In this paper two different methods, the Stochastic Subspace Damage Detection Method and Ultrasonic Guided Waves, are used to detect and to localise cracks in stiffened structures. Piezoelectric sensors and actuators ...
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ISBN:
(纸本)0912053895
In this paper two different methods, the Stochastic Subspace Damage Detection Method and Ultrasonic Guided Waves, are used to detect and to localise cracks in stiffened structures. Piezoelectric sensors and actuators are used to measure the structural response and to excite the structure, respectively. Each stringer is equipped with an actuator and at least one sensor. The input signal for the stochastic subspace based method is a broad band random noise signal with variable bandwidth between 800Hz and 800kHz. A Damage Indicator is introduced describing the change of the dynamic characteristics (modal data) of the structure resulting from the damage. The second method is based on guided Lamb waves. Here, the surface mounted piezoelectric devices are used to generate a stress wave that propagates along the stringer. The input signal is a narrow-band Hanning window modulated sinusoidal pulse. The propagating stress wave is measured by the sensor elements along the stringer. The damage localisation is performed using energy measures of the signal describing the reflection of the wave at the crack. Experiments were carried out on stiffened plates with dimensions of 2m2 and wave propagation distances over 2m. The artificially introduced cracks could be reliably detected and localised even in an early state.
The major challenge in modern controlengineering education is to bring the increasingly sophisticated theory closer to those students who will follow industrial careers. Hybrid system theory addresses practical needs...
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This paper describes the current state of the work done at The University of Wales' College Newport under the 'improve the performance of remotely operated vehicles' programmme (IMPROVES). The work incorpo...
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This paper describes the current state of the work done at The University of Wales' College Newport under the 'improve the performance of remotely operated vehicles' programmme (IMPROVES). The work incorporates advances in two interrelated parts of the project: it presents a technique to extract velocity from a low-cost MEMS inertial measurement unit for system identification and development of a combined control allocation and fault detection technique, The paper presents theoretical developments and results obtained on experimental trials.
The features of a novel dynamical discrete-time algorithm for robust adaptive learning in feed-forward neural networks and its application to the neuro-adaptive nonlinear feedback control of systems with uncertain dyn...
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The major challenge in modern controlengineering education is to bring the increasingly sophisticated theory closer to those students who will follow industrial careers. Hybrid system theory addresses practical needs...
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The major challenge in modern controlengineering education is to bring the increasingly sophisticated theory closer to those students who will follow industrial careers. Hybrid system theory addresses practical needs, but its potential is usually not understood by people from industry. Presented laboratory scale plant designed for original educational experiments with hybrid systems is a contribution to introducing this theory at a practical level. The paper includes a description of the plant structure, an outline of the mathematical model and suggested control experiments. The proposed internet access solves the lack of such laboratory set-ups. Web services architecture provides a standards-based access to all who want to learn about the principles of hybrid systems through remote experiments.
The problem of identification of uncertain nonlinear systems using feedforward neural networks is investigated. The weights of the neural identifier are updated on-line by a discrete-time learning algorithm based on t...
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The problem of identification of uncertain nonlinear systems using feedforward neural networks is investigated. The weights of the neural identifier are updated on-line by a discrete-time learning algorithm based on the sliding mode control technique, which is well known with its robustness to uncertainties. The learning parameters are adjusted to force the error between the actual and desired neural network outputs to satisfy a stable difference error equation and a quasi-sliding mode on the zero learning error is established. The behaviour of the proposed discrete-time algorithm is illustrated by using it for the neural identification of an experimental robotic manipulator. The results show that the neural model inherits some of the advantages of the sliding mode control approach, such as high speed of learning and robustness, and is able to follow the actual robot joint trajectories with a high accuracy.
A scheme is presented for the integration of FDI functional units into control loops embedded in mechatronic systems. The core of this FDI scheme is to design the FDI functional units by making use of the available tr...
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A scheme is presented for the integration of FDI functional units into control loops embedded in mechatronic systems. The core of this FDI scheme is to design the FDI functional units by making use of the available tracking control structure. The developed FDI scheme is applied to the air-intake control system of an SI-engine
This paper describes a passive trinocular Stereovision system which employs only one real camera and a 3F filter. The image captured by this system can be divided into three sub-images which can be taken as the images...
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ISBN:
(纸本)0780386469
This paper describes a passive trinocular Stereovision system which employs only one real camera and a 3F filter. The image captured by this system can be divided into three sub-images which can be taken as the images captured by three virtual cameras. Two different approaches used to understand this system are presented: one is based on camera calibration technique and another is based on geometrical analysis on ray sketching. The later approach provides an interesting way of understanding this system as it does not require complex camera calibration but one field point test process would be enough to determine this system if pin-hole camera model is used to simulate the virtual cameras, which greatly saves the effort of system determination and implementation. Experiments are conducted to test the feasibilities of both approaches.
Based on the optimal control theory, a 3-dimensionnal direct generation algorithm is proposed for anti-ground low altitude penetration tasks under complex terrain. By optimizing the terrain following(TF) objective fun...
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Based on the optimal control theory, a 3-dimensionnal direct generation algorithm is proposed for anti-ground low altitude penetration tasks under complex terrain. By optimizing the terrain following(TF) objective function,terrain coordinate system, missile dynamic model and control vector, the TF issue is turning into the improved optimal control problem whose mathmatical model is simple and need not solve the second order terrain derivative. Simulation results prove that this method is reasonable and feasible. The TF precision is in the scope from 0.3 m to 3.0 m,and the planning time is less than 30 min. This method have the strongpionts such as rapidness, precision and has great application value.
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