Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

BP (Back Propagation) neural network based high-precision correction and test method for resonance cylinder pressure sensor

A BP neural network and pressure sensor technology, applied in biological neural network models, measuring fluid pressure, instruments, etc., can solve the problem that the fitting accuracy cannot meet the accuracy requirements, solve the problem of high-precision calibration and test, enhance the approximation ability, The effect of improving the fitting accuracy

Active Publication Date: 2014-08-20
BEIJING AUTOMATION CONTROL EQUIP INST
View PDF1 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This method cannot meet the accuracy requirements of the model 0.028%FS in terms of fitting accuracy

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • BP (Back Propagation) neural network based high-precision correction and test method for resonance cylinder pressure sensor
  • BP (Back Propagation) neural network based high-precision correction and test method for resonance cylinder pressure sensor
  • BP (Back Propagation) neural network based high-precision correction and test method for resonance cylinder pressure sensor

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0032] The following describes the high-precision calibration method of the resonant cylinder pressure sensor based on the BP neural network provided by the present invention in conjunction with the drawings and embodiments:

[0033] A BP neural network-based resonant cylinder pressure sensor calibration method, including the construction of a sensor BP neural network with a double hidden layer network structure, so that the input variables of the network structure are the output period T and temperature voltage V of the sensor, and the output variable is the pressure value P; Collect the output cycle and temperature voltage of the sensor under different temperature and different pressure input conditions; Collect the sensor output under different temperature and pressure conditions as the calibration and inspection sample points.

[0034] In the sensor BP neural network, the hyperbolic tangent S-type transfer function is used as the transfer function between the input layer and the...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention belongs to the technical field of test and measurement and particularly relates to a BP (Back Propagation) neural network based high-precision correction and test method for a resonance cylinder pressure sensor, aiming to increase the correction and test precision for the resonance cylinder pressure sensor. The method comprises the steps of: structuring a sensor BP neural network of a dual-implicit-strata network structure, wherein input variables of the network structure are respectively the output period T and the temperature voltage V of the sensor, and output variables of the network structure is the pressure value P; acquiring output periods and temperature voltages of the sensor at different temperature under different pressure input conditions; and collecting output quantities of the sensor at different temperature under different pressure conditions to serve as correction and test as well as inspection sample points. According to the method, with the dual-implicit-strata network structure, the number of network parameters is reduced while the output precision is guaranteed; and the correction and test precision of the resonance cylinder pressure sensor is increased by 25%, and the high-precision correction and test of the sensor is realized.

Description

Technical field [0001] The invention belongs to the technical field of test and measurement, and relates to a high-precision calibration test method for a resonance cylinder pressure sensor, in particular to a high-precision calibration test method for a resonance cylinder pressure sensor based on a BP neural network. Background technique [0002] In order to realize the precise control of the missile, the demand for the range and accuracy of pressure measurement is increasing. Therefore, it is necessary to develop high-precision pressure sensors. For the current stable and high-precision resonant cylinder pressure sensor, the level of high-precision calibration technology has become an important factor affecting the accuracy of the sensor. The polynomial fitting method based on the physical model of the sensor is usually used in the past, and the vibration cylinder pressure sensor outputs periodic signals According to the physical model of the sensor, T and the temperature volta...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G01L27/00G06N3/02
Inventor 时兆峰苑景春孙洪庆李邦清刘建丰李劲松周明刘栋苏赵莹
Owner BEIJING AUTOMATION CONTROL EQUIP INST
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com