Research of Condition Monitoring and Fault Diagnosis Techniques for Wind Turbine Gearbox

2012 ◽  
Vol 197 ◽  
pp. 206-210 ◽  
Author(s):  
Xian You Zhong ◽  
Liang Cai Zeng ◽  
Chun Hua Zhao ◽  
Jin Zhang ◽  
Shi Qing Wan
Keyword(s):  
Fault Diagnosis ◽  
Wind Turbine ◽  
Condition Monitoring ◽  
Future Research ◽  
Wind Turbine Gearbox ◽  
Research Directions ◽  
Long Time ◽  
Future Research Directions ◽  
Wind Power Industry ◽  
The Cost

Wind power industry enormously expanded during the last several years. However, wind turbines are subjected to different sorts of failures, which lead to the increasement of the cost. The wind turbine gearbox is the most critical component in terms of high failure rates and long time to repair. This paper described common failures and root causes of wind turbine gearboxes. Then it focused on fault diagnosis and monitoring techniques for the wind turbine gearbox. The challenges and future research directions were presented, and the simulator rig of wind turbine gearbox was designed to develop condition monitoring and fault diagnosis techniques for wind turbine gearbox.

scholarly journals Vestas V90-3MW Wind Turbine Gearbox Health Assessment Using a Vibration-Based Condition Monitoring System

2016 ◽  
Vol 2016 ◽  
pp. 1-18 ◽  
Author(s):  
A. Romero ◽  
Y. Lage ◽  
S. Soua ◽  
B. Wang ◽  
T.-H. Gan
Keyword(s):  
Fault Diagnosis ◽  
Wind Turbine ◽  
Condition Monitoring ◽  
Learning Algorithm ◽  
Health Assessment ◽  
Field Trials ◽  
Health Condition ◽  
Normal Operation ◽  
Wind Turbine Gearbox ◽  
Operation Conditions

Reliable monitoring for the early fault diagnosis of gearbox faults is of great concern for the wind industry. This paper presents a novel approach for health condition monitoring (CM) and fault diagnosis in wind turbine gearboxes using vibration analysis. This methodology is based on a machine learning algorithm that generates a baseline for the identification of deviations from the normal operation conditions of the turbine and the intrinsic characteristic-scale decomposition (ICD) method for fault type recognition. Outliers picked up during the baseline stage are decomposed by the ICD method to obtain the product components which reveal the fault information. The new methodology proposed for gear and bearing defect identification was validated by laboratory and field trials, comparing well with the methods reviewed in the literature.

MATHEMATICAL MODELLING FOR FISH FEED FORMULATION OF MYSTUS NEMURUS SP. CATFISH: OPTIMIZING GROWTH AND NUTRIENTS REQUIREMENTS

2018 ◽  
Vol 80 (6) ◽  
Author(s):  
Nur Aidya Hanum Aizam ◽  
Rabiatul Adawiyah Ibrahim ◽  
Raphael Lee Kuok Lung ◽  
Pang Yen Ling ◽  
Aidilla Mubarak
Keyword(s):  
Mathematical Model ◽  
Nutrient Composition ◽  
Future Research ◽  
Fish Feed ◽  
Research Directions ◽  
Feed Formulation ◽  
Future Research Directions ◽  
The Cost ◽  
The Mathematical Model ◽  
Mystus Nemurus

This study integrates mathematical model in the plan of producing a fish feed formulation by reducing the total cost without neglecting the nutrient requirements. This study focuses on producing the perfect combination of fish feed for Mystus nemurus sp. catfish in different stages of life. The mathematical model developed will consider their required nutrients in each stage, the cost of each ingredient and the amount of nutrients to be consumed (nutrient composition of fish feed ingredients). This research employs AIMMS mathematical software to assist with the computation. The results from this study obtain a much better combination of different ingredients compared to available commercial pellets in terms of nutrient composition and production cost. The combinations yield much cheaper costs yet boosts up the nutrient consumptions, which is an eye-opener for independent local fish farmers. Thorough discussion on utilizing the results with future research directions will also be included.

Fault Diagnosis for Wind Turbine Gearboxes Based on EMD and the Energy Operator

2013 ◽  
Vol 281 ◽  
pp. 10-13 ◽  
Author(s):  
Xian You Zhong ◽  
Liang Cai Zeng ◽  
Chun Hua Zhao ◽  
Xian Ming Liu ◽  
Shi Jun Chen
Keyword(s):  
Fault Diagnosis ◽  
Wind Turbine ◽  
Empirical Mode Decomposition ◽  
Energy Operator ◽  
Vibration Signal ◽  
Intrinsic Mode Functions ◽  
Wind Turbine Gearbox ◽  
Mode Decomposition ◽  
The Cost ◽  
Fault Information

Wind turbine gearbox is subjected to different sorts of failures, which lead to the increasement of the cost. A approach to fault diagnosis of wind turbine gearbox based on empirical mode decomposition (EMD) and teager kaiser energy operator (TKEO) is presented. Firstly, the original vibration signal is decomposed into a number of intrinsic mode functions (IMFs) using EMD. Then the IMF containing fault information is analyzed with TKEO, The experimental results show that EMD and TKEO can be used to effectively diagnose faults of wind turbine gearbox.

scholarly journals The Cost of Excessive Smartphone Use: Guilt Cross the Work-Family Domains

2021 ◽  
Vol 12 ◽  
Author(s):  
Yujing Liu ◽  
Jing Du ◽  
Yuan Li
Keyword(s):  
Future Research ◽  
Family Role ◽  
Role Performance ◽  
Research Directions ◽  
Work Related ◽  
The Family ◽  
Future Research Directions ◽  
Smartphone Use ◽  
Work Family ◽  
The Cost

