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.

Hybrid method based on particle filter and NARX for real-time flow rate estimation in multi-product pipelines

2020 ◽  
Vol 88 ◽  
pp. 19-31 ◽  
Author(s):  
Lei He ◽  
Kai Wen ◽  
Changchun Wu ◽  
Jing Gong ◽  
Xie Ping
Keyword(s):  
Particle Filter ◽  
Real Time ◽  
Flow Rate ◽  
Hybrid Method ◽  
Rate Estimation ◽  
Time Flow

scholarly journals Real-Time Estimation of Drivers’ Trust in Automated Driving Systems

2020 ◽  
Author(s):  
Hebert Azevedo-Sa ◽  
Suresh Kumaar Jayaraman ◽  
Connor T. Esterwood ◽  
X. Jessie Yang ◽  
Lionel P. Robert ◽  
...  
Keyword(s):  
Real Time ◽  
User Study ◽  
Estimation Method ◽  
Time Estimation ◽  
Trust Model ◽  
Estimation Methods ◽  
Model Parameters ◽  
Automated Driving ◽  
Driving System ◽  
Classical State

Abstract Trust miscalibration issues, represented by undertrust and overtrust, hinder the interaction between drivers and self-driving vehicles. A modern challenge for automotive engineers is to avoid these trust miscalibration issues through the development of techniques for measuring drivers’ trust in the automated driving system during real-time applications execution. One possible approach for measuring trust is through modeling its dynamics and subsequently applying classical state estimation methods. This paper proposes a framework for modeling the dynamics of drivers’ trust in automated driving systems and also for estimating these varying trust levels. The estimation method integrates sensed behaviors (from the driver) through a Kalman filter-based approach. The sensed behaviors include eye-tracking signals, the usage time of the system, and drivers’ performance on a non-driving-related task. We conducted a study ($$n=80$$ n = 80 ) with a simulated SAE level 3 automated driving system, and analyzed the factors that impacted drivers’ trust in the system. Data from the user study were also used for the identification of the trust model parameters. Results show that the proposed approach was successful in computing trust estimates over successive interactions between the driver and the automated driving system. These results encourage the use of strategies for modeling and estimating trust in automated driving systems. Such trust measurement technique paves a path for the design of trust-aware automated driving systems capable of changing their behaviors to control drivers’ trust levels to mitigate both undertrust and overtrust.

scholarly journals Foaming of industrial lean methyldiethanolamine solution in the presence of hydrocarbon and fatty acid based corrosion inhibitors

2018 ◽  
Vol 73 ◽  
pp. 76 ◽  
Author(s):  
Mohammad Keewan ◽  
Fawzi Banat ◽  
Priyabrata Pal ◽  
Jerina Zain ◽  
Emad Alhseinat
Keyword(s):  
Fatty Acid ◽  
Pore Size ◽  
Corrosion Inhibitor ◽  
Flow Rate ◽  
Gas Flow ◽  
Corrosion Inhibitors ◽  
Liquid Volume ◽  
Operating Parameters ◽  
Time Flow ◽  
Foaming Time

In natural gas sweetening alkanolamine processes one of the regularly used chemical is the corrosion inhibitor. For better operation of the plant it is essential to understand the effect of their presence on foaming of industrial lean Methyldiethanolamine (MDEA) used as solvents at different temperatures. This study aimed at investigating the effect of HydroCarbon Based (HCB) and fatty acid based corrosion inhibitor having chemical name Bis(2-Hydroxyethyl)Cocoalkylamine (BHCL) on the foaming tendency of industrial real lean MDEA solutions. Experiments were conducted with different operating parameters, including liquid volume of the solution, foaming time, flow rate of nitrogen gas, concentration of the corrosion inhibitors, temperature of the solution, and gas diffuser pore size using the Foam Scan instrument. With the increase in solution volume and foaming time foaming happens to be more. The foaming tendency of lean MDEA solutions decreased with increasing temperature in absence of corrosion inhibitors but showed different behavior in their presence. At small diffuser pore size and high gas flow rate, the final foam volume increased in the presence of HCB but decreased with the BHCL inhibitor. Optimizing the operating parameters to minimize foaming was verified to be a function of the type of inhibitor used.

scholarly journals A Novel Real-Time Human Heart Rate Estimation Method for Noncontact Vital Sign Radar Detection

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 88689-88699
Author(s):  
Yipeng Ding ◽  
Xiali Yu ◽  
Chengxi Lei ◽  
Yinhua Sun ◽  
Xuemei Xu ◽  
...  
Keyword(s):  
Heart Rate ◽  
Real Time ◽  
Vital Sign ◽  
Human Heart ◽  
Estimation Method ◽  
Radar Detection ◽  
Rate Estimation ◽  
Heart Rate Estimation

scholarly journals A New Extended Two-Parameter Distribution: Properties, Estimation Methods, and Applications in Medicine and Geology

Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1578 ◽  
Author(s):  
Hazem Al-Mofleh ◽  
Ahmed Z. Afify ◽  
Noor Akma Ibrahim
Keyword(s):  
Estimation Method ◽  
Estimation Methods ◽  
Parameter Distribution ◽  
Model Parameters ◽  
Unknown Parameters ◽  
Proposed Model ◽  
Rate Functions ◽  
The Mean ◽  
Modeling Data ◽  
Two Parameter

