Gravity-Calibrated Accelerometer Sensing for Drilling Equipment Health Monitoring
编号:62 访问权限:仅限参会人 更新:2026-09-21 22:53:27 浏览:5次 口头报告

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摘要
Reliable vibration measurement requires the sensor output to be separated from bias, scale-factor, cross-axis, and temperature effects. This paper presents a gravity-referenced calibration method for three orthogonally oriented accelerometers in a measurement-while-drilling tool and extends the calibrated sensing layer toward intelligent equipment-health monitoring. The original method samples the three sensor voltages at 24 combinations of upward/downward orientation and 90° rotation, averages repeated measurements, identifies temperature, bias, sensitivity, and non-orthogonality coefficients, and executes the correction in an embedded micro-control unit. The reported total-gravity comparison shows a substantially narrower residual after correction than for the raw measurement. On this validated calibration basis, a monitoring framework is proposed that combines gravity-norm residual, coefficient drift, cross-axis consistency, vibration statistics, spectral features, operating condition, and temperature. Condition-aware normalization and a multi-task model produce a measurement-quality state, equipment-health state, and confidence, while physics-based residuals retain interpretability. The original experiments validate the sensing calibration only; the intelligent-diagnosis layer is therefore stated as a testable extension requiring synchronized vibration and maintenance labels. The resulting architecture connects multi-axis sensing, signal analytics, and robust diagnosis under variable working conditions.
 
关键词
Accelerometer calibration,vibration sensing,intelligent diagnosis,equipment health monitoring,multi-sensor fusion,measurement while drilling
报告人
ETHAN ZHAN
VP SINOPEC GROUP

稿件作者
ETHAN ZHAN SINOPEC GROUP
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重要日期
  • 会议日期

    11月06日

    2026

    至

    11月08日

    2026

  • 10月15日 2026

    初稿截稿日期

主办单位
IEEE Instrumentation and Measurement Society
承办单位
Sichuan University
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