Self-test and calibration methods for micro electro-mechanical systems

Abstract

For the testing of micro electro-mechanical systems, we propose a taxonomy of built-in self-testing methods. These solutions that are non-intrusive, cost-effective and are typically non-intrusive during the testing process are being actively sought after as the cost of micro-electro-mechanical systems (MEMS) testing can account for 50% of the total cost of the end product. The selection of testing methods is analyzed extensively, and a classification table for such methods is presented according to three performance metrics: ease of application, test application, usefulness. Performance table also provides a field test domain for the method. While built-in-self-test (BIST) methods do depend on the application at hand, utilizing the inherent multimodal sensing capability of most sensors could be a promising approach for effective built-in self-test.

A sigma-delta interface built-in self-test and calibration for microelectromechanical system accelerometer's utilizing interpolation method

“…As a result, important system attributes such as sensitivity, linearity, and dynamic range are significantly affected. When a voltage drop (V) is applied to both sensor plates, an electrostatic force of attraction is formed between them, which is given by ( 7) [4],…”

“…Additionally, this system (closed loop) did not achieve sub-g equivalent resolution during testing. This continuous-time capacitive accelerometer interfacing using a high-Q mechanical element was disclosed in [4], [12] with sub-g comparable resolutions. An incredibly low-noise accelerometer, but still no thorough circuit design method, is presented in [13], [14] proposes a low-frequency impedance-based approach for identifying damaged array components, which is supported by actual electrode array readings for drug testing on cardiac and neuronal tissue.…”

Three-Axes Mems Calibration Using Kalman Filter and Delaunay Triangulation Algorithm

“…Tese sensors found usage in a wide range of applications, including navigation and positioning systems, educational software, medical electronics, and more [1][2][3]. Researchers have also recently examined the usage of MEMS devices in user interfaces [4][5][6]. Despite the benefts mentioned above, MEMS sensors' measurements are less precise than those from tactical-grade sensors because of biases, noise, scalability errors, nonlinearity, thermal changes, and misalignment errors.…”