A new signal processing method for phase difference estimation was proposed based on time-varying signal model, whose frequency, amplitude and phase are time-varying. And then be applied Coriolis mass flowmeter signal. First, a bandpass filtering FIR filter was applied to filter the sensor output signal in order to improve SNR. Then, the signal frequency could be calculated based on short-time frequency estimation. Finally, by short window intercepting, the DTFT algorithm with negative frequency contribution was introduced to calculate the real-time phase difference between two enhanced signals. With the frequency and the phase difference obtained, the time interval of two signals was calculated. Simulation results show that the algorithms studied are efficient. Furthermore, the computation of algorithms studied is simple so that it can be applied to real-time signal processing for Coriolis mass flowmeter.
Process control objects mathematical model is difficult to establish. Based on humans thinking mode, control experience, action and intuitional reasoning, Human simulation intelligent control (HSIC) avoids all kinds of difficult problems that we are faced with as seeking the answer of complicated model or establishing brain model, and so there are some advantages for HSIC on process control. In this paper, a detailed algorithm is described for process control by using the method of HSIC. Finally, the results of practical application have proved that HSIC is feasible and effect for process control.
This paper studies the control strategy of non-contact automatic leveling control system and the design of controlkr based on DSP. First, the author analyzes the systemic structure of paver self-leveling device and explains the work principle of this system. On this basis, to establish a self-leveling control system program, analyzes its control strategy, and finaUy fIXes some key technique parameter such as the sensitivity, dead band, proportional pulse band and constant speed control band
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