Abstract
Noise is a major challenge in the petroleum industry. Prior to performing work in a noisy area, the noise map is the tool for assessing noise exposure when planning and performing work. The aim of this paper is to present an ongoing R&D project to develop a wireless noise monitoring system that provides real-time input to a digital noise map that updates dynamically. In operations, this will provide up-to-date information when planning for noise risk controls such as work time restrictions and required hearing protection, as well as feedback during performance of work. The system, which has been named WiNoS, utilizes an industry-standard wireless communication protocol, as well as integrates smoothly into plant architecture. The system consists of a network of battery operated wireless sound level sensors, a wireless infrastructure and software applications for processing and presenting the collected noise data. The main developments in the project are related to design of wireless sensors suitable for operation in oil & gas processing plants, and novel software algorithms for the creation of dynamic noise maps for industrial environments, maintaining the necessary accuracy. A prototype of the system has been successfully demonstrated in an industrial laboratory environment. The demo system was composed from early prototypes of 9 wireless noise sensors and an alfa version of the mapping software. The demo system also included simple functionality for transferring acoustical frequency spectra. The demonstration successfully showed the conceptual functionality of WiNoS, and served as a decision gate for taking WiNoS into the next phase of development towards first-use at a North-Sea offshore installation. The WiNoS system will be technically prepared for acoustical frequency analysis, and will be designed with capabilities for wireless transmission of high-resolution frequency spectra. As a next step in the WiNoS development, the idea is to utilize the acoustical spectrum to assess condition of machinery and processes. Detailed frequency analysis can be used for monitoring and fault detection, e.g. of rotating machinery. Early experiments have already been carried out; showing how different operating conditions alter the emitted acoustical frequency spectrum from a wet gas compressor
