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Figure 2.4 Eigenvalues of the state space matrix A from the first two replications, for the models

Figure 2 4 Eigenvalues of the state space matrix A from the first two replications, for the models

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Figure 2.1 (a) Graph of the singular values of the Hankel matrices of the impulse response for different orders of the state space model. (b) Zoom of Figure 2.1a.
Figure 2.1 (a) Graph of the singular values of the Hankel matrices of the impulse response for different orders of the state space model. (b) Zoom of Figure 2.1a.
Figure 2.2 Matrix A of the estimated state space model for order number 16.
Figure 2.2 Matrix A of the estimated state space model for order number 16.
Figure 2.3 Eigenvalues of the state space matrix A for the models of order 16 (x) and 20 (0).
Figure 2.3 Eigenvalues of the state space matrix A for the models of order 16 (x) and 20 (0).
Figure 2.5 Model selection graph when the no-disturbance option is set.
Figure 2.5 Model selection graph when the no-disturbance option is set.
Figure 2.6 Eigenvalues of the state space matrix A from the first three replications, with the no- disturbance option and for the models of order (a) 16 and (b) 20.
Figure 2.6 Eigenvalues of the state space matrix A from the first three replications, with the no- disturbance option and for the models of order (a) 16 and (b) 20.
Figure 2.7 Eigenvalues of the undamaged system (largest circles), and comparison with those calculated for the three different replications of the previously considered damaged system
Figure 2.7 Eigenvalues of the undamaged system (largest circles), and comparison with those calculated for the three different replications of the previously considered damaged system
Figure 2.1 (a) Graph of the singular values of the Hankel matrices of the impulse response for different orders of the state space model. (b) Zoom of Figure 2.1a.
Figure 2.1 (a) Graph of the singular values of the Hankel matrices of the impulse response for different orders of the state space model. (b) Zoom of Figure 2.1a.
Figure 2.2 Matrix A of the estimated state space model for order number 16.
Figure 2.2 Matrix A of the estimated state space model for order number 16.
Figure 2.3 Eigenvalues of the state space matrix A for the models of order 16 (x) and 20 (0).
Figure 2.3 Eigenvalues of the state space matrix A for the models of order 16 (x) and 20 (0).
Figure 2.4 Eigenvalues of the state space matrix A from the first two replications, for the models
Figure 2.4 Eigenvalues of the state space matrix A from the first two replications, for the models
Figure 2.5 Model selection graph when the no-disturbance option is set.
Figure 2.5 Model selection graph when the no-disturbance option is set.
Figure 2.6 Eigenvalues of the state space matrix A from the first three replications, with the no- disturbance option and for the models of order (a) 16 and (b) 20.
Figure 2.6 Eigenvalues of the state space matrix A from the first three replications, with the no- disturbance option and for the models of order (a) 16 and (b) 20.
Figure 2.7 Eigenvalues of the undamaged system (largest circles), and comparison with those calculated for the three different replications of the previously considered damaged system
Figure 2.7 Eigenvalues of the undamaged system (largest circles), and comparison with those calculated for the three different replications of the previously considered damaged system
Figure 3.1 Construction-cost versus maintenance-estimate and monitoring- impact.
Figure 3.1 Construction-cost versus maintenance-estimate and monitoring- impact.
(a) A hydralic shaker: larger force capacity than electro-dynamic shaker but limited high frequency capability Figure 3.2 Different types of forced excitation methods.
(a) A hydralic shaker: larger force capacity than electro-dynamic shaker but limited high frequency capability Figure 3.2 Different types of forced excitation methods.
Figure 3.3 An embedded network of distributed piezoelectric actuators/sensors: this thin film of sensor/actuator network can be either surface mounted or embedded into composite structures.
Figure 3.3 An embedded network of distributed piezoelectric actuators/sensors: this thin film of sensor/actuator network can be either surface mounted or embedded into composite structures.
Figure 3.4 Examples of ambient excitations.
Figure 3.4 Examples of ambient excitations.
Figure 4.1 Today’s conventional wired monitoring system.
Figure 4.1 Today’s conventional wired monitoring system.
Figure 4.2 Two layers wireless architecture.
Figure 4.2 Two layers wireless architecture.
Figure 4.5 Units with wireless communication.
Figure 4.5 Units with wireless communication.
Figure 5.1 Top row: the Gibbs set, whose representing points are originally in a single cell, evolves with all the points remaining grouped into a single cell. Middle row: the previous Gibbs set evolves by invading a slowly increasing number of cells. Bottom row: the Gibbs set evolves by quickly invading all the state space.
Figure 5.1 Top row: the Gibbs set, whose representing points are originally in a single cell, evolves with all the points remaining grouped into a single cell. Middle row: the previous Gibbs set evolves by invading a slowly increasing number of cells. Bottom row: the Gibbs set evolves by quickly invading all the state space.
