.

The invention relates to a servo hydraulic multi-working-condition parameter self-adaptive switching and correcting method. The method comprises the steps that system real-time data flow including real-time hydraulic pressure, executing mechanism speed and control response deviation is monitored and collected; identifying the current working condition based on the real-time data and indexing the reference control parameters; running a parallel response evaluation program to generate a dynamic stability indicator and determine an expected performance threshold; the dynamic stability index is compared with an expected performance threshold value, and when parameter mismatch is confirmed, a temporary compensation coefficient is generated to correct the reference control parameter in real time; and monitoring the correction offset, and updating the working condition-parameter mapping database when the aging judgment condition is met. The method has the advantages that manual parameter adjustment can be replaced, automatic switching of millisecond-level working conditions is achieved, the problem of parameter mismatching caused by equipment aging is effectively solved through a model self-evolution mechanism, and the control precision and stability of the servo hydraulic system in the whole life cycle are ensured.

A foundation monitoring regulation and control method and system based on adaptive adjustment relates to the field of foundation regulation and control, and the method comprises the following steps: setting a plurality of monitoring points in a target monitoring area according to the foundation stress distribution of the target monitoring area, collecting to obtain monitoring data, endowing the monitoring data with a weight coefficient according to the influence factor of the monitoring data on the foundation stability, calculating the stability index of the current foundation of the target monitoring area according to the weight coefficient; calculating foundation deformation evaluation data according to the stability index, inputting the foundation deformation evaluation data into a foundation settlement prediction model to obtain a foundation settlement change value in a preset time period, and when the foundation settlement change value exceeds a preset safety threshold value, judging that the foundation settlement change value is abnormal. And calculating a foundation bearing capacity adjustment value of the target monitoring area according to the stability index and the foundation settlement change value, and generating a control instruction containing the target adjustment time and the foundation bearing capacity adjustment value. By implementing the method, the accuracy of the foundation regulation and control opportunity can be improved.

The invention relates to a power grid stability evaluation method and device, equipment, a storage medium and a product. The method comprises the steps of determining operation parameters and at least one preset operation fault type according to a preset operation mode of a power grid, and constructing a to-be-analyzed sample according to fault parameters and operation parameters corresponding to the at least one preset operation fault type; performing stability prediction on the power grid based on the to-be-analyzed sample through a pre-trained stability prediction model to obtain a system-level stability index and an equipment-level stability index; performing stability judgment on the power grid based on the system-level stability index to obtain a first judgment result, and performing stability judgment on the power grid based on the equipment-level stability index to obtain a second judgment result; determining a target analysis mode for the power grid according to the first judgment result and the second judgment result; stability evaluation is performed on the power grid by using the target analysis mode to obtain the stability evaluation result of the power grid, so that the stability evaluation accuracy can be effectively improved.

The invention relates to a three-dimensional automatic boxing system and method based on deep learning, and belongs to the technical field of information. The problems that in the current wharf wood loading and unloading process, efficiency is low, the space utilization rate is insufficient, and potential safety hazards exist are solved. According to the system, a container space is discretized into a three-dimensional grid structure, and an optimal placement position is dynamically selected by utilizing a greedy algorithm and a DQN algorithm in deep reinforcement learning according to the size and shape of wood and the state of the container, so that automatic boxing of the wood is realized. The system continuously optimizes a placement strategy by evaluating the size of the residual space and a stability index in combination with a reward mechanism, and maximizes the space utilization rate of the container. The wood loading efficiency and safety are effectively improved, the manual operation intensity is reduced, the placement strategy can be flexibly adjusted according to the actual situation, and the device is suitable for various scenes such as wharf wood loading and unloading.

This invention provides a building lifecycle operation and maintenance management system, belonging to the field of information management technology. The maintenance module of this system performs the following steps: establishing a three-dimensional model of the building based on two-dimensional design drawings and panoramic images; performing finite element analysis on the three-dimensional model to identify multiple areas where the stress exceeds a stress threshold, designated as weak areas; acquiring the building materials and proportions of the weak areas; acquiring the penetrating ultrasonic signals of the weak areas and performing noise reduction, filtering, and enhancement preprocessing to obtain a preprocessed signal; extracting the feature matrix of the preprocessed signal and fusing it with material vectors to form a fusion matrix; using a pre-trained ultrasonic signal-stability model, inputting the fusion matrix to obtain the stability index of the weak areas; if the stability index is lower than the stability index threshold, outputting a maintenance reminder to the user, achieving non-destructive monitoring and high-precision assessment.

