The absolute gravimeters used in gravity measurements have wide applications across disciplines. The precision of a classical free-fall absolute gravimeter is limited by the performance of its dropping mechanism. The mismatch between the linear bearings and guideways can give rise to vibrations in measurement and lead to errors in the gravity results. To detect this problem, this research develops a diagnostic approach based on the current analysis of the motor that drives the dropping mechanism. Several dropping chambers are tested under gravity measurement within 12 hours to calculate the uncertainty of the mean and be tagged as qualified or unqualified. The status of the dropping mechanism is assessed by applying four parameters of the current data in the time and frequency domains during steady motion and feature coefficients of transient current under wavelet packet decomposition (WPD). The proper ranges of the parameters are identified through comparative experiments. Empirical evidence confirms the feasibility of the parameters and coefficients used to determine whether a gravimeter dropping mechanism meets the requirement of precision around 1 micro Gal. In addition, the analysis based on continuous wavelet transform (CWT) proves its potential to locate the faults in the unqualified dropping mechanism. The proposed diagnostic approach can be applied within 20 times of motor current acquisition, which makes it practicable and helpful in improving and achieving high-precision gravity measurement.
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Chen et al. (2023) studied this question.
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