Das Institut für Ingenieurgeodäsie und Messsysteme der Technischen Universität Graz veranstaltet vom 25. bis zum 29. April 2017 den 18. Internationalen Ingenieurvermessungskurs. Dieser Kurs setzt die traditionsreiche Reihe fort, die auf den Optischen Streckenmesskurs von 1928 zurückgeht. Seit 1976 wurde die Tagung unter der Bezeichnung „Ingenieurvermessung“ im vierjährigen Zyklus von den Technischen Universitäten München, Zürich und Graz organisiert. In diesem Tagungsband werden die Vorträge und Poster der Ingenieurvermessung 17 veröffentlicht, die u. a. folgende Themenschwerpunkte behandeln: Bauaufnahme und Baumesstechnik Ingenieurnavigation Monitoring Aktuelle Ingenieurprojekte
Today, deformation measurements are not the sole competence of surveyors anymore as geodetic sensors (tacheometers, GPS, etc.) are commonly used simultaneously with sensors of other disciplines. Although, the combined analysis appears straight forward at the first glance, problems arise when connection measurements between spatially distributed sensors are missing. Furthermore, in practice the measurements of different sensor types are often carried out by different groups and are rarely made simultaneously. The general situation is therefore given by spatially distributed measurements of different types and scattered in time. In this thesis an Integrated Analysis Method (IAM) is proposed which allows the use of spatially distributed, hybrid measurements taken at different times in combination with a Finite Element Model (FEM). With the proposed method it is possible to separate deformations caused by regular changes (e. g. temperature changes) from deformations induced by damage (e. g. cracks, material deterioration). The generic method can be applied to inhomogeneous monitoring data of any structure as long as a physical model can be established. The method consists of a measurement part and of a system part. The system part is derived from the physical model. Both parts are connected by the condition that measured and predicted deformations have to be the same. The condition equations are introduced as observations with very high weight. The physical parameters are then estimated in a least squares estimation.