Figure 5.2 Sections of the Poincaré maps drawn for the two sets of signals introduced in Chapter
Figure 5.2 Sections of the Poincaré maps drawn for the two sets of signals introduced in Chapter
Figure 5.3 Classification of a dynamic system based on Kolmogorov entropy: a) regular, b stochastic or chaotic, and c) fully random.
Figure 5.3 Classification of a dynamic system based on Kolmogorov entropy: a) regular, b stochastic or chaotic, and c) fully random.
Figure 5.4 Entropy evolution from the central cell for the 12 pulses: set of damaged case signals.
Figure 5.4 Entropy evolution from the central cell for the 12 pulses: set of damaged case signals.
Figure 5.5 Entropy evolution from the central cell for the 12 pulses: set of undamaged case
Figure 5.5 Entropy evolution from the central cell for the 12 pulses: set of undamaged case
Figure 5.6 Illustration of the concept of Lyapunov exponent. Let N the dimension of the space, one writes N equations of evolution for Let N the dimension of the space, one writes N equations of evolution for
Figure 5.6 Illustration of the concept of Lyapunov exponent. Let N the dimension of the space, one writes N equations of evolution for Let N the dimension of the space, one writes N equations of evolution for
TABLE 6.1 DATA FOR MULTIPLE LINEAR REGRESSION
TABLE 6.1 DATA FOR MULTIPLE LINEAR REGRESSION
be synthesized into Equation (6.6) with
be synthesized into Equation (6.6) with
are assembled in a 78x78 global stiffness matrix K gicp, following the standar finite element procedures. The 4x4 element stiffness matrices of the form
are assembled in a 78x78 global stiffness matrix K gicp, following the standar finite element procedures. The 4x4 element stiffness matrices of the form
Figure 6.2 F- histogram for the undamaged state of the structure under different load conditions.
Figure 6.2 F- histogram for the undamaged state of the structure under different load conditions.
Figure 6.3 SSE-histograms for the undamaged state of the structure under different load conditions. Response at 20 m, and k = 20 predictors.
Figure 6.3 SSE-histograms for the undamaged state of the structure under different load conditions. Response at 20 m, and k = 20 predictors.
Figure 6.4 F-histograms for the undamaged state of the structure under different load conditions and for three levels of random noises in the measurements. Response at 20 m, and k = 20
Figure 6.4 F-histograms for the undamaged state of the structure under different load conditions and for three levels of random noises in the measurements. Response at 20 m, and k = 20
Figure 6.5 SSE-histograms for the undamaged state of the structure under different load
Figure 6.5 SSE-histograms for the undamaged state of the structure under different load
Figure 6.6 F-histograms for the undamaged state of the structure under different load conditions and for three levels of random noises in the measurements. Response at 20 m, and k = 10
Figure 6.6 F-histograms for the undamaged state of the structure under different load conditions and for three levels of random noises in the measurements. Response at 20 m, and k = 10
Figure 6.7 SSE-histograms for the undamaged state of the structure under different load
Figure 6.7 SSE-histograms for the undamaged state of the structure under different load
Figure 6.9 F-histograms for the damaged and undamaged states of the structure under different
Figure 6.9 F-histograms for the damaged and undamaged states of the structure under different
Figure 6.10 SSE-histograms for the damaged and undamaged states of the structure under
Figure 6.10 SSE-histograms for the damaged and undamaged states of the structure under
Figure 6.11 F-histograms for the damaged and undamaged states of the structure under different load conditions and for three levels of random noises in the measurements.
Figure 6.11 F-histograms for the damaged and undamaged states of the structure under different load conditions and for three levels of random noises in the measurements.
Figure 6.12 SSE-histograms for the damaged and undamaged states of the structure under different load conditions and for the random noises of (a) level 1, (b) level 2, and (c) level 3. Response at 9 m, and k = 10 predictors.
Figure 6.12 SSE-histograms for the damaged and undamaged states of the structure under different load conditions and for the random noises of (a) level 1, (b) level 2, and (c) level 3. Response at 9 m, and k = 10 predictors.
THE COLUMNS CORRESPOND TO THE THREE LEVELS OF NOISE. FIRST ROW: MEAN VALUES OF THE F-
THE COLUMNS CORRESPOND TO THE THREE LEVELS OF NOISE. FIRST ROW: MEAN VALUES OF THE F-
TABLE 6.III SENSOR LOCATIONS.
TABLE 6.III SENSOR LOCATIONS.
Figure 6.13 Flow chart of the proposed SHM scheme.
Figure 6.13 Flow chart of the proposed SHM scheme.
Figure 7.1 The ASCE benchmark structural system: (a) real structure at UBC; and (b) analytical model. From [Johnson et al., 2000].