In this paper, a new two-parameter generalized Ramos–Louzada distribution is proposed. The proposed model provides more flexibility in modeling data with increasing, decreasing, J-shaped, and reversed-J shaped hazard rate functions. Several statistical properties of the model were derived. The unknown parameters of the new distribution were explored using eight frequentist estimation approaches. These approaches are important for developing guidelines to choose the best method of estimation for the model parameters, which would be of great interest to practitioners and applied statisticians. Detailed numerical simulations are presented to examine the bias and the mean square error of the proposed estimators. The best estimation method and ordering performance of the estimators were determined using the partial and overall ranks of all estimation methods for various parameter combinations. The performance of the proposed distribution is illustrated using two real datasets from the fields of medicine and geology, and both datasets show that the new model is more appropriate as compared to the Marshall–Olkin exponential, exponentiated exponential, beta exponential, gamma, Poisson–Lomax, Lindley geometric, generalized Lindley, and Lindley distributions, among others.

Vision-Based Real-Time Microflow-Rate Control System for Cell Analysis

2016 ◽  
Vol 28 (6) ◽  
pp. 854-861 ◽  
Author(s):  
Tadayoshi Aoyama ◽  
◽  
Amalka De Zoysa ◽  
Qingyi Gu ◽  
Takeshi Takaki ◽  
...  
Keyword(s):  
Fluid Flow ◽  
Control System ◽  
Real Time ◽  
Flow Rate ◽  
Rate Control ◽  
Microfluidic Devices ◽  
Cell Analysis ◽  
Time Flow ◽  
On Chip ◽  
Flow Rate Control

[abstFig src='/00280006/09.jpg' width='300' text='Snapshots of particle sorting experiment using our system' ] On-chip cell analysis is an important issue for microtechnology research, and microfluidic devices are frequently used in on-chip cell analysis systems. One approach to controlling the fluid flow in microfluidic devices for cell analysis is to use a suitable pumps. However, it is difficult to control the actual flow-rate in a microfluidic device because of the difficulty in placing flow-rate sensors in the device. In this study, we developed a real-time flow-rate control system that uses syringe pumps and high-speed vision to measure the actual fluid flow in microfluidic devices. The developed flow-rate control system was verified through experiments on microparticle velocity control and microparticle sorting.

1P1-M03 Real-Time Flow-Rate Control System for Cell sorting

2015 ◽  
Vol 2015 (0) ◽  
pp. _1P1-M03_1-_1P1-M03_2
Author(s):  
Tadayoshi AOYAMA ◽  
Zoysa Amalka ◽  
Qingyi GU ◽  
Takeshi TAKAKI ◽  
Idaku ISHII
Keyword(s):  
Control System ◽  
Real Time ◽  
Flow Rate ◽  
Rate Control ◽  
Cell Sorting ◽  
Time Flow ◽  
Flow Rate Control

scholarly journals Does the Complexity of Evapotranspiration and Hydrological Models Enhance Robustness?

2018 ◽  
Vol 10 (8) ◽  
pp. 2837 ◽  
Author(s):  
Dereje Birhanu ◽  
Hyeonjun Kim ◽  
Cheolhee Jang ◽  
Sanghyun Park
Keyword(s):  
Potential Evapotranspiration ◽  
Estimation Method ◽  
Model Performance ◽  
Low Flow ◽  
Estimation Methods ◽  
Model Parameters ◽  
Hydrological Models ◽  
Shuffled Complex Evolution ◽  
University Of Arizona ◽  
Optimizing Model

In this study, five hydrological models of increasing complexity and 12 Potential Evapotranspiration (PET) estimation methods of different data requirements were applied in order to assess their effect on model performance, optimized parameters, and robustness. The models were applied over a set of 10 catchments that are located in South Korea. The Shuffled Complex Evolution-University of Arizona (SCE-UA) algorithm was implemented to calibrate the hydrological models for each PET input while considering similar objective functions. The hydrological models’ performance was satisfactory for each PET input in the calibration and validation periods for all of the tested catchments. The five hydrological models’ performance were found to be insensitive to the 12 PET inputs because of the SCE-UA algorithm’s efficiency in optimizing model parameters. However, the five hydrological models’ parameters in charge of transforming the PET to actual evapotranspiration were sensitive and significantly affected by the PET complexity. The values of the three statistical indicators also agreed with the computed model evaluation index values. Similarly, identical behavioral similarities and Dimensionless Bias were observed in all of the tested catchments. For the five hydrological models, lack of robustness and higher Dimensionless Bias were seen for high and low flow as well as for the Hamon PET input. The results indicated that the complexity of the hydrological models’ structure and the PET estimation methods did not necessarily enhance model performance and robustness. The model performance and robustness were found to be mainly dependent on extreme hydrological conditions, including high and low flow, rather than complexity; the simplest hydrological model and PET estimation method could perform better if reliable hydro-meteorological datasets are applied.

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