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中文译文光电触觉传感器在采煤机设计中的应用 用于在地下煤炭开采中辨认岩石表面摘要 在传统采矿业中自动化的应用并没有很成功。很多时候自动化的益处被认为是解决了许多采矿业所面对的诸如增加安全性和提高生产率等各种问题。这些应用的引入在许多情况下并没有充分考虑采矿环境。因此，有效的技术往往在还没有机会展示其真正的能力之前被贴上了失败的标签。因此，我们认为，要在采矿系统或子系统中有效的发展自动化技术，需要投入最少的操作者。这可以从几个方面来实现。首先，通过缩小自动化采矿系统中必须操作的域名，这样不太复杂的自动化技术可以得到强劲的应用。或者，通过更精密的控制技术要求，可以对由于非结构化的地质多样性和不可预测的环境所导致的采矿操作环境的不明情况作出灵活的反应。采煤机的自动化在光电触觉传感器的协助下，应使机器能检测顶部和底部的煤岩界面。在本文中应用到一种尝试，与现有采煤机联合，当采煤机在地下煤矿的长壁工作面工作时，一个新开发的触觉传感器用来检测不同类型的材料。所推荐的触觉传感器能够辨认其表面纹理发现不同类型的材料（煤，石灰石，砂岩，壳）。关键词：采煤机，煤炭，岩石/煤界面，自动化，光电触觉传感器.1.引言与问题导向采煤机用于在澳大利亚的地下长壁采煤工作面，包括作为主要单元的（图1），一个驱动旋转切割头（滚筒），摇臂，行走部分（装甲链式输送机- AFC）控制部分，机身，鼠笼异步电机，减速器。 5米长的高扭矩旋转切割头能够截割煤层高达5米的煤壁。工作环境嘈杂，尘土飞扬，有潜在的爆炸性。使长壁采煤工作面生产更安全，更高效已成为澳大利亚煤炭协会研究计划中一个长期运行的CSIRO资助项目的主题，其中也提出了设计新的定位技术和指导长壁采煤的切割设备的新技术。澳大利亚长壁采矿作业的停机时间的统计数字显示，10类机械相关故障停机时间占百分之五十1。其中主要的是面对对齐，域控制，信息系统和子系统之间的沟通。一个完全自动化的采煤机必须包括在内和解决这些问题。目前，采煤机自动化控制，主要是指水平控制，即：如何控制自动化采煤机的截割水平，使其始终停留在煤层和削减厚度均匀。为了实现这一目标，采煤机必须能够辨认在顶板和底板的煤岩界面。此外，一旦它确定了煤岩界面的水平位置，必须立即调整其切割滚筒位置。除了随身携带的微处理器，存储和分析数据和命令的问题，一个自动化采煤机系统还需要一个煤岩界面检测系统和倾角用来测量和调整滚筒高度和机身间距。伽玛射线煤层厚度测量系统已经用于检测煤岩界面2。伽马辐射是在页岩高，砂岩低，几乎没有石灰石，煤炭几乎检测不到3。自然伽玛射线背景（核NGB）传感器用于煤矿开采工作面的煤岩界面检测。许多煤岩界面探测器已经开发和测试，但他们都是在实验阶段。这些都是基于吸引力，岩石振动和摄像机4原则。吸引力测量系统的选择决定所确定的位切削力。该系统是根据不同的煤所需的切削力降低煤层中的直接顶的原则。通过随身携带的计算机处理吸引力的变化，可以识别煤岩界面。为了区分煤岩界面，振动评估系统利用计算机分析切割岩石和煤时的振动特性差异的原则。该系统包括一个或多个振动传感器并尽可能靠近切割滚筒安装5。一台采煤机需要两个操作者，一个负责切割滚筒，另一个负责尾部滚筒。他们的目的是控制滚筒的切缝在任何时候保持同一水平。他们通常的做法是通过煤层中一个或多个连续的采矿夹层来引导他们。这适用于大多数情况下，良好的领导滚筒，最大限度地减少顶煤。但是，它对尾部滚筒不起作用因为底板通常是覆盖着底煤和装甲链式输送机（AFC）。因此，采煤机自动化的第一步是控制滚筒的切割水平。一台伽玛射线传感器就是专为这项任务。在采煤机切割之后，距离预定的采煤机背后的掩护梁将必须提前推进。为了完成这项任务，在任何时候必须知道采煤机的位置，这个信息要传达给掩护梁采取推进。这项任务是通过红外传感器或接近传感器完成的。 全部自动化采煤机系统需要以下传感器：一台红外传感器或里程计以在任何时候确定采煤机位置。一台伽玛射线探测器或光电触觉传感器用以确定煤岩界面。两台量坡仪用以控制摇臂的高度和滚筒的切割高度。量坡仪用以确定和控制间距（在采煤方向）和采煤机的启动（在工作面方向）。具有电液控制系统的掩护梁。一种长壁采煤机的自动控制系统原理如图2中显示。该系统6有三个独立的计算机，如一个负责屏幕管理控制，掩护梁与掩护梁界面的中央，以及一个负责采煤机传感器的数据处理计算机和控制采煤机操作站显示器表面的计算机。现代长壁开采采用先进的电力支持（或掩护梁支撑）。它不仅支撑了顶板，推送装甲链式输送机（AFC），并推进本身，而且还为所有相关的采矿活动提供了安全的环境。该自动化采煤机可以用若干种模式操作：速度控制，煤岩界面跟踪，顶板周期削减，固定高度顶板切断，门式断路器。例如，在顶板煤周期削减模式下，顶煤厚度要剩余多少是首要决定的。在最初的运行中，例如从头部到尾部的进程中，摇臂位置传感器（或测斜仪）将调整切割水平，伽玛射线传感器在一个固定的时间间隔读取信息。此信息存储在计算机，引导摇臂位置传感器在从尾至头的下一次进程。顶板削减的可以在命令下被替代更换，如果系统确定需要变化。该机器的控制系统已显示1，它可以在恶劣的条件下进行，成功地通过煤层（图3）在明显的扰动区开采矿产。长壁开采系统1，11包括以下子系统：采煤机，掩护梁，装甲链式输送机，装载机，带式输送机。每个子系统由一个或多个组件构成。对于一个长壁开采系统连续工作，所有子系统及其部件，必须综合或自动化，以激发连续开采系统的全部潜力。今天，大多数子系统部分或完全自动化。为了实现自动化，子系统和子系统组件必须能够自由地相互之间保持沟通。主要包括数据通信识别和将要采取的行动的证实。为了落实子系统元件及子系统集成，组件和子系统之间必须建立通讯联系。通信需要接触和/或提供的监测数据在子系统组件或子系统专用计算机。通信系统的在网络中的运行，很像常用的电子邮件网络。每个子系统都有自己的电脑和可以自行运作，即使网络出现故障。如果网络中断，子系统之间的通信被中断。从表面上看，主机系统包括服务器，网络控制器和处理器以及显示器。也有个人电脑，工作站和笔记本电脑连接到网络。在长壁开采系统中，采煤机是硬件，它的数据是通过现代调制解调器中心传输。采煤机也可以通过无线系统发射器如红外线接收器与掩护梁联系在一起。2.物体的表面纹理物体表面纹理，一般来说，可以通过表面特征和表面粗糙度或不规则波纹度7来表示，如图5所示。虽然看起来，在任何情况下任何表面是完全光滑平面，但是每面总是有一些粗糙的纹理排序。