Machine fault diagnosis with small sample based on variational information constrained generative adversarial network

In actual engineering scenarios, limited fault data leads to insufficient model training and over-fitting, which negatively affects the diagnostic performance of intelligent diagnostic models. To solve the problem, this paper proposes a variational information constrained generative adversarial network (VICGAN) for effective machine fault diagnosis. Firstly, by incorporating the encoder into the discriminator to map the deep features, an improved generative adversarial network with stronger data synthesis capability is established. Secondly, to promote the stable training of the model and guarantee better convergence, a variational information constraint technique is utilized, which constrains the input signals and deep features of the discriminator using the information bottleneck method. In addition, a representation matching module is added to impose restrictions on the generator, avoiding the mode collapse problem and boosting the sample diversity. Two rolling bearing datasets are utilized to verify the effectiveness and stability of the presented network, which demonstrates that the presented network has an admirable ability in processing fault diagnosis with few samples, and performs better than state-of-the-art approaches.     

Integration of imitation learning using GAIL and reinforcement learning using task-achievement rewards via probabilistic graphical model

The integration of reinforcement learning (RL) and imitation learning (IL) is an important problem that has long been studied in the field of intelligent robotics. RL optimizes policies to maximize the cumulative reward, whereas IL attempts to extract general knowledge about the trajectories demonstrated by experts, i.e, demonstrators. Because each has its own drawbacks, many methods combining them and compensating for each set of drawbacks have been explored thus far. However, many of these methods are heuristic and do not have a solid theoretical basis. This paper presents a new theory for integrating RL and IL by extending the probabilistic graphical model (PGM) framework for RL, control as inference. We develop a new PGM for RL with multiple types of rewards, called probabilistic graphical model for Markov decision processes with multiple optimality emissions (pMDP-MO). Furthermore, we demonstrate that the integrated learning method of RL and IL can be formulated as a probabilistic inference of policies on pMDP-MO by considering the discriminator in generative adversarial imitation learning (GAIL) as an additional optimality emission. We adapt the GAIL and task-achievement reward to our proposed framework, achieving significantly better performance than policies trained with baseline methods.     

Image Super-Resolution Based on Generative Adversarial Networks: A Brief Review

Single image super resolution (SISR) is an important research content in the field of computer vision and image processing. With the rapid development of deep neural networks, different image super-resolution models have emerged. Compared to some traditional SISR methods, deep learning-based methods can complete the superresolution tasks through a single image. In addition, compared with the SISR methods using traditional convolutional neural networks, SISR based on generative adversarial networks (GAN) has achieved the most advanced visual performance. In this review, we first explore the challenges faced by SISR and introduce some common datasets and evaluation metrics. Then, we review the improved network structures and loss functions of GAN-based perceptual SISR. Subsequently, the advantages and disadvantages of different networks are analyzed by multiple comparative experiments. Finally, we summarize the paper and look forward to the future development trends of GAN-based perceptual SISR.     

基于ASP.NET技术的新闻发布系统的设计与实现

完整描述了一种在部队师旅级单位通用的新闻发布系统。首先根据用户的特点,对系统进行了需求分析与功能模块划分,然后在此基础上从系统架构、系统流程和数据库设计等3个方面阐述了系统设计中的关键点,并以设计用户登录界面为例写出了部分功能的实现程序,最后对其在中小型企业建站中的应用进行了展望。     

高分辨率阵列感应测井仪在河南油田的应用

文章介绍了美国Baker-Atlas公司研制生产的高分辨率阵列感应成像测井仪（HDIL）,简述了该仪器的工作原理和技术性能指标及主要应用范围,并介绍了高分辨率阵列感应测井（HDIL）资料在河南南阳油田的具体应用实例.     

膨胀套管的弹塑性理论分析

分析认为，膨胀套管在膨胀过程中先进入弹性阶段，然后进入弹塑性阶段，最后进入塑性流动阶段。采用弹塑性分析方法，对膨胀套管膨胀过程中套管内壁的受力与变形进行了研究，模拟了其成形的过程，并建立了解析解，为膨胀套管膨胀操作过程中确定关键操作参数提供了理论支持。根据推导出的力学模型，计算出了外径107．9mm、钢级为J55的膨胀套管膨胀到直径139．7mm时膨胀芯头拉头处的轴向力为195．94kN。     

蒸汽减压站自控系统的巧设计

蒸汽是石油化工装置中最重要的物料。随着石油化工工业的迅猛发展 ,蒸汽在其中扮演着越来越重要的多重角色。因此 ,对蒸汽系统的平稳控制 ,对石油化工生产装置平稳、高效地运行是至关重要的。传统的蒸汽减压站自控系统基建投资大 ,紧急情况下靠人工手动操作稳定蒸汽压力系统 ,往往造成生产的波动或大面积的停车。针对传统蒸汽减压站自控系统的弱点 ,提出蒸汽减压站自控系统的优化设计方案 ,该方案得以在大型生产装置成功应用。新方案不但节省了大量的基建投资 ,而且取得了良好的生产效益     

长距离曲线顶管在杭州河坊街工程中的应用

对杭州市重点工程—杭州河坊街长距离曲线顶管进行了总结和介绍 ,可为同类工程借鉴和参考     

水喷雾灭火系统在电信枢纽工程燃气锅炉房的应用

分析了燃气锅炉的火灾危险性和水喷雾用于燃气锅炉消防的灭火机理,提出了水喷雾灭火系统的设计参数的选择、系统的控制方法以及在设计中可能涉及到的问题和注意事项,并结合工程实例进行了探讨。