Abstract: Provided are a non-transitory computer readable medium, a diagnostic method, and a diagnostic device, in which a computer performs first processing of setting a plurality of regions in a temperature image showing a temperature distribution of a device, second processing of identifying a change in a first correlation which is a correlation of a first feature amount relating to temperature between regions that are different from each other, and third processing of performing an abnormality diagnosis of the device based on the change in the first correlation.

Abstract: In feature value extraction processing step, feature values are extracted from time-series vibroacoustic data in equipment in operation. In machine learning diagnosis step, accumulated are feature values corresponding to normal equipment-operation-state and general measurement data on equipment. Probability distribution model related to correlation between general measurement data and feature values corresponding to normal equipment-operation-state and constructed through machine learning is fed with general-measurement data and feature values extracted in feature value extraction processing step to calculate degree of anomaly based on probability distribution model.

Abstract: Provided is a magnetic material concentration measuring device including: a bobbin having an outer circumference around which an exciting coil, an output coil, and a further exciting coil are wound; an eccentric hole formed in the bobbin; a rotor that is rotatably fitted in the eccentric hole about an eccentric axis line; a first cutout part that forms a first flow passage on one end side in an eccentric axis line direction of the rotor; a second cutout part that forms a second flow passage whose angle is shifted in a rotor rotation direction with respect to the first cutout part, on another end side in the eccentric axis line direction of the rotor; and a communication passage that connects the first flow passage and the second flow passage.