Online Sensor Testing through Superposition of Encoded Stimulus

TL;DR

This paper introduces an improved online sensor testing method that encodes test stimuli and employs covariance algorithms to effectively reject measurand signals, enhancing test accuracy and speed for MEMS accelerometers.

Contribution

It presents a novel encoding and signal processing approach to remove measurand signals, enabling faster and more accurate online sensor testing.

Findings

Rejection ratio exceeds 14dB for 0.7s test time.

Method effectively isolates test stimulus from sensor output.

Accuracy of test signal can be validated online.

Abstract

Online monitoring remains an important requirement for a range of microsystems. The solution based on the injection of an actuating test stimulus into the bias structure of active devices holds great potential. This paper presents an improved solution that aims to remove the measurand-induced signal from the sensor output. It involves encoding the test stimulus and using a covariance algorithm to reject the signal that does not contain the code. The trade-off between the sine wave rejection ratio of the technique and the test time response is studied and, in the case of a MEMS accelerometer, it is demonstrated that the rejection is higher than 14dB for a test time of about 0.7s. Furthermore, the accuracy of the test signal can be evaluated to guarantee the integrity of the online test output.