What is he best known for?
The fields of study he is best known for:
- Mechanical engineering
- Electrical engineering
- Artificial intelligence
Condition monitoring, Electronic engineering, Signal processing, Vibration and Fault are his primary areas of study.
His research integrates issues of Acoustics, Wireless sensor network, Energy harvesting, Noise and Control engineering in his study of Condition monitoring.
His work deals with themes such as Effective method, Encoder, Fault detection and isolation, Torsional vibration and Signal, which intersect with Electronic engineering.
His Signal processing research includes elements of Fast Fourier transform, Statistics, Principal component analysis, Kernel density estimation and Electric motor.
The study incorporates disciplines such as Gas compressor, Reciprocating compressor, Modal and Wavelet transform in addition to Vibration.
The various areas that he examines in his Fault study include Spur, Frequency domain, Multivariate statistics, Reference model and Modal analysis.
His most cited work include:
- A review of numerical analysis of friction stir welding (251 citations)
- A comparative study of acoustic and vibration signals in detection of gear failures using Wigner-Ville distribution. (236 citations)
- An approach to fault diagnosis of reciprocating compressor valves using Teager-Kaiser energy operator and deep belief networks (228 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Condition monitoring, Vibration, Fault, Fault detection and isolation and Acoustics.
His Condition monitoring study incorporates themes from Mechanical engineering, Electric motor, Control engineering, Automotive engineering and Artificial intelligence.
He combines subjects such as Lubrication, Structural engineering, Frequency domain, Nonlinear system and Reciprocating compressor with his study of Vibration.
His Fault research is multidisciplinary, incorporating elements of Control theory, Signal, Noise, Electronic engineering and Bearing.
The concepts of his Fault detection and isolation study are interwoven with issues in Time domain, Algorithm and Pattern recognition.
His studies deal with areas such as Diesel engine and Centrifugal pump as well as Acoustics.
He most often published in these fields:
- Condition monitoring (33.53%)
- Vibration (26.63%)
- Fault (26.04%)
What were the highlights of his more recent work (between 2017-2021)?
- Fault (26.04%)
- Condition monitoring (33.53%)
- Vibration (26.63%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Fault, Condition monitoring, Vibration, Acoustics and Fault detection and isolation.
His study in Fault is interdisciplinary in nature, drawing from both Demodulation, Signal, Control theory, Centrifugal pump and Bearing.
His Condition monitoring research incorporates elements of Lubrication, Automotive engineering and Feature extraction, Artificial intelligence, Pattern recognition.
His Vibration research is multidisciplinary, incorporating perspectives in Signal-to-noise ratio, Structural engineering, Numerical analysis and Standard deviation.
Andrew Ball focuses mostly in the field of Acoustics, narrowing it down to topics relating to Reciprocating compressor and, in certain cases, Control engineering.
His Fault detection and isolation research is multidisciplinary, relying on both Time domain, Reliability and Signal processing.
Between 2017 and 2021, his most popular works were:
- Energy Harvesting Technologies for Achieving Self-Powered Wireless Sensor Networks in Machine Condition Monitoring: A Review. (61 citations)
- A robust detector for rolling element bearing condition monitoring based on the modulation signal bispectrum and its performance evaluation against the Kurtogram (49 citations)
- Response analysis of an accelerating unbalanced rotating system with both random and interval variables (28 citations)
In his most recent research, the most cited papers focused on:
- Mechanical engineering
- Electrical engineering
- Artificial intelligence
The scientist’s investigation covers issues in Condition monitoring, Vibration, Fault, Bispectrum and Control theory.
His Condition monitoring study combines topics in areas such as Automotive engineering, Reliability engineering and Acoustic emission.
His Vibration study combines topics from a wide range of disciplines, such as Ball, Structural engineering, Spectral density and Nonlinear system.
The Bispectrum study combines topics in areas such as Algorithm, Rolling-element bearing, Modulation and Fault detection and isolation.
His biological study spans a wide range of topics, including Signal, Parametric statistics, Transient and Rotor.
His studies in Signal integrate themes in fields like Acoustics and Energy.
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