Deep Learning has been attracting considerable attention as it can autonomously learn important signal features and has shown great potential for fault diagnosis. However, given the variability of ...high-power variable-frequency industrial systems, especially under unfavorable service conditions such as voltage and load fluctuations, the identification of insulated bearing faults in variable-frequency motors has become a key challenge to be addressed. Moreover, the time-varying nature of insulated bearing data poses common technical difficulties for existing models. To bridge these gaps, this research spearheaded the development of a lightweight spatial–temporal focusing framework equipped with a novel optimizer called LSTA-Net, which was designed to address the challenging problem of insulated bearing fault identification in real-world engineering scenarios. Specifically, this involves an innovative design of the Weight Reducing Recursive Unit (WDRU) strategy and an updated backpropagation formulation, which was skillfully applied to the feature extraction module of the LSTA-Net framework for the first time. Furthermore, a novel optimizer called Stochastic Newton Descent (SND) has been developed and skillfully integrated into the LSTA-Net framework with the newly derived weight update formula, providing unique insights to improve diagnostic performance. Finally, the diagnostic performance of the LSTA-Net framework was evaluated from multiple dimensions based on the same dataset, proving its superiority, generalizability, and robustness. t-SNE technique integration intuitively explains the framework’s fault characterization mining process, improving its credibility, reliability, and accuracy.
Accurate and science-based prediction of bearing performance degradation has been a principal concern and a critical challenge issue in the sector of Prognostics and Health Management in the industry ...as the solution to promote the engineering system's reliability, availability, and maintainability. Deep Learning (DL) methods are currently a hotspot in Prognostics and Health Management. Nonetheless, with complex operating conditions, existing forecast models still inevitably suffer from three fatal flaws. Firstly, dynamic modern industrial systems and harsh operational environments make the degradation data of the bearing-rotor system highly stochastic and nonlinear. Secondly, in practice, the bearing-rotor system failure process will be governed by complex failure dynamics and degradation mechanisms, resulting in degradation data characterized by intense temporal order. Thirdly, deep learning models use a multi-layer or cellular design containing numerous weights and biases, generating more computational overhead. To fill this research gap, a new deep interval health monitoring and prediction framework named Lightweight Probabilistic Spatiotemporal (LPST-Net) is proposed, which is integrated with the concepts of lightweight and interval prediction and is capable of state monitoring and Remaining Useful Life (RUL) prediction for bearing-rotor systems under complex operating conditions. Mainly inspired by the improvement of the Gate Recurrent Unit (GRU), this paper designs a time series variable prediction algorithm and derives a new formulation named Weight Diminish Recurrent Unit (WDRU). It dramatically reduces the training parameters of the proposed LPST-Net framework and improves the convergence speed while ensuring prediction accuracy. The degradation data are obtained under 2 actual and complex operating conditions of bearing-rotor system unbalance and high temperature. The three metrics show that the proposed LPST-Net framework can achieve high-precision point prediction, suitable prediction intervals, and reliable probabilistic prediction results. It is also verified that the proposed LPST-Net framework has superior performance and more practical application value compared with seven mainstream methods, such as (b)Squeeze-WDRU-GPR-Net.
The rapid advancement of intelligent theories and models, exemplified by deep learning, has achieved remarkable success across numerous fields. However, given that the complexity and variability of ...offshore wind turbine systems, particularly in the context of high-power variable-frequency control of insulated bearings in offshore wind turbines, the problem of fault identification has become a recognized technical challenge. Additionally, fully exploiting the temporal characteristics of insulated bearing fault data poses a key problem that demands urgent resolution. To address these gaps, this paper pioneers a novel Lightweight Temporal Feature-focused framework, named LTFM-Net, aimed at solving the difficult problem of identifying insulated bearing faults in offshore wind turbines in practical engineering applications. Specifically, this framework enables the intelligent identification of insulated bearing faults under harsh operating conditions such as alternating voltage and variable loads, marking a first in this field. Furthermore, an innovative strategy named Weighted Diminish Recurrent Unit (WDRU) was developed, along with the derivation of its backpropagation formula, which is innovatively applied to the feature extraction module of the LTFM-Net framework for the first time. Thus, an efficient method for acquiring fault data from insulated bearings in offshore wind turbines was proposed. Based on a unified dataset, the diagnostic performance of the LTFM-Net framework was evaluated and compared with seven advanced methods. The results demonstrate that the LTFM-Net achieves precise identification of insulated bearing faults, confirming its excellent generalization, robustness, and superiority. The introduction of t-SNE for visualizing the fault characteristics of insulated bearings uncovered by the LTFM-Net framework further enhances its reliability, accuracy, and credibility.
•This study pioneered innovation by developing a lightweight temporal feature focusing framework, aimed at addressing the challenge of identifying faults.•This research facilitates the first intelligent identification of such faults, offering fresh insights into fault detection for insulated bearings and failure modes of insulated bearings.•It innovatively develops the Weight Reducing Recursive Unit (WDRU) strategy combined with an updated back propagation formulation.
There are many computer applications in the world that use databases to store, process, and use data. That translates into many different ways of handling these databases. It is therefore difficult ...to choose a solution that meets the needs of the user. This article compares three C# solutions in terms of time efficiency: the Entity Framework Core application framework, pure SQL queries, and parameterized Prepared Statement queries. The results obtained in the course of the research has shown that the fastest solution is the use of non-parameterised SQL queries. The use of Entity Framework Core is the slowest of the three tested solutions.
