Prediction, classification and diagnosis of spur gear conditions using artificial neural network and acoustic emission

The gear system is a critical component in the machinery and predicting the performance of a gear system is an important function. Unpredictable failures of a gear system can cause serious threats to human life, and have large scale economic effects. It is necessary to inspect gear teeth periodically to identify crack propagation and, other damages at the earliest. This study has two main objectives. Firstly, the research predicted and classified specific film thickness (λ) of spur gear by Artificial Neural Network (ANN) and Regression models. Parameters such as acoustic emission (AE), temperature and specific film thickness (λ) data were extracted from works of other researchers. The acoustic emission signals and temperature were used as input to ANN and Regression models, while (λ) was the output of the models. Second objective is to use the third generation ANN (Spiking Neural Network) for fault diagnosis and classification of spur gear based on AE signal. For this purpose, a test rig was built with several gear faults. The AE signal was processed through preprocessing, features extraction and selection methods before the developed ANN diagnosis and classification model were built. These processes were meant to improve the accuracy of diagnosis system based on information or features fed into the model. This research investigated the possibility of improving accuracy of spur gear condition monitoring and fault diagnoses by using Feed-Forward Back- Propagation Neural Networks (FFBP), Elman Network (EN), Regression Model and Spiking Neural Network (SNN). The findings showed that use of specific film thickness has resulted in the FFBP network being able to provide 99.9% classification accuracy, while regression and multiple regression models attained 73.3 % and 81.2% classification accuracy respectively. For gear fault diagnosis, the SNN achieved nearly 97% accuracy in its diagnosis. Finally, the methods use in the study have proven to have high accuracy and can be used as tools for prediction, classification and fault diagnosis in spur gear

Performance of distributed information systems

There is an increasing use of distributed computer systems to provide services in both traditional telephony as well as in the Internet. Two main technologies are Distributed Object Computing (DOC) and Web based services. One common DOC architecture investigated in this thesis is the Common Object Request Broker Architecture (CORBA), specified by the Object Management Group. CORBA applications consist of interacting software components called objects. Two other DOC architectures investigated are the Telecommunications Information Net- working Architecture (TINA) and a CORBA based Intelligent Network (IN/CORBA) system. In a DOC environment, the objects of an application are distributed on mul- tiple nodes. A middleware layer makes the distribution transparent to the application. However, the distributed nature creates a number of potential performance problems. Three problems in DOC systems are examined in this thesis: object distribution, load balancing and overload protection. An object distribution describes how objects are distributed in the network. The objective is to distribute the objects on the physical nodes in such a way that intern-node communication overhead is as small as possible. One way to solve the object distribution problem is to use linear programming. The constraints for the problem are then given by both ease of management of the system and performance concerns. Load balancing is used when there are multiple objects that can be used at a particular time. The objective of load balancing is to distribute the load e±ciently on the available nodes. This thesis investigates a number of de- centralized load balancing mechanisms, including one based on the use of intelligent agents. Finally, overload protection mechanisms for DOC systems are investigated. While overload protection is well-researched for telecom networks, only little work has been performed previously concerning DOC and overload protection. Also, this thesis examines the use of overload protection in e-commerce web servers. Two schemes are compared, one which handles admission to the e-commerce site on request basis, and another which handles admission on session basis. The session based mechanism is shown to be better in terms of user-experienced performance

Performance controls for distributed telecommunication services

As the Internet and Telecommunications domains merge, open telecommunication service architectures such as TINA, PARLAY and PINT are becoming prevalent. Distributed Computing is a common engineering component in these technologies and promises to bring improvements to the scalability, reliability and flexibility of telecommunications service delivery systems. This distributed approach to service delivery introduces new performance concerns. As service logic is decomposed into software components and distnbuted across network resources, significant additional resource loading is incurred due to inter-node communications. This fact makes the choice of distribution of components in the network and the distribution of load between these components critical design and operational issues which must be resolved to guarantee a high level of service for the customer and a profitable network for the service operator. Previous research in the computer science domain has addressed optimal placement of components from the perspectives of minimising run time, minimising communications costs or balancing of load between network resources. This thesis proposes a more extensive optimisation model, which we argue, is more useful for addressing concerns pertinent to the telecommunications domain. The model focuses on providing optimal throughput and profitability of network resources and on overload protection whilst allowing flexibility in terms of the cost of installation of component copies and differentiation in the treatment of service types, in terms of fairness to the customer and profitability to the operator. Both static (design-time) component distribution and dynamic (run-time) load distribution algorithms are developed using Linear and Mixed Integer Programming techniques. An efficient, but sub-optimal, run-time solution, employing Market-based control, is also proposed. The performance of these algorithms is investigated using a simulation model of a distributed service platform, which is based on TINA service components interacting with the Intelligent Network through gateways. Simulation results are verified using Layered Queuing Network analytic modelling Results show significant performance gains over simpler methods of performance control and demonstrate how trade-offs in network profitability, fairness and network cost are possible

