18 papers · ranked by Valyu relevance
Xiuguo Zou, Wenchao Liu, Zhiqiang Huo, Sunyuan Wang + 8 more
'Chengrui Xin' 'Yungang Bai' 'Zhenyu Liang' 'Yan Gong' 'Yan Qian' 'Lei Shu' 'Giovanni Betta'] Sensors have been used in various agricultural production scenarios due to significant advances in the Agricultural Internet of Things (Ag-IoT), leading to smart agriculture. Intelligent control or monitoring systems rely…
Shahnaz TayebiHaghighi, Insoo Koo
Anomaly identification for internal combustion engine (ICE) sensors has become an important research area in recent years. In this work, a proposed indirect fuzzy Lyapunov-based computed ratio observer integrated with a support vector machine (SVM) was designed for sensor fault classification. The proposed fuzzy…
Daijiry Narzary, Kalyana Chakravarthy Veluvolu, Dong Wang, Shilong Sun + 1 more
'Shilong Sun' 'Changqing Shen'] The research on sensor fault detection has drawn much interest in recent years. Abrupt, incipient, and intermittent sensor faults can cause the complete blackout of the system if left undetected. In this research, we examined the observer-based residual analysis via index-based…
Amer Kajmakovic, Konrad Diwold, Kay Römer, Jesus Pestana + 2 more
'Nermin Kajtazovic' 'Hossam A. Gabbar'] Safety-critical automation often requires redundancy to enable reliable system operation. In the context of integrating sensors into such systems, the one-out-of-two (1oo2) sensor architecture is one of the common used methods used to ensure the reliability and traceability of…
Nguyen Tri Nghia, Nguyen Van Son, Nguyen Thi Hanh
Wireless Sensor Networks (WSN) are the backbone of essential monitoring applications, but their deployment in unfavourable conditions increases the risk to data integrity and system reliability. Traditional fault detection methods often struggle to effectively balance accuracy and energy consumption, and they may not…
Shashank Verma, Yousaf Rahman, E. Dogan Sumer, Dennis S. Bernstein
Sensor-fault detection is crucial for the safe operation of autonomous vehicles. This paper introduces a novel kinematicsbased approach for detecting and identifying faulty sensors, which is model-independent, rule-free, and applicable to ground and aerial vehicles. This method, called kinematics-based sensor fault…
Luis Miguel Moreno Haro, Adaiton Oliveira-Filho, Bruno Agard, Antoine Tahan + 1 more
'Antoine Tahan' 'Yi Qin'] This paper presents a novel approach for detecting sensor failures using image-based feature representation and the Convolutional Variational Autoencoder (CVAE) model. Existing methods are limited when analyzing multiple failure modes simultaneously or adapting to diverse sensor data. This…
John Z. Cao, Muhammad Umar B. Niazi, Matthieu Barreau, Karl Henrik Johansson
'Karl Henrik Johansson'] Abstract—This paper presents a novel observer-based approach to detect and isolate faulty sensors in nonlinear systems. The proposed sensor fault detection and isolation (s-FDI) method applies to a general class of nonlinear systems. Our focus is on s-FDI for two types of faults: complete…
Tanish Baranwal, Srihari Varada, Santanu Das, Mohammad R. Haider
—In this article, we present a novel redundancy scheme to realize a fault-tolerant IoT structure for application in high-reliability systems. The proposed fault-tolerant structure uses a centralized data fusion block and triplicated IoT devices, along with software-based "digital twins", that duplicate the function of…
Di Wu, Kari Koskinen, Eric Coatanea, Jongmyon Kim
The data collected from sensors are subject to the presence of anomaly data. These anomalies may stem from sensor malfunctions or poor communication. Prior to the processing of the data, it is imperative to detect and isolate the anomaly data from the substantial volume of normal data. The utilization of data-driven…
Kabeer Gulati, Zuhaib Ahmad, Abhishek Raj
Any complex dynamic system's ability to function successfully depends in significant part on the accuracy of the sensor data; hence sensor data validation is crucial. Because sensor data is utilised for monitoring and oversight, erroneous sensor data would result in overall poor process output. In this study, the…
Federico Mazzoli, Davide Alghisi, Vittorio Ferrari, Andrea Cataldo
This paper presents a suitably general model for resistive displacement sensors where the model parameters depend on the current sensor conditions, thereby capturing wearout and failure, and proposes a novel fault detection method that can be seamlessly applied during sensor operation, providing self-diagnostic…
Loïc J. Azzalini, David Crompton, Gabriele M. T. D’Eleuterio, Frances Skinner + 1 more
Data assimilation techniques for state and parameter estimation are frequently applied in the context of computational neuroscience. In this work, we show how an adaptive variant of the unscented Kalman filter (UKF) performs on the tracking of a conductance-based neuron model. Unlike standard recursive filter…
Anomadarshi Barua, Mohammad Abdullah Al Faruque
Sensors are one of the most pervasive and integral components of today's safety-critical systems. Sensors serve as a bridge between physical quantities and connected systems. The connected systems with sensors blindly believe the sensor as there is no way to authenticate the signal coming from a sensor. This could be…
Amir Eshaghi Chaleshtori, Abdollah Aghaie
system based on data-envelopment analysis Authors: ['Amir Eshaghi Chaleshtori' 'Abdollah Aghaie'] Several methods have been proposed to identify which sensor sets are optimal for finding and localizing faults under different conditions for mechanical equipment. In order to preserve acceptable performance while…
Authors not listed
The ongoing threat of global warming necessitates a shift towards clean energy sources to meet rising demands while reducing carbon emissions. Polymer electrolyte fuel cells (PEFCs) represent a promising technology for both mobile and stationary applications but their poor operational lifetimes and frequent faults are…
Authors not listed
Predictive maintenance (PdM) can substantially reduce unplanned downtime and maintenance costs in industrial systems. In this study, we develop a proof-of-concept XGBoost-based machine learning pipeline for detecting component faults in a hydraulic test rig using the publicly available UCI Condition Monitoring of…
Paul Morris, Cory Simon
In many gas sensing tasks, we simply wish to become aware of gas compositions that deviate from normal, "business-as-usual" conditions. We provide a methodology, illustrated by example, to computationally predict the performance of a gas sensor array design for detecting anomalous gas compositions. Specifically, we…