For collecting data from all sensor nodes, some changes in Dynamic Source Routing (DSR) protocol is proposed. At each hop level, route-ranking technique is used for distributing packets to different selected routes dynamically. For calculating rank of a route, different parameters like: delay, residual energy and probability of packet loss are used. A hybrid topology of DMPR(Disjoint Multi Path Routing) and MMPR(Meshed Multi Path Routing) is formed, where braided topology is used in different faulty zones of network. For reducing energy consumption, variant transmission ranges is used instead of fixed transmission range. For reducing number of packet drop, a fuzzy logic inference scheme is used to insert different types of delays dynamically. A rule based system infers membership function strength which is used to calculate the final delay amount to be inserted into each of the node at different clusters. In braided path, a proposed 'Dual Line ACK Link'scheme is proposed for sending ACK signal from a damaged node or link to a parent node to ensure that any error in link or any node-failure message may not be lost anyway. This paper tries to design the theoretical aspects of a model which may be applied for collecting data from any large hanging iron structure with the help of wireless sensor network. But analyzing these data is the subject of material science and civil structural construction technology, that part is out of scope of this paper., {"references":["C. Huang, M. Chatterjee, W. Cui and R. Guha, \"Multipath source\nrouting in sensor networks based on route ranking\", IWDC, 2005.","S. De, C. Qiao and H. Wu. ,\"Meshed multipath routing with selective\nforwarding:..\" WCNC, 2003.","A. Woo, and D. Culler, \"A Transmission control Scheme for Media\nAccess in Sensor Networks\" Proc. ACM Mobile com -01, Rome, Italy,\npp 221-35, July 2001.","D. Ganesan, R. Govindan, S. Shenker, D. Estrin, \"Highly-Resilient,\nEnergy-Efficient Multipath Routing in Wireless Sensor Networks\",\nMobile Computing and Communications Review, volume 1, Number 2.","D. B Johnson, D.A. Maltz , \"Dynamic Source Routing in Ad Hoc\nNetworks\", book \"Mobile computing\" by Kluwer Academic Publishers,\n1996.","A. L. Toledo and X. Wang, \"Efficient multipath in sensor networks\nusingdiffusion and network coding\", in 40th Annual Conference on\nInformation Sciences and Systems, Princeton University, NJ, USA,\nMarch 22-24, 2006.","H K Dass , \" Engineering Mathematics\", S. Chand & Co Ltd. ,2001\nedition, pgs 780-90.","K L Chung, \" Elementary probability theory\", Narosa Publishing house,\nNew Delhi,1995 edition, pgs. 192-200.","Qilian Liang and Qingchun Ren, \"Energy and Mobility Aware\nGeographical Multipath Routing for Wireless Sensor Networks\", IEEE\nCommunications Society / WCNC 2005.\n[10] J W Wilson, G Y Tian and S Barrans, \"Residual Magnetic Field Sensing\nFor Stress Measurement\", University of Huddersfield, UK., ECNDT,\n2006.\n[11] V Singh, M L Wang and G M Lloyd, \"Measuring and modeling of\ncorrosion in structural steels using magnetoelastic sensors\", University\nof Illinois, Chicago, USA, 2005.\n[12] D.Acharjee, N.Sharma, \"Slope based shortest path routing for wireless\nsensor network\", ADCOM-2007, IIT- Guwahati, India.\n[13] www.virtualacquisitionshowcase.com/docs /2008/JENTEK3-Brief.pdf\n:access on 24/10/08\n[14] Saka M, Yang Ju, Daying Luo, Abc H, \"Infrared and Millimeter\nwaves,2000\" conference digest, 25th International conference on vol,\nIssues, pgs 423-424.\n[15] Feng Xia, W. Zhao, et. el., \"Fuzzy Logic Control Based QoS\nManagement in Wireless Sensor/Actuator Network\", Sensors 2007, 7,\npgs. 3179-3191.\n[16] X. Cut, T. Hardian and et. el., \"A Swarm-based fuzzy logic control\nmobile sensor network for hazardous contaminants localization\", IEEE\n2004.\n[17] J.-S.R. Jang, C.-T.Sun and E.Mizutani, \"Neuro-Fuzzy and Soft\nComputing\" by PHI, Eastern economy edition, pgs. 74-79.\n[18] Vojislav Kecman, \"Learning and Soft Computing\", by Pearson\nEducation, 1st Indian reprint, 2004, pgs. 391-394."]}