19 papers · ranked by Valyu relevance
Saeid Safavi, Mohammad Amin Safavi, Hossein Hamid, Saber Fallah + 1 more
'Enrico Meli'] The primary focus of autonomous driving research is to improve driving accuracy and reliability. While great progress has been made, state-of-the-art algorithms still fail at times and some of these failures are due to the faults in sensors. Such failures may have fatal consequences. It therefore is…
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…
Umer Saeed, Young-Doo Lee, Sana Ullah Jan, Insoo Koo
Sensors’ existence as a key component of Cyber-Physical Systems makes it susceptible to failures due to complex environments, low-quality production, and aging. When defective, sensors either stop communicating or convey incorrect information. These unsteady situations threaten the safety, economy, and reliability of a…
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…
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…
Gonçalo Jesus, António Casimiro, Anabela Oliveira
Wireless sensor networks are being increasingly used in several application areas, particularly to collect data and monitor physical processes. Non-functional requirements, like reliability, security or availability, are often important and must be accounted for in the application development. For that purpose, there…
Malathy Emperuman, Srimathi Chandrasekaran
Sensor devices in wireless sensor networks are vulnerable to faults during their operation in unmonitored and hazardous environments. Though various methods have been proposed by researchers to detect sensor faults, only very few research studies have reported on capturing the dynamics of the inherent states in sensor…
Chun Lo, Yechao Bai, Mingyan Liu, Jerome P. Lynch
When faulty sensors are rare in a network, diagnosing sensors individually is inefficient. This study introduces a novel use of concepts from group testing and Kalman filtering in detecting these rare faulty sensors with significantly fewer number of tests. By assigning sensors to groups and performing Kalman…
David Haldimann, Marco Guerriero, Yannick Maret, Nunzio Bonavita + 2 more
'Gregorio Ciarlo' 'Marta Sabbadin'] Abstract—The problem of detecting and identifying sensor faults is critical for efficient, safe, regulatory-compliant and sustainable operations of modern systems. Their increasing complexity brings new challenges for the Sensor Fault Detection and Isolation (SFD-SFI) tasks. One of…
Jayant Gupchup, Abhishek Sharma, Andreas Terzis, Randal Burns + 1 more
'Alexander S. Szalay'] Abstract— Scientists deploy environmental monitoring networks to discover previously unobservable phenomena and quantify subtle spatial and temporal differences in the physical quantities they measure. Our experience, shared by others, has shown that measurements gathered by such networks are…
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…
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…
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…
Nickolas Gantzler, Adrian Henle, Praveen Thallapally, Xiaoli Fern + 1 more
A gravimetric, MOF-based (MOF = metal-organic framework) sensor array functions by measuring the mass of gas adsorbed in an array of MOFs. Changes in the gas composition are expected to produce detectable changes in the mass of gas adsorbed in the MOFs. In practical settings, multiple components of the gas adsorb into…