Kamyr digester-OpenMV.net Datasets

Kamyr digester

Description

Pulp quality is measured by the lignin content remaining in the pulp: the Kappa number. This data set is used to understand which variables in the process influence the Kappa number, and if it can be predicted accurately enough for an inferential sensor application.

Data source

Variables with a number at the end have been lagged by that number of hours to line up the data.

Dayal et al. "Application of feedforward neural networks and partial least squares regression for modelling Kappa number in a continuous Kamyr digester", Pulp and Paper Canada, 95, 1994, p T7-T13.

Data shape

301 rows and 22 columns

Usage restrictions

Unknown

Contact person

Kevin Dunn

Contact details

[email protected]

Added here on

21 October 2011 6:56

Last updated

11 November 2018 16:33

Load this dataset in Python

import pandas as pd

df = pd.read_csv("https://openmv.net/file/kamyr-digester.csv")
df.describe()

Preview (first 10 rows)

Observation	Y-Kappa	ChipRate	BF-CMratio	BlowFlow	ChipLevel4	T-upperExt-2	T-lowerExt-2	UCZAA	WhiteFlow-4	AAWhiteSt-4	AA-Wood-4	ChipMoisture-4	SteamFlow-4	Lower-HeatT-3	Upper-HeatT-3	ChipMass-4	WeakLiquorF	BlackFlow-2	WeakWashF	SteamHeatF-3	T-Top-Chips-4	SulphidityL-4
31-00:00	23.1	16.52	121.717	1177.607	169.805	358.282	329.545	1.443	599.253		16.471	46.011	67.122	329.432	303.099	175.964	1127.197	1319.039	257.325	54.612	252.077
31-01:00	27.6	16.81	79.022	1328.36	341.327	351.05	329.067	1.549	537.201	6.076	16.543	43.954	60.012	330.823	304.879	163.202	665.975	1297.317	241.182	46.603	251.406	29.11
31-02:00	23.19	16.709	79.562	1329.407	239.161	350.022	329.26	1.6	549.611		16.559	44.495	61.304	329.14	303.383	164.013	677.534	1327.072	237.272	51.795	251.335
31-03:00	23.6	16.478	81.011	1334.877	213.527	350.938	331.142	1.604	623.362	6.054	16.562	45.592	68.496	328.875	302.254	181.487	767.853	1324.461	239.478	54.846	250.312	29.02
31-04:00	22.9	15.618	93.244	1334.168	243.131	351.64	332.709		638.672	6.11	16.677	45.512	70.022	328.352	300.954	183.929	888.448	1343.424	215.372	54.186	249.916	29.01
31-05:00	20.89	14.308	94.172	1327.832	251.12	351.263	332.485	1.522	631.514		16.626	45.847	71.286	328.699	300.706	180.229	903.605	1323.082	232.729	54.503	250.084
31-06:00	22.65	14.1	91.887	1307.852	288.989	352.321	331.162	1.468	625.549	6.143	16.62	45.797	71.298	329.662	301.539	179.886	837.178	1315.111	234.047	53.805	249.971	29.22
31-07:00	22.5	14.233	97.249	1346.9	330.325	352.687	328.894	1.48	591.827		16.617	45.832	68.791	331.485	303.488	174.804	889.516	1317.912	226.319	52.546	250.414
31-08:00	24.7	13.85	96.208	1334.892	362.511	352.372	327.358	1.515	553.172	6.199	16.625	45.541	64.249	332.264	305.419	166.12	909.81	1318.725	180.375	48.842	251.121	29.21
31-09:00	22.6	13.875	95.72	1351.24	383.731	347.683	322.363	1.48	541.728		16.624	45.695	62.86	329.58	304.97	163.512	865.051	1319.664	118.24	45.992	251.284