11 Kalman-Based Virtual Sensing for Improvement of Service Response Replication in Environmental Tests 103 0.2 0.4 0.6 0.8 1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.2 0.4 0.6 0.8 1 0 0.05 0.1 0.15 0.2 0.25 0.3 0.4 0.6 0.8 1 1.2 0 0.05 0.1 0.15 0.2 0.25 0.3 0.2 0.4 0.6 0.8 1 0 0.1 0.2 0.3 0.4 0.5 Fig. 11.8 L-curve for the four unknown inputs 0 5 1015202530 -20 0 20 (a) 4.45 4.46 4.47 4.48 4.49 4.5 4.51 -20 -10 0 10 20 (b) 0 200 400 600 800 1000 10-5 100 (c) 0 5 1015202530 -20 0 20 (d) 4.45 4.46 4.47 4.48 4.49 4.5 4.51 -20 -10 0 10 20 (e) 0 200 400 600 800 1000 10-5 100 (f) 0 5 1015202530 -20 0 20 (g) 4.45 4.46 4.47 4.48 4.49 4.5 4.51 -20 -10 0 10 20 (h) 0 200 400 600 800 1000 10-5 100 105 (i) 0 5 1015202530 -20 0 20 (j) 4.45 4.46 4.47 4.48 4.49 4.5 4.51 -20 0 20 (k) 0 200 400 600 800 1000 100 (l) Fig. 11.9 Time history (left), detailed time history (middle) and PSD (right) of input 1 ((a)–(c)), input 2 ((d)–(f)), input 3 ((g)–(i)), input 4 ((j)–(l)). The measured force signals are shown by a solid black line, the identified force signals by a dashed blue line
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