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Dataset for Fault Classification in Rock Drills, a Fast Oscillating Hydraulic System
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This work describes the collection and properties of the publicly available rock drill fault classification data set rockdrill11, used for the 2022 PHM Conference Data Challenge. The data is collected from a carefully instrumented hydraulic rock drill, operating in normal operation in a test cell while inducing a number of faults. Hydraulic pressure is measured at 50kHz at three different locations, resulting in detailed pressure signatures for each fault. Due to wave propagation phenomena, the system is sensitive to individual differences between different rock drills, drills rigs and configurations. Such differences named "individuals" are introduced in the data by altering certain parameters in the test setup. An important part of the data is therefore the availability of No-fault reference cycles, which are supplied for all individuals. These reference cycles give information on how individuals differ from each other, and can be used to improve classification.
Title: Dataset for Fault Classification in Rock Drills, a Fast Oscillating Hydraulic System
Description:
This work describes the collection and properties of the publicly available rock drill fault classification data set rockdrill11, used for the 2022 PHM Conference Data Challenge.
The data is collected from a carefully instrumented hydraulic rock drill, operating in normal operation in a test cell while inducing a number of faults.
Hydraulic pressure is measured at 50kHz at three different locations, resulting in detailed pressure signatures for each fault.
Due to wave propagation phenomena, the system is sensitive to individual differences between different rock drills, drills rigs and configurations.
Such differences named "individuals" are introduced in the data by altering certain parameters in the test setup.
An important part of the data is therefore the availability of No-fault reference cycles, which are supplied for all individuals.
These reference cycles give information on how individuals differ from each other, and can be used to improve classification.
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