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Bells Corners, Canada

Horning S.,Technical and Engineering Services | Gonis A.,GasTOPS Ltd.
Marine Technology | Year: 2015

Propulsion system dynamic analysis (PSDA) entails the use of a computer simulation model of the propulsion system to support the design and evaluation of machinery, ship and control algorithm performance. The PSDA simulation model supports the continual development of the ship by identifying issues during the design of the ship systems, by in-service support of the ship control system, and by supporting ship upgrade programs. During the ship design phase, the proposed propulsion control algorithms can be created in the PSDA model to enable designers to identify design issues early in the program. A PSDA can be run from an ordinary desktop computer, which reduces operating costs when compared to a software test facility or onboard the ship. It also allows for work to be done on the algorithms even when a facility or the ship itself is unavailable for testing purposes. Source


Omrani H.,Queens University | Barnes J.A.,Queens University | Dudelzak A.E.,Queens University | Dudelzak A.E.,GasTOPS Ltd. | And 2 more authors.
Analyst | Year: 2012

Excitation emission matrix (EEM) and cavity ring-down (CRD) spectral signatures have been used to detect and quantitatively assess contamination of jet fuels with aero-turbine lubricating oil. The EEM spectrometer has been fiber-coupled to permit in situ measurements of jet turbine oil contamination of jet fuel. Parallel Factor (PARAFAC) analysis as well as Principal Component Analysis and Regression (PCA/PCR) were used to quantify oil contamination in a range from the limit of detection (10 ppm) to 1000 ppm. Fiber-loop cavity ring-down spectroscopy using a pulsed 355 nm laser was used to quantify the oil contamination in the range of 400 ppm to 100000 ppm. Both methods in combination therefore permit the detection of oil contamination with a linear dynamic range of about 10000. © 2012 The Royal Society of Chemistry. Source


Suresh P.,GasTOPS Ltd.
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2014

Alloy identification of oil-borne wear debris captured on chip detectors, filters and magnetic plugs allows the machinery maintainer to assess the health of the engine or gearbox and identify specific component damage. Today, such identification can be achieved in real time using portable, at-line laser-induced breakdown spectroscopy (LIBS) and Xray fluorescence (XRF) instruments. Both techniques can be utilized in various industries including aviation, marine, railways, heavy diesel and other industrial machinery with, however, some substantial differences in application and instrument performance. In this work, the performances of a LIBS and an XRF instrument are compared based on measurements of a wide range of typical aerospace alloys including steels, titanium, aluminum and nickel alloys. Measurement results were analyzed with a staged correlation technique specifically developed for the purposes of this study - identifying the particle alloy composition using a pre-recorded library of spectral signatures. The analysis is performed in two stages: first, the base element of the alloy is determined by correlation with the stored elemental spectra and then, the alloy is identified by matching the particlea's spectral signature using parametric correlation against the stored spectra of all alloys that have the same base element. The correlation analysis has achieved highly repeatable discrimination between alloys of similar composition. Portable LIBS demonstrates higher detection accuracy and better identification of alloys comprising lighter elements as compared to that of the portable XRF system, and reveals a significant reduction in the analysis time over XRF. © 2014 SPIE. Source


Trademark
GasTOPS Ltd. | Date: 2005-07-12

In-line oil debris detection system, namely electronic sensors and monitors for detecting particles in lubricating oils of machinery.


Trademark
GasTOPS Ltd. | Date: 2007-06-05

Apparatus for detecting and analyzing debris collected by magnetic chip detectors.

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