Dryer airflow calibration and alerts

Abstract

Detection of airflow conditions, such as blockage issues, in a dryer laundry appliance is provided. A current or instant calibration is performed utilizing an airflow model to infer, based on current or instant sensor data from sensors of the dryer laundry appliance, an estimated airflow for an exhaust air conduit of the dryer laundry appliance. The estimated airflow is compared to a baseline airflow previously inferred by the airflow model during a baseline calibration using previous sensor data from the sensors of the dryer laundry appliance. An alert is provided responsive to the estimated airflow being below a threshold level relative to the baseline airflow.

What is claimed is: 
     
         1 . A method for detection of airflow conditions in a dryer laundry appliance, comprising:
 performing a current calibration utilizing an airflow model to infer, based on current sensor data from sensors of the dryer laundry appliance, an estimated airflow for an exhaust air conduit of the dryer laundry appliance;   comparing the estimated airflow to a baseline airflow previously inferred by the airflow model during a baseline calibration using previous sensor data from the sensors of the dryer laundry appliance; and   providing an alert responsive to the estimated airflow being below a threshold level relative to the baseline airflow.   
     
     
         2 . The method of  claim 1 , further comprising:
 responsive to installation of the dryer laundry appliance, performing the baseline calibration utilizing the airflow model to infer, based on baseline sensor data from the sensors of the dryer laundry appliance, the baseline airflow for the exhaust air conduit of the dryer laundry appliance.   
     
     
         3 . The method of  claim 1 , wherein the exhaust air conduit of the dryer laundry appliance is connected to a vent, and the alert indicates that the vent is blocked. 
     
     
         4 . The method of  claim 1 , further comprising determining the estimated airflow responsive to initiation of a drying cycle. 
     
     
         5 . The method of  claim 1 , further comprising determining the estimated airflow responsive to a predefined period of time having passed since a previous estimated airflow or the baseline airflow was inferred. 
     
     
         6 . The method of  claim 1 , further comprising determining the estimated airflow responsive to selection of a calibration mode from a user interface of the dryer laundry appliance. 
     
     
         7 . The method of  claim 1 , further comprising determining the estimated airflow responsive to selection of a calibration mode from a user interface of a mobile device in wireless communication with the dryer laundry appliance. 
     
     
         8 . The method of  claim 1 , further comprising determining the estimated airflow responsive to occurrence of a fault code and/or a self-diagnostic of the dryer laundry appliance. 
     
     
         9 . The method of  claim 1 , wherein the baseline airflow is determined using calibration parameters defining one or more chosen from an ambient temperature, a connection or disconnection of the exhaust air conduit to a vent, or whether the dryer laundry appliance has recently been run and is in a hot state or has cooled and is in a cooled state. 
     
     
         10 . The method of  claim 1 , wherein the current sensor data is indicative of one or more chosen from a load mass in a drum of the dryer laundry appliance, a temperature of air in the exhaust air conduit, or a voltage used to operate electrical components of the dryer laundry appliance. 
     
     
         11 . The method of  claim 1 , wherein the current sensor data comprises machine age data indicative of age or wear level of the dryer laundry appliance, and the machine age data is provided as an input to the airflow model to account for the age or wear level of the dryer laundry appliance. 
     
     
         12 . The method of  claim 1 , wherein the current sensor data comprises machine age data indicative of age or wear level of the dryer laundry appliance, and said method further comprising:
 utilizing the airflow model to compute an unaged airflow using the current sensor data; and   utilizing an aging model to adjust the unaged airflow into the estimated airflow based on the machine age data to account for the age or wear level of the dryer laundry appliance.   
     
     
         13 . The method of  claim 1 , further comprising:
 computing a rolling average of the estimated airflow over time; and   providing the alert responsive to the rolling average of the estimated airflow being below the threshold level indicated by the baseline airflow.   
     
     
         14 . The method of  claim 1 , further comprising:
 performing a first calibration with the exhaust air conduit of the dryer laundry appliance connected to a vent;   performing a second calibration with the dryer laundry appliance disconnected from the vent;   comparing the estimated airflow to the first calibration and to the second calibration; and   providing, in the alert, that the dryer laundry appliance has disconnected from the vent responsive to the estimated airflow matching the second calibration and not the first calibration.   
     
     
         15 . The method of  claim 1 , further comprising:
 performing a first calibration as a cold run with the dryer laundry appliance at ambient temperature;   performing a second calibration as a hot run with the dryer laundry appliance warm from a previous cycle;   utilizing the first calibration for the comparing of the estimated airflow to the baseline airflow responsive to the current sensor data indicative of the estimated airflow as being computed for a subsequent cold run; and   utilizing the second calibration for the comparing of the estimated airflow to the baseline airflow responsive to the current sensor data indicative of the estimated airflow as being computed for a subsequent hot run.   
     
     
         16 . The method of  claim 1 , further comprising:
 performing the baseline calibration responsive to completion of a temperature-based pre-cooldown mode; and   performing the current calibration also responsive to completion of the temperature-based pre-cooldown mode, thereby ensuring a consistent temperature for performance of the baseline calibration and the current calibration.   
     
     
         17 . The method of  claim 1 , wherein the current sensor data comprises historical information to enable the model to estimate changes in the estimated airflow over time. 
     
     
         18 . The method of  claim 17 , wherein the airflow model is a recurrent neural network trained to analyze sequential data; and inputs to the airflow model comprise the historical information in addition to the current sensor data. 
     
     
         19 . The method of  claim 1 , wherein the current sensor data comprises data indicative of a voltage powering the dryer laundry appliance, ambient temperature surrounding the dryer laundry appliance, initial conditions of the dryer laundry appliance, and/or a machine age of the dryer laundry appliance. 
     
     
         20 . The method of  claim 1 , wherein the current sensor data comprises data indicative of a load size in a drum of the dryer laundry appliance, a tumble pattern used by the dryer laundry appliance to perform a selected cycle, a gas pressure of gas powering the dryer laundry appliance, a gas type powering the dryer laundry appliance, and/or a status of a gas heating value connecting the gas to the dryer laundry appliance.