000112404 001__ 112404
000112404 005__ 20240319080957.0
000112404 0247_ $$2doi$$a10.3390/mi13040584
000112404 0248_ $$2sideral$$a128284
000112404 037__ $$aART-2022-128284
000112404 041__ $$aeng
000112404 100__ $$0(orcid)0000-0003-1562-4433$$aMartínez, Javier
000112404 245__ $$aSelf-Calibration Technique with Lightweight Algorithm for Thermal Drift Compensation in MEMS Accelerometers
000112404 260__ $$c2022
000112404 5060_ $$aAccess copy available to the general public$$fUnrestricted
000112404 5203_ $$aCapacitive MEMS accelerometers have a high thermal sensitivity that drifts the output when subjected to changes in temperature. To improve their performance in applications with thermal variations, it is necessary to compensate for these effects. These drifts can be compensated using a lightweight algorithm by knowing the characteristic thermal parameters of the accelerometer (Temperature Drift of Bias and Temperature Drift of Scale Factor). These parameters vary in each accelerometer and axis, making an individual calibration necessary. In this work, a simple and fast calibration method that allows the characteristic parameters of the three axes to be obtained simultaneously through a single test is proposed. This method is based on the study of two specific orientations, each at two temperatures. By means of the suitable selection of the orientations and the temperature points, the data obtained can be extrapolated to the entire working range of the accelerometer. Only a mechanical anchor and a heat source are required to perform the calibration. This technique can be scaled to calibrate multiple accelerometers simultaneously. A lightweight algorithm is used to analyze the test data and obtain the compensation parameters. This algorithm stores only the most relevant data, reducing memory and computing power requirements. This allows it to be run in real time on a low-cost microcontroller during testing to obtain compensation parameters immediately. This method is aimed at mass factory calibration, where individual calibration with traditional methods may not be an adequate option. The proposed method has been compared with a traditional calibration using a six tests in orthogonal directions and a thermal chamber with a relative error difference of 0.3%.
000112404 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000112404 590__ $$a3.4$$b2022
000112404 592__ $$a0.546$$b2022
000112404 591__ $$aCHEMISTRY, ANALYTICAL$$b29 / 86 = 0.337$$c2022$$dQ2$$eT2
000112404 591__ $$aINSTRUMENTS & INSTRUMENTATION$$b25 / 63 = 0.397$$c2022$$dQ2$$eT2
000112404 591__ $$aPHYSICS, APPLIED$$b57 / 160 = 0.356$$c2022$$dQ2$$eT2
000112404 591__ $$aNANOSCIENCE & NANOTECHNOLOGY$$b68 / 107 = 0.636$$c2022$$dQ3$$eT2
000112404 593__ $$aControl and Systems Engineering$$c2022$$dQ2
000112404 593__ $$aMechanical Engineering$$c2022$$dQ2
000112404 593__ $$aElectrical and Electronic Engineering$$c2022$$dQ2
000112404 594__ $$a4.7$$b2022
000112404 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000112404 700__ $$0(orcid)0000-0003-3618-4940$$aAsiain, David
000112404 700__ $$aBeltrán, José Ramón
000112404 773__ $$g13, 4 (2022), 584 [17 p.]$$pMicromachines (Basel)$$tMicromachines$$x2072-666X
000112404 8564_ $$s7151676$$uhttps://zaguan.unizar.es/record/112404/files/texto_completo.pdf$$yVersión publicada
000112404 8564_ $$s2709037$$uhttps://zaguan.unizar.es/record/112404/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000112404 909CO $$ooai:zaguan.unizar.es:112404$$particulos$$pdriver
000112404 951__ $$a2024-03-18-13:43:57
000112404 980__ $$aARTICLE