1、外文資料：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.中文翻譯：對煤礦礦井提升機鋼絲繩損毀的鋼絲檢測裝置的研究王宏姚，華崗， 田杰1信息和電氣工程系，中國礦業科技大學，江蘇徐州2210

40、08 ，中國2機械電子信息工程系，中國礦業科技大學，北京100083 ，中國 摘要： 為了克服目前國內鋼絲故障檢測設備的缺陷，如低精度，低靈敏度和不穩定，一個新的由煤礦-提升機鋼絲繩所造成的漏磁信號的檢測和處理裝置已經研制出。強磁場檢測的原理應用在該設備中，鋼絲由前磁頭磁化強度達到飽和。我們特別的特點是安裝在沿圓圈方向上傳感器的內壁數目通量是在鋼絲繩中兩倍大的數目。周邊組件系列地連接在一起并且由于鋼絲的通量域所產生的滲漏對鋼絲繩的表面干擾有效地被過濾，斷絲所產生的采樣信號序列，其特點是在線纜的表面上由一個三維分布漏磁場通量，可以立體簡明和根據特性提取。BP神經網絡的模型已經被建立和BP神經網絡

41、的算法是用來定量分析地確定有多少鋼絲損毀。在我們的研究，我們用了6 37 +FC， 24毫米線纜作為我們的測試對象。隨機人為地以不同程度破壞和損壞數根鋼絲，實驗共進行了100次，以為來自我們的樣本的100組對象獲取數據， 然后將數據輸進BP神經網絡進行處理。然后該網絡用來識別共計16鋼絲，打破了5個不同地點。測試數據證明我們的新裝置可以提高檢測破碎和損壞的鋼絲的檢測精度。 關鍵詞：鋼絲繩;損壞的鋼絲;信號處理;檢測裝置中圖分類號TB 421 引言 煤礦提升機鋼絲繩是煤礦提升或運輸系統的重要組成部分，這是人所共知的。事實上鋼絲是，由于磨損，腐蝕和疲勞而受到破損，。鋼絲的損害程度和承載能力直接關系

42、到設備和員工的安全。目前， 很多在中國制造的檢測損壞的鋼絲繩裝置，但大多數設備不能理想地滿足實踐需要，原因主要是鋼絲的復雜結構，惡劣的工作條件，鋼絲損毀的多重性和不確定性。因此，檢測到鋼絲損毀的跡象是相當困難，以及作以分析和處理在鋼絲繩 1 里檢測到的鋼絲損毀的信號也是如此 。在此論文中，一套新的煤礦-提升機鋼絲繩和斷絲檢測設備已經深入探討，用傳感器檢測的特殊結構，從鋼絲扭曲而產生的泄漏領域的干擾信號，可以有效地過濾。在之后提取多途徑的信號的三維收縮和特征值， BP神經網絡在鋼絲繩對斷絲的識別得已定量地實現，該測試結果將會顯示出來。 2 聯機的煤礦提升機鋼絲繩檢測儀的基本結構原理 我們研究的該

43、聯機的鋼絲繩檢測裝置的結構原理在圖 1中已經表明 。 檢測傳感器由兩個可開啟或封閉的半圓圓筒形結構組成，磁傳感單元是一種由一個單一的磁芯組成磁通門單元并且是單一繞組。一些磁性傳感單元均勻地安排靠近轉換器的內壁，它的數量是檢測鋼絲繩鐵絲網的兩倍以及，兩個相鄰的單元有系列地聯接在一項檢測通道。 因此，該檢測儀的檢測通道的數量與絲股在線纜的數量相等。如下列圖表1： 煤礦提升機鋼絲繩鋼絲損毀檢測儀的結構原理，經過過濾和重塑，從每個通道發出的檢測信號送到信號處理單元。通過多渠道的A / D轉換，模擬檢測信號轉化為二維離散序列的采樣值，然后通過BP神經網絡的識別和結果的輸出特點提取。檢測時，另外，通過每個

44、單磁通門單元檢測到的漏磁場信號是泄漏在鋼索的地方相應的磁通門單元的電場強度， 那就是，任何jth測試單元的輸出信號Zcj是： 在該公式中，CF是驅動器方波的磁通門 寬度的結構參數， S 是額定定磁導率， Bcj鋼絲損毀漏磁場所產生的應強度，Brj是鋼絲繩曲折所產生的漏磁場的磁感應強度， Zfj損毀鋼絲的信號值，和Zrj是的鋼絲繩扭曲所產生干擾信號值，公式中系數 在Cf，a，s，D確定以后，是一個常數。 線鋼絲繩深感磁化后， US的數值 是很小的。因此， Zcj的值會更大，因此，沒有必要再次去放大和處理的檢測信號。 當傳感器是在指定的速度下沿鋼絲繩運行，每一項磁通門單位檢測到的信號，能有效地顯示磁泄漏三維立體分布狀況，在鋼絲繩表面產生 2-4 。3 鋼絲繩扭曲所產生的干擾信號的波形振蕩的過濾 由一個單一的磁通門檢測單元所獲得的鋼絲繩損毀鋼絲的信號， （公式（ 1 ）包含各種干擾信號。由于鋼絲繩特殊結構產生的磁通量泄露強度Bjb的波形振蕩影