Application of artificial neural network method to predict the breakage properties of PGE bearing chromite ore

In the present investigation, systematic grinding experiments were conducted in a laboratory ball mill to determine the breakage properties of low-grade PGE bearing chromite ore. The population balance modeling technique was used to study the breakage parameters such as primary breakage distribution (B_{i, j}) and the specific rates of breakage (S_i). The breakage and selection function values were determined for six feed sizes. The results stated that the breakage follows the first-order grinding kinetics for all the feed sizes. It was observed that the coarser feed sizes exhibit higher selection function values than the finer feed size. Further, an artificial neural network was used to predict breakage characteristics of low-grade PGE bearing chromite ore. The predicted results obtained from the neural network modeling were close to the experimental results with a correlation of determination R² = 0.99 for both product size and selection function.     

矿用直线振动筛结构故障分析

针对煤矿选煤厂直线振动筛工作过程中出现的结构故障问题,采用有限元仿真与现场测试结合的方法对振动筛出现故障的原因进行了分析研究。介绍了振动筛的主要结构及常见故障,并以某矿选煤厂发生大梁断裂的振动筛为例,对该振动筛进行三维建模和有限元模态分析,分析结果表明:随着模态阶次的增加,振型的变化逐渐由移动转为结构本身的扭曲变形。在该振动筛空载工作状态下,选用本质安全型便携式测振记录仪进行振动测试并处理测试信号,得到该振动筛的工作频率。结合模态分析结果和实际测试结果,判断出空载时频繁运行振动筛是造成其大梁断裂的主要原因。根据故障原因给出维护建议:应当尽量避免振动筛在空载或物料较少的状态下长时间运行;在振动筛投入使用前,应预先了解振动筛的工作状态及可能存在的薄弱环节,尽可能避免结构故障,保证振动筛可靠运行。     

The control of paracetamol particle size and surface morphology through crystallisation in a spray dryer

The parameters governing the crystallisation of paracetamol using various conventional techniques has been extensively studied, however the factors influencing the drug crystallisation using spray drying is not as well understood. The aim of this work was to investigate the crystallisation of an active pharmaceutical ingredient through evaporative crystallisation using a spray dryer to study the physicochemical properties of the drug and to use semi-empirical equations to gain insight into the morphology and particle size of the dried powder. Paracetamol solutions were spray dried at various inlet temperatures ranging from 60 °C to 120 °C and also from a series of inlet feed solvent compositions ranging from 50/50% v/v ethanol/water to 100% ethanol and solid-state characterisation was done. The size and morphology of the dried materials were altered with a change in spray drying parameters, with an increase in inlet temperature leading to an increase in particle Sauter mean diameter (from 3.0 to 4.4 µm) and a decrease in the particle size with an increase in ethanol concentration in the feed (from 4.6 to 4.4 µm) as a result of changes in particle density and atomised droplet size. The morphology of the dried particles consisted of agglomerates of individual crystallites bound together into larger semi-spherical agglomerates with a higher tendency for particles having crystalline ridges to form at higher ethanol concentrations of the feed.     

Dialogic weaving: a favorable tension between design and craft

Focusing on a process where a designer embeds herself in craftspeople’s workshops with the intention of ‘learning from inside’ and ‘making together’; this paper proposes pathways for considering collaboration between designers and craftspeople via digital fabrication and weaving. The tension of forces that make weaving possible, act as an analogy for this collaboration as well as providing the title of the project as ‘One Over, One Under’. The project proposes a mode of working and a spectrum of outcomes where the designer has a first-hand experience of production techniques, engages in a serious and continuous dialogue through making, and develops an intervention that also brings forth her own skill set (introducing digital fabrication and structural variations), thus transforming the conventions and boundaries between established roles and manufacturing techniques. An experiment that resulted in a series of objects considering both the technologies of production and the input of the designer, this process not only increases the potentials that crafts hold for the field of design, but it also offers possibilities of collaboration and a further articulation of the design act.     

Input-to-state learning of recurrent neural networks with delay and disturbance

This article deals with the issue of input-to-state stabilization for recurrent neural networks with delay and external disturbance. The goal is to design a suitable weight-learning law to make the considered network input-to-state stable with a predefined -gain. Based on the solution of linear matrix inequalities, two schemes for the desired learning law are presented via using decay-rate-dependent and decay-rate-independent Lyapunov functionals, respectively. It is shown that, in the absence of external disturbance, the proposed learning law also guarantees the exponential stability of the network. To illustrate the applicability of the present weight-learning law, two numerical examples with simulations are given.     

On monitoring the process mean of autocorrelated observations with measurement errors using the w-of-w runs-rules scheme

Runs-rules have been widely used since the 1950s in industrial and nonindustrial process monitoring applications to improve the performance of basic and other traditional monitoring schemes. However, none of the studies on runs-rules have accounted for a process with a combined effect of measurement errors and autocorrelation. Hence, in this paper, the use of the w-of-w runs-rules to improve the performance of the Shewhart $\overline{X}$ scheme using an additive model with a constant variance and a first-order autoregressive model is proposed. To reduce the combined negative effect of measurement errors and autocorrelation, we implement a sampling strategy based on rational subgroups in which (a) multiple measurements per item are taken (instead of a standard single measurement) and (b) non-neighboring observations are gathered. Moreover, the latter sampling strategy is incorporated into the values of probability elements of a Markov chain matrix which is used to derive some closed-form expressions for the zero- and steady-state run-length distribution. The main finding of this study is that, with respect to some overall performance measures, the proposed scheme outperforms the existing Shewhart $\overline{X}$ scheme by a significant margin. A real-life example is used to illustrate the practical implementation of the proposed scheme.     

基于物联网的智能化窨井管理系统的设计

通信管道承载着户外传输网络,是通信网络的生命管道。管道规模伴随着城市化进程快速成倍增长,但管道管理还处于传统的依赖人工专项梳理、专项盯防的模式。随着智慧城市建设的加速推进,采用“物理加锁+物联网管理平台”的创新管理方式,结合物联网技术和大数据技术,实现对流程、人员、设备的全方位管理。     

Hybrid-triggered fault detection filter design for networked Takagi–Sugeno fuzzy systems subject to persistent heavy noise disturbance

In the network environment, the single time-triggered scheme wastes limited bandwidth resources due to all the sampled data are transmitted to the networks, and the single event-triggered scheme may increase system error because of ignoring factors such as changes in network utilization. To reduce the design conservatism, this paper is concerned with the hybrid-triggered L₁ fault detection filter design for a class of nonlinear networked control systems (NCSs) described by Takagi–Sugeno (T-S) fuzzy model. Taking the effects of time-triggered scheme and event-triggered scheme into consideration simultaneously, we construct a fuzzy fault detection system. New results on stability and L₁ performance are proposed for fuzzy fault detection system by exploiting the Lyapunov–Krasovskii functional and by means of the integral inequality method. Specially, attention is focused on the design of fault detection filter that guarantees a prescribed L₁ noise attenuation level . Finally, two examples are presented to demonstrate the effectiveness of the proposed method.