[1] Doebling, S.W., Farrar, C.R., Prime, M.B., 1998. A summary review of vibration-based damage identification methods. The Shock and Vibration Digest, 30(2):91-105.

[2] Gao, Y., Spencer, Jr.B.F., 2002. Damage localization under ambient vibration using changes in flexibility. Journal of Earthquake Engineering and Earthquake Vibration, 1(1):136-144.

[3] Guo, J., 2004. Study of Structural Damage Identification Based on Wavelet Analysis. Ph.D Thesis, Zhejiang University, Hangzhou, China (in Chinese).

[4] Guo, J., Sun, B.N., 2005. Multi-scale analysis based on wavelet transform in bridge health monitoring. Journal of Zhejiang University (Engineering Science), 39(1):114-119 (in Chinese).

[5] Ni, Y.Q., Wang, B.S., Ko, J.M., 2002. Constructing input vectors to neural networks for structural damage identification. Smart Materials and Structures, 11(6):825-833.

[6] Qu, W.L., Chen, W., Li, Q.S., 2003. Two-step approach for joints damage diagnosis of framed structures by artificial neural networks. China Civil Engineering Journal, 36(50):37-45 (in Chinese).

[7] Sun, Z., Chang, C.C., 2002. Structural damage assessment based on wavelet packet transform. Journal of Structural Engineering, 128(10):1354-1361.

[8] Teng, J., Liu, H.J., Qu, W.L., 2004. Error Compensation Technique for the Structural Health Monitoring Sensor Systems. Proceedings of the Eighth International Symposium on Structural Engineering for Young Exports. Science Press, Xi’an, China, p.345-365.

[9] Yen, G.G., Lin, K.C., 2000. Wavelet packet feature extraction for vibration monitoring. IEEE Transaction on Industrial Electronics, 47(3):650-667.

[10] Wang, M.L., Heo, G., Satpathi, D., 1998. A health monitoring system for large structural systems. Smart Materials & Structures, 7(5):606-616.