Advancing Rotating Machinery Condition Monitoring: Wireless Vibration Sensors in ADNOC's AIP5 Autonomous Operation Plan
Abstract Condition monitoring of rotating machinery is a critical aspect of maintaining operational efficiency, reliability, and sustainability in industrial sectors, particularly within the oil and gas industry. In an era where digital transformation is reshaping industries, ADNOC has embarked on a strategic initiative under its AIP5 autonomous operation plan to leverage advanced technologies such as wireless vibration sensors. This initiative aims to integrate cutting-edge wireless vibration sensors to enhance machinery monitoring processes, especially in remote and offshore environments. The use of wireless vibration sensors in ADNOC's operations represents a significant step forward in digital transformation, aligning with the company's broader goals of innovation, sustainability, and operational excellence. This manuscript discusses a pilot project conducted within ADNOC Offshore to evaluate various sensor manufacturers, highlighting the benefits of wireless vibration sensors in reducing dependency on contractor mobilization, predicting machinery failures early, and improving overall operational efficiency. In addition, this study details a workshop arranged with multiple Original Equipment Manufacturers (OEMs) to explore available products before initiating a pilot installation at one of ADNOC's offshore fields. A thorough comparison of seven OEM products was conducted based on their technical specifications, hazardous area classification, and customer references. This paper also examines the challenges faced during the COVID-19 pandemic, which underscored the necessity for wireless solutions to ensure continuous data acquisition and analysis without on-site mobilization.
Authors
- Khaled Y. Youssef (ORCID: https://orcid.org/0000-0002-1095-142X)
- Ahmed K. Alkaabi (ORCID: https://orcid.org/0000-0001-5389-7964)
Institutions
- Abu Dhabi National Oil (United Arab Emirates) (AE)
Publication Details
- Published
- 2024-10-20
- DOI
- https://doi.org/10.2118/223272-ms
- Primary Topic
- Advanced Sensor Technologies Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00