Dryer Controller Detecting Incomplete Drying via Sensor Data

The system divides the detection function into multiple specialized sensors (temperature sensor in duct, temperature sensor on compressor, temperature sensor on power module, humidity sensor in drum) that each monitor specific parameters. This segmentation allows precise detection of different failure modes (duct clogging, refrigerant insufficiency, heater failure, cooling device failure) without requiring a single complex detection system.

The controller serves multiple functions: it not only controls the drying cycle but also collects data from all sensors, stores historical data in the storage device, compares current data with stored data, identifies failure causes, and communicates with external devices. This multi-functionality consolidates what would otherwise be separate systems into a single integrated controller, managing complexity rather than increasing it.

The controller performs data comparison and failure identification at periodic intervals or at key moments during the drying cycle, rather than continuously analyzing all sensor data in real-time. The system stores historical data and compares it with current readings at strategic points, maintaining high reliability while minimizing energy consumption associated with continuous processing.

The system establishes feedback loops where sensor data is continuously monitored, compared with stored baseline data, and used to identify deviations indicating failures. This feedback mechanism allows the system to maintain high reliability by quickly detecting anomalies while only consuming significant energy when comparisons reveal actual failures or when corrective actions are needed.

The system performs preliminary detection and identification of potential failures during the drying cycle before incomplete drying actually occurs. By continuously monitoring sensor data and comparing it with stored baseline data, the system can identify duct clogging, refrigerant insufficiency, or other failures early and alert the user, allowing corrective action before productivity is significantly impacted.

The dryer performs self-diagnosis through automatic comparison of sensor data with stored reference data, identifying failure causes without requiring external inspection. The controller automatically detects patterns indicating specific failures (e.g., temperature deviations indicating duct clogging, humidity patterns indicating heater failure) and communicates findings to the user, enabling self-service monitoring that improves productivity without proportionally increasing complexity.