矿井提升绞车传动装置设计【JK型单绳缠绕式矿井提升机】
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河南理工大学万方科技学院本科毕业论文附录:外文资料与中文翻译外文资料:Research on Detection Device for Broken Wires of Coal Mine-Hoist CableWANG Hong-yao1, HUA Gang1, TIAN Jie21School of Information and Electrical Engineering, China University of Mining & Technology, Xuzhou, Jiangsu 221008, China2School of Mechanical Electronic and Information Engineering, China University of Mining & Technology, Beijing 100083, ChinaAbstract: In order to overcome the flaws of present domestic devices for detecting faulty wires such as low precision,low sensitivity and instability, a new instrument for detecting and processing the signal of flux leakage caused by broken wires of coal mine-hoist cables is investigated. The principle of strong magnetic detection was adopted in the equipment. Wires were magnetized by a pre-magnetic head to reach magnetization saturation. Our special feature is that the number of flux-gates installed along the circle direction on the wall of sensors is twice as large as the number of strands in the wire cable. Neighboring components are connected in series and the interference on the surface of the wire cable, produced by leakage from the flux field of the wire strands, is efficiently filtered. The sampled signal sequence produced by broken wires, which is characterized by a three-dimensional distribution of the flux-leakage field on the surface of the wire cable, can be dimensionally condensed and characteristically extracted. A model of a BP neural network is built and the algorithm of the BP neural network is then used to identify the number of broken wires quantitatively. In our research, we used a 637+FC, 24 mm wire cable as our test object. Randomly several wires were artificially broken and damaged to different degrees. The experiments were carried out 100 times to obtain data for 100 groups from our samples. The data were then entered into the BP neural network and trained. The network was then used to identify a total 16 wires, broken at five different locations. The test data proves that our new device can enhance the precision in detecting broken and damaged wires.Key words: wire cable; broken wire; signal processing; detection deviceCLC number: TB 421 IntroductionIt is well-known that coal mine-hoist cables are an important part in coal mine-hoists or transportation systems. Wires are, in fact, subjected to breakage due to wear, corrosion and fatigue. The extent of damage and the carrying capacity of wires are directly related to the safety of equipment and staff. At present, there are many detection devices for broken steel cables manufactured in China, but most devices do not meet the conditions ideally required in practice. The reasons are largely the complex structure of wires, bad working conditions, the multiplicity and uncertainty of broken wires. It is therefore quite difficult to detect signs of broken wires as well as to analyze and process detected signal of broken wires in cables 1.A new instrument for broken wires detection and procession of coal mine-hoist cables was investigatedfor this paper. With the special structure of a detection transducer, the interfering signal from the leakage field of wire twists can be filtered efficiently. After the extraction of dimensional contraction and characteristic values of multi-ways signals, a quantitative BP neural network recognition for broken wires in steel cables was realized. The test results are presented.2 Basic Structural Principle of the On-Line Detection Instrument for Coal Mine-Hoist CableThe structural principle of the on-line detection device for wire cables studied by us is shown in Fig. 1.The detection transducer is composed of two semicircle cylindrical structures which can be opened or closed. The magnetic sensing