Active Air-borne noise suppression for pipe break early warning in smart water networks

Abstract

Acoustic alarm systems using IoT (internet of things) smart sensors (e.g. accelerometers) for leak detection in water networks are rapidly gaining popularity. One of the issues for such systems is the false alarms which often occur as a result of signal contamination by environmental noise, especially by air-borne noise resulting in additional vibration. This research proposes a dual-sensor concept for active air-borne noise suppression in accelerometer signals that are excited by both fluid-borne noise (including the leak signal) and air-borne environmental noise. In the proposed arrangement, a microphone adjacent to the measurement station is used to measure the air-borne noise simultaneously to the accelerometer mounted to the pipe. Three methods have been applied in this paper: 1) using the non-coherent output power (NCOP) between the accelerometer and microphone signals; 2) using a Wiener filter; and 3) using adaptive least mean square (LMS) filters together with adaptive infinite impulse response (IIR) filters. Field tests have been carried out on a cast iron water main embedded in a water distribution system. A speaker was used to generate air-borne noise around the measurement station and to excite unwanted vibrations in the pipe. The results show that all three methods can effectively suppress air-borne noise from the accelerometer signals mounted to the pipe. A noise reduction of 30 dB can be achieved using the NCOP in the frequency domain or using the Wiener filter in the time domain. The adaptive filters are relatively less effective and the effectiveness reduces with the increase in bandwidth of the air-borne noise. However, the adaptive filters have the potential to be applied online for real-time processing.