1. A method for diagnosing an anomaly of a plurality of equipment or device based on sensor signals output from a plurality of sensors mounted on the equipment or apparatus, the method comprising the steps of: obtaining multi-dimensional feature vectors from feature values of a plurality of sensor signals in pre-specified learning period; extracting the multi-dimensional feature vectors for each time from feature values of a plurality of sensor signals at the time of diagnosis; calculating reference feature vectors for each time based on the set of the multi-dimensional feature vectors obtained in the pre-specified learning period and on the multi-dimensional feature vector extracted at the each time of diagnosis; calculating the anomaly measure based on difference between the multi-dimensional feature vector extracted at each time and the reference feature vector for each time; detecting an anomaly by comparing the calculated anomaly measure with a predetermined threshold; and; identifying a sensor, from a plurality of sensors, relating to the detected anomalies based on 2-dimensional distribution density of the feature values of a plurality of sensor signals in the time when anomaly was detected.