Universiti Teknologi Malaysia

About: Universiti Teknologi Malaysia is a education organization based out in Johor Bahru, Malaysia. It is known for research contribution in the topics: Membrane & Control theory. The organization has 21644 authors who have published 39500 publications receiving 520635 citations.

Gearbox Fault Diagnosis Using a Deep Learning Model With Limited Data Sample

Abstract: Massive volumes of data are needed for deep learning (DL) models to provide accurate diagnosis results. Numerous studies of fault diagnosis systems have demonstrated the effectiveness of DL models over shallow machine learning (SL) in terms of feature extraction, feature dimensional reduction and diagnosis performance. Occasionally, during data acquisition, a problem with a sensor renders some of the data potentially unsuitable for further analysis, leaving only a small data sample. To compensate for this deficiency, a DL model based on a stacked sparse autoencoder (SSAE) model is designed to deal with limited sample data. In this article, the fault diagnosis system is developed based on time-frequency image pattern recognition. Therefore, two gearbox datasets are used to evaluate the proposed diagnosis system. The results from the experiments prove that the proposed system is capable of achieving high diagnostic accuracy even with limited sample data. The proposed fault diagnosis system achieved 100% and 99% diagnosis performance on experimental gearbox and wind turbine gearbox datasets, respectively. The proposed diagnosis system increased diagnosis performance between 10% and 20% over the standard SSAE model. In addition, the proposed model achieved higher diagnosis performance compared to deep neural network and convolutional neural networks models.

Green retrofitting – A review of current status, implementations and challenges

Abstract: One of the largest threats to future development is climate change Apparently, the building sector has been the largest source of greenhouse gas production One prospective solution to this is “green building” that aims to provide environmentally sustainable building in terms of design, construction and maintenance However, green buildings symbolize the next stage of buildings, and the recent growth of new green building constructions is inadequate to overcome the negative impact of existing buildings One logical solution to reduce the environmental impact of the existing buildings is through green retrofitting Yet there is lack of systematic review on the existing body of knowledge on green retrofitting which is critical for future research This paper aims to critically review the existing literature on green retrofitting and to identify contemporary research trends Additionally, with the view to the current challenges, barriers, obstacles or problems to green retrofitting, this study highlights the needs to identify the Critical Success Factors (CSFs) for successful implementation of green retrofit projects