2018
DOI: 10.3390/s18061952
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A Temperature Drift Compensation Method for Pulsed Eddy Current Technology

Abstract: Pulsed eddy current (PEC) technology is another important non-contact nondestructive testing technology for defect detection. However, the temperature drift of the exciting coil has a considerable influence on the precision of PEC testing. The objective of this study is to investigate the temperature drift effect and reduce its impact. The temperature drift effect is analyzed theoretically and experimentally. The temperature drift effect on the peak-to-peak values of the output signal is investigated, and a te… Show more

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Cited by 8 publications
(4 citation statements)
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References 20 publications
(21 reference statements)
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“…For example, in [18], a method based on binary regression is proposed to compensate the temperature drift effects of the sensing coil. Meanwhile, in [19], a dual-coil solution to compensate for the exponential hysteresis characteristic of the temperature drift errors of ECDSs operating in high-temperature environments is proposed.…”
Section: Related Workmentioning
confidence: 99%
“…For example, in [18], a method based on binary regression is proposed to compensate the temperature drift effects of the sensing coil. Meanwhile, in [19], a dual-coil solution to compensate for the exponential hysteresis characteristic of the temperature drift errors of ECDSs operating in high-temperature environments is proposed.…”
Section: Related Workmentioning
confidence: 99%
“…Temperature drift is one of the key issues that need to be addressed in the design and application of eddy current sensors, and the handling methods mainly include data processing and additional temperature compensation modules. Lei et al proposed a temperature compensation method based on binary regression, reducing the maximum relative measurement error from 169.08% to 9.13% [ 21 ]. Li and Ding utilized a non-inductive compensating coil to design a displacement eddy current sensor, reducing the temperature drift from 12% to 0.7% within a temperature range from 20 °C to 90 °C [ 22 ].…”
Section: Introductionmentioning
confidence: 99%
“…The first approach is data processing, which leverages prior knowledge and algorithms to post-calibrate the sensor’s output data and enhance its precision. For example, a temperature compensation method based on binary regression was proposed by Lei et al to reduce the temperature drift effect, which minimized the maximum relative error from 169.08% to 9.13% [ 7 ].…”
Section: Introductionmentioning
confidence: 99%