Dataset for Sensorless Drive Diagnosis

Donated on 2/23/2015

Features are extracted from motor current. The motor has intact and defective components. This results in 11 different classes with different conditions.

Dataset Characteristics

Multivariate

Subject Area

Computer Science

Associated Tasks

Classification

Feature Type

Real

# Instances

58509

# Features

-

Dataset Information

Additional Information

Features are extracted from electric current drive signals. The drive has intact and defective components. This results in 11 different classes with different conditions. Each condition has been measured several times by 12 different operating conditions, this means by different speeds, load moments and load forces. The current signals are measured with a current probe and an oscilloscope on two phases.

Has Missing Values?

No

Variables Table

Variable NameRoleTypeDemographicDescriptionUnitsMissing Values
no
no
no
no
no
no
no
no
no
no

0 to 10 of 49

Additional Variable Information

The Empirical Mode Decomposition (EMD) was used to generate a new database for the generation of features. The first three intrinsic mode functions (IMF) of the two phase currents and their residuals (RES) were used and broken down into sub-sequences. For each of this sub-sequences, the statistical features mean, standard deviation, skewness and kurtosis were calculated.

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Creators

Martyna Bator

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