对煤矿矿井提升机钢丝绳损毁的钢丝检测装置的研究外文文献翻译、中英文翻译

1、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

2、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 wir

3、es 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

4、 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 b

5、y 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 i

6、dentify 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

7、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; sign

8、al 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

9、 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 worki

10、ng 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 inve

11、stigatedfor 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 re

12、cognition 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 tr

13、ansducer 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

14、 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 p

15、rinciple 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-channe

16、l 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

17、 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 magneti

18、c 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

19、 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-d

20、imensional 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 (for

21、mula (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 consid

22、er 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

23、 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 lengt

24、h 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

25、 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

26、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 t

27、ransducer 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 th

28、is 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. The

29、refore, 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

30、 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

31、 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

32、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

33、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 w

34、ould 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:w

35、here 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

36、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 v

37、ia 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

38、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 technol

39、ogy 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，中国矿业科技大学，江苏徐州2210

40、08 ，中国2机械电子信息工程系，中国矿业科技大学，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

41、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

42、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

43、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

44、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