Title :
Sensor fusion based testing station for unbalanced load estimation in horizontal washing machines
Author_Institution :
Res. & Eng. Center, Whirlpool Corp., Benton Harbor, MI
Abstract :
A sensor fusion testing station has been set up to benchmark the performance of various off-balance estimation algorithms for horizontal washing machines. Multiple mechanical sensors including laser displacement sensors, load cells and are installed on the testing station. The measurements are used to derive the off-balance information, i.e., magnitude and location, inside the washing machine with models established through designed experiments. Neural networks (NN) and support vector machines (SVM) are used for the modeling purpose and their performance are compared in this paper.
Keywords :
domestic appliances; mechanical engineering computing; mechanical testing; neural nets; sensor fusion; support vector machines; SVM; horizontal washing machines; laser displacement sensors; load cells; mechanical sensors; neural networks; off-balance estimation algorithms; sensor fusion based testing station; support vector machines; unbalanced load estimation; Accelerometers; Mechanical sensors; Neural networks; Sensor fusion; Spinning; Support vector machine classification; Support vector machines; Testing; Vibrations; Washing machines; classification; location detection; neural networks; sensor fusion; support vector machines; unbalanced loads; vibration; washing machine;
Conference_Titel :
Instrumentation and Measurement Technology Conference Proceedings, 2008. IMTC 2008. IEEE
Conference_Location :
Victoria, BC
Print_ISBN :
978-1-4244-1540-3
Electronic_ISBN :
1091-5281
DOI :
10.1109/IMTC.2008.4547266