Hong-Nan Li

Methodology Developments in Sensor Placement for Health Monitoring of Civil Infrastructures

Optimal sensor placement (OSP) technique plays a key role in the structural health monitoring (SHM) of large-scale civil infrastructures. This paper outlines an overview of current research and development in the field of OSP problems in a perspective of both researchers and engineers. The paper begins with a definition of the model of sensor placement and provides the basic issues covering relevant methodologies. The primary evaluation criteria and main sensor placement methods are then discussed in details. Following that, the linkage between several influential sensor placement methods is described. Finally, existing problems and promising research efforts in the OSP problem of civil SHM are discussed.

Sensor placement on Canton Tower for health monitoring using asynchronous-climb monkey algorithm

Heuristic optimization algorithms have become a popular choice for solving complex and intricate sensor placement problems which are difficult to solve by traditional methods. This paper proposes a novel and interesting methodology called the asynchronous-climb monkey algorithm (AMA) for the optimum design of sensor arrays for a structural health monitoring system. Different from the existing algorithms, the dual-structure coding method is designed and adopted for the representation of the design variables. The asynchronous-climb process is incorporated in the proposed AMA that can adjust the trajectory of each individual dynamically in the search space according to its own experience and other monkeys. The concept of ?monkey king? is introduced in the AMA, which reflects the Darwinian principle of natural selection and can create an interaction network to correctly guide the movement of other monkeys. Numerical experiments are carried out using two different objective functions by considering the Canton Tower in China with or without the antenna mast to evaluate the performance of the proposed algorithm. Investigations have indicated that the proposed AMA exhibits faster convergence characteristics and can generate sensor configurations superior in all instances when compared to the conventional monkey algorithm. For structures with stiffness mutation such as the Canton Tower, the sensor placement needs to be considered for each part separately.

Noise Smoothing for Structural Vibration Test Signals Using an Improved Wavelet Thresholding Technique

In structural vibration tests, one of the main factors which disturb the reliability and accuracy of the results are the noise signals encountered. To overcome this deficiency, this paper presents a discrete wavelet transform (DWT) approach to denoise the measured signals. The denoising performance of DWT is discussed by several processing parameters, including the type of wavelet, decomposition level, thresholding method, and threshold selection rules. To overcome the disadvantages of the traditional hard- and soft-thresholding methods, an improved thresholding technique called the sigmoid function-based thresholding scheme is presented. The procedure is validated by using four benchmarks signals with three degrees of degradation as well as a real measured signal obtained from a three-story reinforced concrete scale model shaking table experiment. The performance of the proposed method is evaluated by computing the signal-to-noise ratio (SNR) and the root-mean-square error (RMSE) after denoising. Results reveal that the proposed method offers superior performance than the traditional methods no matter whether the signals have heavy or light noises embedded.

A modified monkey algorithm for optimal sensor placement in structural health monitoring

Proper placement of sensors plays a key role in construction and implementation of an effective structural health monitoring (SHM) system. This paper outlines a novel methodology called the modified monkey algorithm (MA) for the optimum design of SHM system sensor arrays, which is very different from the conventional method and is simple to implement. The integer coding method instead of the binary coding method is proposed to code the solution. The Euclidean distance operator and the stochastic perturbation mechanism of the harmony search algorithm are employed to improve the local and global search capability. A computational case of a high-rise building has been implemented to demonstrate the effectiveness of the modified method. The obtained sensor placements using the modified MA are compared with those gained by the existing MA using the integer coding method and the famous forward sequential sensor placement algorithm. Results showed that the innovations in the MA proposed in this paper could improve the convergence of the algorithm and the method is effective in solving combinatorial optimization problems such as optimal sensor placement.

Optimal Sensor Placement for Health Monitoring of High-Rise Structure Based on Genetic Algorithm

Optimal sensor placement (OSP) technique plays a key role in the structural health monitoring (SHM) of large-scale structures. Based on the criterion of the OSP for the modal test, an improved genetic algorithm, called “generalized genetic algorithm (GGA)”, is adopted to find the optimal placement of sensors. The dual-structure coding method instead of binary coding method is proposed to code the solution. Accordingly, the dual-structure coding-based selection scheme, crossover strategy and mutation mechanism are given in detail. The tallest building in the north of China is implemented to demonstrate the feasibility and effectiveness of the GGA. The sensor placements obtained by the GGA are compared with those by exiting genetic algorithm, which shows that the GGA can improve the convergence of the algorithm and get the better placement scheme.

