Machine learning algorithm selection for windage alteration fault diagnosis of mine ventilation system

Machine learning algorithms have been widely used in mine fault diagnosis. The correct selection of the suitable algorithms is the key factor that affects the fault diagnosis. However, the impact of machine learning algorithms on the prediction performance of mine fault diagnosis models has not been fully evaluated. In this study, the windage alteration faults (WAFs) diagnosis models, which are based on K-nearest neighbor algorithm (KNN), multi-layer perceptron (MLP), support vector machine (SVM), and decision tree (DT), are constructed. Furthermore, the applicability of these four algorithms in the WAFs diagnosis is explored by a T-type ventilation network simulation experiment and the field empirical application research of Jinchuan No. 2 mine. The accuracy of the fault location diagnosis for the four models in both networks was 100%. In the simulation experiment, the mean absolute percentage error (MAPE) between the predicted values and the real values of the fault volume of the four models was 0.59%, 97.26%, 123.61%, and 8.78%, respectively. The MAPE for the field empirical application was 3.94%, 52.40%, 25.25%, and 7.15%, respectively. The results of the comprehensive evaluation of the fault location and fault volume diagnosis tests showed that the KNN model is the most suitable algorithm for the WAFs diagnosis, whereas the prediction performance of the DT model was the second-best. This study realizes the intelligent diagnosis of WAFs, and provides technical support for the realization of intelligent ventilation.     

A simulation study of reduction kinetics for sponge iron production in a rotary hearth furnace

ABSTRACT

A mathematical model has been developed by coupling genetic algorithm (GA) with heat and material balance equations to estimate rate parameters and solid-phase evolution related to the reduction of iron ore-coal composite pellets in a multi-layer bed Rotary hearth Furnace (RHF). The present process involves treating iron ore-coal composite pellets in a crucible over the hearth in RHF. The various solid phases evolved at the end of the process are estimated experimentally, and are used in conjunction with the model to estimate rate parameters. The predicted apparent activation energy for the wustite reduction step is found to be lower than those of the reduction of higher oxides. The thermal efficiency is found to decrease significantly with an increase in the carbon content of the pellet. Thermal efficiency was also found to increase mildly up to three layers. Multilayer bed remains as a potential design parameter to increase thermal efficiency.     

A knowledge construction methodology to automate case-based learning using clinical documents

The case-based learning (CBL) approach has gained attention in medical education as an alternative to traditional learning methodology. However, current CBL systems do not facilitate and provide computer-based domain knowledge to medical students for solving real-world clinical cases during CBL practice. To automate CBL, clinical documents are beneficial for constructing domain knowledge. In the literature, most systems and methodologies require a knowledge engineer to construct machine-readable knowledge. Keeping in view these facts, we present a knowledge construction methodology (KCM-CD) to construct domain knowledge ontology (i.e., structured declarative knowledge) from unstructured text in a systematic way using artificial intelligence techniques, with minimum intervention from a knowledge engineer. To utilize the strength of humans and computers, and to realize the KCM-CD methodology, an interactive case-based learning system(iCBLS) was developed. Finally, the developed ontological model was evaluated to evaluate the quality of domain knowledge in terms of coherence measure. The results showed that the overall domain model has positive coherence values, indicating that all words in each branch of the domain ontology are correlated with each other and the quality of the developed model is acceptable.     

基于ABAQUS的显式动力学分析方法研究

显式动力学(The Explicit Dynamic)是针对隐式求解器的一个补充,其分析方法对于求解广泛、各类非线性结构力学问题是一个非常有效的工具,显式方法中的单个增量步取决于模型的最高固有频率,与持续时间、载荷类型无关。ABAQUS/Explicit主要用于碰撞、接触以及失效分析。探讨了ABAQUS显式动力学的基本理论、求解的问题,对显示动力学分析方法中的求解算法、稳定时间极限和能量平衡问题进行研究,给出了显示动力学分析的一般性分析方法。通过案例验证了该方法的可行性,应用该方法可有效解决实际工业生产中的碰撞问题、复杂的接触问题以及复杂的后屈曲问题,可为显式动力学分析方法应用于工程实践奠定理论与方法基础。     

A modified cross-correlation algorithm for PIV image processing of particle-fluid two-phase flow

