System and method for predicting the dryness of clothing article

Drying and gas or vapor contact with solids – Apparatus – With automatic control

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34535, F26B 1310

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active

058990054

ABSTRACT:
The present invention discloses a system and method for predicting the dryness of clothing articles in a clothes dryer 10. In one embodiment of this invention, the clothes dryer 10 uses a temperature sensor 52, a phase angle sensor 54, and a humidity sensor 56 to generate signal representations of the temperature of the clothing articles, the motor phase angle, and the humidity of the heated air in the duct, respectively. A controller 58 receives the signal representations and determines a feature vector. A neural network 168 uses the feature vector to predict a percentage of moisture content and a degree of dryness of the clothing articles in the clothes dryer 10. In another embodiment of this invention, the clothes dryer uses a combination of sensors to predicts a percentage of moisture content and a degree of dryness of the clothing articles.

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patent: 5315765 (1994-05-01), Holst et al.
patent: 5347727 (1994-09-01), Kim
"Application of Radial Basis Function Neural Network Model for Short-Term Load Forecasting" by DK Ranaweera, et al, IEE Proc.-Gener. Transm. Distrib., vol. 142, No. 1, Jan. 1995, pp. 45-50.
"Orthogonal Least-Squares Learning Algorithm with Local Adaptation Process for Radial Basis Function Networks" by E. Chng, et al., IEE Signal Processing Letters, vol. 3, No. 8, Aug. 1996, pp. 253-255.

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