Methods for designing and optimizing fuzzy controllers

We start by discussing fuzzy sets and the algebra of fuzzy sets. We consider some properties of fuzzy modeling tools. This is followed by considering the Mamdani and Sugeno models for designing fuzzy controllers. Various methods for using sets of data for desining controllers are discussed. This is followed by a chapter illustrating the use of genetic algorithms in designing and optimizing fuzzy controllers.Finally we look at some previous applications of fuzzy control in telecommunication networks, and illustrate a simple application that was developed as part of the present work

Modelling and evaluation of load and performance control mechanisms of B-ISDN/ATM switching systems

Behandelt wird die Problematik der Last- und Leistungsregelung im Kontext der ATM-basierten Breitband-Vermittlungstechnik.Objective of this thesis are load control and performance control concepts for broadband switching systems. Focus is the services integrating network technology B-ISDN using ATM as transfer mode. The studied mechanisms and concepts are principally of generic nature. Specifically they are designed within the envisaged context of B-ISDN, due to its extensive vision with respect to service integration, Quality of Service (QoS) support and ATM bearer capabilities. Area of application is implicitly the network control plane, but interactions between user and control plane have to be considered, too. The prime scope are switching nodes between access and core network domain, i.e., B-ISDN switches which have to provide user-to-network and network-to-network signalling protocol functions. Thus, beside service distinction call type differentiation is also covered due to the considered network positioning

An investigation into intelligent network congestion control strategies

This thesis examines the congestion control issues that arise in Intelligent Networks, when it is necessary to support multiple service types with different load requirements and priorities. The area of Intelligent Network (IN) congestion control has been under investigation for over a decade, but in general, the models used in this research were over-simplified and all service types were assumed to have the same priority levels and load requirements at the various IN physical elements. However, as the IN is a dynamic network that must process many different service types that have radically different call load profiles and are based on different service level agreements and charging schemes, the validity of the above assumptions is questionable. The aim of this work, therefore, is to remove a number of the classic assumptions made in IN congestion control research, by: • developing a detailed model of an IN, catering for multiple traffic types, • using this model to establish the shortcomings of classic congestion control strategies, • devising a new IN congestion control strategy and verifying its superiority on the model. To achieve these aims, an IN model (both simulation and analytic) is developed to reflect the physical and functional architecture of the network and model the information flows required between network entities in order to execute services. The effectiveness of various classic active and reactive congestion control strategies are then investigated using this model and it is established that none of these strategies are capable of protecting both the Service Control Point and Service Switching Points under all possible traffic mixes and loads. This is partially due to the fact that all of these strategies are based on the use of fixed parameters (and are therefore not flexible enough to deal with IN traffic) and partially because none of these strategies take into account the different load requirements of the different service types. A new, flexible strategy is then devised to facilitate global IN congestion control and cater for service types with different characteristics. This strategy maximises IN performance by protecting all network elements from overload while maximising network revenue and preserving fairness between service types during overload. A number of factors determining the relative importance or weight of different traffic types are also identified and used by the strategy to maintain call importance during overload. The efficiency of this strategy is demonstrated by comparing its operation to that of the best classic IN overload controls and also to a new strategy, which has scalable and dynamic behaviour (and which was devised for the purpose of providing a fair comparison to the optimisation strategy). The optimisation-based strategy and dynamic strategy are found to be equally effective and far superior to the classic strategies. However, the optimisation algorithm also preserves relative importance and fairness, while maximising network revenue - but at the cost of a not insignificant processing overhead