| 1. |
- Axelberg, Peter
(author)
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On Tracing Flicker Sources and Classification of Voltage Disturbances
- 2007
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Doctoral thesis (other academic/artistic)abstract
- Developments in measurement technology, communication and data storage have resulted in measurement systems that produce large amount of data. Together with the long existing need for characterizing the performance of the power system this has resulted in demand for automatic and efficient information-extraction methods. The objective of the research work presented in this thesis was therefore to develop new robust methods that extract additional information from voltage and current measurements in power systems. This work has contributed to two specific areas of interest. The first part of the work has been the development of a measurement method that gives information how voltage flicker propagates (with respect to a monitoring point) and how to trace a flicker source. As part of this work the quantity of flicker power has been defined and integrated in a perceptionally relevant measurement method. The method has been validated by theoretical analysis, by simulations, and by two field tests (at low-voltage and at 130-kV level) with results that matched the theory. The conclusion of this part of the work is that flicker power can be used for efficient tracing of a flicker source and to determine how flicker propagates. The second part of the work has been the development of a voltage disturbance classification system based on the statistical learning theory-based Support Vector Machine method. The classification system shows always high classification accuracy when training data and test data originate from the same source. High classification accuracy is also obtained when training data originate from one power network and test data from another. The classification system shows, however, lower performance when training data is synthetic and test data originate from real power networks. It was concluded that it is possible to develop a classification system based on the Support Vector Machine method with “global settings” that can be used at any location without the need to retrain. The conclusion is that the proposed classification system works well and shows sufficiently high classification accuracy when trained on data that originate from real disturbances. However, more research activities are needed in order to generate synthetic data that have statistical characteristics close enough to real disturbances to replace actual recordings as training data.
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| 2. |
- Bollen, Math, et al.
(author)
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Classification of Underlying Causes of Power Quality Disturbances: Deterministic versus Statistical Methods
- 2007
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In: Eurasip Journal on Applied Signal Processing. - : Springer Science and Business Media LLC. - 1110-8657 .- 1687-0433. ; 2007, s. 17 pages (Article ID 79747)-
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Journal article (peer-reviewed)abstract
- This paper presents the two main types of classification methods for power quality disturbances based on underlying causes: deterministic classification, giving an expert system as an example, and statistical classification, with support vector machines as an example. An expert system is suitable when one has limited amount of data and sufficient power system expert knowledge, however its application requires a set of threshold values. Statistical methods are suitable when large amount of data is available for training. Two important issues to guarantee the effectiveness of a classifier, data segmentation and featureextraction, are discussed. Segmentation of a sequence of data recording is pre-processing to partition the datainto segments each representing a duration containing either an event or transition between two events. Extraction of features is applied to each segment individually. Some useful features and their effectiveness are then discussed. Some experimental results are included for demonstrating theeffectiveness of both systems. Finally, conclusions are given together with the discussion of some future research directions.
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| 3. |
- Axelberg, P.G.V., et al.
(author)
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Support vector machine for classification of voltage disturbances
- 2007
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In: IEEE Transactions on Power Delivery. - : IEEE. - 0885-8977 .- 1937-4208. ; 22:3, s. 1297-1303
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Journal article (peer-reviewed)abstract
- The support vector machine (SVM) is a powerful method for statistical classification of data used in a number of different applications. However, the usefulness of the method in a commercial available system is very much dependent on whether the SVM classifier can be pretrained from a factory since it is not realistic that the SVM classifier must be trained by the customers themselves before it can be used. This paper proposes a novel SVM classification system for voltage disturbances. The performance of the proposed SVM classifier is investigated when the voltage disturbance data used for training and testing originated from different sources. The data used in the experiments were obtained from both real disturbances recorded in two different power networks and from synthetic data. The experimental results shown high accuracy in classification with training data from one power network and unseen testing data from another. High accuracy was also achieved when the SVM classifier was trained on data from a real power network and test data originated from synthetic data. A lower accuracy resulted when the SVM classifier was trained on synthetic data and test data originated from the power network.
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| 4. |
- Axelberg, P., et al.
(author)
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Trace of Flicker Sources by using the Quantity of Flicker power.
