礦井提升設備的選型設計
礦井提升設備的選型設計,礦井提升設備的選型設計,礦井,提升,晉升,設備,裝備,選型,設計
河南理工大學萬方科技學院本科畢業(yè)論文
附錄：
外文資料與中文翻譯
外文資料：
Research on Detection Device for Broken Wires of Coal Mine-Hoist Cable
WANG Hong-yao1, HUA Gang1, TIAN Jie2
1School of Information and Electrical Engineering, China University of Mining & Technology, Xuzhou, Jiangsu 221008, China
2School of Mechanical Electronic and Information Engineering, China University of Mining & Technology, Beijing 100083, China
Abstract: 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 6×37+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 device
CLC number: TB 42
1 Introduction
It 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 Cable
The 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 magnetic
induction 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 cables[2–4].
3 Filtration of the Wavelike Oscillation Interference Signal Produced by Cable Wire Twists
The 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 signal
produced by the cable twist
Over 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:
j
Where 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 Componen
At 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 wire
signals from wire cables
4 Extraction of Characteristic Value of Signals from Broken Wires
As 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 4×16 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 equation
Where 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 Conclusions
Our 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 the
precision 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(yè)大學，江蘇徐州221008 ，中國
2機械電子信息工程系，中國礦業(yè)大學，北京100083 ，中國
摘要：為了克服目前國內(nèi)鋼絲故障檢測設備的缺陷，如低精度，低靈敏度和不穩(wěn)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(jīng)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(nèi)壁數(shù)目通量是在鋼絲繩中兩倍大的數(shù)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(chǎn)生的滲漏對鋼絲繩的表面干擾有效地被過濾，，斷絲所產(chǎn)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(jù)特性提取。BP神經(jīng)網(wǎng)絡的模型已經(jīng)被建立和BP神經(jīng)網(wǎng)絡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(shù)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(shù)據(jù)， 然后將數(shù)據(jù)輸進BP神經(jīng)網(wǎng)絡進行處理。然后該網(wǎng)絡用來識別共計16鋼絲，打破了5個不同地點。測試數(shù)據(jù)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(guān)鍵詞：鋼絲繩;損壞的鋼絲;信號處理;檢測裝置
中圖分類號TB 42
1引言
煤礦提升機鋼絲繩是煤礦提升或運輸系統(tǒng)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(guān)系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(shù)設備不能理想地滿足實踐需要，原因主要是鋼絲的復雜結(jié)構(gòu)，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(jīng)深入探討，用傳感器檢測的特殊結(jié)構(gòu)，從鋼絲扭曲而產(chǎn)生的泄漏領(lǐng)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(jīng)網(wǎng)絡在鋼絲繩對斷絲的識別得已定量地實現(xiàn)，該測試結(jié)果將會顯示出來。
