Christos Koulamas

Real-Time Vision-Based System for Textile Fabric Inspection

This paper presents an automatic vision-based system for quality control of web textile fabrics. The general hardware and software platform developed to solve this problem is presented and a powerful algorithm for defect inspection is proposed. Based on the improved binary, textural and neural network algorithms the proposed method gives good results in the detection of many types of fabric defects under real industrial conditions, where the presence of many types of noise is an inevitable phenomenon. A high detection rate with good localization accuracy, low rate of false alarms, compatibility with standard inspection tools and low price are the main advantages of the proposed system as well as the overall inspection approach.

Battery Lifetime Prediction Model for a WSN Platform

Wireless Sensor Network devices have by nature limited available energy to perform a wide range of demanding tasks. In order to maximize their operation lifetime, optimal resource management is an important challenge and its success requires methodical modeling of the factors contributing to the overall power consumption. Moreover, the power consumed is not always useful on its own, but it should rather express the expected lifetime concerning the device’s normal operation. To achieve such awareness, this paper contributes with a measuring methodology which involves combining power consumption of platform elementary functionalities with battery discharge characteristics, so that a practical, yet accurate battery lifetime prediction model can be formed.

Defect detection and classification on web textile fabric using multiresolution decomposition and neural networks

In this paper a pilot system for defect detection and classification of web textile fabric in real-time is presented. The general hardware and software platform, developed for solving this problem, is presented while a powerful novel method for defect detection after multiresolution decomposition of the fabric images is proposed. This method gives good results in the detection of low contrast defects under real industrial conditions, where many types of noise are present. An artificial neural network, trained by a back-propagation algorithm, performs the defect classification in categories.

Using cut-through forwarding to retain the real-time properties of Profibus over hybrid wired/wireless architectures

The benefits of wireless extensions in industrial networks are well recognized as long as the integration of the wireless and fieldbus domains will be capable of retaining the real-time and dependability quality of the current wired industrial networking solutions. In this paper, the architecture and the operation of a cut-through forwarding device are described, to be used in broadcasting, hybrid wired/wireless Profibus systems. Analytical models of the delay overhead introduced due to frame forwarding are presented. It is shown that the usage of cut-through forwarding devices relaxes the bit-rate requirements in the radio segments, while it drastically improves the inherent advantages and reduces the drawbacks of hybrid transmission media architectures, which are based on a single Medium Access Control domain.

Experimental evaluation of a WSN platform power consumption

Critical characteristics of wireless sensor networks, as being autonomous and comprising small or miniature devices are achieved at the expense of very strict available energy related limitations. Therefore, it is apparent that optimal resource management is among the most important challenges in WSNs development and success.

A methodology for the development of distributed real-time control applications with focus on task allocation in heterogeneous systems

A distributed application development methodology is necessary to define specific steps, through which the application specification can be successfully mapped to the system devices. Interoperability and real-timeliness are two major issues in distributed control application development. The main focus of this paper is a generic device model, developed to provide interoperability, and the function block allocation (FBALL) algorithm, defined to guarantee that real-time requirements are met. FBALL is a hybrid approach targeted for the nature of distributed control applications, resulting in an assignment of the application tasks to the system resources, as well as a feasible schedule that meets the real-time constraints. Based on these solutions to interoperability and real-time criticality, a methodology is presented, supporting the distributed control application specification, modeling, and implementation to heterogeneous systems.

Real-time vision system for defect detection and neural classification of Web textile fabric

A real-time pilot system for defect detection and classification of web textile fabric is presented in this paper. The general hardware and software platform, developed for solving this problem, is presented and a powerful novel method for defect detection is proposed. This method gives good results in the detection of low contrast defects under real industrial conditions, where the presence of many types of noise is an inevitable phenomenon. For the defect classification an artificial neural network, trained by using a back-propagation algorithm, is implemented. Using a reduced number of possible defect classes, the system gives consistent and repeatable results with sufficient speed.

A layered e-maintenance architecture powered by smart wireless monitoring components

Industrial asset lifecycle management is facing pressing demands to rationalize asset usage in parallel with meeting production, quality, safety, environment and cost-efficiency constraints. The introduction of enabling technologies, within an e-Maintenance framework is a significant contributor to this end. Among the key relevant technological factors are web-based maintenance services, wireless sensing and identification technologies, data and services integration and interoperability, as well as mobile and contextualized computing. Within such a framework, a layered e-Maintenance architecture is introduced, leveraging upon the strengths of smart and wireless components in order to upgrade the maintenance-services from the low level of operations, to the higher levels of planning and decision making.

FPGA-based Design Approaches of Keccak Hash Function

Keccak hash function has been submitted to SHA-3 competition and it belongs to the final five candidate functions. In this paper FPGA implementations of Keccak function are presented. The designs were coded using HDL language and for the hardware implementation, a XILINX Virtex-5 FPGA was used. Some of the proposed implementations use DSP48E blocks in order to accelerate the designs execution. So, comparisons between the proposed designs in terms of time performance and FPGA resources are given in order to examine the efficiency of the using DSP48E blocks. Also, comparisons with previous published works are provided.

Wireless Sensor Network Technologies for Condition Monitoring of Industrial Assets

Systematic and robust condition monitoring of crucial equipment is the cornerstone of any successful preventive maintenance policy in the industrial environment. Recent advances in low-cost wireless sensor network (WSN) technologies and products indicate a promising future for a cost-effective, wider and more permanent deployment of a distributed sensing and processing infrastructure. This paper aims to provide a comprehensive assessment of main WSN technology alternatives available today, based on a qualitative and quantitative analysis of the typical range of requirements in the specific application domain of industrial machine condition monitoring.