To reduce erroneous detection by reducing influence of environmental vibration even when the environmental vibration is changed during learning and during diagnosis when diagnosing an abnormality of mechanical equipment by vibration.
When diagnosing an abnormality of mechanical equipment on the basis of vibration values collected by a vibration sensor installed in the mechanical equipment, a learning value feature quantity differential value to be a difference between each feature quantity is calculated from a first learning vibration value corresponding to a first operation state collected by the vibration sensor during learning and a second learning vibration value corresponding to a second operation state which is different from the first operation state collected by the vibration sensor during learning, a diagnosis value feature quantity differential value to be a difference between each feature quantity is calculated from a first learning vibration value corresponding to the first operation state collected by the vibration sensor during diagnosis and a second learning vibration value corresponding to the second operation state collected by the vibration sensor during diagnosis, the learning value feature quantity differential value is compared with the diagnosis value feature quantity differential value, and the presence or absence of the mechanical equipment is determined.
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Yuji Toda
Shigemi Iwasaki