Figure 7.1 The ASCE benchmark structural system: (a) real structure at UBC; and (b) analytical model. From [Johnson et al., 2000].
Figure 7.3 Sensor locations and id numbers.
Figure 7.3 Sensor locations and id numbers.
Figure 7-5: Histograms comparison at different sensor locations for CASE 2, damage pattern 1.
Figure 7-5: Histograms comparison at different sensor locations for CASE 2, damage pattern 1.
Figure 7-4: Histograms comparison at different sensor locations for CASE 2, damage pattern 2.
Figure 7-4: Histograms comparison at different sensor locations for CASE 2, damage pattern 2.
(THE DASHED LINE CORRESPONDS TO AD Mu =0.2858).
(THE DASHED LINE CORRESPONDS TO AD Mu =0.2858).
(THE DASHED LINE CORRESPONDS TO AD Mu =0.1958).
(THE DASHED LINE CORRESPONDS TO AD Mu =0.1958).
Figure 8.2 (a) Plant view and (b) Elevation of the BABY FRAME specimen.
Figure 8.2 (a) Plant view and (b) Elevation of the BABY FRAME specimen.
Figure 8.3 Details of the welded beam-column connections. (a) Exterior joint. (b) Interior joint. (c) Internal view of an exterior joint.
Figure 8.3 Details of the welded beam-column connections. (a) Exterior joint. (b) Interior joint. (c) Internal view of an exterior joint.
Figure 8.4 Cross-section of the reinforced concrete slab on the beam flange
Figure 8.4 Cross-section of the reinforced concrete slab on the beam flange
Damage Detection and Localization in the Space of the Observed Variables Figure 8.6 (a) Shaker installed on the top of the structure. (b) Technical description of the electro-
Damage Detection and Localization in the Space of the Observed Variables Figure 8.6 (a) Shaker installed on the top of the structure. (b) Technical description of the electro-
Figure 8.9 Acceleration-time histories measured by sensor 3 during (a) the damaged and (b) the
Figure 8.9 Acceleration-time histories measured by sensor 3 during (a) the damaged and (b) the
Figure 8.7 (a) Damaged state and (b) undamaged state of the structure. Note that the sensors
Figure 8.7 (a) Damaged state and (b) undamaged state of the structure. Note that the sensors
Figure 8.8 Force-time histories measured by sensor 1 during (a) the damaged and (b) the located close to the damage are the accelerometers 17, 14, 16, and 18.
Figure 8.8 Force-time histories measured by sensor 1 during (a) the damaged and (b) the located close to the damage are the accelerometers 17, 14, 16, and 18.
Figure 8.10 SSE comparison for the accelerometers 17, 14, 18, and 16.
Figure 8.10 SSE comparison for the accelerometers 17, 14, 18, and 16.
TABLE 8.1 VALUES OF THE A DIMENSIONAL DIFFERENCE OF THE SSE-MEANS AT DIFFERENT SENSOR LOCATIONS; A DASHED LINE DIVIDES THE SENSORS WHICH DETECT DAMAGE FROM THOSE WHICH Do NOT, BY COMPARISON WITH A REFERENCE V ALUE OF AD Mu =0.2553.
TABLE 8.1 VALUES OF THE A DIMENSIONAL DIFFERENCE OF THE SSE-MEANS AT DIFFERENT SENSOR LOCATIONS; A DASHED LINE DIVIDES THE SENSORS WHICH DETECT DAMAGE FROM THOSE WHICH Do NOT, BY COMPARISON WITH A REFERENCE V ALUE OF AD Mu =0.2553.
Figure 9.1 Front prospect (top) and plant (bottom) of Palazzo Geraci: (a) in the nineteenth building presented itself as documented by Figure 9.1a.
Figure 9.1 Front prospect (top) and plant (bottom) of Palazzo Geraci: (a) in the nineteenth building presented itself as documented by Figure 9.1a.
Figure 9.2 (a) The central part of the facade of Palazzo Geraci nowadays, and on the left side they are less evident than on the right side.
Figure 9.2 (a) The central part of the facade of Palazzo Geraci nowadays, and on the left side they are less evident than on the right side.
Figure 9.3 (a) The reduced model in its present location outside of the laboratory (the structure on
Figure 9.3 (a) The reduced model in its present location outside of the laboratory (the structure on
Figure 9.4 Cracks at different locations of the reduced model: (a) left openings; (b) right ee er A , Ch Oh On oF ir 9 Pr 2h i ch er cr oS i 2 a ee ew
Figure 9.4 Cracks at different locations of the reduced model: (a) left openings; (b) right ee er A , Ch Oh On oF ir 9 Pr 2h i ch er cr oS i 2 a ee ew
Figure 9.5 Sensors locations and id numbers. Note that the main cracks in the structure are
Figure 9.5 Sensors locations and id numbers. Note that the main cracks in the structure are
Figure 9.7 Forced excitation methods. (a) Instrumented hammer. (b) Shaker at the top of the structure, in central position.
