International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Noise and Vibration Analyser |
|---|---|
| ABSTRACT | Noise and Vibration Analyser is essential in predictive maintenance and quality control almost in all industries. Noise and vibration analyser is used for real-time monitoring and fault detection. This results in improving machinery reliability and reducing downtime. Utilizing sensors like microphones, these instruments employ FFT (Fast Fourier Transform) algorithms to separate signals into frequency components, enabling precise fault detection. They are critical for optimizing performance, ensuring structural integrity, and reducing operational noise in systems. |
| AUTHOR | RIYA DABHADE, SRUSHTI BHASKAR, PRIYANKA CHAVAN, ATHARVA CHAVAN, PROF. MESHRAM A.G Polytechnic Student, Dept. of E&TC., Bhivrabai Sawant Polytechnic, J.S.P.M. University, Wagholi, Pune, Maharashtra, India Dept. of E&TC., Bhivrabai Sawant Polytechnic, J.S.P.M. University, Wagholi, Pune, Maharashtra, India |
| VOLUME | 182 |
| DOI | DOI: 10.15680/IJIRCCE. 2026.1403007 |
| pdf/7_Noise and Vibration Analyser.pdf | |
| KEYWORDS | |
| References | 1. Eshleman, R 1999, Basic machinery vibrations: An introduction to machine testing, analysis, and monitoring 2. Mußler, Marvin, Kälber, Florian, Hohmann, Soeren, & Becker, Juergen (2024). Low-Power Vibration-Based Predictive Maintenance for Industry 4.0 using Neural Networks: A Survey. https://arxiv.org/pdf/2408.00516v1 3. L. Bravo-Moncayo et al. A machine learning approach for traffic-noise annoyance assessment Appl Acoust (2019) |