The present invention discloses a method for evaluating production line stability based on a fault tree, comprising the following steps: obtaining multiple parameters of each device on the production line collected by sensors over a period of time, calculating the process capability index corresponding to each parameter, inputting the obtained process capability index corresponding to each parameter of each device into a pre-trained multiple linear regression model to obtain a stability index for the device, and inputting the stability index of each device into a pre-built fault tree-based stability analysis model to obtain a final stability judgment result for the device. The present invention can solve the technical problem that existing machine learning methods are complex for production lines, require long training times, and are unable to adapt to the real-time requirements of production environments in actual deployment and operation.

The invention discloses a sensor and port infrastructure coupling and construction method, and relates to the technical field of coupling, and the method comprises the steps: calculating a first comprehensive score and a second comprehensive score of a selected sensor at a current preselected installation position, and enabling the design of the first comprehensive score to integrate a data error value, a time stability index and a space consistency index; according to the method, comprehensive evaluation on the basic performance of the sensor is provided, on the basis, the second comprehensive score intervenes, the overall performance of the sensor can be evaluated more comprehensively, and therefore screening of the most appropriate installation position can be further helped effectively, threshold value judgment and the refined sorting and screening process can be further helped effectively, and the accuracy and the reliability of the sensor are improved. According to the method, the final preferential installation position is scientifically and effectively screened out, so that the performance of the sensor can be reflected to the maximum at the final preferential installation position, the influence on the accuracy of monitoring data can be effectively reduced, and meanwhile, the influence on the coupling of subsequent sensors and the reliability of construction can be effectively reduced.

The application discloses a flexible circuit board production quality monitoring method and system based on data feedback, collects physical parameters such as line width, line spacing, hole diameter, roundness and copper thickness of developing etching, drilling and copper plating processes, and workshop temperature and humidity and dust concentration data, generates a single variable control chart for single process physical parameters, generates a multivariate T 2 Control chart for multiple coupling parameter processes, calculates process stability index and comprehensive fluctuation index, inputs abnormal data into a BP neural network, identifies abnormal mode types and outputs characteristic parameters, generates parameter correction instructions according to the abnormal mode and the characteristic parameters, adjusts equipment parameters in real time, recalculates the process capability index based on the adjusted data, triggers secondary feedback if the process capability index does not meet the standard, and dynamically adjusts the control chart threshold value according to the standard deviation and mean value of the process capability index of continuous batches. The application comprehensively covers key production parameters, discovers abnormalities in time, accurately and comprehensively detects, adjusts in real time to ensure stability and controllability, and improves product quality.

The invention discloses a bearing anti-gluing design method based on internal structure parameter optimization, and relates to the technical field of bearing design. The problems that an existing bearing anti-gluing design mainly depends on experience, collaborative optimization of internal structure parameters is lacked, and the gluing risk is difficult to quantitatively predict are solved. The method comprises the following steps: firstly, constructing a basic database containing key internal structure parameters and typical service conditions of a bearing, obtaining gluing failure characteristic data through test or numerical simulation, and calculating a quantitative index-gluing risk factor for comprehensively representing a gluing risk; on this basis, an optimization model with the goal of minimizing a gluing risk factor and maximizing a bearing rated dynamic load and an operation stability index is established, a multi-objective optimization algorithm is adopted to carry out collaborative optimization on key structure parameters, and finally an optimal parameter combination is selected from a Pareto optimal solution set. According to the method, the bearing gluing risk can be quantitatively predicted and effectively reduced in the design stage, and the operation reliability of the bearing under harsh working conditions is remarkably improved.

