10 An Experimental Modal Channel Reduction Procedure Using a Pareto Chart 109 10.7 Conclusion A novel modal sensor location identification method was shown to provide a quick, relatively simple, non-contact experimental way to determine important sensor locations through the use of a Pareto chart. A laser vibrometer was used to measure the response at several locations along the aircraft and the RMS values were calculated. A Pareto chart was used to identify which of these locations are important to instrument by identifying which locations contribute to most of the motion experienced by the aircraft. This method would be most effectively used by measuring the motion at several locations on the structure and placing sensors at the nodes that capture a certain percentage of the motion that was measured. This provides the user with the flexibility to choose the percentage of motion that is important for that structure. A study was done on channel reduction and three tests with different levels of channel reduction were performed and analyzed. While maintaining the ability to detect the modes of interest, the number of channels used was reduced from 16 channels down to 10 channels, which is a 38 % reduction in channels. This reduction not only saves money by using less sensors and supporting equipment, but also saves time that would have been spent on data collection and analysis on the extra channels. Finite element simulations were conducted that also demonstrated the ability to simulate mode shapes and natural frequencies. Relatively simple models of complex systems can generate accurate modal results. The nodes identified by the channel evaluation tool also correspond to the locations of large modal participation in the FE results. Over 99 % of the effective mass of the system is captured in the first two modes, which correspond to the nodal locations with the highest participation found in the experimental study. In addition, this experimental procedure can be used in conjunction with numerical simulations for model validation and other sensor placement optimization techniques. The procedure also can augment the evaluation and assessment of their structural behavior of previously constructed structures. Future utilization and expansion of the methodology presented includes the correlation of the Pareto chart method to other sensor placement techniques. Also, studies providing additional guidelines for candidate sensor locations could improve the efficacy of the method. In general, this purely experimental procedure provides an effective method for enhanced modal analysis and can serve as a supplement to the procedures currently engaged in by the modal analysis community. Acknowledgements This research was supported in part by Department of Defense contract number FA4861-06-C-C006 “Unmanned Aerial System Remote Sense and Avoid System and Advanced Payload Analysis and Investigation,” the Air Force Research Laboratory, “MEMS Antenna for Wireless Communications Supporting Unmanned Aerial Vehicles in the Battlefield,” and the North Dakota Department of Commerce, “UND Center of Excellence for UAV and Simulation Applications.” The authors would like to also acknowledge the contributions of the Unmanned Aircraft Systems Laboratory team at UND. References 1. Fleming GA, Buehrle RD (1998) Modal analysis of an aircraft fuselage panel using experimental and finite-element techniques. In: 3rd international conference on vibration measurements by laser techniques SPIE 3411, vol 1. Anacona, Italy, p 537–549 2. Carne TG, Dohrmann CR (1995) A modal test design strategy for model correlation. In: 13th international modal analysis conference (IMACXIII), Nashville, TN 3. 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