US Patent Application 18245015. LEARNING DEVICE AND INFERENCE DEVICE FOR STATE OF AIR CONDITIONING SYSTEM simplified abstract
Contents
LEARNING DEVICE AND INFERENCE DEVICE FOR STATE OF AIR CONDITIONING SYSTEM
Organization Name
Mitsubishi Electric Corporation
Inventor(s)
Mitsuhiro Ishigaki of Tokyo (JP)
Takahiro Hashikawa of Tokyo (JP)
LEARNING DEVICE AND INFERENCE DEVICE FOR STATE OF AIR CONDITIONING SYSTEM - A simplified explanation of the abstract
This abstract first appeared for US patent application 18245015 titled 'LEARNING DEVICE AND INFERENCE DEVICE FOR STATE OF AIR CONDITIONING SYSTEM
Simplified Explanation
The patent application describes a learning device that acquires operation data from an air conditioning system and converts a specific model into a trained model using this data. The operation data includes various parameters related to the system's performance. The specific model estimates a specific parameter based on the other operation data. The specific parameter includes the operating frequency of the compressor, the degree of opening of the expansion valve, and the amount of air blown per unit time by the blower.
- Learning device for air conditioning systems
- Acquires operation data from the system
- Converts a specific model into a trained model
- Operation data includes various parameters
- Specific model estimates a specific parameter based on other operation data
- Specific parameter includes compressor frequency, expansion valve opening, and blower airflow
Original Abstract Submitted
The learning device includes: a first data acquisition unit; and a model generation unit. The first data acquisition unit is configured to acquire operation data of an air conditioning system. The model generation unit is configured to convert a specific model into a trained model using the operation data. The operation data includes a specific parameter and at least one of a temperature of air passing through the second heat exchanger, a temperature and a pressure of refrigerant, and a temperature outside a space where each of at least one indoor unit is arranged. The specific model estimates the specific parameter from the operation data other than the specific parameter. The specific parameter includes at least one of an operating frequency of the compressor, a degree of opening of the expansion valve, and an amount of air blown per unit time by the blower.