unit is a fluxgate unit made of a single magnetic core and is single-winding. Some magnetic sensing units are evenly arranged around the inner wall of the transducer, the number of which is twice as many as the number of the wire strands in the inspected cable. As well, two neighboring units are connected in series to a detection channel.Consequently, the number of detection channels of the detection instrument is equal to the number of wire strands in the cable.Fig. 1 Structural principle of detection instrument for broken wires in coal mine-hoist cables.After being filtered and reshaped, the detection signal from each channel is sent to the signal processing unit. The analog detection signal is converted into adiscrete dimensional sequence of sampling values by multi-channel A/D conversion, followed by a characteristic extraction, a BP neural network recognition and the output of the result. When viewed separately, the leakage field signal detected by each single fluxgate unit is the leakage field intensity in the steel cable where the corresponding fluxgate units are located. That is, the outputsignal Zjk of any jth test unit is:Where FC is the structural parameter of the fluxgate, the width of the drive square-wave, s the saturated magneto-conductivity rate, B c, j the magneticinduction intensity of the leakage field produced by broken wires, Br, j the magnetic induction intensity of the leakage field produced by wire cable twists, Zf j the signal value of broken wires and Z r, j the value of the interference signal produced by wire cable twists.After , F C ,a , us , Fare assured, F is a constant.After the wire cables are deeply magnetized, the numerical value of sis very small. As a result, the value of c, j is larger and there is no need to magnify and process the detection signal again. When the sensor is operating along wire cables at a specified speed, the signals detected by each of the magnetic fluxgate units can effectively show the three-dimensional distribution status of magnetic flux leakage, generated at the surface of wire cables24.3 Filtration of the Wavelike Oscillation Interference Signal Produced by Cable Wire TwistsThe signal of broken wires from wire cables obtained by a single fluxgate detection unit of the transducer (formula (1) contains all kinds of interfering signals. The effect of the wavelike oscillation magnetic flux leakage B r, j due to the special structure of the steel cables is largest, which directly affects the detection of broken or damaged wires, especially in coal mine-hoist cables. We should consider the possibility of filtering the interference signals. In formula (1), the interference signal r, j caused by a wavelike oscillation shows up as periodic variation. This kind of wavelike oscillation interferencesignal can be regarded approximately as a sine wave,as shown in Fig. 2.Fig. 2 Wavelike oscillation interference signalproduced by the cable twistOver the length direction of wire cables, its variation period T is a Lay length of cable wire strands. At the circle direction of the wire cable, its variation period is the reciprocal of the number of outer wire strands of the circle length of the wire cable. Therefore, the wavelike oscillation interference signal of the jth detection channel can be expresse d as: jWhere a is the Direct Current Component of the wavelike oscillation signal, m the Alternating Current Component magnitude of the wavelike oscillartion signal, T represents the value of periods, y is the position of the detection unit, starting from the initial spot, j the initial phase of the wavelike oscillation signal, N the number of wire strands of the steel cable, and is the number of detection units. cObviously when c , i.e., when the number of detection units doubles the number of outer strands