適応ファジィモデリングによる連続溶融亜鉛メッキラインの付着量制御

Determination of Heat Transfer Coefficient in Pool Boiling of Organic Liquids Using Fuzzy Modeling Approach

Development of an adaptive fuzzy logic-based inverse dynamic model for laser cladding process

Pyrolysis of waste polyethylene in a semi-batch reactor to produce liquid fuel: Optimization of operating conditions

Galvanizing facilities are highly energy intensive operation with electrical and fuel energy representing a significant share of their total energy usage. Furnaces are extensively used in galvanizing process. Production process expertise along with the energy conservation practices can play a significant role in proper usage of energy at galvanizing facilities. Therefore, benchmarking galvanizing energy consumption and understanding the specific energy consumption by various elements are critical. E-GEPDSS (Enhanced Galvanizing Energy Profiler Decision Support System) was built to identify this specific energy consumption by using heat balance analysis. The use of E-GEPDSS does not hinder the production process and the user may run the model for different set of operating conditions and observe the results. The results obtained from the analysis will help the user to make energy enhancing decisions.;This research involved the analysis of galvanizing operations focusing on the furnace side of energy consumption. The furnace heat balance was built and applied using the data collected from a host company during the plant visit. Sensitivity analysis were done to study the impact of changing process and product parameters on the total heat loss from the system.;From the energy analysis conducted for the furnace equipment at the host facility, it was found that the useful heat absorbed by the product is only 50% of the heat supplied to the furnace and rest of heat dissipates as losses. Heat losses from surfaces, walls, water cooling and stack are significant. Heat loss due to opening and phase change heat loss seem not to be significant. Emissivity, dimensions of the furnace, temperature of the zones, thermal conductivity of insulation materials and the strip temperature at the entry and exit of each zone have significant impact on the total heat loss. In the future, the model will be applied extensively to more galvanizing lines in order to help the galvanizers to have a better understanding about the energy consumption while producing their product.

The Continuous Galvanizing Line (CGL) has mechanisms in which electric drives are interconnected by the processed strip. The subject to investigation is the entrance zone, the mechanism for welding the ends of the rolls, the drive strip to ensure the continuity of the galvanizing process. During welding the speed of the input zone is zero and the process of selecting a strip from the input drive is in progress at the input of the technological zone. After the welding operation is completed, the value of strip speed exceeds the strip processing speed in the technological zone. To study processes in an interconnected electromechanical system, a mathematical description of the electric drives and the processed strip. The study of such interconnected electric drives should be carried out. The research results are presented in the form of oscillograms of the operation of electric drives when performing various technological operations.

Steel coils are welded end to end for processing in a continuous galvanizing line of a cold rolling mill. Failure of the welds in the line during processing results into mill stoppages causing huge production downtime. An automated ultrasonic-based non-destructive measurement system for assessing the weld integrity of 0.6–2-mm-thick steel sheets immediately after welding is described. The system was designed to detect any physical weld defects, viz., lack of fusion, expulsion, cracks, etc., which compromises the integrity of weld leading to its failure in the processing line. A high-frequency ultrasonic probe with an integrated water chamber was designed for enabling high-speed non-contact automated inline inspection of the weld considering the limited inspection time available in the mill (40 s). A prototype scanning system was made using the developed ultrasonic probe which was successfully able to detect the weld defects formed in actual plant samples.

Path bridging: A novel local search methodology for optimizing scheduling in highly constrained continuous galvanizing line operations

The useful life of a power transformer is linked to the integrity of its solid (cellulosic) insulation. The insulation deterioration is time dependent and is influenced by varying temperatures, moisture, oxygen, oil conditions and loading profiles. Accordingly, once the solid insulation state is compromised, its dielectric and mechanical properties are not recoverable. Thus, longevity in service of a power transformer can only be achieved by incessant monitoring and assessing the credibility of its insulation system. The tensile strength of the solid insulation can be indicated by determining the degree of polymerization of the paper. Consequently, the degree of polymerization is a key indicator of the insulation status that correlates well with the transformer remnant life. Since degree of polymerization measurement is an intrusive test involving transformer disassembling, utilities have opted to the use of furans concentration in the oil as a way of determining the degree of polymerization of transformer solid insulation. However, these furans and degree of polymerization correlations are based on mathematical models. This paper introduces an adaptive neuro fuzzy model to estimate the degree of polymerization of a mineral oil-immersed power transformer based on furan content and CO 2 /CO gas concentration ratio in the insulation system. Practical data from numerous power transformers of different lifespans subjected to different operating regimes have been used to validate the accuracy and credibility of the established adaptive neuro fuzzy model. Compared to the conventional models, the results show that the proposed model is effective in estimating the degree of polymerization of transformer solid insulation.

