Jyoti K. Sinha
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View article: A Unified Modelling Framework Combining FTA, RBD, and BowTie for Reliability Improvement
A Unified Modelling Framework Combining FTA, RBD, and BowTie for Reliability Improvement Open
Ensuring reliability and safety is essential in complex energy systems such as wind turbines, where failures can trigger unexpected downtimes, severe incidents, and significant costs. This study proposes a hybrid BowTie-based reliability f…
View article: Standardisation of Vibration-based Parameters for Rotor and Bearing for Machine Faults Detection Using Machine Learning Model
Standardisation of Vibration-based Parameters for Rotor and Bearing for Machine Faults Detection Using Machine Learning Model Open
Purpose In vibration-based condition monitoring of rotating machinery, machine learning (ML) models have demonstrated significant diagnostic capabilities; however, their efficacy is fundamentally constrained by the selection and quality of…
View article: A structured approach for shifting from TBM to CBM in the maintenance of freight locomotives
A structured approach for shifting from TBM to CBM in the maintenance of freight locomotives Open
This paper presents findings from a survey into locomotive and train maintenance professionals’ insights about their current maintenance approaches and a short review of existing research literature to help provide greater understanding of…
View article: The Effect of Defect Size and Location in Roller Bearing Fault Detection: Experimental Insights for Vibration-Based Diagnosis
The Effect of Defect Size and Location in Roller Bearing Fault Detection: Experimental Insights for Vibration-Based Diagnosis Open
In rotating machines, any faults in anti-friction bearings occurring during operation can lead to failures that are unacceptable due to considerable downtime losses and maintenance costs. Hence, early fault detection is essential, and diff…
View article: From Envelope Spectra to Bearing Remaining Useful Life: An Intelligent Vibration-Based Prediction Model with Quantified Uncertainty
From Envelope Spectra to Bearing Remaining Useful Life: An Intelligent Vibration-Based Prediction Model with Quantified Uncertainty Open
Bearings are pivotal components of rotating machines where any defects could propagate and trigger systematic failures. Once faults are detected, accurately predicting remaining useful life (RUL) is essential for optimizing predictive main…
View article: The Extent of Participation and Empowerment of Rural Women in Lac Cultivation in Koderma District of Jharkhand, India
The Extent of Participation and Empowerment of Rural Women in Lac Cultivation in Koderma District of Jharkhand, India Open
Lac cultivation in Koderma District, Jharkhand, offers a unique pathway for empowering rural women, serving as a significant source of income and socio-economic upliftment. This review examines the depth of women’s participation in various…
View article: Damage Identification in Steel Girder Based on Vibration Responses of Different Sinusoidal Excitations and Wavelet Packet Permutation Entropy
Damage Identification in Steel Girder Based on Vibration Responses of Different Sinusoidal Excitations and Wavelet Packet Permutation Entropy Open
Damage identification, both in terms of size and location, in bridges is important for timely maintenance and to avoid any catastrophic failure. An earlier experimental study showed that damage in a steel box girder orthotropic plate can b…
View article: Fault Detection of Rotating Machines Using poly-Coherent Composite Spectrum of Measured Vibration Responses with Machine Learning
Fault Detection of Rotating Machines Using poly-Coherent Composite Spectrum of Measured Vibration Responses with Machine Learning Open
This study presents an efficient vibration-based fault detection method for rotating machines utilising the poly-coherent composite spectrum (pCCS) and machine learning techniques. pCCS combines vibration measurements from multiple bearing…
View article: A framework for analysis of stakeholder dynamics and value creation in industrial maintenance projects: the stakeholder ipot
A framework for analysis of stakeholder dynamics and value creation in industrial maintenance projects: the stakeholder ipot Open
This paper proposes a methodological approach that can be applied in practice for evaluating stakeholder dynamics and assessing projects against appropriate value propositions within an industrial maintenance project context. A conceptual …
View article: Sparse Tensor Decomposition of Multi-Sensory Data for Fault Localization in Rotating Machinery Health Monitoring
Sparse Tensor Decomposition of Multi-Sensory Data for Fault Localization in Rotating Machinery Health Monitoring Open
Multi-sensor monitoring is prevalent in modern structural health monitoring (SHM) practice. As the number of sensors and sampling requirements increase, a monitoring sensor network can generate substantial data which are high-volume and hi…
View article: Two-step vibration-based machine learning model for the fault detection and diagnosis in rotating machine and its blind application
Two-step vibration-based machine learning model for the fault detection and diagnosis in rotating machine and its blind application Open
A robust and reliable condition monitoring and fault diagnosis system is crucial for an efficient operation of industries. Because of the advances in technologies over the past few decades, there is an increased interest in developing inte…
View article: A Comprehensive 3-Steps Methodology for Vibration-based Fault Detection, Diagnosis and Localization in Rotating Machines
A Comprehensive 3-Steps Methodology for Vibration-based Fault Detection, Diagnosis and Localization in Rotating Machines Open
In any industry, it is the requirement to know whether the machine is healthy or not to operate machine further. If the machine is not healthy then what is the fault in the machine and then finally its location. The paper is proposing a 3-…
View article: Early Prediction of Remaining Useful Life for Rolling Bearings Based on Envelope Spectral Indicator and Bayesian Filter
Early Prediction of Remaining Useful Life for Rolling Bearings Based on Envelope Spectral Indicator and Bayesian Filter Open
On top of the condition-based maintenance (CBM) practice for rotating machinery, the robust estimation of remaining useful life (RUL) for rolling-element bearings (REB) is of particular interest. The failure of a single bearing often resul…
