DIAGNOSIS OF ABNORMAL OPERATION MODES OF A MACHINE UTILIZING SELF ORGANIZING MAP

Patent №

US 7,743,005

Granted

2010-06-22

Filed 2006

Owner

SHIN CATERPILLAR MITSUBISHI LTD.

Lab

AI components

5

ml · vision · kr · planning · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

11630571

A method and apparatus that detects a multiplicity of normal data sets, each of which includes values of n parameters, for each of the operation modes of an object having a plurality of operation modes. Self-organizing maps are provided for each operation mode using the normal data sets. Abnormal data sets representing virtual abnormal states are created by modifying the values of the n parameters of each of the multiple normal data sets so that as many abnormal data sets as the number of deviation vectors are created for each of the multiple normal data sets. Abnormal operation mode proportion vectors are then created by selecting a self-organizing map from the above noted self-organizing maps which has the highest similarity degree to each of the abnormal data sets.

Machine learningVisionKnowledge representationPlanningAI hardwareG05B 23/024E02F 9/26G05B 23/021G05B 23/0283G06N 3/045G06N 3/0499G06N 3/082G06N 3/09

AI classification

Vision1.00
Knowledge representation1.00
Planning1.00
AI hardware1.00
Machine learning0.98
Natural language0.00
Evolutionary computation0.00
Speech0.00

Ownership

SHIN CATERPILLAR MITSUBISHI LTD.

assignment · 187360741

Assignors

VATCHKOV, GANTCHO LUBENOV, KOMATSU, KOJI, FUJII, SATOSHI, MUROTA, ISAO

On an employer assignment, the assignors are typically the inventors.

From the same owner

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