This study helps athletes avoid and reduce the risk of injury in training more effectively by constructing a sports training injury risk assessment system to ensure they can train and compete safely ...and healthily. Based on the B/S model and .NET framework, this paper successfully develops a sports training injury risk assessment system and proposes a human exercise training detection program. The system integrates the measurement of physiological parameters such as blood oxygen saturation and blood pressure changes. It constructs a kinematic model to analyze the forces in training through inverse dynamics. In the system test, the response time was only 0.09ms/frame and the standby power consumption was as low as 11.43mW, demonstrating superior operational and energy efficiency. In addition, it was found that under specific conditions, such as after holding breath for 27.5s, the non-contact oximetry measurement showed a strong linear relationship with the physiological parameter detection module, which may predict the risk of falling when the peak motion acceleration SMV exceeds 3.23m
/s. Through this system, athletes can understand their body stress and physiological changes in the training process in real time, effectively avoiding potential training injuries, thus safeguarding their training safety and health.
The Asp.Net Core 2.0 Framework has been designed to meet all the needs of today's web developers. It provides better control, support for test-driven development, and cleaner code. Moreover, it's ...lightweight and allows you to run apps on OSX and Linux, making it the most popular web framework with modern day developers.
Enhance your applications' performance using best practices for benchmarking, application profiling, asynchronous programming, designing responsive UIs, gRPC communication, and distributed ...applications Key Features * Make the best use of performance enhancements in C# 10.0 and.NET 6 * Boost application performance by identifying hardware bottlenecks and common performance pitfalls * Get to grips with best practices and techniques for improving the scalability of distributed systems Book Description Writing high-performance code while building an application is crucial, and over the years, Microsoft has focused on delivering various performance- related improvements within the.NET ecosystem. This book will help you understand the aspects involved in designing responsive, resilient, and high- performance applications with the new version of C# and.NET. You will start by understanding the foundation of high-performance code and the latest performance-related improvements in C# 10.0 and.NET 6. Next, you'll learn how to use tracing and diagnostics to track down performance issues and the cause of memory leaks. The chapters that follow then show you how to enhance the performance of your networked applications and various ways to improve directory tasks, file tasks, and more. Later, you'll go on to improve data querying performance and write responsive user interfaces. You'll also discover how you can use cloud providers such as Microsoft Azure to build scalable distributed solutions. Finally, you'll explore various ways to process code synchronously, asynchronously, and in parallel to reduce the time it takes to process a series of tasks. By the end of this C# programming book, you'll have the confidence you need to build highly resilient, high-performance applications that meet your customer's demands. What you will learn * Use correct types and collections to enhance application performance * Profile, benchmark, and identify performance issues with the codebase * Explore how to best perform queries on LINQ to improve an application's performance * Effectively utilize a number of CPUs and cores through asynchronous programming * Build responsive user interfaces with WinForms, WPF, MAUI, and WinUI * Benchmark ADO.NET, Entity Framework Core, and Dapper for data access * Implement CQRS and event sourcing and build and deploy microservices Who this book is for This book is for software engineers, professional software developers, performance engineers, and application profilers looking to improve the speed of their code or take their skills to the next level to gain a competitive advantage. You should be a proficient C# programmer who can already put the language to good use and is also comfortable using Microsoft Visual Studio 2022.
Leverage the full potential of Entity Framework with this collection of powerful and easy-to-follow recipesAbout This Book• Learn how to use the new features of Entity Framework Core 1• Improve your ...queries by leveraging some of the advanced features• Avoid common pitfalls• Make the best of your.NET APIs by integrating with Entity FrameworkWho This Book Is ForThis book is for.NET developers who work with relational databases on a daily basis and understand the basics of Entity Framework, but now want to use it in a more efficient manner. You are expected to have some prior knowledge of Entity Framework.What You Will Learn• Master the technique of using sequence key generators• Validate groups of entities that are to be saved / updated• Improve MVC applications that cover applications developed using ASP.NET MVC Core 1• Retrieve database information (table, column names, and so on) for entities• Discover optimistic concurrency control and pessimistic concurrency control.• Implement Multilatency on the data side of things.• Enhance the performance and/or scalability of Entity Framework Core• Explore and overcome the pitfalls of Entity Framework CoreIn DetailEntity Framework is a highly recommended Object Relation Mapping tool used to build complex systems. In order to survive in this growing market, the knowledge of a framework that helps provide easy access to databases, that is, Entity Framework has become a necessity. This book will provide.NET developers with this knowledge and guide them through working efficiently with data using Entity Framework Core. You will start off by learning how to efficiently use Entity Framework in practical situations. You will gain a deep understanding of mapping properties and find out how to handle validation in Entity Framework. The book will then explain how to work with transactions and stored procedures along with improving Entity Framework using query libraries. Moving on, you will learn to improve complex query scenarios and implement transaction and concurrency control. You will then be taught to improve and develop Entity Framework in complex business scenarios. With the concluding chapter on performance and scalability, this book will get you ready to use Entity Framework proficiently.Style and approachFilled with rich code-based examples, this book takes a recipe-based approach that will teach.NET developers to improve their understanding of Entity Framework and help them effortlessly apply this knowledge in everyday situations.