对于加工或铸造，或以任何其他产品的过程，都会产生一个特定的表面，这是一个特定的流程和工具的行动造成的结果/或程序和科学现象在表面上留下的后果，造成表面波纹度和粗糙度。其他产品获得表面特征由于各种自然现象。如石头与煤的表面性质，取决于由于火山喷发所产生的巨大压力造成的结果。据推测，煤与石头的表面纹理也与晶体一样受其内部晶体结构的影响。表面粗糙度或波纹的特点如下几何图形的高峰和低谷（图4和5）。用触觉传感器或手写笔，表面纹理的变化可以评估，如上升角（），波峰到波谷的高度（h），一个波峰到下一个波峰的距离（f）。一个触觉传感器触可以指定一个表面的几何参数。3.触觉传感器在采煤机中的应用对象可以感觉到通过视觉，听觉，嗅觉或触摸，通过触摸屏可接触和非接触式感应7。知道了某些物体表面纹理性质，为机器或智能系统，创造一个近似的物体识别的想法。每一个对象，如煤炭，水泥，瓷砖，地毯，地毡，路面或墙壁，石头或音色，一个螺栓或一个加工产品或铸造产品，总之，每一个对象的性质包括其表面结构，相位和纹理的完整性。因此传感表面纹理和结构可以允许对象的部分承认，在某些情况下的充分肯定是可能的。在这个特定的工作中触觉式传感器用于检测表面纹理和承认它。对于帕特森和内维尔设计的较成功的人造皮肤类型触觉传感器8称为诱导振动物体表面的评估触摸传感器（IVTS）。目前，作者正在探索触觉传感器功能，利用在地下采煤机中的应用，感觉和区分煤和岩石表面。一个光电触觉传感器通过一系列合理的实验7，9 被证明，它具有区分和识别能力，通过触摸不同的非流体物体表面纹理。显然，石头和煤的表面纹理和表面完整性等性质不同。文献调查表明，一台手指状触觉传感器是基于W. Lo, Y. Shen, and Y. Liu (2001)提供的光学技术，它已被应用10来捕捉一个对象被接触的面积。如图6所示，手指状的光学触觉传感器包括一个透明和灵活的光纤波导由橡胶弹性膜，一个有机玻璃的支持下，一组镜头，光纤电缆形象，微光源，覆盖1 CCD器件。根据作者所写，光源被安置在管道，以避免光线散射。光注入光学波导。如果没有对象接触与传感器，光线反射回内橡胶电缆指南内，没有光线传递到镜头。 为了煤矿井下采煤机设备的进一步自动化，我们正尝试使用选择触觉传感器。4.光电触觉传感器该光电触觉传感器系统可用于评估确认特定岩石和煤的表面纹理。该传感器的光纤技术 7，其设计原则和工作原理如图8所示。它是由一个全镀银镜，触觉针，一个发光二极管（LED小片），一个光电晶体管，两条光纤电缆，指纹笔尖颠簸橡胶弹性体组成。如7所述，全镀银镜垂直对触觉针内端安装硬性。在另一端的触觉引入了弹性橡胶体，它类似于一个人的手。指纹的凸起，仿佛是铰接到身体碰撞的橡胶中的一部分，它使各地的假想旋转铰链在其偏转关节。一个发光二极管（LED）作为主要光源，用于发射的纤维之一，通过光线光缆。传播的光线穿过光学纤维的载体，作为对 7的解释，在全镀银镜聚焦。一些射线的传播反映的部份立即返回通过二次光学纤维载体。5.实验这是进行了合理的现实生活中的实验工程，以便使发达国家光电触觉传感器可以被用于采煤机的自动化，因为该传感器已被实验承认。对于研究煤和石头表面可以达到类似的结果。现实生活中的一个实验室正在进行一系列试验，并分为三个阶段：分为（一）从实际开采区采集足够数量的石和煤；（二）下面的描述的程序7， 9，以及（三）使用现代计算技术的处理方法开发和辨识（煤或岩石）。所得到的触觉传感器单元处理与软计算技术帮助的结果，可用于工业采煤机的主控制系统接口部分。6.结论 自动化采煤机的应用产生了以下好处： 提高了煤炭回收率和质量因为始终保持在自切割煤层，径流式采煤干净多了。此外，在许多煤层边界煤含有较高的硫含量;留下顶煤将提高产品质量。 加强顶板控制许多煤层直接顶薄弱，一些顶煤必须继续加以保护。自动视野控制可以很容易做到这一点。顶板和底板都非常流畅。支撑可以完全更好的接触顶板和底板，并消除了双方面对面的路线和开采方向的运行。采矿高度也能比较均匀的削减。 触觉传感器可有效地应用于矿山机械自动化系统，可能为采矿业带来的潜在利益。特别是在这篇文章中描述的光电触觉传感器有潜力用于鉴别煤岩界面，识别煤和石头的表面纹理和完整性 Application of Opto-tactile Sensor in Shearer Machine Design to Recognise Rock Surfaces in Underground Coal Mining Ratikanta Sahoo Faculty of Sciences, Engineering by touch can be contact and non-contact sensing 7. Knowing the nature of surface texture of certain object it is possible, for a robot or intelligent systems, to create an approximated idea for recognition of the object. Each and every object such as coals, concrete, tiles, carpet, floor vinyl, road surface or wall, a piece of stone or timbre, a bolt or a pin, machined product or cast product, in a word, every object in nature has its own surface structure, phase, and texture Authorized licensed use limited to: CHINA UNIVERSITY OF MINING AND TECHNOLOGY. Downloaded on May 29,2010 at 07:37:46 UTC from IEEE Xplore. Restrictions apply. integrity. Therefore sensing of surface texture and structure can allow partial recognition of object, in some cases full recognition may be possible. In this