Sensor fusion

Henderson, Thomas C.; Dekhil, Mohamed; Kessler, Robert R.; Griss, Martin L.

doi:10.1007/bfb0015084

Cited by 5 publications

(3 citation statements)

References 31 publications

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“…The use of magnitudes obtained by several sensors or measuring systems and compiled to obtain a value (or values) that describe the static or dynamic behaviour of processes have been popularized in the scientific community with the expressions ''sensor fusion'' or ''fusion sensory data'' [98,125,126].…”

Section: Sensor Fusion In Arc Welding Processesmentioning

confidence: 99%

Measurement and estimation of the weld bead geometry in arc welding processes: the last 50 years of development

Bestard

Alfaro

2018

J Braz. Soc. Mech. Sci. Eng.

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The arc welding process is widely used in industry, but the automatic control is limited by the difficulty in the process for measuring the principal magnitudes and to close the control loop. Adverse environmental conditions make use of conventional measurement systems difficult for obtaining information of the weld bead geometry. Under these conditions, indirect sensing techniques are a good option. Different sensing and estimation techniques are used, but few researchers are focusing on the flat welding position. The theory and practice prove that the dynamic models are the best representation to control the welding process, but most studies are performed with static models. This work is a review of the algorithms and sensing techniques used for collecting values of the arc welding process that allow the measurement or estimation of the weld bead geometry. Special attention is given to sensor fusion techniques due to its promising future in the welding process. Discussed in this text are the papers, patents, thesis and other documents found on the theme. It shows a summary of their evolution over the last 50 years.

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Section: Sensor Fusion In Arc Welding Processesmentioning

confidence: 99%

Measurement and estimation of the weld bead geometry in arc welding processes: the last 50 years of development

Bestard

Alfaro

2018

J Braz. Soc. Mech. Sci. Eng.

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“…Sensor fusion techniques are used to describe the static and dynamic behaviour of process variables [ 18 , 19 , 20 , 21 ]. These techniques are increasingly being used to estimate magnitudes that are impossible to measure directly.…”

Section: Introductionmentioning

confidence: 99%

Sensor Fusion to Estimate the Depth and Width of the Weld Bead in Real Time in GMAW Processes

Bestard

Sampaio

Vargas

et al. 2018

Sensors

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The arc welding process is widely used in industry but its automatic control is limited by the difficulty in measuring the weld bead geometry and closing the control loop on the arc, which has adverse environmental conditions. To address this problem, this work proposes a system to capture the welding variables and send stimuli to the Gas Metal Arc Welding (GMAW) conventional process with a constant voltage power source, which allows weld bead geometry estimation with an open-loop control. Dynamic models of depth and width estimators of the weld bead are implemented based on the fusion of thermographic data, welding current and welding voltage in a multilayer perceptron neural network. The estimators were trained and validated off-line with data from a novel algorithm developed to extract the features of the infrared image, a laser profilometer was implemented to measure the bead dimensions and an image processing algorithm that measures depth by making a longitudinal cut in the weld bead. These estimators are optimized for embedded devices and real-time processing and were implemented on a Field-Programmable Gate Array (FPGA) device. Experiments to collect data, train and validate the estimators are presented and discussed. The results show that the proposed method is useful in industrial and research environments.

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“…Multiple sensors in a control system can be used to provide more information, robustness, and complementary information [9]. When two or more sensory data or data derived from sensory data are combined, the results can be better than would be possible if only the individual sensors were used.…”

Section: Sensor Fusionmentioning

confidence: 99%

Indoor Location Tracking and Orientation Estimation Using a Particle Filter, Ins, and Rssi

Nouri¹

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Indoor Location Tracking and Orientation Estimation using a Particle Filter, INS, and RSSI Cameron NouriWith the advent of wireless sensor technologies becoming more and more common-place in wearable devices and smartphones, indoor localization is becoming a heavily researched topic. One such application for this topic is in the medical field where wireless sensor devices that are capable of monitoring patient vitals and giving accurate location estimations allow for a less intrusive environment for nursing home patients.This project explores the usage of using received signal strength indication (RSSI) in conjunction with an inertial navigation system (INS) to provide location estimations without the use of GPS in a Particle Filter with a small development microcontroller and base station. The paper goes over the topics used in this thesis and the results.Page iv ACKNOWLEDGMENTS Thank you Rudi Bendig and Ryan Green and Kenneth Finnigan for information at the onset of this thesis. Thank you Collin MacGregor and Karl Preheim for the help in reviewing data and providing input. Thank you to my advisor committee for the knowledge and helpful tutelage throughout my college career.

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Sensor fusion

Cited by 5 publications

References 31 publications

Measurement and estimation of the weld bead geometry in arc welding processes: the last 50 years of development

Measurement and estimation of the weld bead geometry in arc welding processes: the last 50 years of development

Sensor Fusion to Estimate the Depth and Width of the Weld Bead in Real Time in GMAW Processes

Indoor Location Tracking and Orientation Estimation Using a Particle Filter, Ins, and Rssi

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