Pantelis N. Botsaris

Fault diagnosis of photovoltaic modules through image processing and Canny edge detection on field thermographic measurements

Today, conventional condition monitoring of installed, operating photovoltaic (PV) modules is mainly based on electrical measurements and performance evaluation. However, such practices exhibit restricted fault-detection ability. This study proposes the use of standard thermal image processing and the Canny edge detection operator as diagnostic tools for module-related faults that lead to hot-spot heating effects. The intended techniques were applied on thermal images of defective PV modules, from several field infrared thermographic measurements conducted during this study. The whole approach provided promising results with the detection of hot-spot formations that were diagnosed to specific defective cells in each inspected module. These evolving hot spots lead to abnormally low performance of the PV modules, a fact that is also validated by the manufacturers standard electrical tests.

An estimation of three-way catalyst performance using artificial neural networks during cold start

Abstract In this paper, an estimation of a three-way catalyst performance with artificial neural networks is presented. It may be an alternative approach far an on-board diagnostic system (OBD) to predict the catalyst performance. This method was tested using data sets from two specific kind of ceramic catalysts, a brand new and an old one on a laboratory bench at idle speed. Further experiments are needed for different catalyst types before the method is proposed generally. The catalyst operation during the “ cold start ” phase (the phase that the catalyst has not reached its operating conditions yet) is examined. It consists of 200 elements of catalyst inlet–outlet temperature difference (DT), hydrocarbons (HC), and carbonmonoxide (CO) and carbon dioxide (CO 2 ) emissions. The simulation: detects the values of HC, CO, CO 2 using the DT as an input to our network forms a neural network. Results showed serious indications that artificial neural networks could estimate the catalyst performance adequately depending their training process. In this paper the “ cold start ” period experimental results are presented.

An infrared thermographic approach as a hot-spot detection tool for photovoltaic modules using image histogram and line profile analysis

As ecological awareness has intensified during the past two decades, renewable energy sources (RES) and, consequently, photovoltaic (PV) systems have undergone an impressively fast evolution. However, the sustainability of an installed PV system can only be achieved through its performance optimisation by reducing any source of fault, structural defect or malfunction during either the manufacturing or the operating (after installation) stage. This paper suggests the use of a hot-spot detection tool for PV modules, based on condition monitoring by infrared thermography. The experimentation of the intended approach includes several daily sets of in-situ thermography measurements of specific PV arrays, installed on the rooftop of a laboratory building in the School of Engineering Campus of Democritus University of Thrace (DUTH), Greece. Further processing of the obtained thermal images, by means of a basic image histogram and line profile analysis, provides useful data for the detection and quantification of hot spots within each PV module. In particular, specific variations in the morphological features of both thermal images’ histograms and linear profiles witness the presence of defects, their source within the module and, ultimately, their impact on the degradation of the inspected PV array’s performance due to the hot-spot heating effect.

Estimation of the energy payback time (EPR) for a PV module installed in North Eastern Greece

Energy Payback Time is defined as the time necessary for a photovoltaic panel to generate the equivalent amount of energy used to produce it. The goal of this paper is to estimate the energy payback ratio for a 185*Wp multicrystalline photovoltaic module with specific characteristics and structure. The methodology followed was attested in two ways of extracting the EPR (Energy Payback Ratio). The first one was based on precedent researches, whereas the second one was based on the use of two softwares (CES EduPack 2008 and RETScreen). The results, then, were compared and confirmed in order to deal with crossbred information.

Single-stage Kanban system with deterioration failures and condition-based preventive maintenance

Abstract Despite the fact that the fields of pull type production control policies and condition-based preventive maintenance have much in common contextually, they have evolved independently up to now. In this investigation, an attempt is made to bridge the gap between these two branches of knowledge by introducing the single-stage Kanban system with deterioration failures and condition-based preventive maintenance. The formalism of continuous time Markov chains is used to model the system and expressions for eight performance metrics are derived. Two important, from a managerial perspective, constrained optimization problems for the proposed model are defined where the objective is the simultaneous optimization of the Kanban policy, the preventive maintenance policy and the inspection schedule under conflicting performance criteria. Multiple instances of each optimization problem are solved by means of the augmented Lagrangian genetic algorithm. The results from the optimization trials coupled by the results from extensive numerical examples facilitate the thorough investigation of the system’s behaviour.

