Disclosed is a real-time solenoid-operated valve monitoring system which analyzes the integrity of a solenoid-operated valve in real time. The real-time solenoid-operated valve monitoring system uses an artificial neural network to monitor whether a solenoid-operated valve is abnormal, and comprises: a sensor connected to the solenoid-operated valve to measure data sensed from the solenoid-operated valve; and a diagnosis unit connected to the sensor to acquire, process, and analyze data measured by the sensor to monitor and diagnose whether the solenoid-operated valve is abnormal. The diagnosis unit includes: a data acquisition and transmission unit to acquire data measured by the sensor from the sensor connected to the solenoid-operated valve, and transmit the acquired data to a data processing unit; a data processing unit to receive data from the data acquisition and transmission unit to preprocess the data to be suitable for processing to extract core data; and a data analysis unit to use a pre-learned artificial neural network to analyze core data extracted by the data processing unit to monitor and diagnose the solenoid-operated valve in real time. The artificial neural network receives learning data as input data from valves for learning in a normal state and an abnormal state for a prescribed period to be learned to analyze whether the solenoid-operated valve is abnormal.;COPYRIGHT KIPO 2020
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