The invention discloses a grid division method and device for a simulation model, electronic equipment and a computer program product. The method comprises the steps that a three-dimensional scanning model of a to-be-simulated object is acquired, and the three-dimensional scanning model is subjected to grid division based on preset grid density; performing multi-physical field modeling on the three-dimensional scanning model to obtain a simulation model to be evaluated; performing simulation calculation on the to-be-evaluated simulation model, and determining calculation time for performing simulation calculation on the to-be-evaluated simulation model and a stability index for measuring a simulation calculation result; performing iterative adjustment on the preset grid density to obtain a target grid density which enables the calculation time to be not greater than a preset time threshold value and the stability index to be not less than a preset index threshold value; and determining the to-be-evaluated simulation model subjected to grid division based on the target grid density as a target simulation model. According to the method, the technical problem that the grid density cannot be accurately selected under the condition of multi-physical modeling in the prior art is solved.

The invention relates to the technical field of stacking and typesetting, in particular to an intelligent stacking and typesetting method and system based on a self-adaptive algorithm, and the method comprises the steps: respectively obtaining a product parameter set and a tray parameter set, and extracting the maximum length, the maximum width and the maximum height from the product parameter set to determine the division step length of a three-dimensional discrete space set; pre-screening coordinate points meeting a threshold value by the system, and inputting the coordinate points into a target function to generate an arrangement scheme set; introducing a support consistency index and a mass weighted average value to generate a unit stability mark set and an overall structure judgment mark; the system generates an operable product set in the arrangement scheme set by traversing the structure dependency relationship, and the user performs adjustment according to the operable product set; and the system screens the arrangement points conforming to the threshold value to form an execution task set and sorts the execution task set, corresponding robot execution vectors are constructed, and an instruction sequence formed by all the execution vectors is coded into a standard action file issued to a robot controller.

The invention discloses a foundation pit stability monitoring method, and relates to the technical field of foundation pit stability monitoring, and the method comprises the steps: monitoring and collecting an nth monitoring displacement value Wn of a current foundation pit in real time through a monitoring data collection module, and extracting and collecting a first monitoring displacement value W1, an (n-1) th monitoring displacement value Wn-1 and a last predicted displacement value Wlast.vt of the current foundation pit, the method comprises the following steps of: calculating and outputting an adjustment factor X, a displacement change rate WL, a stability index WD and a current predicted displacement value Wvt in sequence by using a data processing and predicting module according to an error between a previous predicted displacement value Wlast.vt and an nth monitored displacement value Wn before the current predicted displacement value Wvt is calculated, and calculating and outputting the current predicted displacement value Wvt according to the error between the previous predicted displacement value Wlast.vt and the nth monitored displacement value Wn after the current predicted displacement value Wvt is calculated. According to the method, by means of the relevance of error adjustment and correction and foundation pit monitoring calculation, the prediction accuracy is remarkably improved, real-time dynamic feedback and adjustment are achieved, and the robustness of the system is enhanced.

The invention relates to an elastic prediction control method and device based on interval target self-optimization. The method comprises the steps that process output at the current moment and a process output sequence in a past preset time period are acquired; determining a process stability index for representing process stability according to the process output sequence; judging whether the process stability index is smaller than an index threshold value or not; if it is determined that the process stability index is not smaller than the index threshold value, a first objective function of a set value control strategy is solved; if it is determined that the process stability index is smaller than the index threshold value, whether process output at the current moment is within the range of the target interval or not is further judged; if it is determined that the process output at the current moment is within the range of the target interval, solving a second target function of the reference trajectory self-optimization strategy; and if it is determined that the process output at the current moment is out of the range of the target interval, the first target function is solved, so that the system robustness and the device operation benefit are both considered.

The invention provides a stability index management system for a container sign production process. The stability index management system comprises an index system construction module, a production data supervision module and a result display module, according to the method, a container sign production process stability evaluation index system is established, and a manager can know the whole production process more visually through real-time data acquisition and visual display of an analysis result, so that more visual and accurate decision support is provided for the manager, and efficient and stable operation of a factory is facilitated.

