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BP neural network based temperature gain compensation method applied to electronic scale

A BP neural network and temperature compensation technology, applied in the field of electronic scales, can solve problems such as poor versatility, increased measurement costs, and limited accuracy

Inactive Publication Date: 2018-07-27
CHIPSEA TECH SHENZHEN CO LTD
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  • Abstract
  • Description
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Problems solved by technology

[0004] Calibration using hardware methods will make the capacitance detection circuit complicated, troublesome to debug, poor in versatility, and limited in accuracy. At the same time, more components will slow down the circuit response speed and increase the measurement cost.

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  • BP neural network based temperature gain compensation method applied to electronic scale
  • BP neural network based temperature gain compensation method applied to electronic scale
  • BP neural network based temperature gain compensation method applied to electronic scale

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Embodiment Construction

[0030] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0031] The method for compensating temperature gain based on BP neural network applied to electronic scales implemented by the present invention comprises the following steps:

[0032] 1. Establish a neural network model for temperature gain compensation of the load cell. figure 1 As shown, the neural network model for establishing the temperature gain compensation of the weighing sensor realized by the present invention, the neural network model is composed of an input layer, a hidden layer and an output layer. The output voltage u is selected as the input layer unit of the BP neural network. At ...

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Abstract

The invention discloses a BP neural network based temperature gain compensation method applied to an electronic scale. The method comprises the steps of: 101, establishing a neural network model for temperature gain correction of a weighing sensor; 102, obtaining learning training sample data of the network; 103, pre-processing the sample data; 104, performing network training on the number of samples; 105, testing the network prediction effect; and 106, writing a compensation formula into a firmware program of a single-chip microcomputer. The method of the invention can correct a temperaturesensor by using the neural network method, can quickly and accurately realize the temperature compensation of the weighing sensor, not only makes the accuracy of the compensation link reach the measurement allowable error range, but also has a prediction compensation effect for temperature points without training.

Description

technical field [0001] The invention belongs to the technical field of electronic scales, in particular to a protection device and method for touch screen equipment. Background technique [0002] In the field of electronic scales, sensors are easily affected by surrounding environmental factors in actual work, such as temperature, humidity, vibration, electric field, magnetic field, etc., especially the influence of temperature on sensors is the most significant. Temperature changes will cause additional output errors of the sensor; temperature will also cause corresponding changes in the parameters of the electronic components of the detection circuit [0003] The usual approach to this problem is to first place the load cell in a specific temperature environment for a long enough time to allow the temperature distribution to reach a steady state, then apply force to the load cell, and analyze and study by changing the different steady-state temperatures of the sensor The ...

Claims

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Application Information

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IPC IPC(8): G01G23/01G01G23/48G06N3/08
CPCG01G23/01G01G23/48G06N3/084
Inventor 姜智陈华辉
Owner CHIPSEA TECH SHENZHEN CO LTD
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