particular work tactile type sensor is used to sense surface texture and recognize it. For these purposes the more successful artificial skin type tactile sensor was designed and fabricated by Patterson and Nevill 8 called as induced vibration touch sensor (IVTS) for object surface assessment. Currently the authors are exploring capabilities of tactile sensors to use in design of underground coalmining shearer machines to sense and differentiate coal and rock surfaces. An opto-tactile sensor has reasonably proven by a series of experiments 7, 9 its capabilities to distinguish and recognize surface textures of different non-fluidic objects by touch. Evidently coal surface and stone surfaces are different in nature of surface texture integrity. The experimental procedure for recognition of coal and stone surfaces and distinguishing them according to surface texture integrity is underway. Literature survey shows that, a finger-shaped tactile sensor based on optical technology have been offered by W. Lo, Y. Shen, and Y. Liu (2001) and it has been applied 10 to capture tactile image of the touched area of an object. As shown in Fig. 6, the given finger-shaped optical based tactile sensor is consisted of a transparent and flexible rubber optic wave guide covered by an elastic membrane, an organic glass support, a group of lenses, an optical fiber image cable, micro- light sources, and a CCD device. According to authors, the light sources are accommodated in pipes to avoid scattering of light. The light is injected into the optic wave guide. If no object is in touch with the sensor, the light is reflected internally inside the rubber optic guide and no light rays are passing on to the lenses. Figure 6. Optical based finger-shaped tactile sensor Figure 7. Image of a cross-head screwdriver head touched by the sensor We are attempting to use opt-tactile sensor/s for further automation of shearer machines in underground coalmines. Tactile sensors, involving arrays of force sensing elements are recognized as a principal need for next generation robots 7, and so as for intelligent systems. Potential robotic applications require some form of sensing. IV. AN OPTO-TACTILE SENSOR The opto-tactile sensor system can be used for assessing rock and coal surface textures for recognizing a particular surface texture. The sensor works on the principle of fiber optics technology 7. The design and working principles of the set-up is depicted in Fig. 8. It is consisted of a small piece of full-silvered mirror, a tactile-pin, a light emitting diode (LED), a phototransistor, two pieces of optical fiber cable, flexible rubber body with bumps / fingerprints /nibs. As described in 7, the full-silvered mirror is perpendicularly