The invention provides a backfill process intelligent design method based on multi-dimensional data analysis and optimization control, which comprises the following steps: judging whether a material difference exceeds a preset threshold according to a classified material group, and if so, predicting non-uniform distribution of a soil body through a support vector machine model, and determining coordinates of a potential non-uniform region; side slope instability risk points are extracted from the coordinates of the potential non-uniform area, stress distribution under the backfilling technology is analyzed and simulated through finite elements, and a stress distribution map is obtained; for the stress distribution map, obtaining a material selection scheme, adjusting a material combination proportion through an optimization algorithm, and determining an optimized material matching sequence; generating an inner waste dump three-dimensional model through the backfill process parameters, and evaluating a long-term stability index by adopting a numerical simulation method to obtain a stability evaluation score; and optimized feedback data are extracted from the stability evaluation score, whether the long-term stability requirement is met or not is judged, and if yes, a final backfill process scheme is output to control settlement and slope instability.

The invention provides an evaluation method and device for a time-of-use electricity price making policy, electronic equipment and a storage medium. The method comprises the following steps: acquiring historical load data in a reference period and to-be-evaluated load data in an evaluation period; the reference period and the evaluation period have homogeneous comparability; constructing an undetermined reference load curve and a to-be-evaluated load curve according to the historical load data and the to-be-evaluated load data; adjusting the to-be-determined reference load curve by using the load adjustment coefficient to obtain a reference load curve; and according to the user industry response characteristics and the reference load curve, analyzing the to-be-evaluated load curve, and calculating the following indexes: a net load transfer amount, a peak-valley optimization effect index, a response stability index and an industry differentiation evaluation matrix. According to the embodiment of the invention, the multi-dimensional reference load curve is constructed and the load adjustment coefficient is introduced, so that the interference of external factors such as natural fluctuation and seasonal change of the total power consumption on the evaluation result is effectively eliminated, the evaluation precision is high, and the anti-interference capability is high.

The present invention discloses an automated diversion and conveying method and system for packaging barrels based on the Internet of Things, and relates to the technical field of electrical digital data processing. The automated diversion and conveying method for packaging barrels based on the Internet of Things comprises the following steps: sending a diversion operation instruction; obtaining a stability index and a synchronization performance evaluation index; and obtaining a real-time status evaluation value. The present invention determines whether to perform a diversion operation by obtaining the information resolution, and then obtains the stability index of the packaging barrel to be conveyed during the diversion operation and the synchronization performance evaluation index during the conveying operation. Finally, it determines whether to perform a conveying parameter adjustment according to the obtained real-time status evaluation value and the real-time status evaluation threshold range, thereby achieving the effect of improving the accuracy of the synchronization performance evaluation of the packaging barrel during the automated diversion and conveying process, and solves the problem of low accuracy of the synchronization performance evaluation of the packaging barrel during the automated diversion and conveying process in the prior art.

The present invention discloses a software stability evaluation method, device, storage medium and equipment. By obtaining abnormal data information and running data information during the running process of the software to be evaluated, calculating the overall abnormal rate index and the proportion of abnormal running time, calculating the stability index according to the overall abnormal rate index and the proportion of abnormal running time, evaluating the stability of the software to be evaluated according to the size of the stability index, quantifying the evaluation index of software stability, and evaluating the stability in combination with the causal relationship and relative importance between software anomalies, the stability evaluation is more comprehensive; by removing the repeated abnormal times in the abnormal data information through the abnormal causality matrix, the accuracy of the abnormal data information is improved; by determining the abnormal weighting coefficient through the abnormal importance comparison matrix, the stability evaluation is more accurate.

The invention relates to the technical field of gas leakage detection, in particular to an intelligent detection and early warning method and system for gas leakage, and the method comprises the steps: completing the division of monitoring sub-regions of a target region according to the pipeline layout and use scene of a target gas pipeline, and carrying out the unique identification of each monitoring sub-region; according to the method, the monitoring sub-regions are divided by combining the layout and the use scene of the target gas pipeline, the working condition characteristics of each region are extracted, the working condition types are defined, and the data acquisition parameters are adjusted in a targeted manner according to the working condition characteristics, so that the data acquisition is more targeted, the acquisition of invalid data is effectively reduced, and the effectiveness of the monitoring data is improved; the initial stability index is subjected to deviation correction through the working condition characteristic correction model, monitoring errors caused by working condition fluctuation are eliminated, and the stability index can better reflect the actual operation state of each area.

