Signal analysis and processing on high airflow meter design
High airflow meters in the range of 0.0 SLM (Standard Liters Per Minute) to 200.0 SLM and using a built-in microbridge sensor in flow housing, induce a significant amount of turbulence noise on the output signal. This imposes severe constraints on the flowmeter performance. Therefore, investigative work was carried out to determine the extent of the problem. The resultant tests show that turbulent noise is highest (± 800 mv with no flow screens) when airflow is from 0.0 SLM to 100.0 SLM. The lowest signal noise ratio is 5.45 db. The objective of this paper is to analyze the sensor output signal and introduce an analog/digital filter design to reduce the random noise and to realize the industrial standard voltage output range of 1.00 VDC to 5.00 VDC. The unique and variable characteristics of the flow noise are presented in very detail. Tests were performed with the A/D data acquisition system for flow data analysis and the flow data file was used for off-line time and frequency domain analysis and digital filter design simulation. Frequency and time domain measurements were obtained in real-time from a series of flow tests with this heat transfer type flowmeter. Magnitude of the signal were measured. The mean and the autocorrelation were calculated and measured as the important information of noise induced on the output signal. Analog Butterworth filter was implemented on this high flow meter for real time signal processing, signal noise ratio is improved; overshoot is 1 0 %; and the response time is 350 ms. Simulations were done on traditional Butterworth digital filter design and Adaptive Noise Cancellation and Forward Linear Predictor strategy. The Forward Linear Prediction application was implemented with the TMS320C25 digital signal processor (DSP), signal noise ratio is higher than signal noise ratio of analog filter; overshoot is zero; and response time is 195 ms. The effectiveness of these filter designs are presented for a wide range of airflows. This paper includes theoretical analysis and practical application of filter theory as well as hardware design on analog circuits and software implementation on TMS320C25 for real time signal processing.