Weerasinghe, R.; Ratnayake, C. Measuring Onshore Wind Turbine Noise Levels for Developing an Expert Knowledge-Based Risk Assessment Approach. Preprints2024, 2024101589. https://doi.org/10.20944/preprints202410.1589.v1
APA Style
Weerasinghe, R., & Ratnayake, C. (2024). Measuring Onshore Wind Turbine Noise Levels for Developing an Expert Knowledge-Based Risk Assessment Approach. Preprints. https://doi.org/10.20944/preprints202410.1589.v1
Chicago/Turabian Style
Weerasinghe, R. and Chandima Ratnayake. 2024 "Measuring Onshore Wind Turbine Noise Levels for Developing an Expert Knowledge-Based Risk Assessment Approach" Preprints. https://doi.org/10.20944/preprints202410.1589.v1
Abstract
Wind turbines are associated with noise pollution and make a significant impact on social and environmental stability. The surrounding activities affect the noise pollution in residential locations. It is significantly important that wind power asset owners proactively consider the impact to the surrounding environment while constructing and in the operational phase of wind farms. This will enable the investigation of potential solutions for mitigating public inconvenience. Regulatory authorities regularly demand that asset owners take noise level measurements to investigate the consequences to the public and the environment from wind farms; however, the local authorities do not consider low-frequency noise generation. This manuscript presents a noise risk assessment approach using fuzzy set theory. In this study, two wind farms were selected which are located in the north-central region of Sri Lanka and studied during the southwest monsoon, northeast monsoon and inter-monsoon seasons. Noise data were collected from wind turbines near the residential areas to investigate their impact on the environment and society. To perform noise risk assessment proactively in populated areas, and to identify the risk, a fuzzy logic-based expert system was presented in this study.
Keywords
Low frequency noise, wind turbine, health risk, noise mitigation, noise measurement
Subject
Engineering, Safety, Risk, Reliability and Quality
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
