Fault Diagnostics on Steam Boilers and Forecasting System Based on Hybrid Fuzzy Clustering and Artificial Neural Networks in Early Detection of Chamber Slagging/Fouling

The slagging/fouling due to the accession of fireside deposits on the steam boilers decreases boiler efficiency and availability which leads to unexpected shut-downs. Since it is inevitably associated with the three major factors namely the fuel characteristics, boiler operating conditions and ash behavior, this serious slagging/fouling may be reduced by varying the above three factors. The research develops a generic slagging/fouling prediction tool based on hybrid fuzzy clustering and Artificial Neural Networks (FCANN). The FCANN model presents a good accuracy of 99.85% which makes this model fast in response and easy to be updated with lesser time when compared to single ANN. The comparison between predictions and observations is found to be satisfactory with less input parameters. This should be capable of giving relatively quick responses while being easily implemented for various furnace types.

Study on Strengthening of RC Beam Column Joint Using Hybrid FRP Composites

Beam-Column joints are critical zones in reinforced concrete structures which are most vulnerable to earthquake forces. Hence strengthening beam-column joint is vital to save the structure and its inhabitants in case of seismic forces. Numerous retrofitting works using fibre reinforced polymer (FRP) composites are being undertaken worldwide. This work aims to investigate the effectiveness of strengthening beam-column joints using natural and artificial fibres. In this study, basalt (natural fibres) as monolithic composite (BFRP) and as hybrid composite along with glass (artificial fibres) were used for strengthening of beam-column joints. Totally six specimens were prepared and tested under monotonic loading. Specimen details used were: two control specimen, two specimens for monolithic wrapping and remaining two specimens for hybrid wrapping. The test results were compared with control and rehabilitated specimens. The performance of the treated joints was studied using the following parameters: initial and ultimate cracking loads, energy absorption, deflection ductility and stiffness at ultimate. From the test results, it was found that the hybrid combination of Basalt and Glass FRPs were found to be more effective in the treatment of beam-column joints. The strong column weak beam concept was achieved by failure in beam portion which helped in preventing the catastrophic failure of the entire structure.

Paddy Leaf Disease Detection Using an Optimized Deep Neural Network

Precision Agriculture is a concept of farm management which makes use of IoT and networking concepts to improve the crop.Plant diseases are one of the underlying causes in the decrease in the number of quantity and quality of the farming crops.Recognition of diseases from the plant images is an active research topic which makes use of machine learning(ML)approaches.A novel deep neural network(DNN)classification model is proposed for the identification of paddy leaf disease using plant image data.Classification errors were minimized by optimizing weights and biases in the DNN model using a crow search algorithm(CSA)during both the standard pre-training and fine-tuning processes.This DNN-CSA architecture enables the use of simplistic statistical learning techniques with a decreased computational workload,ensuring high classification accuracy.Paddy leaf images were first preprocessed,and the areas indicative of disease were initially extracted using a k-means clustering method.Thresholding was then applied to eliminate regions not indicative of disease.Next,a set of features were extracted from the previously isolated diseased regions.Finally,the classification accuracy and efficiency of the proposed DNN-CSA model were verified experimentally and shown to be superior to a support vector machine with multiple cross-fold validations.

SAC-TA: A Secure Area Based Clustering for Data Aggregation Using Traffic Analysis in WSN

Clustering is the most significant task characterized in Wireless Sensor Networks (WSN) by data aggregation through each Cluster Head (CH). This leads to the reduction in the traffic cost. Due to the deployment of the WSN in the remote and hostile environments for the transmission of the sensitive information, the sensor nodes are more prone to the false data injection attacks. To overcome these existing issues and enhance the network security, this paper proposes a Secure Area based Clustering approach for data aggregation using Traffic Analysis (SAC-TA) in WSN. Here, the sensor network is clustered into small clusters, such that each cluster has a CH to manage and gather the information from the normal sensor nodes. The CH is selected based on the predefined time slot, cluster center, and highest residual energy. The gathered data are validated based on the traffic analysis and One-time Key Generation procedures to identify the malicious nodes on the route. It helps to provide a secure data gathering process with improved energy efficiency. The performance of the proposed approach is compared with the existing Secure Data Aggregation Technique (SDAT). The proposed SAC-TA yields lower average energy consumption rate, lower end-to-end delay, higher average residual energy, higher data aggregation accuracy and false data detection rate than the existing technique.

Heat Transfer Analysis of an Elevated Linear Absorber with Trapezoidal Cavity in the Linear Fresnel Reflector Solar Concentrator System

This paper describes various aspects of the design methodology and heat transfer calculations for an elevated linear absorber. The absorber is a part of the linear Fresnel reflector solar concentrator system, in which hot fluid is generated. The design of the absorber is an inverted trapezoidal air cavity with a glass cover enclosing a multi tube absorber. In a trapezoidal cavity absorber, a set of linear multi tube absorber with plate(named as "plane surface") and without plate(named as "tube surface") underneath are considered. An analytical simulation is done for different gaps between the tubes and for different depths of the cavity. A better design of the absorber is found out to maximize the heat transfer rate supplied to the absorber tube fluid. Also, the experimentally obtained overall heat loss coefficients are compared with the analytical values for the considered arrangements of absorber set up and results are discussed in details.