View article: Stakeholder dynamics and their impact on value creation for industrial maintenance projects-a literature review
Stakeholder dynamics and their impact on value creation for industrial maintenance projects-a literature review Open
This paper analyses research developments in the dynamics of stakeholders and their impact mechanisms on the creation of value through a literature review. Three databases, Scopus, Science Direct and Google Scholar are selected to search a…
View article: Experimental Vibration Data in Fault Diagnosis: A Machine Learning Approach to Robust Classification of Rotor and Bearing Defects in Rotating Machines
Experimental Vibration Data in Fault Diagnosis: A Machine Learning Approach to Robust Classification of Rotor and Bearing Defects in Rotating Machines Open
This study builds upon previous research that utilised a vibration-based machine learning (VML) approach for diagnosing rotor-related faults in rotating machinery. The original method used artificial neural networks (ANN) to classify rotor…
View article: Adaptive Band Extraction Based on Low Rank Approximated Nonnegative Tucker Decomposition for Anti-Friction Bearing Faults Diagnosis Using Measured Vibration Data
Adaptive Band Extraction Based on Low Rank Approximated Nonnegative Tucker Decomposition for Anti-Friction Bearing Faults Diagnosis Using Measured Vibration Data Open
Condition monitoring and fault diagnosis are topics of growing interest for improving the reliability of modern industrial systems. As critical structural components, anti-friction bearings often operate under harsh conditions and are cont…
View article: Reliability of quantitative risk models: a case study from offshore gas production platform
Reliability of quantitative risk models: a case study from offshore gas production platform Open
In response to the competing factors governing the operation of oil and gas facilities, i.e., the stringent safety and environmental regulations, and the challenging business environment that entails minimizing the running cost, a risk-bas…
View article: Mathematical Validation of Experimentally Optimised Parameters Used in a Vibration-Based Machine-Learning Model for Fault Diagnosis in Rotating Machines
Mathematical Validation of Experimentally Optimised Parameters Used in a Vibration-Based Machine-Learning Model for Fault Diagnosis in Rotating Machines Open
Mathematical models have been widely used in the study of rotating machines. Their application in dynamics has eased further research since they can avoid time-consuming and exorbitant experimental processes to simulate different faults. T…
View article: Robust vibration-based faults diagnosis machine learning model for rotating machines to enhance plant reliability
Robust vibration-based faults diagnosis machine learning model for rotating machines to enhance plant reliability Open
Plant availability and reliability can be improved through a robust condition monitoring and fault diagnosis model to predict the current status (healthy or faulty) of any machines and critical assets. The model can then predict the exact …
View article: PM4 SMP model proposed for system reliability criticality assessment and maintainability improvement
PM4 SMP model proposed for system reliability criticality assessment and maintainability improvement Open
This paper gives a practical systematic approach towards the maintenance procedure optimisation of a critical industrial unit in operation, to improve its maintainability. The resolution of the maintainability challenge in the industrial u…
View article: Practical Demonstration of a Hybrid Model for Optimising the Reliability, Risk, and Maintenance of Rolling Stock Subsystem
Practical Demonstration of a Hybrid Model for Optimising the Reliability, Risk, and Maintenance of Rolling Stock Subsystem Open
Railway transport system (RTS) failures exert enormous strain on end-users and operators owing to in-service reliability failure. Despite the extensive research on improving the reliability of RTS, such as signalling, tracks, and infrastru…
View article: Improved quantitative risk model for integrity management of liquefied petroleum gas storage tanks: Mathematical basis, and case study
Improved quantitative risk model for integrity management of liquefied petroleum gas storage tanks: Mathematical basis, and case study Open
Chemical, petrochemical, and refinery sectors have been facing tougher safety, environmental and mechanical integrity regulations as well as challenges associated with the need for cost reduction to improve competitiveness. Risk‐based Insp…
View article: Parameter Optimisation in the Vibration-Based Machine Learning Model for Accurate and Reliable Faults Diagnosis in Rotating Machines
Parameter Optimisation in the Vibration-Based Machine Learning Model for Accurate and Reliable Faults Diagnosis in Rotating Machines Open
Artificial intelligence (AI)-based machine learning (ML) models seem to be the future for most of the applications. Recent research effort has also been made on the application of these AI and ML methods in the vibration-based faults diagn…
View article: Blind Application of Developed Smart Vibration-Based Machine Learning (SVML) Model for Machine Faults Diagnosis to Different Machine Conditions
Blind Application of Developed Smart Vibration-Based Machine Learning (SVML) Model for Machine Faults Diagnosis to Different Machine Conditions Open
Purpose The development and application of intelligent models to perform vibration-based condition monitoring in industry seems to be receiving attention in recent years. A number of such research studies using the artificial intelligence,…
View article: Mechanical characterization of millimetric agarose spheres using a resonant technique
Mechanical characterization of millimetric agarose spheres using a resonant technique Open
This paper presents a methodology for the mechanical characterization of agarose millimetric spheres using resonant principles. Detection of the modes of vibration was conducted using a low-cost experimental setup based on an electret micr…
View article: Hybrid Dynamic Probability-Based Modeling Technique for Rolling Stock Failure Analysis
Hybrid Dynamic Probability-Based Modeling Technique for Rolling Stock Failure Analysis Open
The purpose of this study is to propose a novel hybrid dynamic probability-based failure analysis technique consisting of dynamic Bayesian discretization (DBD) and stochastic Petri nets (SPNs) for railway rolling stock (RS) failure analysi…