F
Fengshou Gu
Researcher at University of Huddersfield
Publications - 560
Citations - 7894
Fengshou Gu is an academic researcher from University of Huddersfield. The author has contributed to research in topics: Condition monitoring & Fault (power engineering). The author has an hindex of 38, co-authored 495 publications receiving 6014 citations. Previous affiliations of Fengshou Gu include Anhui University of Science and Technology & University of Manchester.
Papers
More filters
Journal ArticleDOI
A review of numerical analysis of friction stir welding
TL;DR: In this article, the authors review the latest developments in the numerical analysis of friction stir welding processes, microstructures of friction-stir welded joints and the properties of friction spat welded structures.
Journal ArticleDOI
Prediction Models for Density and Viscosity of Biodiesel and their Effects on Fuel Supply System in CI Engines
TL;DR: In this article, the effect of temperature on density and viscosity of a variety of biodiesels and their blends on the performance of the engine fuel supply system such as fuel pump, fuel filters and fuel injector was investigated.
Journal ArticleDOI
The measurement of instantaneous angular speed
TL;DR: In this paper, a general-purpose data acquisition system and pure software implementation are presented for the measurement of instantaneous angular speed. But, the authors do not consider the use of hardware resources without incurring additional costs in the form of upgrades to the measurement system.
Journal ArticleDOI
Energy Harvesting Technologies for Achieving Self-Powered Wireless Sensor Networks in Machine Condition Monitoring: A Review.
TL;DR: The principles of a number of energy harvesting technologies applicable to industrial machines are overviews by investigating the power consumption of WSNs and the potential energy sources in mechanical systems.
Journal ArticleDOI
Detecting the crankshaft torsional vibration of diesel engines for combustion related diagnosis
TL;DR: In this paper, the authors presented an investigation of the diesel engine combustion related fault detection capability of crankshaft torsional vibration using the instantaneous angular speed (IAS) waveform.