ISA transactions最新文献_第8页

An optimal control algorithm toward unknown constrained nonlinear systems based on the sequential sampling and updating of surrogate model 基于代用模型顺序采样和更新的未知约束非线性系统优化控制算法

IF 6.3 2区计算机科学

ISA transactions Pub Date : 2024-07-08 DOI: 10.1016/j.isatra.2024.07.012

引用次数: 0

An extended hysteresis observer-based adaptive robust control method for nonlinear macro–micro motion system 基于滞后观测器的非线性宏微运动系统自适应鲁棒控制扩展方法

IF 6.3 2区计算机科学

ISA transactions Pub Date : 2024-07-08 DOI: 10.1016/j.isatra.2024.07.003

引用次数: 0

Finite-time compensation control with dead-zone estimation for a rehabilitative walker considering internal disturbance forces 考虑内部干扰力的康复助行器死区估计有限时间补偿控制。

IF 6.3 2区计算机科学

ISA transactions Pub Date : 2024-07-08 DOI: 10.1016/j.isatra.2024.07.007

引用次数: 0

Spatially resolved capacitance-based stress self-sensing in concrete 基于空间分辨电容的混凝土应力自感。

IF 6.3 2区计算机科学

ISA transactions Pub Date : 2024-07-07 DOI: 10.1016/j.isatra.2024.06.034

{"title":"Spatially resolved capacitance-based stress self-sensing in concrete","authors":"","doi":"10.1016/j.isatra.2024.06.034","DOIUrl":"10.1016/j.isatra.2024.06.034","url":null,"abstract":"<div>Spatially resolved capacitance-based stress self-sensing in unmodified concrete has been demonstrated. The spatial resolution is 45 mm in one dimension, which is in the direction of the capacitance measurement. Parallel coplanar component electrodes (aluminum, 5-mm wide), attached to the concrete using double-sided adhesive tape) separated by 45 mm are used to measure the in-plane capacitance in the direction perpendicular to the length of the electrodes. Combinations of component electrodes are electrically connected to form an electrode. The capacitance ranges from ∼200 pF to ∼750 pF. The greater is the number of component electrodes in an electrode, the higher is the capacitance. The compressive loading is applied at selected areas located between adjacent component electrodes. The stress (defined as load divided by the 300 ×300-mm2 concrete area) is up to 3000 Pa. The load decreases the capacitance monotonically and reversibly. The fractional decrease in capacitance ranges from ∼0.1 % to ∼0.5 %. More spatially concentrated loading, as for loading near the edges of the specimen, gives greater fractional decrease in capacitance. The capacitance decreases with increasing inter-electrode distance. Embedded steel rebars with a 20.0-mm concrete cover do not affect the capacitance or capacitance-based sensing.</div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141565423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A knowledge-data integration framework for rolling element bearing RUL prediction across its life cycle 用于滚动轴承全寿命周期 RUL 预测的知识数据集成框架。

IF 6.3 2区计算机科学

ISA transactions Pub Date : 2024-07-06 DOI: 10.1016/j.isatra.2024.06.022

{"title":"A knowledge-data integration framework for rolling element bearing RUL prediction across its life cycle","authors":"","doi":"10.1016/j.isatra.2024.06.022","DOIUrl":"10.1016/j.isatra.2024.06.022","url":null,"abstract":"<div>Prediction of Remaining Useful Life (RUL) for Rolling Element Bearings (REB) has attracted widespread attention from academia and industry. However, there are still several bottlenecks, including the effective utilization of multi-sensor data, the interpretability of prediction models, and the prediction across the entire life cycle, which limit prediction accuracy. In view of that, we propose a knowledge-based explainable life-cycle RUL prediction framework. First, considering the feature fusion of fast-changing signals, the Pearson correlation coefficient matrix and feature transformation objective function are incorporated to an Improved Graph Convolutional Autoencoder. Furthermore, to integrate the multi-source signals, a Cascaded Multi-head Self-attention Autoencoder with Characteristic Guidance is proposed to construct health indicators. Then, the whole life cycle of REB is divided into different stages based on the Continuous Gradient Recognition with Outlier Detection. With the development of Measurement-based Correction Life Formula and Bidirectional Recursive Gated Dual Attention Unit, accurate life-cycle RUL prediction is achieved. Data from self-designed test rig and PHM 2012 Prognostic challenge datasets are analyzed with the proposed framework and five existing prediction models. Compared with the strongest prediction model among the five, the proposed framework demonstrates significant improvements. For the data from self-designed test rig, there is a 1.66 % enhancement in Corrected Cumulative Relative Accuracy (CCRA) and a 49.00 % improvement in Coefficient of Determination (R2). For the PHM 2012 datasets, there is a 4.04 % increase in CCRA and a 120.72 % boost in R2.</div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141581870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Complex system anomaly detection via learnable temporal-spatial graph with degradation tendency segmentation 通过可学习时空图与退化趋势分割进行复杂系统异常检测。