- 2008
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In: IEEE Transactions on Power Delivery. - : IEEE. - 0885-8977 .- 1937-4208. ; 23:1, s. 465-471
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Journal article (peer-reviewed)abstract
- Industries that produce flicker are often placed close to each other and connected to the same power grid system. This implies that the measured flicker level at the point of common coupling (PCC) is a result of contribution from a number of different flicker sources. In a mitigation process it is essential to know which one of the flicker sources is the dominant one. We propose a method to determine the flicker propagations and trace the flicker sources by using flicker power measurements. Flicker power is considered as a quantity containing both sign and magnitude. The sign determines if a flicker source is placed downstream or upstream with respect to a given monitoring point and the magnitude is used to determine the propagation of flicker power throughout the power network and to trace the dominant flicker source. This paper covers the theoretical background of flicker power and describes a novel method for calculation of flicker power that can be implemented in a power network analyzer. Also conducted simulations and a field test based on the proposed method will be described in the paper.
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| 5. |
- Göbel, Hannes, et al.
(author)
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Towards an agile method for ITSM self-assessment : A Design Science Research Approach
- 2013
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In: Proceedings of ICMLG 2013 The International Conference on Management, Leadership and Governance.. - : ICMLG.
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Conference paper (peer-reviewed)abstract
- IT Service Management (ITSM) is an expensive field where small and medium sized enterprises (SMEs) need to become more efficient in their ITSM related work in order to cut costs and improve quality. The focus of this paper is to suggest a solution to the scarcity of process improvement methods dedicated to ITSM-processes in SMEs. The solution consists of an agile self-assessment method designed and evaluated in accordance with Design Science Research. The aim of the method is to support SMEs in their attempt to evaluate and improve their quality of ITSM processes. The findings show that the method creates opportunities for organizations to improve their ITSM processes. The method can be used to identify process gaps in comparison to standards for ITSM. It can also be used for benchmarking purposes within an organization as well as it can guide an organization’s improvement efforts. The method also depicts a standard that is easy for SMEs to understand and to use as guidance (with ITSM specific examples). Finally, the method enables SMEs to implement standards for ITSM in a resource-efficient way. Based on empirical evidence from applying the method the conclusion is that the method is useful for the intended target group and that the method agrees well with theories within the field.
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| 6. |
- Vega-Barbas, Mario, et al.
(author)
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Confidence: dependencies and their critical role in fostering user acceptance in pervasive applications
- 2014
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Conference paper (peer-reviewed)abstract
- Pervasive computing offers new scenarios where users are surrounded by invisible and proactive technology making smart spaces. Although the utility and power of solutions developed using this computer paradigm are proved, there are unresolved problems that hinder their acceptance and inclusion in our private life. Users have problems understanding the operations of a pervasive computing solution, and therefore they should trust that the solution works properly and according to their expectations. Nevertheless, the concept of trust is already framed in a specific use within the ecosystem of applications that can populate a smart space. To take this concept of trust to the whole space, we propose to study and define the concept of confidence. In contrast to the concept of trust, confidence has deeper psychological implications.
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| 7. |
- Agrawal, Tarun Kumar, et al.
(author)
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Blockchain-Based Framework for Traceability – A Case Example of Nonwoven Supply Chain
- 2019
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In: EDANA-Nonwovens Innovation Academy 2019.
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Conference paper (peer-reviewed)abstract
- Supply chain traceability has emerged as a prime requirement for multi-tier supply chains. It not only enables the supply chain visibility but also caters to the consumer requirements related to transparency, quality assurance, and production tracking. Nonwoven supply chain is one such example that particularly requires traceability implementation due to prevailing problems related to information asymmetry and complex supply chain networks. Conversely, it is challenging for supply chain partners to share all the competitive information in the unsecure environment. In this context, in line with Industry 4.0, this study investigates blockchain technology, which uses a shared and secured data infrastructure to keep track of information about assets and requires no central authority to function. It further proposes a blockchain-based traceability framework that explains supply chain partner interaction and network architecture at organizational level and smart contract and transaction validation rules at the operational level. In order to illustrate the application of the framework, the study presents an example of a nonwoven supply chain to track the nonwoven manufacturing and distribution processes. The proposed system can build a technology-based trust among the supply chain actors, where the distributed ledger would be used to store and authenticate of supply chain transactions.
