基于新息理论的变点检测及其在长输管道泄漏监测中的应用

1、 3 ¯ Þ¹ É© « È ­¹ Æ Å ¶ ½ ÁŵÀ¶¼Æ ¡ 467 5 1 Fig. 5 The rst parameter of detecting abrupt change of the press at inlet ¥ Á Å ¶³ ¢ 6 2 Fig. 6 The second parameter of d

2、etecting abrupt change of the press at inlet ¥ Á Å ¶³ ¢ 7 3 Fig. 7 The third parameter of detecting abrupt change of the press at inlet ¥ Á Å ¶³ ¢ 8 1 Fig. 8 The rst parameter of detecting abrupt change of the press at outlet ¥ Á

3、Å ¶³ ¢ 9 2 Fig. 9 The second parameter of detecting abrupt change of the press at outlet ¥ Á Å ¶³ ¢ 10 3 Fig. 10 The third parameter of detecting abrupt change of the press at outlet ¥ Á Å ¶³ ¢ 11 1 Fig. 11 The rst param

4、eter of detecting abrupt change of ow rate at inlet ¥³ Å ¶³ ¢ 12 2 Fig. 12 The second parameter of detecting abrupt change of ow rate at inlet ¥³ Å ¶³ ¢ 468 ¼ ¯ 32 Û 13 3 Fig. 13 The third parameter of detecting abrupt change

5、 of ow rate at inlet ¥³ Å ¶³ ¢ 14 1 Fig. 14 The rst parameter of detecting abrupt change of ow rate at outlet ¥³ Å ¶³ ¢ 15 2 Fig. 15 The second parameter of detecting abrupt change of ow rate at outlet ¥³ Å ¶³ ¢

6、; 16 3 Fig. 16 The third parameter of detecting abrupt change of ow rate at outlet ¥³ Å ¶³ ¢ Ä´ 14 IJ ¡ Í ¨ 01 = 02 = 0.005, 10 = 20 = 0.001, 12 = 21 = 0.005, 00 = 0.998, 11 = 0.99, 22 = 0.99 À± Ä ¤ Ä ± &#

7、196; ´µÚ Ä Ç¿ ¢ 516 Ö ªØ ¨ IJ ¡ µ Ú ¤± Ä Ç¿ ¬ Ã Ä Ä ´ Ä ´² ¡ ¥ 57 ² ªØ ¤ Ä Ç¿ ¬ ÃÄ Ä ´

8、; ² ¡ µ ¢ º º ¿ Ú 500 ¦ Ï © ¢ , Ä µ 7.6 0µ ªÉ ¶ ß Ñ ¢ ß Ñ ´¶ µ ° µ ¢ªØ Ä Ã ß HÄ ¸ ¦ Ê¥ 1113 ² ª

9、Ø ¤± ¬ Ä Ä ´ ² ¡ µ ¢ Ôº ¿ º Ú 500 ¦ Ï © ¢ , Ä µ 7.6 0µ ªÉ ¶ ß Ñ µ 7.6, ßÑ ´¶ µ ¾ µ ¢ªØ Ä Ã 

10、3; H ¦ ± £ Ä ¸ ¥ « Ú ªØ 810 Ä Ä ´ ² ¡ µ à ¦ Ä ¸¢ ª Ø 1416 Ä Ä ´ ² ¡ µ à ¦ ± Ä ¸¥ ± Þ¾Ä Ã À 

11、6;´¢ × ¸­Û À Ä´ÄÕ Ç·±¥ 7 º ÏÄ´ ϲ ¡ Ë Ä § À Ä ´¥ ¶ Ä Ï Ä ´ØÑ ÌÎ ª Ä « É Ä ´¢

12、; Ä ´¥ Þ Î Ç¿ ¢  ESPRT ØÑ Õ Ä Ù 10 20 21 10 20 21 2 10 20 21 10 20 21 1 ln A10 = ln A20 = 6.89, ln A01 = ln A02 = 5.29, ln A12 = ln A21 = 5.28, Bu = 7.6, Bl = 7.6 ² ¯ Þ¹ É© « È ­¹

13、Æ Å ¶ ½ Á Å µ À ¶ ¼ Æ ¡ 469 ² ݵÄ× ¥ Â Ä ¢ BP »Ü  ¯ ´ØÑ Ë ¼ À ¤ ¤ ² ¡ Ä Ç¿ ËÚ Ä ´ Ä

14、´ Ë ¢²Ç¿ Ë Ä Ë ­ × ¿ Ç ÄØ Ñ¥ ÞΧ ¸ Ĩ Ï Ä ÀÄ´ ¹ º² À ¤ ¤ ²¡ Ä Ï Ä ´¢ ¼ ÀÄ´&

15、#196; Ä ´¥ 3 References 1 Michele Basseville, Igor V Nikiforov. Detection of Abrupt Changes: Theory and Application. Englewood Clis, N.J.: Prentice-Hall, 1993. 1528 2 Abraham Wald. Sequential Analysis. New York: J. Wiley & Sons Inc., 1947. 1212 3 Armitage P. Sequential analysis wi

16、th more than two alternative hypotheses and its relation to discriminant function analysis. Journal of the Royal Statistial Society, 1950, B(12: 137144 4 Chien T T, Adams M B. A sequential failure detection technique and its application. IEEE Transactions on Automatic Control, 1977, 22(5: 750757 5 S

17、imon Haykin. Adaptive Filter Theory. Beijing: Publishing House of Electronics Industry, 2003. 1731 6 Wu J P, Duan F Y. Study non-linear time series forecasting method based on neural networks. Systems Engineering, 1997, 15(5: 6164 (LI Jun-Hua Ph. D. candidate at Dalian University of Technology. Her

18、research interests include hydraulics and uvial dynamics, heath monitoring. Î Ñ Á à ¬¬ Ô £ Õ Ù ³¥ ³ ² ¡Ê µ¦ (SUN Zhao-Chen Professor of Dalian University of Technology. His research interests include interaction of wave and structure, interaction of wave and porous medium, and ocean envi