IF 6.3 2区计算机科学

ISA transactions Pub Date : 2024-07-06 DOI: 10.1016/j.isatra.2024.06.025

{"title":"Complex system anomaly detection via learnable temporal-spatial graph with degradation tendency segmentation","authors":"","doi":"10.1016/j.isatra.2024.06.025","DOIUrl":"10.1016/j.isatra.2024.06.025","url":null,"abstract":"<div>To guarantee the safety and reliability of equipment operation, such as liquid rocket engine (LRE), carrying out system-level anomaly detection (AD) is crucial. However, current methods ignore the prior knowledge of mechanical system itself, and seldom unite the observations with the inherent relation in data tightly. Meanwhile, they neglect the weakness and nonindependence of system-level anomaly which is different from component fault. To overcome above limitations, we propose a separate reconstruction framework using worsened tendency for system-level AD. To prevent anomalous feature being attenuated, we first propose to divide single sample into two equal-length parts along the temporal dimension. And we maximize the mean maximum discrepancy (MMD) between feature segments to force encoders to learn normal features with different distributions. Then, to fully explore the multivariate time series, we model temporal-spatial dependence by temporal convolution and graph attention. Besides, a joint graph learning strategy is proposed to handle prior knowledge and data characteristics simultaneously. Finally, the proposed method is evaluated on two real multi-sensor datasets from LRE and the results demonstrate the effectiveness and potential of the proposed method on system-level AD.</div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141581871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Robust internal model control based on a novel generalized extended state observer and its application on a two-inertia system 基于新型广义扩展状态观测器的鲁棒内部模型控制及其在双惯性系统中的应用

IF 6.3 2区计算机科学

ISA transactions Pub Date : 2024-07-06 DOI: 10.1016/j.isatra.2024.07.005

引用次数: 0

Dynamics modeling and nonlinear attitude controller design for a rocket-type unmanned aerial vehicle 火箭型无人飞行器的动力学建模和非线性姿态控制设计。

IF 6.3 2区计算机科学

ISA transactions Pub Date : 2024-07-06 DOI: 10.1016/j.isatra.2024.06.029

{"title":"Dynamics modeling and nonlinear attitude controller design for a rocket-type unmanned aerial vehicle","authors":"","doi":"10.1016/j.isatra.2024.06.029","DOIUrl":"10.1016/j.isatra.2024.06.029","url":null,"abstract":"<div>This paper presents an altitude and attitude control system for a newly designed rocket-type unmanned aerial vehicle (UAV) propelled by a gimbal-based coaxial rotor system (GCRS) enabling thrust vector control (TVC). The GCRS is the only means of actuation available to control the UAV’s orientation, and the flight dynamics identify the primary control difficulty as the highly nonlinear and tightly coupled control distribution problem. To address this, the study presents detailed derivations of attitude flight dynamics and a control strategy to track the desired attitude trajectory. First, a Proportional-Integral-Derivative (PID) control algorithm is developed based on the formulation of linear matrix inequality (LMI) to ensure robust stability and performance. Second, an optimization algorithm using the Levenberg–Marquardt (LM) method is introduced to solve the nonlinear inverse mapping problem between the control law and the actual actuator outputs, addressing the nonlinear coupled control input distribution problem of the GCRS. In summary, the main contribution is the proposal of a new TVC UAV system based on GCRS. The PID control algorithm and LM algorithm were designed to solve the distribution problem of the actuation model and confirm altitude and attitude tracking missions. Finally, to validate the flight properties of the rocket-type UAV and the performance of the proposed control algorithm, several numerical simulations were conducted. The results indicate that the tightly coupled control input nonlinear inverse problem was successfully solved, and the proposed control algorithm achieved effective attitude stabilization even in the presence of disturbances.</div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141629550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fault causes and its detection in standalone PV system using ANN and GEO technique 使用 ANN 和 GEO 技术检测独立光伏系统中的故障原因及其检测方法