Characterization and extraction of global positioning system multipath signals using an improved particle-filtering algorithm

Driving down multipath errors is probably the single most important objective of the current research into the use of the global positioning system (GPS) for high-accuracy applications. This paper focuses on the characterization of multipath signals and techniques for their removal by improved particle filtering. By the characteristic analysis of the GPS multipath signal in carrier phase observations, a specific set of generating and monitoring systems for multipath signals is established and a series of controlled experiments are carried out to assess the efficiency of the improved particle filtering. Experimental results show that the method has the advantage of being able to adapt to the close reflector situation, while remaining quite efficient when the reflector gets further away. The extracted multipath signals may be used to improve positioning accuracies.

A review of damage detection methods for wind turbine blades

Wind energy is one of the most important renewable energy sources and many countries are predicted to increase wind energy portion of their whole national energy supply to about twenty percent in the next decade. One potential obstacle in the use of wind turbines to harvest wind energy is the maintenance of the wind turbine blades. The blades are a crucial and costly part of a wind turbine and over their service life can suffer from factors such as material degradation and fatigue, which can limit their effectiveness and safety. Thus, the ability to detect damage in wind turbine blades is of great significance for planning maintenance and continued operation of the wind turbine. This paper presents a review of recent research and development in the field of damage detection for wind turbine blades. Specifically, this paper reviews frequently employed sensors including fiber optic and piezoelectric sensors, and four promising damage detection methods, namely, transmittance function, wave propagation, impedance and vibration based methods. As a note towards the future development trend for wind turbine sensing systems, the necessity for wireless sensing and energy harvesting is briefly presented. Finally, existing problems and promising research efforts for online damage detection of turbine blades are discussed.

Seismic Control of Power Transmission Tower Using Pounding TMD

AbstractLattice transmission towers are vital components of transmission line systems, which play an important role in the operation of electrical power systems. This paper proposes a new type of tuned mass damper (TMD), the pounding tuned mass damper (PTMD), to upgrade the seismic resistant performance of a transmission tower. In the PTMD, a limiting collar with viscoelastic material laced on the inner rim is installed to restrict the stroke of the TMD and to dissipate energy through collision. The pounding force is modeled based on the Hertz contact law, whereas the pounding stiffness β is estimated in a small-scale test. A multimass model of a 55-m tower is established to verify the effectiveness of the PTMD numerically. Harmonic excitation and time-history analysis demonstrate the PTMD’s superiority over the traditional TMD. Finally, a parametric study is performed for the optimal design.

H_{\infty } robust control design of active structural vibration suppression using an active mass damper

A mathematical model of any real system is always just an approximation of the true, physical reality of the system dynamics. There are always uncertainties in the system modeling. This paper outlines a general approach to the design of an control of an active mass damper (AMD) for vibration reduction of a building with mass and stiffness uncertainties. Linear fractional transformation (LFT) is utilized in this paper for uncertainty modeling. To facilitate the computation of the controller, an efficient solution procedure based on linear matrix inequalities (LMIs) is employed. The controller uses the acceleration signal for feedback. A two-story building test-bed with an AMD is used to test the designed controller. Earthquake ground motion is introduced by a shaking table. A pair of diagonal shape memory alloy (SMA) wire braces are installed in the first floor to introduce stiffness uncertainty to the structure by controlling the temperature of the SMA wire brace. Masses are added to the structure to introduce mass uncertainty. Experiments were conducted and the results validate the effectiveness of the proposed controller in dealing with stiffness and mass uncertainties.

Health monitoring system for offshore platform with fiber Bragg grating sensors

Fiber Bragg grating (FBG) sensors show superior potential for structural health monitoring of civil structures to ensure their structural integrity, durability, and reliability. In this work, FBG sensors, including strain and temperature sensors, are applied for health monitoring of the oil production offshore platform number CB271, which is located in the Bohai Sea, East China. The procedure of FBG sensor installation during platform construction, as well as model validation in a laboratory under a variety of loading conditions on a seismic simulation shaking table, is also presented. In the tests, FBG strain sensors are placed as a strain rosette on the surface of the platform central pillar, and an FBG temperature sensor is installed close to those strain sensors for temperature compensation. The FBG sensors have been in operation for one year without any significant reduction of working performance. Strain responses induced by the impacts of ocean waves and the ships hundred tons of weight are monitored on site successfully. The fundamental frequency of the platform identified by the results of the FBG sensors agrees well with that obtained by theoretical analysis. In the monitoring, FBG sensors exhibit excellent performance and higher tolerance to harsh environments in the long-term real-time health monitoring of ocean offshore platforms.