Papers by Mikhail Roshchin
2017 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA), 2017
The CERN's accelerator complex and its experiments rely on the proper functioning of a multit... more The CERN's accelerator complex and its experiments rely on the proper functioning of a multitude of heterogeneous industrial control systems. Over 600 industrial control systems with more than 40 million sensors, actuators and control objects store more than 100 terabytes of data per year (the volume of generated data is much more). This paper describes a mathematical approach to monitor online a multitude of sensors/actuators and automatically detect signals oscillations. In order to achieve it the presented method combines both expert knowledge and spectrum analysis. Some results, obtained by the application of this analysis to the CERN cryogenics system, are presented showing multiple plant-wide oscillations. Finally the paper briefly describes the deployment of Spark and Hadoop platform into the CERN industrial environment to deal with huge datasets and to spread the computational load of the analysis across multiple hosts.
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2017 IEEE 15th International Conference on Industrial Informatics (INDIN), 2017
In industrial power generation plants, subsystem monitoring and analytics play a vital role in qu... more In industrial power generation plants, subsystem monitoring and analytics play a vital role in quantifying the knowledge about different factors that impact their overall performance. Multi-dimensional performance metrics, e.g. thermal efficiency, in-service time, mean-time-to-failure etc., are calculated that may have different data constraints, modelling techniques, and execution frameworks. Automating these calculations and combining multiple metrics to form a single performance index (e.g. reliability) is a challenging task as it requires considerable domain-specific expertise and consolidation of performance-related data and its underlying models. In this paper, we propose to use ontologies to assist domain analyst to first, capture appropriate semantic data of an individual performance metric, and later to provide means to integrate and execute multiple metrics to accurately reflect the overall performance of a plant. We present our prototypical implementation, its evaluation; furthermore, we discuss an ontology model that currently describes three distinct analytical models and its related data based on the case study of Siemens gas turbines. We also demonstrate how ontologies can support to infer the appropriate aggregation method in calculating composite indices.
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Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017
Rule-based diagnostics of power generating equipment is an important task in industry. In this de... more Rule-based diagnostics of power generating equipment is an important task in industry. In this demo we present how semantic technologies can enhance diagnostics. In particular, we present our semantic rule language sigRL that is inspired by the real diagnostic languages in Siemens. SigRL allows to write compact yet powerful diagnostic programs by relying on a high level data independent vocabulary, diagnostic ontologies, and queries over these ontologies. We present our diagnostic system SemDia. The attendees will be able to write diagnostic programs in SemDia using sigRL over 50 Siemens turbines. We also present how such programs can be automatically verified for redundancy and inconsistency. Moreover, the attendees will see the provenance service that SemDia provides to trace the origin of diagnostic results.
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Annual Conference of the PHM Society, 2015
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The aim of our work is to present solutions and a methodical support for automated techniques and... more The aim of our work is to present solutions and a methodical support for automated techniques and procedures in domain engineering, in particular for variability modeling. Our approach is based upon Semantic Modeling concepts, for which semantic description, representation patterns and inference mechanisms are defined. Thus, model-driven techniques enriched with semantics will allow flexibility and variability in representation means, reasoning power and the required analysis depth for the identification, interpretation and adaptation of artifact properties and qualities
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Annual Conference of the PHM Society, 2013
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The aim of our work is to present solutions and a methodical support for automated techniques and... more The aim of our work is to present solutions and a methodical support for automated techniques and procedures in domain engineering, in particular for variability modeling. Our approach is based upon Semantic Modeling concepts, for which semantic description, representation patterns and inference mechanisms are defined. Thus, model-driven techniques enriched with semantics will allow flexibility and variability in representation means, reasoning power and the required analysis depth for the identification, interpretation and adaptation of artifact properties and qualities. Problem Statement Let us assume that we require a software system that is specifically tailored to rely on our needs; that is valid and consistent within the reality of the environment and involved domains. But the cost issue plays an important role, and the development of specific and generic products is not that cost-effective as we expect. For reduction of costs, software engineering aims of an increasing reuse ...
