Pattern Matching: A Signal Processing Method for Time-of-Flight Measurement in Ultrasonic Flowmeter

Transit time ultrasonic flowmeters offer a variety of advantages over other flowmetry methods; including low pressure loss, no moving parts, self-diagnosing capabilities, and possibility of hot-tap installation. In a transit time ultrasonic flowmeter, the average flow velocity is calculated from the upstream and downstream time-of-flights (ToFs) of the sound. To improve the ToF measurement, a novel signal processing method named pattern matching is introduced in this article. In this method, the wave packet is compared with a trainable pattern to measure the ToF. An ultrasonic flowmeter setup is designed to record the wave signals on a computer as an offline dataset. The performance of the pattern matching method is evaluated by its comparison with common classic and state-of-the-art algorithms by implementing them on the same dataset. The standard deviation (SD) of the time-flight in zero flow is used as the performance criterion. The results demonstrate that the pattern matching method (average SD $= 0.87~\mu $ s) exhibits the best performance compared to various threshold methods and cross correlation method. Ultimately, the pattern matching method along with state-of-the-art algorithms are implemented on an embedded hardware in a flow test setup. Only pattern matching method was able to follow the flow rate profile in high noise environment and had significantly lower error and better repeatability compared to other methods (error reduced from 14.1% to 0.322% compared to the second best performing cross correlation method).