Laundry appliance and methods of motion-based drying detection

Abstract

A laundry appliance may include a cabinet, a tub, a laundry basket, a heater, and a controller. The laundry basket may be rotatably mounted within the tub and define a chamber for receipt of articles for washing or drying. The heater may be configured to heat and remove moisture. The controller may be operably coupled to the heater and configured to initiate a laundry operation. The laundry operation may include directing a dry cycle, directing the dry cycle comprising activating the heater according to the dry cycle. The laundry operation may also include receiving a plurality of motion signals during the dry cycle, evaluating the plurality of received motion signals, and determining a dry state of the articles based on the evaluation of the plurality of received motion signals. The laundry operation may further include modifying direction of the dry cycle based on the determined dry state.

What is claimed is: 
     
         1 . A laundry appliance comprising:
 a cabinet;   a tub positioned within the cabinet, the tub defining a tub outlet and a tub inlet;   a laundry basket rotatably mounted within the tub, the laundry basket defining a chamber for receipt of articles for washing or drying;   a heater configured to heat and remove moisture from air within the chamber; and   a controller operably coupled to the heater and configured to initiate a laundry operation, the laundry operation comprising
 directing a dry cycle for the articles, directing the dry cycle comprising activating the heater according to the dry cycle, 
 receiving a plurality of motion signals during the dry cycle, 
 evaluating the plurality of received motion signals, 
 determining a dry state of the articles based on the evaluation of the plurality of received motion signals, and 
 modifying direction of the dry cycle based on the determined dry state. 
   
     
     
         2 . The laundry appliance of  claim 1 , wherein directing the dry cycle comprises directing rotation of the laundry basket. 
     
     
         3 . The laundry appliance of  claim 2 , wherein modifying direction comprises modifying rotation of the laundry basket. 
     
     
         4 . The laundry appliance of  claim 3 , wherein modifying rotation of the laundry basket comprises halting rotation in response to determining the dry state. 
     
     
         5 . The laundry appliance of  claim 1 , wherein the plurality of motion signals are received from an accelerometer mounted to the tub. 
     
     
         6 . The laundry appliance of  claim 1 , wherein the plurality of received motion signals are sequential signals collected at discrete time points, and
 wherein determining the dry state comprises detecting the dry state at three or more sequential time points of the discrete time points for the sequential signals.   
     
     
         7 . The laundry appliance of  claim 1 , wherein evaluating comprises using a machine-learned model. 
     
     
         8 . The laundry appliance of  claim 7 , wherein the machine-learned model comprises at least one of a convolution neural network (“CNN”) model, a logistics model, a gradient boost model, an XGBoost model, or a neural network. 
     
     
         9 . The laundry appliance of  claim 1 , wherein modifying direction comprises modifying activation of the heater following determining the dry state of the articles. 
     
     
         10 . The laundry appliance of  claim 9 , wherein modifying activation of the heater comprises halting activation of the heater is in response to determining the dry state. 
     
     
         11 . A method of operating a laundry appliance, the method comprising:
 directing a dry cycle for articles for drying within a laundry basket of the laundry appliance;   directing the dry cycle comprising activating a heater mounted within a cabinet of the laundry appliance according to the dry cycle;   receiving a plurality of motion signals during the dry cycle;   evaluating the plurality of received motion signals;   determining a dry state of the articles based on the evaluation of the plurality of received motion signals; and   modifying direction of the dry cycle based on the determined dry state.   
     
     
         12 . The method of  claim 11 , wherein directing the dry cycle comprises directing rotation of the laundry basket. 
     
     
         13 . The method of  claim 12 , wherein modifying direction comprises modifying rotation of the laundry basket. 
     
     
         14 . The method of  claim 13 , wherein modifying rotation comprises halting rotation in response to determining the dry state. 
     
     
         15 . The method of  claim 11 , wherein the plurality of motion signals are received from an accelerometer mounted to a tub mounted with the cabinet. 
     
     
         16 . The method of  claim 11 , wherein the plurality of received motion signals are sequential signals collected at discrete time points, and
 wherein determining the dry state comprises detecting the dry state at three or more sequential time points of the discrete time points for the sequential signals.   
     
     
         17 . The method of  claim 11 , wherein evaluating comprises using a machine-learned model. 
     
     
         18 . The method of  claim 17 , wherein the machine-learned model comprises at least one of a convolution neural network (“CNN”) model, a logistics model, a gradient boost model, an XGBoost model, or a neural network. 
     
     
         19 . The method of  claim 11 , wherein modifying direction comprises modifying activation of the heater following determining the dry state of the articles. 
     
     
         20 . The method of  claim 11 , wherein modifying activation of the heater comprises halting activation of the heater is in response to determining the dry state.