of the wire cable, the wavelike oscillation signal contained in the leakage magnetic field signal inspected by any two neighboring detection units is in a reversal phase. Therefore, when the neighboring detection units along the inner wall of the cylinder of the transducer structure are connected forward into a test channel in series two by two, it is equivalent to adding the (j+1)th test channel signal to the jth test channel signal. Thus the strand peak value of the wavelike oscillation signal compensates for the strand value for the moment. That is, at this moment, the only remaining wavelike oscillation signal is the Direct Current ComponenAt this moment, the magnetic field signal of leakage from any of the inspection channels made up of the fluxgate array should be:of this formula can be eliminated when the zero detection position is adjusted. Therefore, we considered that the wavelike oscillation interference signal of cable wires is filtered by formula (4). After this pretreatment, each leakage from broken wires, shown by magnetic field signals from the transducer, becomes a channel sample value by A/D conversion, as shown in Fig. 3.Fig. 3 Multi-channel sampling value of broken wiresignals from wire cables4 Extraction of Characteristic Value of Signals from Broken WiresAs is shown in Fig. 3, the N-channel inspection signals from the transducer becomes its sampling sequence by A/D conversion. If the number of samples of the signals of broken wires is K, the sequence of broken wire sample signals of the jth channel can be expressed as a row vector with K elements.The N-channel signal sequence will make up a N-dimensional series vector group of broken wiresignals:At this moment, Z is a characteristic matrix of broken wires and it contains all the information on the status of the broken wires. NK Given the analysis of repeated experiments, the width of the diffused leakage from the magnetic fieldon the surface of wire cables created by broken wires is not larger than 20 mm. When the speed of the inspected wire cable is 3 m/s and the sampling interval is 1.2 mm, the number of samples K is 16 at most. When the number of inspection channels is N=4, Z should be a 416 matrix. If the analysis of the characteristic matrix of broken or damaged wires Z were directly carried out, the analytical process would be very complex and would need to be carried out as acomparison and judgment of the sequential value of each line. So instead, we carried out a reduction in the order processing of formula (6), i.e., we carried out a dimensional contraction. According to a lemma of theoretical linear algebra Z can also be expressed as:Where are arbitrary, independent base vectors. h is the characteristic vector of one-dimensional broken wires expected to be obtained after dimensionalcontraction. So long as the appropriate t is found, h can be derived:According to the L-K transformation principle, when the value of t is the latent vector of the covariance matrix z P of Z, the transformation error is a minimum, i.e., t satisfies the characteristic equationWhere j is the characteristic value of z and I is an identity matrix. Represented by formula (8), the expected characteristic vector h of the broken wires could be obtained via the dimensional contraction. The process of transformation of the dimensional contraction is, in fact, a conversion from a N-dimensional characteristic vector to a one-dimensional vector. P The average of the one-dimensional h sequence is regarded as an eigenvector which represents each state of the N-channel broken wire signals:5 ConclusionsOur detection of broken wires in steel cables is a quantitative inspection method. It will identify not only whether there are broken wires or not, but also will identify the position and number of broken wires. By combining transducer detection technology and computer technology and using advanced signal processing technology, we can effectively enhance theprecision and sensitivity of detection devices to realize the automation and the intellectualization of the detection equipment.