فصلنامه روشهای هوشمند در صنعت برق
پیاپی 41 (بهار 1399)

At various stages of fabric production, there are numerous damages to the surface of the fabric. Regardless of the causes of the failures, precise identification of their types helps to correctly classify the fabric and thus provides a high percentage of the quality control process. Quality control of fabrics is of great importance in order to improve product quality and maintain a competitive market. Identification of faulty areas in automated methods is of great importance. In this paper, a new method is presented in the clustering of faulty zones based on clustering as well as morphological operators. In the proposed method, after preprocessing necessary to improve image quality, the first step is to cluster the image to create similar areas. Then morphological operators are applied to extract the defective area. The defective area is represented by the active contour algorithm. Although many methods such as local binary patterns and other methods have been proposed, the speed of detection of these algorithms is low and has high computational complexity. The proposed method is implemented on the CMUPIE database and evaluated using accuracy assessment criteria and accuracy criteria. The accuracy of identifying defective areas in the proposed method is 93.82%, and the precision of detecting defective areas in the suggested method is 98.33% which are significantly improved compared to similar methods.

The map-reduce model is a method for executing large data applications. It is also a parallel programming model for writing applications that can be executed on the cloud. Organizations are increasingly producing data that is generated by business processes, user activities, website tracking, sensors, finance, accounting, and more. Data clustering algorithms are used as tools for analyzing large volumes of data. The main purpose of these algorithms is to categorize data into clusters so that the data objects in each cluster are more similar. In this paper, a dense hierarchical clustering algorithm, one of the data mining techniques, is implemented using map-reduce design and then the results of this algorithm are compared with the usual one. Experiments show that runtime decreases with increasing input data size. The runtime of the algorithm improved by 16.80% for the 200 data-point dataset, and 29.26% for the dataset with 1000 data points. The percentage of CPU usage in the parallel system also increased from 22% to 94%.

In this study, we try to present a complete model of skeletal muscle, with the aim of expressing it's behavior in a precise manner. This model is presented with considering the role of sensory receptors in muscle function. Muscle spindle and Golgi tendon receptors provide information on length changes and muscle force, respectively . Then this information is sent to the central nervous system for final decision making. In this study, adaptive combination of the Spindle and Golgi tendon afferents Due to the changes in their level of activity and the force produced in the muscle under different functional conditions is suggested. Considering the control feedbacks of the afferents in the presented model can optimize the precise behavior of the muscle under different loads and eliminate the limitations of previous models. The results of the proposed model according to the precise modeling of sensory receptors (Muscle spindle and Golgi tendon) have been consistent with the experimental results of muscle activity. This model can be used to predict muscle's behavior in preventing muscular nervous system damage, as well as the design of artificial muscles and different prostheses.

In this paper, Finite Element Method (FEM) is used to study the ferroresonance phenomenon from the perspective of the electromagnetic forces introduced on the transformer windings. In order to simulate this phenomenon, a consecutive 3–phase short–circuit fault is considered to be on the primary side at a relatively distant from the transformer. Then, due to the capacitance of the line, between the error point and transformer, the single–phase short–circuit faults are generated, one–by–one. Because of the switching, for isolation feeder from the fault point, the ferroresonance appears in power system. Then, voltages and currents of the primary and secondary windings will be changed. The effect of current changes on the forces that transformer coils withstand, when the ferroresonance happens, is an interesting topic to this paper. With modeling of the transformer and feeder switching in the FLUX 12.2 software, the ferroresonance condition is simulated. Due to the dependence of the ferroresonance on the non-linearity of the magnetic characteristic of the transformer core, Jiles–Atherton vector hysteresis model is used to modeling the core hysteresis loops for enhancement the results accurate.

Electronic waste (E-waste) consists of obsolete electrical or electronic devices. Electronic waste recycling is of importance when it comes to protecting resources and environment. Today, nearly 1.3 billion tons/year of waste is produced worldwide, which is expected to increase to 4.3 billion tons/year by 2025. E-waste from old PCs is predicted to increase to 500 percent over a decade, and by 2020, compared to 2007, the disposal of cell phones will be increased by almost 18 times. Understanding and distinguishing different components of E-waste can help their efficient recycling. Sophisticated electronic devices contain approximately 60 different elements, which include valuable and hazardous materials. The most valuable component of E-waste is PCB, which contain many hazardous materials besides valuable metals. To prevent human and environmental poisoning, it is necessary to analyze the properties and compounds of different materials in E-waste and to find ways of re-managing it using healthy and environmentally friendly processes. In this paper, we focus on the general E-wasteland problems, such as the classification of E-waste, its constituents, various eco-friendly waste manage me n t and recycling processes, as well as considering valuable metals extraction. Despite many efforts to develop the recycling technology, this technology has many disadvantages due to the complexity of E-waste treatment systems. Therefore, the disadvantages of each process are discussed by considering technical problems and environmental protection level.

Frequency carries the most important parameters for identifying and classifying signals in electronic warfare systems and measuring them is one of the most important tasks of an electromagnetic support measure. To this end, various receiver structures with different capabilities and features have been proposed; however, given the technology available, it is usually necessary to combine different structures to achieve receivers. Used with the specification and function given. Although analogue receptors are capable of measuring essential parameters, they have limitations on sensitivity and accuracy. Therefore, digital receivers, by removing the limitations, have created a good signal in such systems. Adding multi-signal simultaneous presence detection capabilities and CW signal presence to the receiver structure are among other activities to complete the receiver's conceptual design. In this paper, we investigate the principles of performance, error analysis and finally simulation of receiver frequency moment measurement (DIFM) based on data characteristics. After a comprehensive overview of the proposed receivers for electronic warfare backup systems, we propose the overall structure of the receiver in order to allow it to be used in receivers with appropriate parameters and provide relationships to calculate its performance. To give. We also choose the appropriate estimator by simulation using MATLAB software. Then, by summarizing the material presented, we introduce the structure of the final receiver and, after appropriate mathematical modeling, obtain the overall performance of the system. As we shall see, the introduced receiver structure is capable of meeting the desired receiver specifications in the defined project.