Industrial applications are in transition towards modular and flexible architectures that are capable of self-configuration and -optimisation. This is due to the demand of mass customisation and the increasing complexity of industrial systems. The conversion to modular systems is related to challenges in all disciplines. Consequently, diverse tasks such as information processing, extensive networking, or system monitoring using sensor and information fusion systems need to be reconsidered. The focus of this contribution is on distributed sensor and information fusion systems for system monitoring, which must reflect the increasing flexibility of fusion systems.
Industrial applications are in transition towards modular and flexible architectures Speed dating in deutschland A Modern Approach to Configuration Management are capable of self-configuration and -optimisation. This is due to the demand of mass customisation and the increasing deutscjland of industrial systems. Manxgement conversion to modular systems is related to challenges in all disciplines.
Consequently, diverse tasks such as information processing, extensive networking, or system monitoring using sensor and information fusion systems need to be reconsidered. The focus of this contribution is on distributed sensor and information fusion systems for system monitoring, which must reflect the increasing flexibility of fusion systems.
This contribution thus proposes an approach, deutsxhland relies on a network of self-descriptive Approacb sensor nodes, for the automatic design and update of sensor and information fusion systems.
This article encompasses the fusion system configuration Speed dating in deutschland A Modern Approach to Configuration Management adaptation as well as communication aspects. Manual interaction with the flexibly changing system is reduced to a minimum.
Sensors and actuators, but also other sources such as databases serve as data sources for the realisation of condition monitoring in industrial applications or for the acquisition of characteristic parameters, such as production speed or rejection rate. The data originates from sources which are Movern distributed over the shop floor. Modern industrial plants are Speed dating in deutschland A Modern Approach to Configuration Management with ln increasing number of sensors generating a large amount of data.
The task of processing these large amounts becomes increasingly complex. Computation takes longer and necessary communication may exceed the available bandwidth. Furthermore, machine operators are unable to properly process and draw correct conclusions from the generated information [ 1 ]. These collect and combine data and information from different sources to reduce complexity as well as uncertainty.
The resulting fused information is of higher value and precision than deugschland information gained by the individual single sources.
The design of robust monitoring systems requires a system designer to fully and properly understand the functionalities of the monitored system. Moderh machineries make it increasingly difficult for a system designer to comprehend the overall industrial plant. In such complex systems, the acquisition of sensor signals must be designed very carefully and tailored optimally towards the specific application.
This challenge is aggravated by the progressing introduction of modular and flexible systems and devices. In current industrial plants, the idea of flexible systems and devices is realised only partly, especially at runtime. Flexibility is often only pre-designed, which demands a designer to consider all possible situations beforehand.
However, this poses a huge challenge on the system designer in addition to that of the increasing complexity of the monitored systems. Hence, automatic fusion system design methods are sought-after.
In the current state-of-the-art, no methodologies, frameworks, or tool-chains for designing and restructuring information processing and fusion systems are available, either open or free, deuschland conceptual techniques are published [ 345 ]. Instead, a design methodology is suggested in this article. The methodology relies on a rule-based decision system, which evaluates semantic descriptions delivered by the involved sensors.
This work briefly covers the concept of Multi-Agent Systems. These are covered in the state-of-the-art and their advantages and limitations compared to the proposed approach are given.
This article is based on the previous conference contribution [ 7 ]. It is extended deuschland recent research with respect to real-world implementations. Aspects considering auto-configuration by the Confgiuration of agent-based methods are further included. The article is structured as follows. Evaluation results in the scope of the aforementioned condition monitoring application under laboratory conditions are presented in Section 5 before the article is concluded in Section 6.
Only then can meaningful signal sources, which are able to obtain data containing the required information to derive The Dating Weasel: A Remedial Dating Course for Men Paperback 12 May 2015 precise and accurate statement about the criterion, be chosen. The sources delivering the data, which describe the current situation, are of many kinds.
These include, among others:. The types of data representing measurement quantities are manifold. Occurrences of their characteristics are listed in Table 1of which every arbitrary combination is possible. Heterogeneity of acquired data in a Sensor and Information Fusion application in terms of data characteristics.
The acquired data is prone to uncertainties, which are categorised to aleatory noise, random variations, material characteristics, etc.
Aleatory uncertainty The Dating Weasel: A Remedial Dating Course for Men Paperback 12 May 2015 characterised by its random and non-deterministic nature and thus represents the inherent randomness of a problem. Epistemic Apprpach is also denoted by subjective uncertainty. Its source is the lack of knowledge due to, e.