PIV (Particle Image Velocimetry) technique for flow field measurement has achieved popular self-identify through over ten years development, and its application range is becoming wider and wider. PIV post-processing techniques have a great influence on the success of particle-fluid two-phase flow field measurement and thus become a hot and difficult topic. In the present study, a Phase Respective Identification Algorithm (PRIA) is introduced to separate low-density solid particles or bubbles and high-density tracer particles from the PIV image of particle-fluid two-phase flow. PTV (Particle Tracking Velocimetry) technique is employed to calculate the velocity fields of low-density solid particles or bubbles. For the velocity fields of high-density solid particles or bubble phase and continuous phase traced by high-density smaller particles, based on the thought of wavelet transform and multi-resolution analysis and the theory of cross-correlation of image, a delaminated processing algorithm (MCCWM) is presented to conquer the limitation of conventional Fourier transform. The algorithm is firstly testified on synthetic two-phase flows, such as uniform steady flow, shearing flow and rotating flow, and the computational results from the simulated particle images are in reasonable agreement with the given simulated data. The algorithm is then applied to images of actual bubble-liquid two-phase flow and jet flow, and the results also confirmed that the algorithm proposed in the present study has good performance and reliability for post-processing PIV images of particle-fluid two-phase flow.     

Mímir: An open-source semantic search framework for interactive information seeking and discovery

Semantic search is gradually establishing itself as the next generation search paradigm, which meets better a wider range of information needs, as compared to traditional full-text search. At the same time, however, expanding search towards document structure and external, formal knowledge sources (e.g. LOD resources) remains challenging, especially with respect to efficiency, usability, and scalability.This paper introduces Mímir—an open-source framework for integrated semantic search over text, document structure, linguistic annotations, and formal semantic knowledge. Mímir supports complex structural queries, as well as basic keyword search.Exploratory search and sense-making are supported through information visualisation interfaces, such as co-occurrence matrices and term clouds. There is also an interactive retrieval interface, where users can save, refine, and analyse the results of a semantic search over time. The more well-studied precision-oriented information seeking searches are also well supported.The generic and extensible nature of the Mímir platform is demonstrated through three different, real-world applications, one of which required indexing and search over tens of millions of documents and fifty to hundred times as many semantic annotations. Scaling up to over 150 million documents was also accomplished, via index federation and cloud-based deployment.     

Service composition for generic service graphs

Service composition is a promising approach to multimedia service provisioning, due to its ability to dynamically produce new multimedia content, and to customize the content for individual client devices. Previous research work has addressed various aspects of service composition such as composibility, QoS-awareness, and load balancing. However, most of the work has focused on applications where data flow from a single source is processed by intermediate services and then delivered to a single destination. In this paper, we address the service composition problem for multimedia services that can be modeled as directed acyclic graphs (DAGs). We formally define the problem and prove its NP hardness. We also design a heuristic algorithm to solve the problem. Our simulation results show that the algorithm is effective at finding low-cost composition solutions, and can trade off computation overhead for better results. When compared with a hop-by-hop approach for service composition, our algorithm can find composition solutions that aress 10% smaller in cost, even when the hop-by-hop approach uses exhaustive searches.     

HART通信协议在汽油机速度测量和监控方面的应用

首先介绍了HART通信协议及他的优点，然后介绍了HART通信协议在汽油机测速方面的软件实现。该软件主要采用目前流行的VB编程语言。可设计出界面友好、功能强大的测量和监控软件。     

基于模式理论光栅椭偏参数反演的数值模拟

将一种广泛用于求解系统优化问题的方法——正单纯形法，求解光栅的椭偏方程。首先，利用求解光栅的傅立叶模式理论对TE和TM波的复反射系数进行求解。然后计算出其相应的椭偏参数(△，Ψ)，并在该值的基础上加入不同偏差的随机高斯噪声，将加入噪声后的值(△m，Ψm)作为模拟测量值。最后使用优化算法进行反演。通过对几种常用面形光栅椭偏参数的数值模拟，一方面表明傅立叶模式理论计算光栅的椭偏参数不仅精度高。而且速度快；另一方面表明利用正单纯形法得到的光栅参数值很接近于正演时假设的参数值，从而从理论上证明了利用椭偏法测量光栅各种光学参数的可行性。