IF 6.3 2区计算机科学

ISA transactions Pub Date : 2024-07-06 DOI: 10.1016/j.isatra.2024.06.030

{"title":"Fault causes and its detection in standalone PV system using ANN and GEO technique","authors":"","doi":"10.1016/j.isatra.2024.06.030","DOIUrl":"10.1016/j.isatra.2024.06.030","url":null,"abstract":"<div>Power generation systems using photovoltaic (PV) technology have become increasingly popular due to their high production efficiency. A partial shading defect is the most common defect in this system under the process of production, diminishing both the amount and quality of energy produced. This paper proposes an Artificial Neural Network and Golden Eagle Optimization based prediction of the fault and its detection in a standalone PV system to recover the optimum performance and diagnosis of the PV system. The proposed technique combines the Artificial Neural Network (ANN) and Golden Eagle Optimization (GEO) algorithm. The major contribution of this work is to raise PV systems' performance. The result is a defect in the classification and identification of an ANN is used. The use of GEO provides an efficient optimization technique for ANN training, which reduces the training time and improves the accuracy of the model. The proposed technique is executed on the MATLAB site and contrasted with different present techniques, like genetic algorithm (GA),Elephant Herding Optimization (EHO) and Particle Swarm Optimization (PSO). The findings displays that the proposed technique is more accurate and effective than the existing methodologies for detecting and diagnosing defects in PV systems.</div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141695917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Refined composite multiscale slope entropy and its application in rolling bearing fault diagnosis 完善的复合多尺度斜率熵及其在滚动轴承故障诊断中的应用

IF 6.3 2区计算机科学

ISA transactions Pub Date : 2024-07-04 DOI: 10.1016/j.isatra.2024.07.008

{"title":"Refined composite multiscale slope entropy and its application in rolling bearing fault diagnosis","authors":"","doi":"10.1016/j.isatra.2024.07.008","DOIUrl":"10.1016/j.isatra.2024.07.008","url":null,"abstract":"<div>Rolling bearing is the key component of rotating machinery, and its vibration signal usually exhibits nonlinear and nonstationary characteristics when failure occurs. Multiscale permutation entropy (MPE) is an effective nonlinear dynamics analysis tool, which has been successfully applied to rolling bearing fault diagnosis in recent years. However, MPE ignores the deep amplitude information when measuring the complexity of the time series and the original multiscale coarse-graining is insufficient, which requires further research and improvement. In order to protect the integrity of information structure, a novel nonlinear dynamic analysis method termed refined composite multiscale slope entropy (RCMSlE) is proposed in this paper, which introduced the concept of refined composite to further boost the performance of MPE in nonlinear dynamical complexity analysis. Furthermore, RCMSlE utilizes a novel symbolic representation that takes full account of mode and amplitude information, which overcomes the weaknesses in describing the complexity and regularity of bearing signals. Based on this, a GWO-SVM multi-classifier is introduced to fulfill mode recognition, and then a new intelligent fault diagnosis method for rolling bearing based on RCMSlE and GWO-SVM is proposed. The experimental results show that the proposed method can not only accurately identify different fault types and degrees of rolling bearing, but also has a short computation time and better performance than other comparative methods.</div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141708968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0