Ultrasonic flowmeter diagnostics
Donated on 1/12/2018
Fault diagnosis of four liquid ultrasonic flowmeters
Dataset Characteristics
Multivariate
Subject Area
Computer Science
Associated Tasks
Classification
Feature Type
Real
# Instances
540
# Features
-
Dataset Information
Additional Information
Meter A contains 87 instances of diagnostic parameters for an 8-path liquid ultrasonic flow meter (USM). It has 37 attributes and 2 classes or health states: Class '1' - Healthy Class '2' - Installation effects Meter B contains 92 instances of diagnostic parameters for a 4-path liquid USM. It has 52 attributes and 3 classes: Class '1' - Healthy Class '2' - Gas injection Class '3' - Waxing Meter C contains 181 instances of diagnostic parameters for a 4-path liquid USM. It has 44 attributes and 4 classes: Class '1' - Healthy Class '2' - Gas injection Class '3' - Installation effects Class '4' - Waxing Meter D contains 180 instances of diagnostic parameters for a 4-path liquid USM. It has 44 attributes and 4 classes: Class '1' - Healthy Class '2' - Gas injection Class '3' - Installation effects Class '4' - Waxing
Has Missing Values?
No
Variables Table
| Variable Name | Role | Type | Description | Units | Missing Values |
|---|---|---|---|---|---|
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no |
0 to 10 of 173
Additional Variable Information
All attributes are continuous, with the exception of the class attribute. Meter A (1) -- Flatness ratio (2) -- Symmetry (3) -- Crossflow (4)-(11) -- Flow velocity in each of the eight paths (12)-(19) -- Speed of sound in each of the eight paths (20) -- Average speed of sound in all eight paths (21)-(36) -- Gain at both ends of each of the eight paths (37) -- Class attribute or health state of meter: 1,2 Meter B (1) -- Profile factor (2) -- Symmetry (3) -- Crossflow (4) -- Swirl angle (5)-(8) -- Flow velocity in each of the four paths (9) -- Average flow velocity in all four paths (10)-(13) -- Speed of sound in each of the four paths (14) -- Average speed of sound in all four paths (15)-(22) -- Signal strength at both ends of each of the four paths (23)-(26) -- Turbulence in each of the four paths (27) -- Meter performance (28)-(35) -- Signal quality at both ends of each of the four paths (36)-(43) -- Gain at both ends of each of the four paths (44)-51 -- Transit time at both ends of each of the four paths (52) -- Class attribute or health state of meter: 1,2,3 Meters C and D (1) -- Profile factor (2) -- Symmetry (3) -- Crossflow (4)-(7) -- Flow velocity in each of the four paths (8)-(11) -- Speed of sound in each of the four paths (12)-(19) -- Signal strength at both ends of each of the four paths (20)-(27) -- Signal quality at both ends of each of the four paths (28)-(35) -- Gain at both ends of each of the four paths (36)-(43) -- Transit time at both ends of each of the four paths (44) -- Class attribute or health state of meter: 1,2,3,4
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pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset ultrasonic_flowmeter_diagnostics = fetch_ucirepo(id=433) # data (as pandas dataframes) X = ultrasonic_flowmeter_diagnostics.data.features y = ultrasonic_flowmeter_diagnostics.data.targets # metadata print(ultrasonic_flowmeter_diagnostics.metadata) # variable information print(ultrasonic_flowmeter_diagnostics.variables)
Gyamfi,Kojo and Marshall,Craig. (2018). Ultrasonic flowmeter diagnostics. UCI Machine Learning Repository. https://doi.org/10.24432/C5B895.
@misc{misc_ultrasonic_flowmeter_diagnostics_433,
author = {Gyamfi,Kojo and Marshall,Craig},
title = {{Ultrasonic flowmeter diagnostics}},
year = {2018},
howpublished = {UCI Machine Learning Repository},
note = {{DOI}: https://doi.org/10.24432/C5B895}
}Creators
Kojo Gyamfi
Craig Marshall
DOI
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.