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Abstract: The aim of this position statement is to describe our work to support Web service techn... more Abstract: The aim of this position statement is to describe our work to support Web service technology as contribution to SOA by providing semantically “rich ” descriptions of Web services together with methods and techniques to handle and to manipulate them by introducing Semantic Web technologies and additional logical formalisms into the annotation process. The annotation process will thus be enriched by new features and techniques to solve inference tasks (for instance with respect to consistency checking), to allow automated reasoning about annotation contents, to support automated search and complex query design, and to realize information derivation and interpretation based on different foci. 1
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Massive data streams from sensors and devices are prominent form of industrial data generated dur... more Massive data streams from sensors and devices are prominent form of industrial data generated during condition-monitoring and diagnosis of complex systems. Data analytics and reasoning has emerged as a vital tool to harness massive data sets, providing insights into historical and real-time system conditions; enhanced decision support, reliability and cost reduction. However, application of data analytics is mainly challenged by the complexity of data-access, integration, domain-specific query support and contextual reasoning capabilities. The current state-of-the-art only uses dedicated scenarios and sensors, but this limits reuse, scalability and are not sufficient for an integrated solution. Our thesis investigates if semantic technology can be a potential solution to interact and leverage data analytics for operational use. First, we have studied related work and utilized ontology-based data access (OBDA) techniques for semantic interpretation of diagnosis for Siemens Turbine us...
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L'invention concerne un systeme et un procede de configuration concus pour realiser une confi... more L'invention concerne un systeme et un procede de configuration concus pour realiser une configuration ou une reconfiguration d'applications executees par un systeme d'automatisation, ledit systeme de configuration comprenant : une unite de traitement concue pour traiter au moins une instruction en langage naturel d'une entree d'exigence d'utilisateur par un utilisateur concernant une fonctionnalite de commande et/ou de surveillance du systeme d'automatisation sur la base d'une ontologie d'utilisateur de l'utilisateur et/ou d'une ontologie de systeme d'automatisation du systeme d'automatisation pour generer une specification d'exigences formelle ; et une unite de mise en correspondance concue pour faire correspondre la specification d'exigences formelle et des specifications de composant formelles lues a partir d'une bibliotheque de composants pour deriver un deploiement de configuration comprenant un ou plusieurs compos...
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Integration, access, and analyses of streaming data plays an important role in predictive and rea... more Integration, access, and analyses of streaming data plays an important role in predictive and reactive diagnostics of turbines and other large appliances in Siemens Energy. In this demo we will show how semantic technologies implemented in the ontology-based data access platform OPTIQUE can help in enhancing these tasks. We will demonstrate how to deploy our platform over relational streams, register continuous queries, and perform monitoring via a devoted dashboard. For this purpose we will use an anonymised version of streaming data gathered from 200 gas and steam turbines between 2002 and 2011.
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The CERN automation infrastructure consists of over 600 heterogeneous industrial control systems ... more The CERN automation infrastructure consists of over 600 heterogeneous industrial control systems with around 45 million deployed sensors, actuators and control objects. Therefore, it is evident that the monitoring of such huge system represents a challenging and complex task. This paper describes three different mathematical approaches that have been designed and developed to detect anomalies in any of the CERN control systems. Specifically, one of these algorithms is purely based on expert knowledge; the other two mine the historical generated data to create a simple model of the system; this model is then used to detect faulty sensors measurements. The presented methods can be categorized as dynamic unsupervised anomaly detection; “dynamic” since the behaviour of the system and the evolution of its attributes are observed and changing in time. They are “unsupervised” because we are trying to predict faulty events without examples in the data history. So, the described strategies i...
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Industrial turbine systems produce massive amount of data and adopt intelligent diagnostic soluti... more Industrial turbine systems produce massive amount of data and adopt intelligent diagnostic solutions to detect a potential fault and provide early warning for possible failure. However, these solutions rely on a wide range of standalone applications and data-dependent components together with greater expertise on part of the analyst. For example, a solution based on an artificial neural network requires a dedicated data-set and software component to extract features first and then provide a manual setup to the model for classifying faults within a hierarchy of a device. For practical purpose, the shallow architecture of the models and application-dependent diagnosis makes such solutions less flexible and reusable for other tasks. As a breakthrough in artificial intelligence driven diagnostics, a semantically enabled IoT solution holds the potential to overcome the aforementioned challenges. By constructing an open and shared semantic model, where physical and virtual ‘Things’ have i...
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In order to exploit the adaptability of a SOA infrastructure, it becomes necessary to provide pla... more In order to exploit the adaptability of a SOA infrastructure, it becomes necessary to provide platform mechanisms that support a mapping of the variability in the applications to the variability provided by the infrastructure. The approach focuses on the configuration of the needed infrastructure mechanisms including support for the derivation of the infrastructure variability model.
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Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017
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Proceedings of the International Conference on Knowledge Discovery and Information Retrieval, 2012
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Journal of Web Semantics, 2018
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Lecture Notes in Computer Science, 2017
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Journal of Web Semantics, 2017
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Papers by Mikhail Roshchin