Maximum releasable capacity and internal resistance are often used as the health indicators (HIs) of a lithium-ion battery for degradation modeling estimation remaining useful life (RUL). However, maximum is usually difficult to estimate in online applications due complex operating conditions field. Moreover, measuring too expensive be implemented on-line. In this paper, an HI extraction optimization framework requiring only parameters batteries proposed RUL estimation. The carries out raw...

Explore the potential mediating effects of anxiety symptoms and hopelessness on relationship between academic stress depressive among Chinese college students.A total 1309 students with informed consent were recruited from a local university in China. Academic stress, symptoms, hopelessness, assessed by self-report scales. Haye's PROCESS macro for SPSS was used to test hypothesized mediation effect symptoms.Anxiety common all significantly positively associated levels. could indirectly...

With the wide applications of unmanned aerial vehicle (UAV), operating safety becomes a critical issue. Thus, fault detection (FD) has been focused, which can realize alarm and schedule maintenance in time. Since accurate physical model UAV is usually difficult to obtain flight data with random noise both spatial temporal correlation, huge challenge posed FD. In this article, data-driven multivariate regression approach based on long short-term memory residual filtering (LSTM-RF) proposed...

With the wide applications of unmanned aerial vehicle (UAV) in civilian and military fields, its operational safety has drawn much attention. A series fault detection methods are studied to avoid disasters. Due capabilities strong feature extraction massive flight data processing, deep learning-based have received extensive However, restricted by UAV airborne size, weight, power consumption, a significant challenge is posed deploy these complicated application, which requires run real time....

In recent years, a notable development for predicting the remaining useful life (RUL) of components is prognostics that use data-driven approaches based on deep learning. particular, long short-term memory networks (LSTMNs) have been successfully applied in RUL prediction. However, to best our knowledge, these learning-based do not take into account uncertainty, and their prediction performance needs improvement. Bayesian model averaging (BMA) very ensemble method because it can quantify...

When localizing the position of an unknown node for wireless sensor networks, received signal strength indicator (RSSI) value is usually considered to fit a fixed attenuation model with corresponding communication distance. However, due some negative factors, relationship not valid in actual localization environment, which leads considerable error. Therefore, we present method improved RSSI-based through uncertain data mapping. Starting from advanced RSSI measurement, distributions tuples...

An approach to estimate the remaining useful life (RUL) by Echo State Network (ESN) is presented, which a new paradigm in recurrent neural network (RNN). ESN randomly establishes large sparse reservoir replace hidden layer of RNN, overcomes shortcomings complicated computing, difficulties determining topology traditional RNN. sub-models strategy composed classified models matching varied training data set retraining and classification explored RUL turbofan engine system. The experimental...

Unmanned Aerial Vehicle (UAV) can accomplish various specific tasks and play an increasingly essential role in military, industrial civil fields. However, the safety of UAV is lower than that manned aircraft, great economic loss caused due to its relatively high failure rate. Therefore, it significance study anomaly detection method for system. In recent years, deep learning has been widely applied fields outstanding advantages such as strong ability approximate complex functions automatic...

Fault detection for sensors of unmanned aerial vehicles is essential ensuring flight security, in which the control system conducts real-time relying on sensing information from sensors, and erroneous sensor data will lead to false commands, causing undesirable consequences. However, because scarcity faulty instances, it still remains a challenging issue fault detection. The one-class support vector machine approach favorable classifier without negative samples, however, sensitive outliers...

The aircraft auxiliary power unit (APU) is mainly used to provide electricity and compressed air the aircraft. Not only can it help start main engines, but also essential thrust for emergency landing. It required be reliable as high possible when installed in However, reality that degradation of APU a nonlinear process. In this term, data-driven method or physics-based hardly make accurate prediction remaining useful life (RUL) APU. Therefore, hybrid RUL proposed by fusing an artificial...

Accurate fault detection for unmanned aerial vehicle (UAV) actuators is essential ensuring flight safety and mission completion. Without the requirement of modeling complex physical mechanism, data-driven actuator approaches have attracted much attention. Among them, long short-term memory (LSTM) approach has shown superior performance due to its capability spatial–temporal features. However, uncertainty LSTM actually changeable under different conditions, which not been well considered in...


 Long term prediction such as multi-step time series is a challenging prognostics problem. This paper proposes an improved AR model called ND-AR (Nonlinear Degradation AutoRegression) for Remaining Useful Life (RUL) estimation of lithium-ion batteries. The nonlinear degradation feature the lithium- ion battery capacity analyzed and then non-linear accelerated factor extracted to improve linear model. In this model, can be obtained with curve fitting, applied adaptive data- driven...

Performance degradation and remaining useful life (RUL) estimation for lithium-ion battery has broad practical applications in almost all industrial fields. The model-based prognostics is so complicated, moreover, they are not suitable on-line application since that more parameters modeling information should be obtained advance. An data-driven RUL prediction approach based on Online Support Vector Regression (Online SVR) proposed. With SVR algorithm, the monitoring data series can...

In aerospace engineering, condition monitoring is an important reference for evaluating the performance of complex systems. Especially, effective anomaly detection, based on telemetry data, plays role system health management a spacecraft. With advantages easy-to-use, high efficiency, and data-driven, predicted model has been applied anomalous point detection data. However, compared with abnormal mode, fragment more attractive meaningful identification. Therefore, strategy proposed...

DC/DC converters play an important role in electrical systems. The anomalous state of a dc/dc converter has major impact on the operation back-end components and entire system. To effectively recognize state, particularly for with unknown circuit structures, online anomaly detection method that involves statistical feature estimation using Gaussian process regression (GPR) genetic algorithm (GA) is proposed. In proposed method, normal output range built upon signal GPR, seven features are...

The aluminum electrolytic capacitor (AEC) is one of the most important parts a power electronic converter. Throughout its lifespan, equivalent series resistance (ESR) AEC will increase, which affect performance To guarantee reliability converter, it necessary to monitor health state AEC, for common technique estimate ESR AEC. Equipment with high sampling rate usually required because converter works at frequency. This requirement increase cost monitoring. address this issue, article proposes...

The joint estimation of the spectrum, carrier, and direction arrival (DOA) is significant in radar, sonar, wireless communications, cognitive radio systems. traditional parameter measurement methods based on Shannon–Nyquist theorem require very high sampling rates, which put a lot pressure sampling, processing, storage devices. In this article, novel beamforming modulated wideband converter (BMWC) system for DOA proposed to improve robustness reduce structural complexity. From spatial signal...

Organic materials show great potential in the fields of biomimetics and neuromorphic computing due to their molecular diversity, cost-effective manufacturing processes, unique optical chemical properties, remarkable mechanical flexibility. In this work, an optoelectronic synaptic device based on organic semiconductor poly[2,5-(2-octyldodecyl)-3,6-diketopyrrolopyrrole-alt-5,5-(2,5-di(thien-2-yl))thieno[3,2b]thiophene] (DPPDTT) is fabricated by a simple solution process. The successfully...