ViSIAr – A virtual sensor integration architecture

Hardy, Nigel; Maroof, Aftab Ahmad

doi:10.1017/s0263574799001915

Cited by 13 publications

(4 citation statements)

References 20 publications

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“…There has been a rapid development of virtual sensing technology over the past decade within a number of different domains, including avionics, autonomous robots, telemedicine, traffic, automotive, nature and building monitoring and control (Dorst, et al1998;Hardy and Maroof, 1999;Oosterom and Babuska, 2000;Kestell, et al 2001;Oza,et al 2005;Srivastava, et al 2005;Gawthrop 2005;Kabadayi, et al 2006;Bose, et al 2007;Ibarg¨uengoytia, et al 2008;Said, et al 2009;Raveendranathan, et al 2009;. In particular, virtual sensing has found widespread applications in process controls and automobiles, so here focuses on these two fields in providing a brief history of notable developments.…”

Section: Major Milestones In Virtual Sensing Developmentmentioning

confidence: 99%

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A virtual supply airflow rate meter for rooftop air-conditioning units

Yu¹,

Li²,

Yang³

2011

Building and Environment

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Section: Major Milestones In Virtual Sensing Developmentmentioning

confidence: 99%

“…This problem can be described as systemization of virtual sensors (SoVS), which has been an active area of research in other fields 93 93 for more than a decade (Hardy and Maroof 1999;Gu et al 2004;Chin et. al, 2005;Bose et al 2007).…”

Section: Future Needs For Virtual Sensing Technology In Building Systemsmentioning

confidence: 99%

A virtual supply airflow rate meter for rooftop air-conditioning units

Yu¹,

Li²,

Yang³

2011

Building and Environment

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“…Virtual sensing techniques have recently gained great attention in many research fields. As proved in several application areas such as transportation system [4], computer science [5], chemistry [6], automation [7], and building automation [8], they are a viable solution for lowering the cost of sensors networks. Furthermore, they enable accurate measurements to be obtained at critical locations where sensors are not easy to install.…”

Section: Introductionmentioning

confidence: 99%

Output-only response mapping of bridges for dynamic response estimation of gusset plate using convolutional neural networks

Dabbaghchian,

Eshkevari,

Marasco

et al. 2024

J. Phys.: Conf. Ser.

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Structural health monitoring of bridges aims to provide an assessment of the condition of the structure, using collected structural response. The efficacy of the methods usually is constrained by the number and spatial distribution of sensors. Developing methods to map the response from known to unknown locations has been a challenging yet interesting area of study in recent years. In this research, we propose and study a novel framework to estimate and reconstruct the dynamic response of bridges at the connection level from the vibration response at global locations. The bridge is considered as a dynamic system in which vehicle excitations are the input and responses at sensor locations are the outputs. The proposed method studies an output-only problem and the input is considered unknown. The response at two types of output locations of the bridge, one at a global and one at the connection detail level are used to learn the dynamic relationship between the time signals via convolutional neural networks. This model-free framework is validated through a finite element simulation to reconstruct the strain response at the gusset plate of a truss bridge from the responses at other nodes along the bridge.

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“…Los sensores o instrumentos virtuales son resultado de algunas de estas investigaciones, emulan el comportamiento de instrumentos reales y su operación se basa en la relación que existe entre las variables medibles y métodos para estimación de otras [3], [4]. En la actualidad los sensores virtuales son empleados en una amplia variedad de campos: aviación [5], robótica [6], control de tráfico [7], entre otros [8], [9], [10]. Tal es el caso [11], que se usan sensores virtuales en técnicas de visión artificial para la lectura de transmisores indicadores, y [12], [13] se presentan sensores software, basados en téc-Resumen-En un circuito hidráulico, el fluido sufre pér-didas de presión al atravesar tramos o diferentes accesorios, estas pueden ser inspeccionadas observando el nivel del fluido en piezómetros.…”

Section: Introductionunclassified

Medición de pérdidas de presión usando visión por computador

Cerquera-Yacumal

Córdoba-Papamija

Realpe-Chamorro

et al. 2016

Iteckne

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Resumen-En un circuito hidráulico, el fluido sufre pér-didas de presión al atravesar tramos o diferentes accesorios, estas pueden ser inspeccionadas observando el nivel del fluido en piezómetros. Este trabajo presenta un desarrollo en visión artificial, que permite la medición en línea de los niveles de presión registrados en dieciséis columnas piezométricas. La técnica de extracción de fondo basada en el algoritmo de Codebook, combinada con el filtrado morfológico y unión de blobs, es usada para obtener los niveles piezométricos. El algoritmo de procesamiento está diseñado en Open CV y soportado en Linux. Se obtuvieron coeficientes de variación inferiores al 0,1% y errores máximos del 1,4 %.Palabras clave-Codebook, extracción de fondo, instrumentación y medición, piezómetro, visión por computador.Abstract-In a hydraulic circuit, the fluid pressure loss when passing through different sections or accessories, and it can be inspected by observing the fluid level in piezometers. This paper presents a development in artificial vision, which allows on-line measurement of pressure levels recorded in sixteen piezometric columns. The technique of background subtraction based in algorithm on Codebook, combined with morphological filtering and junction blobs, are used to obtain piezometrics levels. The processing algorithm is designed in Open CV and supported on Linux. Coefficients of variation of less than 0.1% and maximum error of 1.4% were obtained.

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ViSIAr – A virtual sensor integration architecture

Cited by 13 publications

References 20 publications

A virtual supply airflow rate meter for rooftop air-conditioning units

A virtual supply airflow rate meter for rooftop air-conditioning units

Output-only response mapping of bridges for dynamic response estimation of gusset plate using convolutional neural networks

Medición de pérdidas de presión usando visión por computador

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