Event tracking for real-time unaware sensitivity analysis (EventTracker)

This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.This paper introduces a platform for online Sensitivity Analysis (SA) that is applicable in large scale real-time data acquisition (DAQ) systems. Here we use the term real-time in the context of a system that has to respond to externally generated input stimuli within a finite and specified period. Complex industrial systems such as manufacturing, healthcare, transport, and finance require high quality information on which to base timely responses to events occurring in their volatile environments. The motivation for the proposed EventTracker platform is the assumption that modern industrial systems are able to capture data in real-time and have the necessary technological flexibility to adjust to changing system requirements. The flexibility to adapt can only be assured if data is succinctly interpreted and translated into corrective actions in a timely manner. An important factor that facilitates data interpretation and information modelling is an appreciation of the affect system inputs have on each output at the time of occurrence. Many existing sensitivity analysis methods appear to hamper efficient and timely analysis due to a reliance on historical data, or sluggishness in providing a timely solution that would be of use in real-time applications. This inefficiency is further compounded by computational limitations and the complexity of some existing models. In dealing with real-time event driven systems, the underpinning logic of the proposed method is based on the assumption that in the vast majority of cases changes in input variables will trigger events. Every single or combination of events could subsequently result in a change to the system state. The proposed event tracking sensitivity analysis method describes variables and the system state as a collection of events. The higher the numeric occurrence of an input variable at the trigger level during an event monitoring interval, the greater is its impact on the final analysis of the system state. Experiments were designed to compare the proposed event tracking sensitivity analysis method with a comparable method (that of Entropy). An improvement of 10% in computational efficiency without loss in accuracy was observed. The comparison also showed that the time taken to perform the sensitivity analysis was 0.5% of that required when using the comparable Entropy based method.EPSR

Sztuczna inteligencja i ochrona środowiska budynków

Global environmental pollution has an extremely negative impact on the population of the planet and threatens the future of mankind. One of the main sources of waste and toxic emissions into the atmosphere is the construction sector. It is necessary to find ways to minimize the damage caused to nature. Currently, artificial intelligence technologies are among the most promising ways to improve the environment. Automatic control systems solve a number of problems related to reducing costs and resources, full use of renewable energy sources, improving the safety of energy systems, and many others. The purpose of this article is to determine the functionality of artificial intelligence technologies and ways of their application in green construction. To solve this problem, methods of analysis and synthesis of existing information models were applied. The article discloses automatic control systems in the design, construction, and operation of buildings. These include well-known methods, such as Building Information Model, Machine Learning, Deep Learning, and narrow-profile ones: Response Surface Methodology, Multi-Agent System, Digital Twins, etc. In addition, the study states that when planning and arranging green buildings must adhere to the following principles: high energy efficiency, rational use of natural resources, adaptation to the environment and climate, ensuring comfort and safety for residents. The article presents the standards of green construction existing in the world. This work can serve as a guide when choosing information models and is of practical value in the development of green buildings.Globalne zanieczyszczenie środowiska ma niezwykle negatywny wpływ na naszą planetę i zagraża przyszłości ludzkości. Jednym z głównych źródeł emisji odpadów i substancji toksycznych do atmosfery jest sektor budowlany. Konieczne jest znalezienie sposobów na zminimalizowanie szkód wyrządzanych przyrodzie. Obecnie technologie sztucznej inteligencji należą do najbardziej obiecujących sposobów poprawy stanu środowiska. Układy automatyki rozwiązują szereg problemów związanych z redukcją kosztów i zasobów, pełnym wykorzystaniem odnawialnych źródeł energii, poprawą bezpieczeństwa systemów energetycznych i wieloma innymi. Celem artykułu jest określenie funkcjonalności technologii sztucznej inteligencji oraz sposobów jej zastosowania w zielonym budownictwie. Zastosowano metody analizy i syntezy istniejących modeli informacyjnych. W artykule opisano systemy automatycznego sterowania w projektowaniu, budowie i eksploatacji budynków. Należą do nich dobrze znane metody, takie jak Building Information Model, Machine Learning, Deep Learning, oraz wąskoprofilowe: Response Surface Methodology, Multi-Agent System, Digital Twins itp. Ponadto badanie stwierdza, że podczas planowania i aranżacji zielone budynki muszą spełniać następujące zasady: wysoka efektywność energetyczna, racjonalne wykorzystanie zasobów naturalnych, dostosowanie do środowiska i klimatu, zapewnienie komfortu i bezpieczeństwa mieszkańcom. W artykule przedstawiono standardy zielonego budownictwa istniejące na świecie. Praca ta może służyć jako przewodnik przy wyborze modeli informacyjnych i ma praktyczną wartość w rozwoju zielonych budynków