This paper assesses the operator functional state (OFS) of human operators based on a collection of psychophysiological and performance measures. Two types of adaptive fuzzy models, namely ANFIS (adaptive-network-based fuzzy inference system) and GA (genetic algorithm) based Mamdani fuzzy model, are employed to estimate the OFSs under a set of simulated process control tasks involved in an automation-enhanced cabin air management system (aCAMS). The adaptive fuzzy modelling procedures are described and then validated using real-life data measured from such a simulated human-machine process control system.

Adaptive fuzzy inference causal graph approach to fault detection and isolation of field devices in nuclear power plants

This paper presents a new approach for the model-based diagnosis. The model is based on an adaptation with a variable forgetting factor. The variation of this factor is managed thanks to fuzzy logic. Thus, we propose a design method of a diagnosis system for the sensor defaults. In this study, the adaptive model is developed theoretically for the Multiple-Input Multiple-Output (MIMO) systems. We present the design stages of the fuzzy adaptive model and we give details of the Fault Detection and Isolation (FDI) principle. This approach is validated with a benchmark: a hydraulic process with three tanks. Different defaults (sensors) are simulated with the fuzzy adaptive model and the fuzzy approach for the diagnosis is compared with the residues method. The method is efficient to detect and isolate one or more defaults. The results obtained are promising and seem applicable to a set of MIMO systems.KeywordsAdaptive modelfuzzy system modelsdiagnosisFault DetectionIsolation (FDI)

The main process variables to produce galvanized dual phase (DP) steel sheets in continuous galvanizing lines are time and temperature of intercritical austenitizing (tIA and TIA), cooling rate (CR1) after intercritical austenitizing, holding time at the galvanizing temperature (tG) and finally the cooling rate (CR2) to room temperature. In this research work, the effects of CR1, tG and CR2 on the ultimate tensile strength (UTS), yield strength (YS), and elongation (EL) of cold rolled low carbon steel were investigated by applying an experimental central composite design and a multivariate regression model. A multi-objective optimization and the Pareto Front were used for the optimization of the continuous galvanizing heat treatments. Typical thermal cycles applied for the production of continuous galvanized AHSS-DP strips were simulated in a quenching dilatometer using miniature tensile specimens. The experimental results of UTS, YS and EL were used to fit the multivariate regression model for the prediction of these mechanical properties from the processing parameters (CR1, tG and CR2). In general, the results show that the proposed multivariate model correctly predicts the mechanical properties of UTS, YS and %EL for DP steels processed under continuous galvanizing conditions. Furthermore, it is demonstrated that the phase transformations that take place during the optimized tG (galvanizing time) play a dominant role in determining the values of the mechanical properties of the DP steel. The production of hot-dip galvanized DP steels with a minimum tensile strength of 1100 MPa is possible by applying the proposed methodology. The results provide important scientific and technological knowledge about the annealing/galvanizing thermal cycle effects on the microstructure and mechanical properties of DP steels.

Intelligent Quality Monitoring System as an Effective Tool for Quality Control in Continuous Galvanizing Line at Tata Steel

In a continuous galvanizing line (CGL), three so-called pot rolls are usually used to guide steel strips in a zinc pot. Generally zinc pot rolls are coated with WC–Co to protect the pot roll surface from severe corrosion by molten zinc. The degradation process of the WC–Co coating was evaluated through analyses of coated pot rolls used in a CGL zinc pot for 33 and 56 days. The rolls were coated by high velocity oxygen fuel spraying with WC–12% Co powders that were produced through sintering and crushing processes. On the surface of the WC–Co coated rolls, several types of deposits were observed including top dross (Fe2Al5 inter-metallic compound) that might induce dross defect on the surface of galvanized steel. The diffusion depth of zinc into the WC–Co coating used for 33 days was only 10 μm, but some areas were severely attacked along cracks within the coating layer because of a preferential reaction with aluminum. Through SEM study, we observed that not only zinc but also aluminum diffused into the WC–Co coating after being in the zinc pot for 56 days. In some cases, Al–Fe–Zn layers were observed on the surface of the spray coating. Those layers were analyzed to be Fe2Al5 as their chemical compositions are very similar to those of Fe2Al5 top dross. However, they are not the Fe2Al5 dross, but the reaction products between molten zinc and the coating layer according to their morphologies.

<div class="htmlview paragraph">A Hot Dip Simulator has been constructed at Inland Steel Research Laboratories to support product development and process optimization. The Hot Dip Simulator can reproduce the heat treating, galvanizing, and galvannealing processes that occur on a continuous galvanizing line. The equipment and computer control system provide a high degree of experimental control and flexibility. This allows simulation of the galvanizing and galvannealing processes at coating lines located at Inland's Indiana Harbor Works and at l/N Kote. The primary use of the Hot Dip Simulator has been to determine the effects of process variables on the galvannealing process and on galvannealed products.</div>