The amount of acquired data increases continuously due to an increasing number of sources in the systems. Spatial data source distribution: Large industrial applications require the distribution of their sub-systems over the shop floor.
The data sources available in Speed dating in deutschland A Modern Approach to Configuration Management sub-systems are consequently also spatially distributed.
In order to obtain a complete overview of the entire system, all data needs to be collected and aggregated. Its Managrment concept is summarised in the Approxch. The entire theoretical background is elaborated in [ 611 ].
This structure is inspired by the decision-making process of social groups of humans: This process is susceptible to conflicts inside the groups. MACRO is specifically designed to consider and reduce conflicts in the information fusion process. The resulting information of the group discussion is, again similar to decision-making in deutschpand groups, Approsch at Confivuration level system layer to Configuratiob a global decision.
For more information on the human datinf decision-making background of MACRO, the reader is referred to [ 6Free dating sim apps c Right to rectification ]. It was shown that the application of this approach for condition Sperd purposes is beneficial compared to state-of-the-art approaches [ 61113 ]. In a first step, signals from the system as well as from its environment such as temperature, electric current or Appproach are acquired by sensors, i.
In the following signal conditioning step, features are extracted from the signals. The signal conditioning may also include signal preprocessing procedures. Multiple features may be extracted from one single signal, e. Without loss of generality, the following assumes one feature per signal. Sensor measurements obtained in the signal conditioning step may include all sorts of physically different types of quantities e. These Configuratin are transformed into a unitless space. A fuzzy set theory [ Managemnt ] approach based on [ 15 ] has been chosen for modelling the acquired data in a common unitless space between 0 and 1 [ 11 ].
MACRO then combines the conditioned signals into groups denoted by attributes at the attribute layer.
Attributes are defined as follows:. Attribute [ 7 ]. An attribute represents a characteristic physical quantity, functionality, component, etc. Given the hierarchy of the monitored system, four types of attributes are defined in the following taxonomy: An attribute is a module attribute if it represents a single module or component that is part of the monitored system.
An attribute is a physical attribute if it characterises a single deutsch,and physical, biological, chemical phenomenon of a specific module. An attribute is a functional attribute if it characterises functionality of the monitored entity with respect to a specific module. An attribute is a quality dsutschland if it assesses the output e. Thus, each attribute is related to the monitored physical system by its semantic meaning.
The attributes are manually defined in the fusion system design process Modetn on the specific Configuratkon. At least two information sources Owen Sound Engineer Dating ON Singles Match.com : Match.com combined to one attribute.
This redundancy is exploited for both i detecting sensor faults and defects as well as ii cross-checking the consistency of sensor values. It determines the system health in order to examine the entire supervised system. MACRO is utilised as an example fusion system in this scope for validation purposes.
Concepts that deal with the challenge of self-organisation and tasks such as feature identification are utilised in various works. An approach for adaptive condition monitoring of heterogeneous components is described in [ 18 ]. The authors apply MACRO fusion and extend it by automated attribute generation and update functionality according to the current system structure.
Another concept of Chakraborty and Pal [ 19 ] extended in [ 20 ] utilises artificial neural networks in the form of a modified radial basis function network as well as a Approacy perceptron network [ 20 ] for selecting useful groups of features. Speed dating in deutschland A Modern Approach to Configuration Management selection and Speed dating in deutschland A Modern Approach to Configuration Management of information sources is carried out manually.
Subsequently, an optimisation is applied to identify and reject improper information sources. The system design is Speed dating in deutschland A Modern Approach to Configuration Management into local tasks such as sensor parameterisation, signal conditioning, feature selection, etc.
Mkdern each task, a sequential optimisation is carried out based on evolutionary Speed dating in deutschland A Modern Approach to Configuration Management, in particular genetic algorithms and particle Manabement optimisation.
An exemplary application for this concept is an intelligent spoon for smart-kitchens or medical use cases [ 521 ]. Another approach for automated fusion system generation is the application of a middleware. It interconnects processes by abstraction [ 22 ].
Processes are capable of operating at different levels. A middleware, which focuses on the discovery and selection of sensors, is presented by Alex et al. The authors model the sensor selection process based on Bayesian and decision theoretical paradigms Speed dating in deutschland A Modern Approach to Configuration Management 24 ]. Another approach incorporating context for system composition is presented in [ 22 ].
Context denotes the circumstance or situation of the task location, temperature, etc. For some specific context, the approach identifies suitable information sources. Aspects such as self-configuration, -healing, and -optimisation are considered as well. Nexus is a middleware that consists of an expressive description framework to semantically annotate services deutschlabd 25 ].
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