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| 8. |
- Axelberg, Peter G.V., et al.
(author)
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Performance Tests of a Support Vector Machine used for Classification of Voltage Disturbances
- 2006
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In: in proc. of 12th International conf. on Harmonics and Quality of Power (ICHQP 2006), Cascais, Portugal, Oct.1-5, 2006.
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Conference paper (peer-reviewed)abstract
- This paper proposes a novel method for classifying voltage disturbances in electric power systems by using the Support Vector Machine (SVM) method. The proposed SVM classifier is designed to classify five common types of voltage disturbances and experiments have been conducted on recorded disturbances with good classification results. The proposed SVM classifier is also shown to be robust in terms of using training data and testing data that originate from two different power networks.
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| 9. |
- Buendia, Ruben, 1982, et al.
(author)
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A Novel Approach for Removing the Hook Effect Artefact from Electrical Bioimpedance Spectroscopy Measurements
- 2009
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In: Journal of Physics: Conference Series. - : Institute of Physics Publishing Ltd.. - 1742-6596.
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Conference paper (peer-reviewed)abstract
- Very often in Electrical Bioimpedance (EBI) spectroscopy measurements the presence of stray capacitances creates a measurement artefact commonly known as Hook Effect. Such an artefact creates a hook-alike deviation of the EBI data noticeable when representing the measurement on the impedance plane. Such Hook Effect is noticeable at high frequencies but it also causes a data deviation at lower measurement frequencies. In order to perform any accurate analysis of the EBI spectroscopy data, the influence of the Hook Effect must be removed. An established method to compensate the hook effect is the well known Td compensation, which consist on multiplying the obtained spectrum, Zmeas() by a complex exponential in the form of exp[jTd]. Such a method cannot correct entirely the Hook Effect since the hook-alike deviation occurs a broad frequency range in both magnitude and phase of the measured impedance, and by using a real value for Td. First, a real value only modifies the phase of the measured impedance and second, it can only correct the Hook Effect at a single frequency. In addition, the process to select a value for Td by an iterative process with the aim to obtain the best Cole fitting lacks solid scientific grounds. In this work the Td compensation method is revisited and a modified approach for correcting the Hook Effect that includes a novel method for selecting the correcting values is proposed. The initial validation results confirm that the proposed method entirely corrects the Hook Effect at all frequencies.
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| 10. |
- Buendia, Ruben, 1983-, et al.
(author)
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Cole Parameter Estimation from the Modulus of the Electrical Bioimpeadance for Assessment of Body Composition : A Full Spectroscopy Approach
- 2011
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In: Journal of Electrical Bioimpedance. - Oslo : University of Oslo. - 1891-5469. ; 2, s. 72-78
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Journal article (peer-reviewed)abstract
- Activities around applications of Electrical Bioimpedance Spectroscopy (EBIS) have proliferated in the past decade significantly. Most of these activities have been focused in the analysis of the EBIS measurements, which eventually might enable novel applications. In Body Composition Assessment (BCA) the most common analysis approach currently used in EBIS is based on the Cole function, which most often requires curve fitting. One of the most implemented approaches for obtaining the Cole parameters is performed in the impedance plane through the geometrical properties that the Cole function exhibit in such domain as depressed semi-circle. To fit the measured impedance data to a semi-circle in the impedance plane, obtaining the Cole parameters in an indirect and sequential manner has several drawbacks. Applying a Non-Linear Least Square (NLLS) iterative fitting on the spectroscopy measurement, obtains the Cole parameters considering the frequency information contained in the measurement. In this work, from experimental total right side EBIS measurements, the BCA parameters have been obtained to assess the amount and distribution of whole body fluids. The values for the BCA parameters have been obtained using values for the Cole parameters estimated with both approaches: circular fitting on the impedance plane and NLLS impedance-only fitting. The comparison of the values obtained for the BCA parameters with both methods confirms that the NLLS impedance-only is an effective alternative as Cole parameter estimation method in BCA from EBIS measurements. Using the modulus of the Cole function as the model for the fitting would eliminate the need for performing a phase detection in the acquisition process, simplifying the hardware specifications of the measurement instrumentation when implementing a bioimpedance spectrometer.
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