Full Text Available

Note: Clicking the button above will open the full text document at the original institutional repository in a new window.

Turbomachine internal pressure and blade response modelling

Dissertation (MEng)--University of Pretoria, 2015.

Saved in:
Bibliographic Details
Other Authors: Heyns, P.S. (Philippus Stephanus)
Format: Thesis
Language:English
Published: University of Pretoria 2016
Subjects:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1867613497276235776
access_status_str Open Access
author2 Heyns, P.S. (Philippus Stephanus)
author_browse Heyns, P.S. (Philippus Stephanus)
author_facet Heyns, P.S. (Philippus Stephanus)
collection Thesis
dc_rights_str_mv © 2016 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria.
description Dissertation (MEng)--University of Pretoria, 2015.
format Thesis
id oai:repository.up.ac.za:2263/56131
institution University of Pretoria (South Africa)
language English
last_indexed 2026-06-10T12:37:05.077Z
license_str Other — see source repository
provenance_str_mv Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository
publishDate 2016
publishDateRange 2016
publishDateSort 2016
publisher University of Pretoria
publisherStr University of Pretoria
record_format dspace
source_str UPSpace — University of Pretoria Institutional Repository
spelling oai:repository.up.ac.za:2263/56131 Turbomachine internal pressure and blade response modelling Heyns, P.S. (Philippus Stephanus) u29083916@tuks.co.za Church, Chris Bryan UCTD Turbomachinery Internal pressure modelling Blade response Aeroelasticity Engineering, built environment and information technology theses SDG-09 SDG-09: Industry, innovation and infrastructure Engineering, built environment and information technology theses SDG-07 SDG-07: Affordable and clean energy Dissertation (MEng)--University of Pretoria, 2015. Blades are critical components of turbomachines, failure of a single blade may result in catastrophic failure of the entire machine. One study found that blade failure was the third largest cause of power generation unit unavailability. Their condition during operation is therefore of interest to monitor. Various intrusive and non-intrusive blade vibration measurement (BVM) techniques have been developed for this purpose. Intrusive techniques such as strain gauge approaches and the frequency modulated grid method require expensive and complex alteration of the actual blades and/or casing. Further, they are prone to failure due to operation in harsh working environments. Therefore the use of intrusive techniques has been predominantly limited to design verification, testing and research. Blade tip timing approaches are currently at the forefront of BVM. The practicality, accuracy and ease of implementation of these approaches have limited their commercial roll out. An alternative nonintrusive source of blade vibration information was found in the internal casing pressure signal (CPS). As the machine operates the blade movement excites the fluid in the casing, producing a measureable response. Unlike BTT approaches which deal with a scarcity of information, CPS based methods must identify blade vibration from a complex signal which contains multiple other sources of information. The issue of how to model the blades response and fluid interaction is the topic of this investigation. An available single stage turbomachine mock setup was modified for internal pressure and direct blade vibration measurements. Pressure measurements were taken in line with a redesigned hub and rotor blade assembly. Strain gauges (SG) were applied to blades in order to capture their response. The blades response was modelled as the combination of a forcing function and a multiple degree of freedom transfer function. Repurposed experimental modal analysis frequency response reconstruction techniques were used to model the blades transfer function. It was found that this technique was able to capture the blades underlying behaviour to a high degree. The forcing function was modelled in the time domain as a series of Gaussian shaped force distributions. It was found that the model was able to capture many important aspects of the forcing behaviour. Both the forcing function and blade transfer function were explored using constrained optimisation techniques. The blade-fluid interaction was modelled as a Fourier series. It was shown that the blade behaviour cannot be extracted from a pressure signal using standard frequency analysis techniques. The viability of an inverse problem solution methodology, for the purpose of blade behaviour extraction, was investigated. This was achieved by solving reduced components of the model with SG measurements and observations from pressure measurements. Further the need to isolate the pressure field about individual blades was motivated and a novel time domain windowing technique provided. tm2016 mi2025 Mechanical and Aeronautical Engineering MEng Unrestricted SDG-09: Industry, innovation and infrastructure SDG-07: Affordable and clean energy 2016-07-29T11:02:17Z 2016-07-29T11:02:17Z 2016-04-15 2015 Dissertation Church, CB 2015, Turbomachine internal pressure and blade response modelling, MEng Dissertation, University of Pretoria, Pretoria, viewed yymmdd <http://hdl.handle.net/2263/56131> A2016 http://hdl.handle.net/2263/56131 en © 2016 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. application/pdf University of Pretoria
spellingShingle UCTD
Turbomachinery
Internal pressure modelling
Blade response
Aeroelasticity
Engineering, built environment and information technology theses SDG-09
SDG-09: Industry, innovation and infrastructure
Engineering, built environment and information technology theses SDG-07
SDG-07: Affordable and clean energy
Turbomachine internal pressure and blade response modelling
title Turbomachine internal pressure and blade response modelling
title_full Turbomachine internal pressure and blade response modelling
title_fullStr Turbomachine internal pressure and blade response modelling
title_full_unstemmed Turbomachine internal pressure and blade response modelling
title_short Turbomachine internal pressure and blade response modelling
title_sort turbomachine internal pressure and blade response modelling
topic UCTD
Turbomachinery
Internal pressure modelling
Blade response
Aeroelasticity
Engineering, built environment and information technology theses SDG-09
SDG-09: Industry, innovation and infrastructure
Engineering, built environment and information technology theses SDG-07
SDG-07: Affordable and clean energy
url http://hdl.handle.net/2263/56131