This paper formulates wireless sensor networks (WSNs) fault diagnosis problem as a pattern-classification and introduces newly developed algorithm, neighborhood hidden conditional random field (NHCRF), for determining states between sensors. The health conditions of WSN are determined by using the NHCRF model to estimate posterior probability different faulty scenarios. can improve diagnosis, because it has relaxed independence assumption Markov model. To enhance robustness antinoise ability...

Deep learning has been obtained extensive attention in many fields. In this paper, a fault detection based on deep belief network (DBN) method is proposed for nonlinear processes. Then the industrial processes abnormal monitoring realized by test statistics, which built feature variables and residual produced DBN. The Tennessee-Eastman (TE) process have used to evaluate efficiency of method.

Due to the interconnected characteristics between subsystems and strong correlation within subsystems, monitoring of plant-wide processes has become a challenging problem, especially for tandem that exist in various industrial fields, such as petrochemicals, metallurgy, sewage treatment. In this article, novel spatio-temporal method is proposed hot strip mill (HSM) process, typical process. First, process divided into different subblocks based on structure. Then, distributed conditional...

This article presents SPSTS, an automated sequential procedure for computing point and Confidence-Interval (CI) estimators the steady-state mean of a simulation-generated process subject to user-specified requirements CI coverage probability relative half-length. SPSTS is first method based on Standardized Time Series (STS) area variance parameter (i.e., sum covariances at all lags). Whereas its leading competitors rely batch means remove bias due initial transient, estimate parameter,...

Customized production, quality variation of raw materials and other factors make industrial processes work in multiple operating modes. In general, complex have strong nonlinearity under each mode. this paper, a Gaussian mixture variational autoencoder (GMVAE) model, which combines with VAE, is proposed to monitor nonlinear Due the distribution limitation latent variable space, GMVAE can not only automatically extract features system, but also these follow distribution. Based on space...

The stable and efficient operation of the cold source system can significantly reduce building energy consumption improve indoor comfort. Health monitoring is a necessary means to ensure such requirement. Due variations ambient temperature load, often running in multiple modes, which limits application conventional health methods with poor performance, e.g. high false alarm rate. Therefore, this paper uses our previously proposed method, just-in-time-learning aided canonical correlation...

We propose SPSTS, an automated sequential procedure for computing point and confidence-interval (CI) estimators the steady-state mean of a simulation output process. This is based on variance computed from standardized time series, it characterized by its simplicity relative to methods batch means ability deliver CIs parameter The effectiveness SPSTS evaluated via comparisons with means. In preliminary experimentation waiting-time process M/M/1 queue server utilization 90%, we found that...

<title>Abstract</title> Seismic signal detection is a crucial technology for enhancing the efficiency of earthquake early warning systems.However, existing deep learning-based seismic models often face limitations in resource-constrained monitoring engineering environments due to their high computational resource demands. To address this challenge, we introduce an innovative network, which integrates advantages Coordinate Attention modules and Transformer attention mechanisms (ICAT-net). It...

Discrete element method was used to investigate the rutting depth variation of asphalt mixture under condition different aggregate gradation, varying loads and temperatures. The results indicate that for either gap gradation or continuous mixture, when content coarse is same, ability resist deformation specimens enhances maximum nominal size increases, latter superior former. Rutting depths with loading sequences are similar. For same average load, close. When temperature very close changes...

We present an experimental study of pattern variability and defectivity, based on a large data set with more than 112 million SEM measurements from HMI high-throughput e-beam tool. The test case is 10nm node SRAM via array patterned DUV immersion LELE process, where we see variation in mean size litho sensitivities between different unique patterns that leads to seemingly qualitative differences defectivity. available volume enables further analysis reliably distinguish global local CDU...

The efficient operation of the cooling source system depends on a reasonable control strategy, and accurate load prediction provides important guidance for optimal control. As there are numerous variables that affect loads, many methods try to exploit in temporal domain. However, correlations between not reasonably utilized by methods. To implicit information data obtain an prediction, correlative graph convolutional network (CTGCN) is used predict load, which can extracted correlation...

The accurate prediction of remaining useful life (RUL) can provide reference information for the maintenance aircraft engines, and it is also an important guarantee improving reliability safety system. Generally, effective RUL achieved through a large amount monitoring data, while how to extract degradation characteristics from contaminated data monitor performance trend system, then estimate challenge. Therefore, method based on support vector description (SVDD) particle filter (PF)...

Process monitoring and fault detection (PM-FD) methods have been widely used in practice to ensure the safe operation of process. It has found that although lots PM-FD were proposed, there is few work focusing on developing a versatile performance assessment software determine optimal method for on-line monitoring. This paper devoted develop MATLAB-based toolbox (PA-OMT) process The friendly graphical user interface (GUI), packaged into separate version. can be installed different versions...

In recent years, the rapid development of high-speed railway, and video inspection are important means railway safety detection. However, in process shooting, there overexposure underexposure, which lead to wrong classification dropper fault. It is urgent solve this problem improve accuracy fault Therefore, an image filtering method proposed, can determine whether abnormal exposure by calculating maximum minimum gray value row. Then random forest used classify collected sample data remove...

Probabilistic models, which can model the process noise and handle problem of missing data in probabilistic framework, recently have been got much attention monitoring fa...

With the development of Internet Things, collected data from Things include more and incomplete because network fault or sensing terminal breakdown. A lot do harm to IoT application decision. For filling in effectively, this paper presents a new method based on power graph, which first uses graph abstract important attributes objects. Then proposed fills using improved similarity. Experimental results show effectiveness our method, especially for massive IoT.

Chillers are the key equipment in heating, ventilation, and air conditioning (HVAC) system, which has a decisive impact on daily life industrial production. However, since operation maintenance of chillers mainly rely personnel experience, this may lead to problems such as unreasonable setting operating parameters, untimely troubleshooting abnormalities, degradation unit performance, resulting additional waste energy. Therefore, researching performance monitoring trend visualization...

Solid-state batteries (SSB) have received increasing attention as a next-generation energy storage technology due to their potential in delivering superior density, power density and safety compared commercial Li-ion batteries. One of the main challenges limiting practical implementation is rapid capacity decay caused by loss contact between cathode active material solid electrolyte upon cycling. Here we use promising high voltage, low-cost spinel LiNi0.5Mn1.5O4 (LNMO) model system...