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

Inactive Publication Date: 2016-01-20
NANJING UNIV OF INFORMATION SCI & TECH
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Problems solved by technology

[0004] Purpose of the invention: The present invention provides an array type air pressure measurement compensation device and method based on quantum particle swarm wavelet neural network, in or

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  • Array type air pressure measurement compensation device and method based on quantum particle swarm wavelet neural network
  • Array type air pressure measurement compensation device and method based on quantum particle swarm wavelet neural network
  • Array type air pressure measurement compensation device and method based on quantum particle swarm wavelet neural network

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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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Abstract

The invention discloses an array type air pressure measurement compensation device and method based on quantum particle swarm wavelet neural network. A micro-processing module is started to send instruction to a pressure sensor array and a temperature sensor, so that the air pressure and temperature are measured; measurement data is transmitted to the micro-processing module and a host computer respectively; the host computer establishes a wavelet neural network according to the received air pressure and temperature, and the wavelet neural network is optimized by utilizing the quantum particle swarm algorithm, the quantum particle swarm wavelet neural network is trained at the same time, and an obtained air pressure correction compensation formula is transmitted to the micro-processing module; the micro-processing module calculates the accurate air pressure value whose error is compensated; and the accurate air pressure value is transmitted to a display module and displayed. Retardation error of air pressure measured by arrays is compensated on the basis of the quantum particle swarm wavelet neural network, temperature drift and non-linearity are compensated, errors are reduced, effective signals are enhanced, air pressure measurement is more accurate, and requirements for meteorology measurement are met.

Description

technical field [0001] The invention belongs to the technical field of high-precision air pressure measurement, and in particular relates to an array type air pressure measurement compensation device and a method thereof based on a quantum particle swarm wavelet neural network. Background technique [0002] In order to prevent meteorological disasters, prevent huge economic losses to the society, and ensure people's travel safety, the work of meteorological monitoring and early warning is very important. The movement of the atmosphere is closely related to the change of weather conditions, but the uneven distribution of atmospheric pressure causes the movement of the atmosphere, which makes accurate measurement of air pressure very important for meteorological monitoring. Today, high-precision MEMS atmospheric pressure sensors are widely used in ground weather stations and radiosondes. Ground automatic weather stations are full of sensors that measure various meteorological ...

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Application Information

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IPC IPC(8): G01L9/06G01L19/04G06N3/02G01W1/00
Inventor 张加宏刘震宇顾芳张月香沈雷包志伟
Owner NANJING UNIV OF INFORMATION SCI & TECH
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