Research on dynamic calibration and compensation method of strain-gauge type force sensor

IF 1.6 4区工程技术 Q3 INSTRUMENTS & INSTRUMENTATION

Sensor Review Pub Date : 2024-01-10 DOI:10.1108/sr-08-2023-0330

Tingwei Gu, Shengjun Yuan, Lin Gu, Xiaodong Sun, Yanping Zeng, Lu Wang

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引用次数: 0

Abstract

Purpose

This paper aims to propose an effective dynamic calibration and compensation method to solve the problem that the statically calibrated force sensor would produce large dynamic errors when measuring dynamic signals.

Design/methodology/approach

The dynamic characteristics of the force sensor are analyzed by modal analysis and negative step dynamic force calibration test, and the dynamic mathematical model of the force sensor is identified based on a generalized least squares method with a special whitening filter. Then, a compensation unit is constructed to compensate the dynamic characteristics of the force measurement system, and the compensation effect is verified based on the step and knock excitation signals.

Findings

The dynamic characteristics of the force sensor obtained by modal analysis and dynamic calibration test are consistent, and the time and frequency domain characteristics of the identified dynamic mathematical model agree well with the actual measurement results. After dynamic compensation, the dynamic characteristics of the force sensor in the frequency domain are obviously improved, and the effective operating frequency band is widened from 500 Hz to 1,560 Hz. In addition, in the time domain, the rise time of the step response signal is reduced from 0.29 ms to 0.17 ms, and the overshoot decreases from 26.6% to 9.8%.

Originality/value

An effective dynamic calibration and compensation method is proposed in this paper, which can be used to improve the dynamic performance of the strain-gauge-type force sensor and reduce the dynamic measurement error of the force measurement system.

查看原文本刊更多论文

应变片式力传感器的动态校准与补偿方法研究

目的本文旨在提出一种有效的动态校准和补偿方法，以解决静态校准的力传感器在测量动态信号时会产生较大动态误差的问题。设计/方法/途径通过模态分析和负阶跃动态力校准试验分析了力传感器的动态特性，并基于广义最小二乘法和特殊增白滤波器确定了力传感器的动态数学模型。结果通过模态分析和动态校准测试获得的力传感器动态特性是一致的，所确定的动态数学模型的时域和频域特性与实际测量结果吻合良好。经过动态补偿后，力传感器在频域的动态特性得到明显改善，有效工作频带从 500 Hz 扩大到 1 560 Hz。原创性/价值本文提出了一种有效的动态校准和补偿方法，可用于改善应变片式力传感器的动态性能，降低力测量系统的动态测量误差。

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来源期刊

Sensor Review 工程技术-仪器仪表

CiteScore

3.40

自引率

6.20%

发文量

审稿时长

3.7 months

期刊介绍： Sensor Review publishes peer reviewed state-of-the-art articles and specially commissioned technology reviews. Each issue of this multidisciplinary journal includes high quality original content covering all aspects of sensors and their applications, and reflecting the most interesting and strategically important research and development activities from around the world. Because of this, readers can stay at the very forefront of high technology sensor developments. Emphasis is placed on detailed independent regular and review articles identifying the full range of sensors currently available for specific applications, as well as highlighting those areas of technology showing great potential for the future. The journal encourages authors to consider the practical and social implications of their articles. All articles undergo a rigorous double-blind peer review process which involves an initial assessment of suitability of an article for the journal followed by sending it to, at least two reviewers in the field if deemed suitable. Sensor Review’s coverage includes, but is not restricted to: Mechanical sensors – position, displacement, proximity, velocity, acceleration, vibration, force, torque, pressure, and flow sensors Electric and magnetic sensors – resistance, inductive, capacitive, piezoelectric, eddy-current, electromagnetic, photoelectric, and thermoelectric sensors Temperature sensors, infrared sensors, humidity sensors Optical, electro-optical and fibre-optic sensors and systems, photonic sensors Biosensors, wearable and implantable sensors and systems, immunosensors Gas and chemical sensors and systems, polymer sensors Acoustic and ultrasonic sensors Haptic sensors and devices Smart and intelligent sensors and systems Nanosensors, NEMS, MEMS, and BioMEMS Quantum sensors Sensor systems: sensor data fusion, signals, processing and interfacing, signal conditioning.