Figure 9.7 Forced excitation methods. (a) Instrumented hammer. (b) Shaker at the top of the structure, in central position.
TABLE 9.I TESTS PERFORMED ON THE DAMAGED STATE OF THE STRUCTURE.
TABLE 9.I TESTS PERFORMED ON THE DAMAGED STATE OF THE STRUCTURE.
Figure 9.8 Undamaged state of the structure. side (r.h.s.) of the structure, and of sensor 2 on the left hand side (1.h.s).
Figure 9.8 Undamaged state of the structure. side (r.h.s.) of the structure, and of sensor 2 on the left hand side (1.h.s).
TABLE 9.II TESTS PERFORMED ON THE UNDAMAGED STATE OF THE STRUCTURE.
TABLE 9.II TESTS PERFORMED ON THE UNDAMAGED STATE OF THE STRUCTURE.
TABLE 9.III GLOBAL MEASURES COMPUTED ON THE UNDAMAGED AND DAMAGED SIGNAL SETS.
TABLE 9.III GLOBAL MEASURES COMPUTED ON THE UNDAMAGED AND DAMAGED SIGNAL SETS.
TABLE 9.IV STATISTICALLY COMPARED RESPONSE TIME HISTORIES (ONLY THE ONES IN BOLD WERE USED FOR THE ANALYSES).
TABLE 9.IV STATISTICALLY COMPARED RESPONSE TIME HISTORIES (ONLY THE ONES IN BOLD WERE USED FOR THE ANALYSES).
Figure 9.9 Accelerations recorded by sensor 11 during the tests performed with different
Figure 9.9 Accelerations recorded by sensor 11 during the tests performed with different
(THE DASHED LINE CORRESPONDS TO AD Mu =0.0663).
(THE DASHED LINE CORRESPONDS TO AD Mu =0.0663).
(THE DASHED LINE CORRESPONDS TO AD Mu =0.0923).
(THE DASHED LINE CORRESPONDS TO AD Mu =0.0923).
(THE DASHED LINE CORRESPONDS TO AD Mu = 0.1563).
(THE DASHED LINE CORRESPONDS TO AD Mu = 0.1563).
These equations are called the least squares normal equations. Note that there
These equations are called the least squares normal equations. Note that there
scalar form. Writing out Equation (A.10) in detail, we obtain
scalar form. Writing out Equation (A.10) in detail, we obtain
TABLE A.II ANALYSIS OF VARIANCE FOR SIGNIFICANCE OF REGRESSION on a decomposition of the total variability in the response variable y.
TABLE A.II ANALYSIS OF VARIANCE FOR SIGNIFICANCE OF REGRESSION on a decomposition of the total variability in the response variable y.
baa A Figure B.1 (a) The original 1:2 scale model of the Palazzo Geraci facade built at the ELSA Laboratory, in Ispra. (b) Front prospect and sections of the original model.
baa A Figure B.1 (a) The original 1:2 scale model of the Palazzo Geraci facade built at the ELSA Laboratory, in Ispra. (b) Front prospect and sections of the original model.
Figure B.2 Construction phases of the specimen: (a) support plane; (b) round-headed arch; (c) wooden beams at the intrados of the platbands above the lateral openings; (d) steel anchored to the top of the column capitals.
Figure B.2 Construction phases of the specimen: (a) support plane; (b) round-headed arch; (c) wooden beams at the intrados of the platbands above the lateral openings; (d) steel anchored to the top of the column capitals.
Figure B.3 Structural details of the columns.
Figure B.3 Structural details of the columns.
Figure B.4 Structural details of the anchorage of the steel element to the top of the column capital.
Figure B.4 Structural details of the anchorage of the steel element to the top of the column capital.
Figure B.6 Reference earthquake used for the pseudo-dynamic tests.
Figure B.6 Reference earthquake used for the pseudo-dynamic tests.
Figure B.5 Pseudo-dynamic tests of the specimen.
Figure B.5 Pseudo-dynamic tests of the specimen.
Figure B.7 Cracks tormed into the structure following the pseudo- dynamic tests. (a) Model without the base isolation after the test at 200%. (b) Repaired model (without base isolation) after the test at 200%.
Figure B.7 Cracks tormed into the structure following the pseudo- dynamic tests. (a) Model without the base isolation after the test at 200%. (b) Repaired model (without base isolation) after the test at 200%.
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Civil EngineeringMechanicsNumerical SimulationsStatisticsEngineering MechanicsStructural EngineeringMultivariate StatisticsSensors and SensingSystem IdentificationSignal Processing
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