Distributed on-line safety monitor based on safety assessment model and multi-agent system

On-line safety monitoring, i.e. the tasks of fault detection and diagnosis, alarm annunciation, and fault controlling, is essential in the operational phase of critical systems. Over the last 30 years, considerable work in this area has resulted in approaches that exploit models of the normal operational behaviour and failure of a system. Typically, these models incorporate on-line knowledge of the monitored system and enable qualitative and quantitative reasoning about the symptoms, causes and possible effects of faults. Recently, monitors that exploit knowledge derived from the application of off-line safety assessment techniques have been proposed. The motivation for that work has been the observation that, in current practice, vast amounts of knowledge derived from off-line safety assessments cease to be useful following the certification and deployment of a system. The concept is potentially very useful. However, the monitors that have been proposed so far are limited in their potential because they are monolithic and centralised, and therefore, have limited applicability in systems that have a distributed nature and incorporate large numbers of components that interact collaboratively in dynamic cooperative structures. On the other hand, recent work on multi-agent systems shows that the distributed reasoning paradigm could cope with the nature of such systems. This thesis proposes a distributed on-line safety monitor which combines the benefits of using knowledge derived from off-line safety assessments with the benefits of the distributed reasoning of the multi-agent system. The monitor consists of a multi-agent system incorporating a number of Belief-Desire-Intention (BDI) agents which operate on a distributed monitoring model that contains reference knowledge derived from off-line safety assessments. Guided by the monitoring model, agents are hierarchically deployed to observe the operational conditions across various levels of the hierarchy of the monitored system and work collaboratively to integrate and deliver safety monitoring tasks. These tasks include detection of parameter deviations, diagnosis of underlying causes, alarm annunciation and application of fault corrective measures. In order to avoid alarm avalanches and latent misleading alarms, the monitor optimises alarm annunciation by suppressing unimportant and false alarms, filtering spurious sensory measurements and incorporating helpful alarm information that is announced at the correct time. The thesis discusses the relevant literature, describes the structure and algorithms of the proposed monitor, and through experiments, it shows the benefits of the monitor which range from increasing the composability, extensibility and flexibility of on-line safety monitoring to ultimately developing an effective and cost-effective monitor. The approach is evaluated in two case studies and in the light of the results the thesis discusses and concludes both limitations and relative merits compared to earlier safety monitoring concepts

A standardization approach to Virtual Commissioning strategies in complex production environments

The ongoing industrial revolution puts high demands on the component manufacturers and suppliers to meet the tough requirements set by the development industries to follow the technological advancement of highly digitalized factories with more future-oriented applications as Virtual Commissioning for cyber-physical systems. This paper provides a production system lifecycle assessment regarding the technical specification strategies using Virtual Commissioning for implementation and integration of new systems or plants and its predicted future challenges. With the use of standards and a common language practice between a purchaser/contractor procurement situation and across the different technical disciplines internally and externally, the implementation strategies is reiterated to achieve a new sustainable business model. The paper investigates different types of production systems and how a defined classification framework of different levels of Virtual Commissioning can connect the implementation requirements to a desired solution. This strategy includes aspects of standardization, communication, process lifecycle, and predicted cost parameters