Array type air pressure measurement compensation device and method based on quantum particle swarm wavelet neural network
A wavelet neural network, quantum particle swarm technology, applied in measurement devices, biological neural network models, fluid pressure measurement by changing ohmic resistance, etc., can solve problems such as sensitivity drift and temperature drift
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[0127] Before using the wavelet neural network algorithm optimized by quantum particle swarm optimization for sensor signal correction and compensation, the data calibration of the air pressure sensor must be performed first to obtain the output data of the pressure sensor at each temperature. Use the C180 chilled mirror dew point meter temperature control box to provide different temperature environments for the sensor. The temperature can be adjusted from -40°C to 180°C. The temperature difference in the entire temperature control box is ±2°C. Use the Fluke PPC-4 pressure generator to provide reliable and stable pressure for the pressure sensor. The measuring range of the pressure sensor is 500~1100hPa, and the calibration temperature range is -20~50℃. First, select the appropriate pressure point and temperature point for calibration. In the experiment, the pressure is selected every 100hPa, and the temperature is calibrated every 10°C, so that more data volume and sensor in...
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