Analog circuits play a vital role in ensuring the availability of industrial systems. Unexpected circuit failures such systems during field operation can have severe implications. To address this concern, we developed method for detecting faulty condition, isolating fault locations, and predicting remaining useful performance analog circuits. Through successive refinement circuit's response to sweep signal, features are extracted diagnosis. The diagnostics problem is posed solved as pattern...

A novel data-driven prognostic approach for lithium-ion batteries remaining useful life (RUL) based on the Verhulst model, particle swarm optimization (PSO) and filter (PF) is proposed. First, model capacity fade trends of proposed, which used as fitting predicting respectively. Second, PSO applied to improve model. Third, improved combined with Euclidean distance employed determine upper lower bounds parameters. Fourth, estimate exploited Then, compensate prediction error, PF update...

The remaining useful life (RUL) prediction for hydrogen fuel cells is an important part of its prognostics and health management (PHM). Artificial neural networks (ANNs) are proven to be very effective in RUL prediction, as they do not need understand the failure mechanisms behind cells. A novel method based on gated recurrent unit ANN proposed this paper. Firstly, data were preprocessed remove outliers noises. Secondly, performance different compared, including back propagation network...

Soft-fault diagnosis and tolerance are two challenging problems in analog-circuit fault diagnosis. Although many analog faults can be diagnosed theoretically, they cannot accurately due to the influence of component tolerance. This paper proposes approaches tolerance-handling method soft-fault First, slope model its theoretical proof presented. In linear circuits, voltage equation between nodes is expressed by a point–slope-form which point determined nominal values on selected nodes, slope,...

The near-optimal test-point set selection for an analog fault dictionary is formulated as a heuristic depth-first graph search problem. Then, the test point process becomes graph-node-expanding process. During of expansion, information-theoretic concepts entropy are used to develop criterion how choose intermediate node expand. If has already isolated those faults that hard isolate, then residual can easily be isolated. difficulty isolating given evaluated by concept entropy. harder...

Prognostics of the remaining useful life (RUL) lithium-ion batteries is a crucial role in battery management systems (BMS). An artificial neural network (ANN) does not require much knowledge from systems, thus it prospective data-driven prognostic method batteries. Though ANN has been applied prognostics some references, no one compared based on different ANN. The generally can be classified to two categories: shallow ANN, such as back propagation (BP) and nonlinear autoregressive (NAR) deep...

Lithium-ion batteries (LiBs) are the most important part of electric vehicle (EV) systems. Because there two different degradation rates during LiB degradation, many two-phase models for LiBs. However, these methods do not consider randomness changing point in model and cannot update change time real time. Therefore, this paper proposes a method based on combination Wiener an extreme learning machine (ELM). The is used to derive mathematical expression remaining useful life (RUL), ELM...

A novel multidimensional fitness function discrete particle swarm optimization algorithm is proposed to optimize analog test point selection. The method uses fault isolation rate and the number of points formulate a search global minimal set, an elitist set used get more than one possible best solution in described approach. efficiency proven by same experiments verify other methods for optimal points. Results show that this paper cannot only reduce computation complexity but also shorten...

Feature selection techniques have become an apparent need for diagnostic methods such as a least squares support vector machine (LS-SVM). Most researchers use wavelet transform coefficients of the time-domain transient response data obtained from filtered analog circuits features to train LS-SVM classifier diagnose faults. But coefficient certain disadvantages no physical meanings. Thus, in this paper, two new feature vectors with clearly defined meanings based on curve and frequency filter...

To address the common issues of wrinkling, tearing, and uneven wall thickness in actual sheet metal stamping process outer ring needle roller bearings, this study analyzes critical technical indicators such as forming limits, distribution, principal strains detail. Three-dimensional models concave convex dies were constructed. The effects different parameters, including speed, edge pressure, thickness, friction coefficient, on quality parts investigated by varying these parameters....

Analog fault diagnosis has been an active area of research since the mid-1970s, now many methods use neural networks. But it needs lots samples and is also not easy to train network. We have presented a analog-circuit method based on LS-SVM. To reduce feature vectors LS-SVM, we energy high frequency wavelet transform coefficients (detail signals) various levels as features analog circuits. The simulation experiment results show that need less samples, produce higher class correct rate,...

Once all available measurements are determined, the highest testability index of a complex system is determined. To achieve such with lowest test cost, AND/OR graph search algorithms were developed for years to determine an optimal or near-optimal sequence. However, in most cases, achieving induces extremely high cost. The purpose this paper optimize set and sequence so as cut down cost while keeping required, not necessarily highest, FIR (Fault Isolation Rate) satisfied. Traditionally,...

Accurate prediction of the remaining useful life (RUL) lithium-ion batteries can ensure normal and effective operation power systems using batteries. However, how to select battery parameters through scientific methods accurately predict RUL values under high low temperature conditions are still a huge challenge. Thus according technique for order preference by similarity ideal solution (TOPSIS) based on information entropy, improved particle swarm optimization (PSO) moving average...

Invalid points, such as shadow and background, in the captured fringe patterns of projection profilometry (FPP) are often inevitable due to limited field view measurements three-dimensional (3D) imaging equipment. To ensure quality 3D reconstruction data, these invalid points must be identified removed. FPP captures co-frequency-based pattern sequences approximately distributes this data along an ideal cosine curve. We propose removal method based on error energy function. By analyzing...