Monitoring laundry machine operation using machine learning analysis of acoustic transducer signal information

A method carried out by a system comprising:

• an acoustic sensor data interface;
• and
• a machine learning-based processing system;
• wherein the method comprises:
• receiving, by the acoustic sensor data interface, digital acoustic signal data corresponding to sensed sound from components of a laundry machine during operation of the laundry machine, wherein the acoustic sensor includes at least a microphone configured to render a transduced electronic signal of sound waves sensed by the microphone during operation of the laundry machine;
• and
• rendering, by the machine learning-based processing system, a reason code indicative of a current operational status of the laundry machine,
• wherein the processing system comprises a processor and a non-transitory computer readable medium including computer-executable instructions that, when executed by the processor, facilitate carrying out a method during the rendering that comprises:
• receiving an acoustic data set rendered from the transduced electronic signal;
• rendering a functional metric parameter values indicative of an operational status of the laundry machine by applying machine learning models to the acoustic data set;
• identifying, by applying a set of conditions to a set of predictive maintenance indicators derived from the functional metric parameter values, a reason code corresponding to a degraded operational status of the laundry machine;
• and
• issuing, in accordance with the identifying, an electronic maintenance alert relating to a remedial operation for the laundry machine.