mounted on the inner end of the tactile pin rigidly. The other end of the tactile is introduced into a bump of the elastic rubber body, which resembles a human hand, and the bumps as fingerprints. As if it is hinged to the middle part of the bump of the rubber body, it allows rotating around the imaginary hinge joint during its deflection. A light-emitting diode (LED), as a primary light source, is used to emit light rays through one of the fiber optic cables. Object l = Pitch distance between two consecutive peaks of surface texture; h = Height of a peak, from the valley, the stylus is in contact at some stage; = Angle of rise of a peak from the valley (Fig. 5). Considering an object surface is a plane one, there is no deflection of the tactile bump. Therefore the intensity of the propagated light ray achieves the highest value, and let it be denoted by . That means if max I0,= then 0,lh= 0,and 0=. Where, = of inclination of the ta (Fig. s rig angle ctile bump 6). The tle iidly and perpendicularly attached to the m acti erirror. Th efore, it is evident that, =. Now considering a textured surface as depicted in Fig. 6, where there is at least some deflection of the tactile bump, which changes its angle dependinthg on e surface texture geometry. We can assume, in any case the relation between and is expressed as follows: = Analyzing the geometry of a single peak and corresponding valley as shown in Fig. 9, we can write, /2 tan 2hh = (2) There ll fore, max tan 2 l I h = (3) Therefore, for general casesxpress we can e tanand 2 Taking into consideration a coefficient e l (4) II h qn. (6) can be rewritten as follows: 2 IC h = ( Or l 5) 2hI C l = (6) Where, is the coefficient ontensity for the system. Using any one of these two equations (5) and (6) it is tohelp of he developed mechanism. It is proposed to carry out a reasonable amount of real life experimental works so that the developed opto-tactile sensor can be usehines, since the e that similar result for researching coal and Cf i possible assess surface texture of any object with the t V. EXPERIMENT d for automation of shearer mac sensor has been experimented 9 for recognizing surfaces of objects like cast iron surface, tabletop, and floor carpet. The results of the experiments have been demonstrated and can be revisited (Fig. 10). The laboratory experiments which have been successful for surfaces of cast iron, floor carpet and table top, is an advantageous exampl stone surfaces can be achieved. A series of laboratory real life experiments is underway and divided into three stages: (a) adequate number of stone and coal samples collection from the real mining areas, (b) following the procedure as described in 7, 9, and (c) using modern soft computing technology Authorized licensed use limited to: CHINA UNIVERSITY OF MINING AND TECHNOLOGY. Downloaded on May 29,2010 at 07:37:46 UTC from IEEE Xplore. Restrictions apply. processing method development for object (coals or rocks) recognition. 