Empirical evidence has accumulated showing that smartphone use at work has the double-edged sword impacts on work-related attitudes and behaviors, but little is known about how its effects transmit and spill over from the workplace to the family domain. Drawing upon compensatory ethics theory, we hypothesize positive associations of employees’ daily private smartphone use at work with their family role performance after work through feeling of guilt. Using an experience sampling methodology, we test our hypotheses in a sample of 101 employees who completed surveys across 10 consecutive workdays. Multilevel path analysis results showed that excessive smartphone use at work triggered experienced guilt, and had a positive indirect effect on family role performance via feeling of guilt. Furthermore, employees with high ability of emotion regulation can be better resolve own painful emotion by engaging in family role performance. Theoretical and practical implications, limitations, and propose future research directions are discussed.

scholarly journals Current Advances in Hyperspectral Face Recognition

2020 ◽  
Author(s):  
Rizwan Qureshi ◽  
Muhammad Uzair ◽  
Anam Zahra
Keyword(s):  
Computer Vision ◽  
Face Recognition ◽  
Hyperspectral Imaging ◽  
Hyperspectral Image ◽  
Document Image ◽  
Hyperspectral Images ◽  
Future Research ◽  
Research Directions ◽  
Future Research Directions ◽  
The Cost

Hyperspectral imaging systems are well established, for satellite, remote sensing and geosciences applications. Recently, the reduction in the cost of hyperspectral sensors and increase in the imaging speed has attracted computer vision scientists to apply hyperspectral imaging to ground based computer vision problems such as material classification, agriculture, chemistry and document image analysis. Hyperspectral imaging has also been explored for face recognition; to tackle the issues of pose and illumination variations by exploiting the richer spectral information of hyperspectral images. In this article, we present a detailed review on the potential of hyperspectral imaging for face recognition. We present hyperspectral image aquisition process and discuss key preprocessing challenges. We also discuss hyperspectral face recognition databases and techniques for feature extraction from the hyperspectral images. Potential future research directions are also highlighted

scholarly journals A Comprehensive Survey of COVID-19 Detection Using Medical Images

2020 ◽  
Author(s):  
Faisal Muhammad shah ◽  
Sajib Kumar Saha Joy ◽  
Farzad Ahmed ◽  
Mayeesha Humaira ◽  
Amit Saha Ami ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Medical Images ◽  
Future Research ◽  
Research Directions ◽  
X Ray ◽  
Time Period ◽  
Comprehensive Survey ◽  
Future Research Directions ◽  
The Cost ◽  
Day By Day

The outbreak of the COVID-19 pandemic caused the death of a large number of people. Millions ofpeople are infected by this virus and are still getting infected day by day. As the cost and required time ofconventional RT-PCR tests to detect COVID-19, researchers are trying to use medical images like X-Ray andComputed Tomography (CT) images to detect it with the help of Artificial Intelligence (AI) based systems. Inthis paper, we reviewed some of these newly emerging AI-based models that can detect COVID-19 frommedical images using X-Ray or CT of lung images. We collected information about available research resourcesand inspected a total of 80 papers from the time period of February 21, 2020 to June 20, 2020. We explored andanalyzed datasets, preprocessing techniques, segmentation, feature extraction, classification and experimentalresults which can be helpful for finding future research directions in the domain of automatic diagnosis ofCovid-19 disease using Artificial Intelligence (AI) based frameworks.

scholarly journals Current Advances in Hyperspectral Face Recognition

2020 ◽  
Author(s):  
Rizwan Qureshi ◽  
Muhammad Uzair ◽  
Anam Zahra
Keyword(s):  
Computer Vision ◽  
Face Recognition ◽  
Hyperspectral Imaging ◽  
Hyperspectral Image ◽  
Document Image ◽  
Hyperspectral Images ◽  
Future Research ◽  
Research Directions ◽  
Future Research Directions ◽  
The Cost

Hyperspectral imaging systems are well established, for satellite, remote sensing and geosciences applications. Recently, the reduction in the cost of hyperspectral sensors and increase in the imaging speed has attracted computer vision scientists to apply hyperspectral imaging to ground based computer vision problems such as material classification, agriculture, chemistry and document image analysis. Hyperspectral imaging has also been explored for face recognition; to tackle the issues of pose and illumination variations by exploiting the richer spectral information of hyperspectral images. In this article, we present a detailed review on the potential of hyperspectral imaging for face recognition. We present hyperspectral image aquisition process and discuss key preprocessing challenges. We also discuss hyperspectral face recognition databases and techniques for feature extraction from the hyperspectral images. Potential future research directions are also highlighted

A Review of Condition Monitoring and Fault Diagnosis of Wind Turbine Gearbox Using Signal Processing

2012 ◽  
Vol 608-609 ◽  
pp. 673-676 ◽  
Author(s):  
Zhi Qiang Xu ◽  
Jian Hua Zhang ◽  
Jing Fang Ji ◽  
Xiang Jun Yu
Keyword(s):  
Signal Processing ◽  
Fault Diagnosis ◽  
Wind Turbine ◽  
Failure Rate ◽  
Condition Monitoring ◽  
Economic Losses ◽  
High Failure Rate ◽  
Wind Turbine Gearbox ◽  
Signal Process

Due to gearbox is one of the high failure rate component in the wind turbine, the research of it has been paid wide attention in recent years. This paper reviewed the two aspects about the wind turbine gearbox. First, some signal process methods including how to determine the threshold were summarized. Then, the condition monitoring and fault diagnosis of gearbox were reviewed using the measured signals. These researches are benefited for reducing economic losses which is caused by the gearbox failure. Based on the above reviews, this paper gives some developmental direction.

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