METHOD AND SYSTEM FOR UNSUPERVISED ANOMALY DETECTION AND ACCOUNTABILITY WITH MAJORITY VOTING FOR HIGH-DIMENSIONAL SENSOR DATA

• Main Authors: Sasaki, Yukinori, Raghavan, Ajay, Minegishi, Akira, Jung, Deokwoo, Ogura, Tetsuyoshi, Cheng, Fangzhou, Tajika, Yosuke
• Format: Patent
• Language: English
• Published: 10.12.2020
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; MEASURING; PHYSICS; TESTING; TESTING STATIC OR DYNAMIC BALANCE OF MACHINES ORSTRUCTURES; TESTING STRUCTURES OR APPARATUS NOT OTHERWISE PROVIDED FOR

One embodiment can provide a system for detecting anomaly for high-dimensional sensor data associated with one or more machines. During operation, the system can obtain sensor data from a set of sensor associated with one or machines, apply data exploration techniques on the sensor data to automatically process sensor data to identify a subset of feature sensors from the available set of feature sensors, apply an unsupervised machine-learning technique to the identified subset of feature sensors and the target sensor to learn a set of pair-wise univariate models, and determine whether and how an anomaly occurs in the operation of the one or more machines based on the set of pair-wise univariate models.