0102030405060708090100 800 810 820 830 840 850 860 870 Time (s) (voltage*1023)/5 table top carpet cast iron 4 Figure 10. Surface texture evaluation by opto-tactile sensor The obtained results processed by the tactile sensor unit with the help of soft computing technique can be used in on stem of the shearer machine. shearers has produced t llowing benefits: Increased coal recoverye cutting always sta coal will enhance product quality. upp can actile sensors can be effectively used in mining machinery automation systems which may bring potential benefit for the mining industries. In particular the opto-tactile sen elays, Australia longwalls, a technical report, Australia. 2003. 43pages (unpublished). 2 Mowrey, G. L., Hori key to automation, Coal, T sor described in this article has potential to use it for distinguishing coal-rock interface recognizing coal and stone surface textures and integrity. REFERENCES 1 Hookham, M., Study identifies d zon control holds Australia Part I, December 1991, pp. 44-48, Part II, January 1992, pp. 47-51. 3 Nelson, M. G., Simulation of boundary coal thickness sensor, PhD Dissertation, Department of Mining Engineering, West Virginia University, 1989, pp. 153 pages. Kelly, M., Outcome of the landmark longwall automation project with reference to ground control. Proceedings of 24th International Conference on Ground Control in Miningh, West Virginia, August 2005, pp. 66-73. 5 Kurdo, H., Nishimura, K., and Esaki, M., Integrated automation of longwall mining system, Coal Power 87, The AusIMM Annual Conference, Newcastle, Australia, 1987. Pp. 143-152. trol 6 Bessinger, S. L., A review of CONSOL longwall innovation, Proceedings of longwall USA Conference and Exhibits, Pittsburgh, PA, June 1996, 16 pages. industrial shearer machines interfacing with the main c sy CONCLUSION Application of automated 7 M. A. Mazid, R. Andrew Russell, A Robotic Opto-tactile Sensor for Assessing Object Surface Texture, Proceedings, 2006 IEEE International Conference on Robotics, Automation and Mechatronics (RAM 2006). Bangkohe k. 2006. Pp. 387-391. 8 Robert W. Patterson, Gale E. Nevill, Jr., The induced vibration touch sensor a new dynamic touch sensing concept. Robotica, vol. 4. 1985. pp. 27-31. fo and quality sinc ys in-seam, run-of-mine coal is much cleaner. In addition, the boundary coal in many coal seams contains higher sulphur content; leaving top 9 M. A. Mazid, M. Fakhrul Islam Grasping Force Estimation Recognizing Object Slippage by Tactile Da