System identification and modal tracking on ship structures
| dc.contributor.advisor | Bekker, Annie | en_ZA |
| dc.contributor.advisor | Bienert, J. | en_ZA |
| dc.contributor.author | Soal, Keith Ian | en_ZA |
| dc.contributor.other | Stellenbosch University. Faculty of Engineering. Dept. of Mechanical and Mechatronic Engineering. | en_ZA |
| dc.date.accessioned | 2018-02-28T16:53:27Z | |
| dc.date.accessioned | 2018-04-09T07:09:33Z | |
| dc.date.available | 2018-02-28T16:53:27Z | |
| dc.date.available | 2018-04-09T07:09:33Z | |
| dc.date.issued | 2018-03 | |
| dc.description | Thesis (PhD)--Stellenbosch University, 2018. | en_ZA |
| dc.description.abstract | ENGLISH SUMMARY: are currently based mainly on dynamic response feedback. Navigators decide on how to operate the vessel based on how they feel it pitching, heaving, rolling and vibrating. The aim of this thesis is to investigate the idea of using system identification and modal tracking on polar vessels towards the development of a decision aiding system. System identification provides a powerful tool for building mathematical models of dynamic systems. An open source toolbox (openSID) for system identification using Stochastic Subspace Identification (SSI) was developed as a research and learning tool. Full scale measurements were performed on the research vessel Polarstern during an expedition to the Arctic. This is the first comprehensive data set including vibration responses and environmental parameters to span the entire operational profile of a research voyage to the Arctic. System identification successfully identified seven global modes in the bandwidth 2 - 10 Hz. Comparisons between different methods were used to cross validate results. A modal tracking algorithm was developed and relationships between identified modes and system inputs were observed. A novel method is developed to improve the uncertainty and sensitivity of system identification and tracking, based on a data driven statistical model and a Kalman filter. A key objective is to make experimental data maximally informative by using additional system inputs. The model was found to accurately re-create the training data set and was used to make predictions based on future system inputs. The Kalman filter estimates were observed to produce balanced and consistent results. These results demonstrate the potential of an ice force estimation and structural health monitoring system. | en_ZA |
| dc.description.abstract | AFRIKAANSE OPSOMMING: Kritieke besluite in terme van die veilige en doelgerigte bedryf van skepe in ys is tans hoofsaaklik gebasseer op dinamiese hanterings terugvoer. Besluite oor hoe om die vaartuig te navigeer word toegelig deur hoe seevaarders die skip voel duik, heg, rol en vibreer. Die doel van hierdie tesis is om die idee van stelselidentifikasie en modale naspeuring op poolskepe te ondersoek ten einde die ontwikkeling van ’n besluitnemingstelsel. Stelselidentifikasie bied ’n kragtige metode vir die bou van wiskundige modelle van dinamiese stelsels. Oopbron gereedskap algoritme (openSID) vir stelselidentifikasie, met die gebruik van Stochastiese Subspasie Identifikasie (SSI) is ontwikkel as ’n navorsings en leer instrument. Volskaal metings is uitgevoer op die navorsing skip Polarstern tydens ’n ekspedisie na die Arktiese gebied. Dit is die eerste omvattende datastel wat vibrasierespons en omgewingsparameters insluit om die hele operasionele profiel van ’n navorsingsreis na die Arktiese omgewing te dek. Stelselidentifikasie het sewe globale modes in die bandwydte 2 - 10 Hz geïdentifiseer. Vergelykings tussen twee metodes is gebruik om resultate te bekragtig. Modale naspeuringsalgoritme is ontwikkel en verhoudings tussen geïdentifiseerde modusse en stelselinsette is waargeneem. Nuwe metode is ontwikkel om die onsekerheid en sensitiwiteit van stelselidentifikasie en naspeuring te verbeter, gebasseer op ’n data gedrewe statistiese model en ’n Kalman filter. ’n Hoof doelwit is om eksperimentele data maksimaal insiggewend te maak deur addisionele stelsel insette te gebruik. Dit is gevind dat die model die opleidingsdatastel akkuraat naboots. Hierna is dit gebruik om voorspellings te maak gebasseer op toekomstige stelselinsette. Beraming met die Kalman filter is waargeneem om gebalanseerde en konsekwente resultate te lewer. Hierdie resultate demonstreer die potensiaal van ’n besluitnemingsstelsel om ys kragte af te skat en strukturele integriteit te monitor. | af_ZA |
| dc.format.extent | xiv, 107 pages ; illustrations | en_ZA |
| dc.identifier.uri | http://hdl.handle.net/10019.1/103788 | |
| dc.language.iso | en_ZA | en_ZA |
| dc.publisher | Stellenbosch : Stellenbosch University | en_ZA |
| dc.rights.holder | Stellenbosch University | en_ZA |
| dc.subject | Structural dynamics | en_ZA |
| dc.subject | Icebreakers (Ships) | en_ZA |
| dc.subject | Modal analysis | en_ZA |
| dc.subject | System identification | en_ZA |
| dc.subject | Artificial intelligence -- Engineering applications | en_ZA |
| dc.subject | Ship resistance -- Computer programs | en_ZA |
| dc.subject | UCTD | |
| dc.title | System identification and modal tracking on ship structures | en_ZA |
| dc.type | Thesis | en_ZA |