Real-time Neonatal Respiratory Rate Estimation using a Pressure-Sensitive Mat

2018 ◽  
Author(s):  
Amente Bekele ◽  
Shermeen Nizami ◽  
Yasmina Souley Dosso ◽  
Cheryl Aubertin ◽  
Kim Greenwood ◽  
...  
Keyword(s):  
Respiratory Rate ◽  
Real Time ◽  
Rate Estimation ◽  
Pressure Sensitive

scholarly journals Measuring Uncertainty During Respiratory Rate Estimation Using Pressure-Sensitive Mats

2018 ◽  
Vol 67 (7) ◽  
pp. 1535-1542 ◽  
Author(s):  
Shermeen Nizami ◽  
Amente Bekele ◽  
Mohamed Hozayen ◽  
Kimberley J. Greenwood ◽  
JoAnn Harrold ◽  
...  
Keyword(s):  
Respiratory Rate ◽  
Rate Estimation ◽  
Pressure Sensitive

scholarly journals Experimental Verification of Real-Time Flow-Rate Estimations in a Tilting-Ladle-Type Automatic Pouring Machine

2021 ◽  
Vol 11 (15) ◽  
pp. 6701
Author(s):  
Yuta Sueki ◽  
Yoshiyuki Noda
Keyword(s):  
Real Time ◽  
Molten Metal ◽  
Flow Rate ◽  
Kalman Filters ◽  
Estimation Method ◽  
Estimation Methods ◽  
Liquid Volume ◽  
Model Parameters ◽  
Rate Estimation ◽  
Time Flow

This paper discusses a real-time flow-rate estimation method for a tilting-ladle-type automatic pouring machine used in the casting industry. In most pouring machines, molten metal is poured into a mold by tilting the ladle. Precise pouring is required to improve productivity and ensure a safe pouring process. To achieve precise pouring, it is important to control the flow rate of the liquid outflow from the ladle. However, due to the high temperature of molten metal, directly measuring the flow rate to devise flow-rate feedback control is difficult. To solve this problem, specific flow-rate estimation methods have been developed. In the previous study by present authors, a simplified flow-rate estimation method was proposed, in which Kalman filters were decentralized to motor systems and the pouring process for implementing into the industrial controller of an automatic pouring machine used a complicatedly shaped ladle. The effectiveness of this flow rate estimation was verified in the experiment with the ideal condition. In the present study, the appropriateness of the real-time flow-rate estimation by decentralization of Kalman filters is verified by comparing it with two other types of existing real-time flow-rate estimations, i.e., time derivatives of the weight of the outflow liquid measured by the load cell and the liquid volume in the ladle measured by a visible camera. We especially confirmed the estimation errors of the candidate real-time flow-rate estimations in the experiments with the uncertainty of the model parameters. These flow-rate estimation methods were applied to a laboratory-type automatic pouring machine to verify their performance.

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