Emission reduction during cold start via catalyst surface control

Abstract The present paper is a preliminary investigation of a new approach to the reduction of pollutant emissions during a cold start. During a cold start the volume of the exhaust gases is considerably smaller than those under full load. Therefore, only a small portion of the catalyst active surface is required to process the gases. As the exhaust gases flow from the upstream surface to the downstream surface, they meet with the cold surface of the catalyst, which they should warm up first, before light-off. The larger that surface, the more time will be needed for its warm-up, which will increase the time required for a light-off. The experimental results presented here indicate that there can be a significant reduction of the pollutant emissions during the cold start of an engine, if a system can be devised that could adjust the catalyst active surface during start-up proportionally to the exhaust gas volume. There are strong indications that a quicker warm-up of the catalyst and a faster initiation of catalysis can be achieved by focusing the gas flow towards the centre core of the monolith. In this way the remaining ceramic body of the catalytic converter operates as a heat insulator. This idea may be utilized in the design of catalyst system with variable active surface.

A comparative analysis of a cdte and a poly-Si photovoltaic module installed in North Eastern Greece1

The aim of this paper is the comparison of 2 different photovoltaic (PV) modules installed in North Eastern Greece, a CdTe thin film and a poly-Si PV module, in terms of energy reimbursement through the extraction of Energy Payback Time (EBPT). In addition, the environmental burden of the examined systems was assessed by examining their Global Warming Potential (GWP) and their Ecological Footprint (EF). For both the energy analysis and the environmental assessment, life cycle oriented approach was implemented using relative software and literature review. Results are expected to help decision makers, investors and researchers interested in photovoltaic technological issues and their performance.

Viability analysis of an offshore wind farm in North Aegean Sea, Greece

The scope of the present work is the techno-economic study with concern for the environmental issues and the investigation of the viability of an offshore wind farm in the Greek sea area, northeast of the island of Limnos. In the context of this study, the wind data, the suitable location for the installation of the wind turbines beyond nature protected areas, the type of the wind turbines, the losses due to wind turbines interaction, and the visual impact at the respective study areas are analyzed. Moreover, reliable costing models are used and applied, internationally recognized for techno-economic studies of offshore wind farms. Thereafter, the viability of the project is studied through investment benchmarks. This means that specific economic indices are estimated indicating whether the realization of such an investment is viable or not. In conclusion, based on the analysis performed in this study, it is noted that in the Greek archipelago and especially at the island of Limnos, there is a sufficient ...

Microprocessor controlled three-way catalyst efficiency monitoring system

Abstract The present paper describes a new design for a microcontrolled three-way catalyst efficiency monitoring system. The system is based on the Motorola 68HC11e2 microprocessor and utilizes the differential signal from a pair of thermocouples installed at the catalyst outlet and inlet sections. This signal is processed in real time using an appropriate statistical algorithm and the corresponding results are compared to experimentally determined limiting values to assess the current state of the catalyst efficiency during driving conditions. The result of this comparison is presented on an LCD display as an A, B, C, or FAIL catalyst condition signal. The system can be readily installed and can operate on new and used cars provided that the type of catalyst used has been experimentally tested to provide the necessary limiting values that characterize its relative levels of efficiency. It can also be reprogrammed and calibrated via a RS232C serial interface.

Management of linked knowledge in industrial maintenance

Purpose Field expertise in industry is often poorly recorded and unexploited. The purpose of this paper is to introduce a methodology and tool that incorporates a knowledge validation loop to leverage upon human-contributed field observations in industrial maintenance management. Starting from a failure mode, effects and criticality analysis (FMECA) model, it defines a collaborative process that links FMECA knowledge with field maintenance practice. Design/methodology/approach A metadata management system is designed to encourage staff involvement in enriching knowledge with field observations. The process supports easy feedback and collaborative annotation and is pilot tested via an industrial case study. Findings Streamlining FMECA validation is welcomed by maintenance staff, empowering them to exert more control over the management, usage and versioning of reference knowledge. Research limitations/implications The methodology for metadata management in industrial maintenance enables staff participation in a collaborative knowledge enrichment process. Metadata management is a pre-cursor and therefore an important step to drive future analytics. Practical implications Industry personnel are more inclined to contribute to organisational knowledge if the process is based on reference knowledge and requires minimal interaction. Social implications Facilitating individual contribution to collective knowledge strengthens the sense that each staff member can have organisational impact. Originality/value The paper introduces a methodology and tool to stimulate human-contributed knowledge in industrial maintenance, strengthening collaborative organisation knowledge flows.