Radar Technology

In this book “Radar Technology”, the chapters are divided into four main topic areas: Topic area 1: “Radar Systems” consists of chapters which treat whole radar systems, environment and target functional chain. Topic area 2: “Radar Applications” shows various applications of radar systems, including meteorological radars, ground penetrating radars and glaciology. Topic area 3: “Radar Functional Chain and Signal Processing” describes several aspects of the radar signal processing. From parameter extraction, target detection over tracking and classification technologies. Topic area 4: “Radar Subsystems and Components” consists of design technology of radar subsystem components like antenna design or waveform design

Advanced Operation and Maintenance in Solar Plants, Wind Farms and Microgrids

This reprint presents advances in operation and maintenance in solar plants, wind farms and microgrids. This compendium of scientific articles will help clarify the current advances in this subject, so it is expected that it will please the reader

7th EEEIC International Workshop on Environment and Electrical Engineering : Wroclaw - Cottbus, 5 - 11. May 2008

The proposed solution meets the latest trends in world power engineering and has the lowest ecological costs amongst the accessible power engineering solutions. It is also in accordance with the Polish power engineering law, which takes into account the recommendations of the European Economic Commission, the Second Sulphur Protocol and the Framework Convention of the United Nations (concerning the changes of climate)

Closing the loop: the integration of long-term ambient vibration monitoring in structural engineering design

his study investigated the integration of long-term monitoring into the structural engineering design process to improve the design and operation of civil structures. A survey of civil and structural engineering professionals, conducted as part of this research, identified the cost and complexity of in-situ monitoring as key barriers to their implementation in practice. Therefore, the research focused on the use of ambient vibration monitoring as it is offers a low cost and unobtrusive method for instrumenting new and existing structures. The research was structured around the stages of analysing ambient vibration data using operational modal analysis (OMA), defined in this study as: i) pre-selection of analysis parameters, ii) pre-processing of the data, iii) estimation of the modal parameters, iv) identification of modes of vibration within the modal estimates, and v) using modal parameter estimates as a basis for understanding and quantifying in-service structural behaviour. A method was developed for automating the selecting of the model order, the number of modes of vibrations assumed to be identifiable within the measured dynamic response. This method allowed the modal estimates from different structures, monitoring periods or analysis parameters to be compared, and removed part of the subjectivity identified within current OMA methods. Pre-processing of ambient acceleration responses through filtering was identified as a source of bias within OMA modal estimates. It was shown that this biasing was a result of filtering artefacts within the processed data. Two methods were proposed for removing or reducing the bias of modal estimates induced by filtering artefacts, based on exclusion of sections of the response corrupted by the artefacts or fitting of the artefacts as part of the modal analysis. A new OMA technique, the short-time random decrement technique (ST-RDT) was developed on the basis of the survey of industry perceptions of long-term monitoring and limitations of existing structural monitoring techniques identified within the literature. Key advantages of the ST-RDT are that it allows the uncertainty of modal estimates and any changes in modal behaviour to be quantified through subsampling theory. The ST-RDT has been extensively validated with numerical, experimental and real-world case studies including multi-storey timber buildings and the world's first 3D printed steel bridge. Modal estimates produced using the ST-RDT were used as a basis for developing an automated method of identifying modes of vibration using a probabilistic mixture model. Identification of modes of vibration within OMA estimates was previously a specialized skill. The procedure accounts for the inherent noise associated with ambient vibration monitoring and allows the uncertainty within the modal estimates associated with each mode of vibration to be quantified. Methods of identifying, isolating and quantifying weak non-linear modal behaviour, changes in dynamic behaviour associated with changes in the distributions of mass or stiffness within a structure have been developed based on the fundamental equations of structural dynamics. These methods allow changes in dynamic behaviour associated with thermally-induced changes in stiffness or changes in static loading to be incorporated within the automated identification of modes of vibration. These methods also allow ambient vibration monitoring to be used for estimating structural parameters usually measured by more complex, expensive or delicate sensors. Examples of this include estimating the change in elastic modulus of simple structures with temperature or estimating the location and magnitude of static loads applied to a structure in-service. The methods developed in this study are applicable to a wide range of structural monitoring technologies, are accessible to non-specialist audiences and may be adapted for the monitoring of any civil structure