Wastewater Level Measurement Techniques

Stable blast furnace operation requires proper drainage of liquid from the hearth. The estimation of drainage rate and hearth liquid level are of utmost importance for understanding the underlying hearth phenomena. The present review gives an insight of the need for measurement of the hearth liquid level and further throws light on various methods of estimation of hearth liquid level in-depth, which is primarily divided into 2 categories namely; model-based estimation and sensor-based estimation. Although the model-based estimation and sensor-based estimation have their own advantages and disadvantages, an integrated system comprising of both methods could potentially facilitate operators to reveal the state of hearth, which is unless not available with the implementation of a single method of estimation. Furthermore, the challenges in the estimation and the prospects for determining the reliable hearth liquid level measurement in blast furnace are discussed. The article is presented to give prospect of encountering the drift occurring in estimation of liquid level, which leads to inaccurate prediction and simulation with the industrial blast furnace. Lastly, the article gives recommendation for improving the liquid level estimation methods in blast furnace.

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Helium II level measurement techniques

Cryogenics ◽

10.1016/s0011-2275(01)00092-3 ◽

2001 ◽

Vol 41 (5-6) ◽

pp. 355-366 ◽

Cited By ~ 10

Author(s):

D Celik ◽

D.K Hilton ◽

T Zhang ◽

S.W Van Sciver

Keyword(s):

Measurement Techniques ◽

Helium Ii ◽

Level Measurement

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Measurement of Activity Levels in Patients with Chronic Pain

The Occupational Therapy Journal of Research ◽

10.1177/153944929201200402 ◽

1992 ◽

Vol 12 (4) ◽

pp. 217-228 ◽

Cited By ~ 11

Author(s):

Jill White ◽

Jenny Strong

Keyword(s):

Chronic Pain ◽

Measurement Techniques ◽

Activity Level ◽

Activity Measurement ◽

Chronic Lower Back Pain ◽

Activity Levels ◽

Automated Measurement ◽

Self Monitoring ◽

Measurement Systems ◽

Level Measurement

Patients with chronic pain frequently are asked to keep daily activity diaries. Information from the diaries can be used as an index of improvement in physical functioning. For some patients, however, the reliability of activity diary data may be poor. Because of this problem, it is suggested that increased attention be given to alternative activity measurement techniques. The present study examined the comparability between self-monitoring and automated activity level measurement. Subjects included 20 chronic lower back pain patients. Activity levels were concurrently recorded over 4 days with the two measurement systems. Results showed that subjects recorded significantly lower levels of activity with self-monitoring compared to reliable automated measurement. These results call into question reliance on self-monitoring activity level systems by chronic pain researchers and clinicians. Expanded development and use of automated measurement systems is recommended.

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Advances in thermal level measurement techniques using mathematical models, statistical models and decision support systems in blast furnace

Metallurgical Research & Technology ◽

10.1051/metal/2019019 ◽

2019 ◽

Vol 116 (4) ◽

pp. 421

Author(s):

Ashish Agrawal ◽

Anil Kumar Kothari ◽

Arun Kumar ◽

Manish Kumar Singh ◽

Shivendra Kumar Dubey ◽

...

Keyword(s):

Blast Furnace ◽

Decision Support ◽

Mathematical Models ◽

Decision Support Systems ◽

Statistical Models ◽

Historical Data ◽

Support Systems ◽

Measurement Techniques ◽

Level Measurement ◽

Thermal Level

The estimation of thermal level in blast furnace is of utmost importance, because the processes occurring inside the blast furnace are complex in nature and any drift in thermal level could lead to abnormal furnace state. The present review is made to understand the methods for estimating thermal level in blast furnace, and the drift in estimation of the thermal level. The thermal level estimation is divided into 3 categories, viz. mathematical models, statistical models and decision support systems. The mathematical models are based on the first principle of thermodynamics and give an estimate of the thermal level in blast furnace. On the other hand, the statistical models are mainly the data-based approach that uses the historical data to predict the instability in blast furnace. Lastly, the decision support systems are the prescriptive models that give the recommendations for making the necessary corrections in the process parameters to avoid occurrence of abnormality in blast furnace. Further, the drifts in estimation of thermal level by these techniques are identified and recommendations are made to improve the accuracy of thermal level estimation. The recommendations to control thermal level in blast furnace are provided which when applied in the industrial blast furnace, can avoid the occurrence of catastrophic condition.

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