The application provides a device stability analysis method and system, a device and a storage medium, and comprises the following steps: acquiring an action time difference of the same action of different types of products of the same device; calculating a statistical value of the action time difference, wherein the statistical value comprises one or more of an average, a mode, a median and a standard deviation; deriving an action stability index according to the statistical value; and comparing the action stability index with a preset stability index to determine the stability of the device. By comparing the action stability index value with the preset stability index value, it is determined that the device is in a stable state, a relatively stable state or an unstable state, and corresponding maintenance work is performed according to the obtained device stability state result.

This invention provides a cloud service assurance method and system based on eBPF observable data and a prediction model. The method includes: collecting historical observable operational status data of the kernel, containers, and application layers and mapping and associating them; aligning and concatenating the associating data to generate a time-series feature vector; using the time-series feature vector to train and test the constructed model, calculating the residuals based on the predicted values ​​and corresponding actual observed values ​​during the testing period, and analyzing the residual probability distribution characteristics; using the model's prediction results for cloud services to calculate the residuals, and generating anomaly confidence scores based on the residual probability distribution characteristics; under the condition that the anomaly confidence score is greater than a threshold, analyzing the anomaly type and its impact range, then matching a remediation plan in the policy library and automatically executing the remediation plan; monitoring the execution effect of the remediation plan and feeding it back to the model; calculating a stability index based on key stability indicators to form a stability change curve, and then evaluating the execution effect of the remediation plan.

The present disclosure relates to a train operation method and device based on the coupler state, equipment, storage medium and computer program, the method comprising: initializing all gear discrete points in the discrete position domain to obtain a discrete gear sequence set, calculating an expected speed sequence according to the discrete gear sequence set, calculating a train coupler state sequence according to the pre-acquired coupler critical displacement and the discrete position domain sequence, calculating a train coupler state change sequence according to the train coupler state sequence, calculating a coupler state change index sequence according to the train coupler state change sequence, calculating a stability index sequence according to the coupler state change index sequence, calculating a speed following index sequence according to the expected speed sequence and a preset target speed sequence, calculating a comprehensive evaluation index sequence according to the stability index sequence and the speed following index sequence, selecting an optimal gear sequence in the discrete gear sequence set according to the comprehensive evaluation index sequence, and controlling the train to run by using the optimal gear sequence.

The invention discloses a report information acquisition method and system based on project cost management, and relates to the technical field of project cost management. The report information acquisition method based on project cost management comprises the following steps: acquiring a monitoring performance evaluation index; acquiring a transmission stability index; obtaining an early warning execution efficiency score; and obtaining report information. According to the method, whether data acquisition is started or not is determined by monitoring performance evaluation indexes; and then, according to the transmission stability index, whether fault early warning needs to be sent out is judged. And finally, comparing a preset value in a database according to the early warning execution efficiency score to determine whether to generate a report. The effect of improving the data transmission stability of the engineering cost report information in the collection and management process is achieved, and the problem that the data transmission stability is not considered when the engineering cost report information of a material warehouse in a construction site is collected and managed in the prior art is solved.

The invention provides a data management system based on data quality evaluation, and relates to the technical field of data management. According to the system, a data monitoring module intercepts a data packet, segments the data packet according to a time window and then transmits the data packet, an evaluation rule generation module calculates an instantaneous offset percentage and maps the instantaneous offset percentage into a credible mark, a turnover frequency is counted to obtain a stability index, and an executable vector is generated. And the real-time evaluation module compares the field value of the data packet with the vector boundary, and outputs a report if the boundary is exceeded. And the data governance module covers and marks the abnormal field with the boundary value and sends the abnormal field back to a downstream link. The feedback optimization module adjusts the stability index to optimize the evaluation rule. According to the method, the timeliness of abnormal data capture is improved, data qualification judgment is precise through three-level progressive judgment, the fault tolerance rate of quality evaluation is improved, self-optimization iteration of evaluation rules is achieved through a feedback mechanism, and the long-term operation adaptability of the system is enhanced.

A method includes obtaining an actual value of a condition affected by operating the building equipment, operating the building equipment using a setpoint for the condition, calculating a stability index based on a timeseries of errors between the actual value and the setpoint, comparing the stability index to a criterion, in response to the stability index satisfying the criterion, executing an action relating to the building equipment, and in response to the stability index not satisfying the criterion, not executing the action.