Design Simulation of Improved Power Quality Conditioner System for Enhancement of Power Quality

The increased usage of power-sensitive electronic devices has prompted interest in power conditioning solutions, which is no surprise. As a result, some type of compensation must be supplied if power output remains below the standards' prescribed limitations. The UPQC (Unified Power Quality Controller) is one of numerous AC Transmission System families that can control voltage, impedance, and phase angle among other factors (FACTS). This study focuses on modern UPFC systems that have increased power quality efficiency to help utilities reduce voltage concerns. One of the FACTS controls for lowering stress sales effects is a unified power quality conditioner (UPQC). The quadrature voltage is specified using the UPQC series compensator. As a result, the compensator series never utilizes active power in a continuous scenario. As mentioned in the approach, a low power rating compensator injects voltage to remedy the system's power quality problem. The voltage is decreased and the power factor is raised when the fluid logic controller is used in conjunction with traditional UPQC. Furthermore, the load factor has been improved. The circuit is then imitated in MATLAB / SIMULINK using a fluctuating logo controller.

Radiologists in the loop: the roles of radiologists in the development of AI applications

Objectives To examine the various roles of radiologists in different steps of developing artificial intelligence (AI) applications. Materials and methods Through the case study of eight companies active in developing AI applications for radiology, in different regions (Europe, Asia, and North America), we conducted 17 semi-structured interviews and collected data from documents. Based on systematic thematic analysis, we identified various roles of radiologists. We describe how each role happens across the companies and what factors impact how and when these roles emerge. Results We identified 9 roles that radiologists play in different steps of developing AI applications: (1) problem finder (in 4 companies); (2) problem shaper (in 3 companies); (3) problem dominator (in 1 company); (4) data researcher (in 2 companies); (5) data labeler (in 3 companies); (6) data quality controller (in 2 companies); (7) algorithm shaper (in 3 companies); (8) algorithm tester (in 6 companies); and (9) AI researcher (in 1 company). Conclusions Radiologists can play a wide range of roles in the development of AI applications. How actively they are engaged and the way they are interacting with the development teams significantly vary across the cases. Radiologists need to become proactive in engaging in the development process and embrace new roles. Key Points • Radiologists can play a wide range of roles during the development of AI applications. • Both radiologists and developers need to be open to new roles and ways of interacting during the development process. • The availability of resources, time, expertise, and trust are key factors that impact how actively radiologists play roles in the development process.

Blockchain in manufacturing quality control: A computer simulation study

Blockchain has been applied to quality control in manufacturing, but the problems of false defect detections and lack of data transparency remain. This paper proposes a framework, Blockchain Quality Controller (BCQC), to overcome these limitations while fortifying data security. BCQC utilizes blockchain and Internet-of-Things to form a peer-to-peer supervision network. This paper also proposes a consensus algorithm, Quality Defect Tolerance (QDT), to adopt blockchain for during-production quality control. Simulation results show that BCQC enhances data security and improves defect detections. Although the time taken for the quality control process increases with the number of nodes in blockchain, the application of QDT allows multiple inspections on a workpiece to be consolidated at a faster pace, effectively speeding up the entire quality control process. The BCQC and QDT can improve the quality of parts produced for mass personalization manufacturing.

Dual-loop generalized predictive control method for two-phase three-wire railway active power quality controller

One of the most challenging topics in electric railway networks (ERNs) is power quality (PQ) problems caused by single-phase feeding of time-varying and high-power locomotives. During previous years, many techniques and compensators have been offered to alleviate these problems. Railway active power quality controller (RAPQC) is considered as one of the most efficient approaches. Due to the time-variant, uncertainty and distorted features of ERNs, the controlling of RAPQCs has always been a substantial concern to experts. This paper presents, a new robust control system for two-phase three-wire RAPQC (ThRAPQC) based on generalized model predictive control integrated with modified instantaneous reactive power theory (GMPC-MIRP). A dual-loop balancing system has been adopted in the proposed control system to equalize the active powers of traction power substation (TPSS) adjacent feeders, compensate reactive powers and suppress harmonic simultaneously. The performance of the proposed method in comparison with the conventional Fryze-Buchholz-Depenbrock (FBD)-based current strategy together with hysteresis current controller (FBD-HCC) has been evaluated through the detailed simulations and Opal-RT 5600-based laboratory setup results. The fast response, high precision, lower fluctuation in reference current tracking and high capability of working in distorted conditions are the outstanding privileges of the proposed method that are confirmed by the output results.