中文翻译:对煤矿矿井提升机钢丝绳损毁的钢丝检测装置的研究王宏姚,华岗, 田杰 1信息和电气工程系,中国矿业大学,江苏徐州221008 ,中国2机械电子信息工程系,中国矿业大学,北京100083 ,中国摘要:为了克服目前国内钢丝故障检测设备的缺陷,如低精度,低灵敏度和不稳定,一个新的由煤矿-提升机钢丝绳所造成的漏磁信号的检测和处理装置已经研制出。强磁场检测的原理应用在该设备中,钢丝由前磁头磁化强度达到饱和。我们特别的特点是安装在沿圆圈方向上传感器的内壁数目通量是在钢丝绳中两倍大的数目。周边组件系列地连接在一起并且由于钢丝的通量域所产生的渗漏对钢丝绳的表面干扰有效地被过滤,断丝所产生的采样信号序列,其特点是在线缆的表面上由一个三维分布漏磁场通量,可以立体简明和根据特性提取。BP神经网络的模型已经被建立和BP神经网络的算法是用来定量分析地确定有多少钢丝损毁。在我们的研究,我们用了6 37 +FC, 24毫米线缆作为我们的测试对象。随机人为地以不同程度破坏和损坏数根钢丝,实验共进行了100次,以为来自我们的样本的100组对象获取数据, 然后将数据输进BP神经网络进行处理。然后该网络用来识别共计16钢丝,打破了5个不同地点。测试数据证明我们的新装置可以提高检测破碎和损坏的钢丝的检测精度。 关键词:钢丝绳;损坏的钢丝;信号处理;检测装置中图分类号TB 421引言煤矿提升机钢丝绳是煤矿提升或运输系统的重要组成部分,这是人所共知的。事实上钢丝是,由于磨损,腐蚀和疲劳而受到破损,。钢丝的损害程度和承载能力直接关系到设备和员工的安全。目前, 很多在中国制造的检测损坏的钢丝绳装置,但大多数设备不能理想地满足实践需要,原因主要是钢丝的复杂结构,恶劣的工作条件,钢丝损毁的多重性和不确定性。因此,检测到钢丝损毁的迹象是相当困难,以及作以分析和处理在钢丝绳 1 里检测到的钢丝损毁的信号也是如此 。在此论文中,一套新的煤矿-提升机钢丝绳和断丝检测设备已经深入探讨,用传感器检测的特殊结构,从钢丝扭曲而产生的泄漏领域的干扰信号,可以有效地过滤。在之后提取多途径的信号的三维收缩和特征值, BP神经网络在钢丝绳对断丝的识别得已定量地实现,该测试结果将会显示出来。 2联机的煤矿提升机钢丝绳检测仪的基本结构原理我们研究的该联机的钢丝绳检测装置的结构原理在图 1中已经表明 。 检测传感器由两个可开启或封闭的半圆圆筒形结构组成,磁传感单元是一种由一个单一的磁芯组成磁通门单元并且是单一绕组。一些磁性传感单元均匀地安排靠近转换器的内壁,它的数量是检测钢丝绳铁丝网的两倍以及,两个相邻的单元有系列地联接在一项检测通道。 因此,该检测仪的检测通道的数量与丝股在线缆的数量相等。如下列图表1:煤矿提升机钢丝绳钢丝损毁检测仪的结构原理,经过过滤和重塑,从每个通道发出的检测信号送到信号处理单元。通过多渠道的A / D转换,模拟检测信号转化为二维离散序列的采样值,然后通过BP神经网络的识别和结果的输出特点提取。检测时,另外,通过每个单磁通门单元检测到的漏磁场信号是泄漏在钢索的地方相应的磁通门单元的电场强度, 那就是,任何jth测试单元的输出信号Zcj是:在该公式中,CF是驱动器方波的磁通门 宽度的结构参数, S 是额定定磁导率, Bcj钢丝损毁漏磁场所产生的应强度,Brj是钢丝绳曲折所产生的漏磁场的磁感应强度, Zfj损毁钢丝的信号值,和Zrj是的钢丝绳扭曲所产生干扰信号值,公式中系数在Cf,a,s,D确定以后,是一个常数。 线钢丝绳深感磁化后, US的数值 是很小的。因此, Zcj的值会更大,因此,没有必要再次去放大和处理的检测信号。 当传感器是在指定的速度下沿钢丝绳运行,每一项磁通门单位检测到的信号,能有效地显示磁泄漏三维立体分布状况,在钢丝绳表面产生 2-4 。3.钢丝绳扭曲所产生的干扰信号的波形振荡的过滤由一个单一的磁通门检测单元所获得的钢丝绳损毁钢丝的信号, (公式( 1 )包含各种干扰信号。由于钢丝绳特殊结构产生的磁通量泄露强度Bjb的波形振荡影响是最大地,这直接影响到检测的破碎或损坏的钢丝,特别是在煤矿-提升机的钢丝绳。我们应该考虑过滤干扰信号可能性。在公式( 1 ) ,波形振荡所造成的干扰信号Zrj周期地显示。这种波形振荡干扰信号,可算是大约作为一个正弦波,如图图2所示:图2钢丝绳扭曲波形振荡所产生的干扰信号通过钢丝绳的长度方向,其震荡周期T是一个奠定长度电缆丝。在钢丝绳的循环方向,其震荡周期是钢丝绳圆周长度的外钢丝数目的倒数, 因此,jth检测通道的波形振荡干扰信号Zrj可表示为:这里Ra是振荡直流电信号组成部分,Rm是波形震荡信号的交流电组成量,T代表周期值, Y是检测单元的位置,从最初的位置开始,初期阶段波形振荡信号, n的数目丝股的钢索,以及数是检测单位。N是钢丝绳中的钢丝根数Nc是检测单元的个数. 显然,当Nc= 2 n ,即,当检测单元的数目是钢丝绳外部钢丝数目的双倍,由任何两个邻的检测单位产生的漏磁场信号的波形振荡信号是在一个还原阶段。因此,当周边的检测单位,沿传感器的结构圆柱内壁两个两个地系列连接着成为一个测试频道,这是相当于向jth测试通道信号添加了j+1次测试通道信号。因此,钢绞线波形振荡信号的峰值补偿为钢绞线的价值是当务之急。这是,在这一刻,剩下的唯一波形振荡信号是直流电量的组成部分此时,从任何检查的渠道泄漏的磁场信号,组成了该磁通门阵列应该是:当零检测位置被调整时,这个公式的Zr可以被减掉,因此,我们可以认为钢丝绳的波形振荡干扰信号是被式( 4)过滤了。这预处理后,损毁钢丝的每个泄漏,由传感器所表现出的磁场信号,由A / D转换,变成一个渠道采样值,显示在图3 图3来自钢丝绳的断钢丝信号的多渠道的采样值4. 从损毁的钢丝信号的特征值提取正像图3所表示的那样,来自传感器N通道检查信号通过A / D转换成为其采样序列,如果损坏的钢丝信号的采样数值是K, jth渠道的损坏钢丝样本信号序列,可以表示为一个与K有关的行向量.N通道信号序列将组成损坏钢丝的信号的一个n维向量组:此时, Z是一个具有损毁钢丝的矩阵的特点,它包含所有损毁钢丝的程度的信息。鉴于反复试验分析, 钢丝绳表面上损坏的钢丝所造成的扩散泄漏磁场的宽度断丝不大于20毫米。当检测到钢丝绳的速度是3米/秒和采样间隔是1.2毫米,样本数目K至多是16。 当检查渠道数目是N = 4时, Z 应该是一个4 16矩阵。如果破碎或损坏的钢丝z的特征矩阵分析直接进行,分析过程将十分复杂,将需要对该序列每一行的值进行作为比较和判断。因此,相反,我们减少了一项,在指令处理公式( 6 ) ,即,我们进行了维收缩。根据一项引理理论线性代数,z也可以表示为:其中, , , ,是任意的,独立的基体。 h是该损毁钢丝的一维特征向量,预计在三维收缩后将取得。因此,只要找到适当的t, h可以得出:根据该L-K转换的原则, 当t值为是协方差矩阵的Z的潜在的基体,是转型错误最低一个情况,即:t满足特征方程:其中,是的特征值,I是一单位矩阵。由公式( 8)所代替,损坏钢丝的 期望的特征向量h可以通过三维收缩得到。 这个三维收缩的转变过程,实际上就是一个从一个N维特征向量向一个维向量的转换。平均一维空间h序列被视为一个特征向量代表N通道断丝信号的每个状态:5.结论我们对钢丝绳中损毁的钢丝的检测是一个定量检测方法。它将不只是确定否有钢丝损毁,也将确定损毁钢丝的位置和数目。 结合传感器检测技术及计算机技术和使用先进的信号处理技术,我们可以有效地提高检测装置的精度和灵敏度,从而实现检测设备的自动化和智能化。20湖南农业大学全日制普通本科生毕业论文(设计)中期检查表学院:工学院学生姓名学号年级专业及班级指导教师姓名指导教师职称副教授论文(设计)题目矿井提升绞车传动装置设计毕业论文(设计)工作进度已完成的主要内容尚需解决的主要问题主要完成:拟定设计方案;设计计算。主轴装置的钢丝绳,滚筒,主轴等强度计算和校核。存在问题:1、部分设计参数不精确,需反复进行验算;2、未完全熟悉设计中的结构设计,认真研究后进行更正完成;3、对其传动系统及其制动系统未了解透彻。查考参考文献,在老师的专业指导,同学互相帮助下积极解决上述问题。指导教师意见签名:年月日检查小组意见组长签名:年月日注:1.此表可用黑色签字笔填写,也可打印,但意见栏必须相应责任人亲笔填写。2.此表可从教务处网站下载中心下载。
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