2聯(lián)機的煤礦提升機鋼絲繩檢測儀的基本結(jié)構(gòu)原理
我們研究的該聯(lián)機的鋼絲繩檢測裝置的結(jié)構(gòu)原理在圖 1中已經(jīng)表明 。 檢測傳感器由兩個可開啟或封閉的半圓圓筒形結(jié)構(gòu)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(zhuǎn)換器的內(nèi)壁，它的數(shù)量是檢測鋼絲繩鐵絲網(wǎng)的兩倍以及，兩個相鄰的單元有系列地聯(lián)接在一項檢測通道。 因此，該檢測儀的檢測通道的數(shù)量與絲股在線纜的數(shù)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(jié)構(gòu)原理，
經(jīng)過過濾和重塑，從每個通道發(fā)出的檢測信號送到信號處理單元。通過多渠道的A / D轉(zhuǎn)換，模擬檢測信號轉(zhuǎn)化為二維離散序列的采樣值，然后通過BP神經(jīng)網(wǎng)絡的識別和結(jié)果的輸出特點提取。檢測時，另外，通過每個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(qū)動器方波的磁通門 寬度的結(jié)構(gòu)參數(shù)， S 是額定定磁導率， Bcj鋼絲損毀漏磁場所產(chǎn)生的應強度，Brj是鋼絲繩曲折所產(chǎn)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(chǎn)生干擾信號值，公式中系數(shù)
在Cf，a，s，D確定以后，是一個常數(shù)。 線鋼絲繩深感磁化后， US的數(shù)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(chǎn)生 [ 2-4 ] 。
3..鋼絲繩扭曲所產(chǎn)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(jié)構(gòu)產(chǎn)生的磁通量泄露強度Bjb的波形振蕩影響是最大地，這直接影響到檢測的破碎或損壞的鋼絲，特別是在煤礦-提升機的鋼絲繩。我們應該考慮過濾干擾信號可能性。
在公式（ 1 ） ，波形振蕩所造成的干擾信號Zrj周期地顯示。這種波形振蕩干擾信號，可算是大約作為一個正弦波，如圖圖2所示：
圖2鋼絲繩扭曲波形振蕩所產(chǎn)生的干擾信號
通過鋼絲繩的長度方向，其震蕩周期T是一個奠定長度電纜絲。在鋼絲繩的循環(huán)方向，其震蕩周期是鋼絲繩圓周長度的外鋼絲數(shù)目的倒數(shù)， 因此，jth檢測通道的波形振蕩干擾信號Zrj可
表示為：
這里Ra是振蕩直流電信號組成部分，Rm是波形震蕩信號的交流電組成量，T代表周期值， Y是檢測單元的位置，從最初的位置開始，初期階段波形振蕩信號， n的數(shù)目絲股的鋼索，以及數(shù)是檢測單位。N是鋼絲繩中的鋼絲根數(shù)Nc是檢測單元的個數(shù). 顯然，當Nc= 2 n ，即，當檢測單元的數(shù)目是鋼絲繩外部鋼絲數(shù)目的雙倍，由任何兩個鄰的檢測單位產(chǎn)生的漏磁場信號的波形振蕩信號是在一個還原階段。因此，當周邊的檢測單位，沿傳感器的結(jié)構(gòu)圓柱內(nèi)壁兩個兩個地系列連接著成為一個測試頻道，這是相當于向jth測試通道信號添加了j+1次測試通道信號。因此，鋼絞線波形振蕩信號的峰值補償為鋼絞線的價值是當務之急。這是，在這一刻，剩下的唯一波形振蕩信號是直流電量的組成部分
此時，從任何檢查的渠道泄漏的磁場信號，組成了該磁通門陣列應該是：
當零檢測位置被調(diào)整時，這個公式的Zr可以被減掉，因此，我們可以認為鋼絲繩的波形振蕩干擾信號是被式（ 4）過濾了。這預處理后，損毀鋼絲的每個泄漏，由傳感器所表現(xiàn)出的磁場信號，由A / D轉(zhuǎn)換，變成一個渠道采樣值，顯示在圖3
圖3來自鋼絲繩的斷鋼絲信號的多渠道的采樣值
4. 從損毀的鋼絲信號的特征值提取
正像圖3所表示的那樣，，來自傳感器N通道檢查信號通過A / D轉(zhuǎn)換成為其采樣序列，如果損壞的鋼絲信號的采樣數(shù)值是K， jth渠道的損壞鋼絲樣本信號序列，可以表示為一個與K有關(guān)的行向量.
N通道信號序列將組成損壞鋼絲的信號的
一個n維向量組
：
此時， Z是一個具有損毀鋼絲的矩陣的特點，它包含所有損毀鋼絲的程度的信息。鑒于反復試驗分析， 鋼絲繩表面上損壞的鋼絲所造成的擴散泄漏磁場的寬度斷絲不大于20毫米。當檢測到鋼絲繩的速度是3米/秒和采樣間隔是1.2毫米，樣本數(shù)目K至多是16。 當檢查渠道數(shù)目是N = 4時， Z 應該是一個4 × 16矩陣。如果破碎或損壞的鋼絲z的特征矩陣分析直接進行，分析過程將十分復雜，將需要對該序列每一行的值進行作為比較和判斷。因此，相反，我們減少了一項，在指令處理公式（ 6 ） ，即，我們進行了維收縮。根據(jù)一項引理理論線性代數(shù)，z也可以表示為：
其中， ， ，… ，是任意的，獨立的基體。 h是該損毀鋼絲的一維特征向量，預計在三維收縮后將取得。因此，只要找到適當?shù)膖， h可以得出：
根據(jù)該L-K轉(zhuǎn)換的原則， 當t值為是協(xié)方差矩陣的Z的潛在的基體，是轉(zhuǎn)型錯誤最低一個情況，即：t滿足特征方程:
其中，是的特征值，I是一單位矩陣。由公式（ 8）所代替，損壞鋼絲的 期望的特征向量h可以通過三維收縮得到。 這個三維收縮的轉(zhuǎn)變過程，實際上就是一個從一個N維特征向量向一個維向量的轉(zhuǎn)換。平均一維空間h序列被視為一個特征向量代表N通道斷絲信號的每個狀態(tài)：
5.結(jié)論
我們對鋼絲繩中損毀的鋼絲的檢測是一個定量檢測方法。它將不只是確定否有鋼絲損毀，也將確定損毀鋼絲的位置和數(shù)目。 結(jié)合傳感器檢測技術(shù)及計算機技術(shù)和使用先進的信號處理技術(shù)，我們可以有效地提高檢測裝置的精度和靈敏度，從而實現(xiàn)檢測設備的自動化和智能化。
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