Dimension-Reduced Analog-Digital Mixed Measurement Method of Inductive Proximity Sensor

Area of Science:

• Metrology
• Sensor Technology
• Instrumentation

Background:

• Inductive proximity sensors (IPSs) are crucial for non-contact displacement measurement in industries like aerospace.
• Temperature drift in IPSs affects measurement accuracy, necessitating compensation techniques.
• Existing methods, such as 2D look-up tables, have limitations including large data capacity and dependency on precise parameter measurement.

Purpose of the Study:

• To develop a dimension-reduced measurement method for IPSs that overcomes the limitations of existing temperature compensation techniques.
• To improve the efficiency and accuracy of displacement measurements performed by inductive proximity sensors under varying temperatures.

Main Methods:

• Examined the nonlinear relationship between IPS sensing core response and ambient temperature.
• Proposed a dimension-reduced method using linear approximation of response curves at two temperatures.
• Developed calibration procedures for direct look-up table construction, avoiding precise sensing core parameter measurement.

Main Results:

• Achieved a lookup table capacity reduction to less than 0.37% of the 2D look-up table.
• Extended the measurement range from 0-5 mm to 0-7 mm.
• Improved measurement accuracy by over 0.1 mm (50% at 5 mm) compared to the 2D look-up table method across a temperature range of 20°C to 110°C.

Conclusions:

• The proposed dimension-reduced method effectively eliminates temperature drift influence on IPS displacement measurements.
• This novel approach offers significant improvements in lookup table capacity, accuracy, and measurement range.
• The method provides a more efficient and accurate solution for industrial displacement sensing applications.