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Data · dataset · 2025

The Arc Loss Dataset

Listed in Borealis

The Arc Loss Dataset is a benchmark dataset designed for time series classification in industrial applications, particularly for fault detection and diagnosis (FDD).

Description

It was collected from a large-scale pyrometallurgical plant and captures the real-world complexities of industrial processes, including high dimensionality, sensor noise, and variable system dynamics. The dataset consists of 3,226 multivariate time series samples, each containing 1,101 time steps (equivalent to 55 minutes) with 96 process variables.

The dataset is split into three subsets: I) train.pt (70% of the samples, 2,258 samples), II) val.pt (10%, 323 samples), and III) test.pt (20%, 645 samples). More information can be found in the README.txt

Links

Where it is published

Catalogue records · 1

Topics

Provenance · 1 source records, 10 field assertions
SourceKeyLast seenRaw
Borealisdoi:10.5683/SP3/NREPZM10 d agoJSON v1
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