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Road roughness is an important factor in road network maintenance and ride quality. This paper proposes a road-roughness estimation method using the frequency response function (FRF) of a vehicle. First, based on the motion equation of the vehicle and the time shift property of the Fourier transform, the vehicle FRF with respect to the displacements of vehicle–road contact points, which describes the relationship between the measured response and road roughness, is deduced and simplified. The key to road roughness estimation is the vehicle FRF, which can be estimated directly using the measured response and the designed shape of the road based on the least-squares method. To eliminate the singular data in the estimated FRF, the shape function method was employed to improve the local curve of the FRF. Moreover, the road roughness can be estimated online by combining the estimated roughness in the overlapping time periods. Finally, a half-car model was used to numerically validate the proposed methods of road roughness estimation. Driving tests of a vehicle passing over a known-sized hump were designed to estimate the vehicle FRF, and the simulated vehicle accelerations were taken as the measured responses considering a 5% Gaussian white noise. Based on the directly estimated vehicle FRF and updated FRF, the road roughness estimation, which considers the influence of the sensors and quantity of measured data at different vehicle speeds, is discussed and compared. The results show that road roughness can be estimated using the proposed method with acceptable accuracy and robustness.
Qingxia Zhang; Jilin Hou; Zhongdong Duan; Łukasz Jankowski; Xiaoyang Hu. Road Roughness Estimation Based on the Vehicle Frequency Response Function. Actuators 2021, 10, 89 .
AMA StyleQingxia Zhang, Jilin Hou, Zhongdong Duan, Łukasz Jankowski, Xiaoyang Hu. Road Roughness Estimation Based on the Vehicle Frequency Response Function. Actuators. 2021; 10 (5):89.
Chicago/Turabian StyleQingxia Zhang; Jilin Hou; Zhongdong Duan; Łukasz Jankowski; Xiaoyang Hu. 2021. "Road Roughness Estimation Based on the Vehicle Frequency Response Function." Actuators 10, no. 5: 89.
Damage of bridge cables is mainly manifested as the decrease in cable forces. These forces are affected by the boundary conditions, cable length, cable stiffness, and cable appendages, making it hard to identify the cable forces. Based on the substructure isolation method, this study proposes an approach for cable force identification to judge cable damage by adding virtual supports to each cable so that the cables share the same length and boundary conditions. The cable forces can then be identified according to the relationship between the natural frequency and cable forces. The basic concept is that the boundary sensors are transformed into virtual supports by a linear combination of the convolution of measured responses to achieve the zero boundary response. A finite element model of a suspension bridge was used to validate the proposed method in a simulation. When the virtual supports were added to the cables, the relationship between the cable forces and the natural frequency was almost linear, and the cable damage could be successfully identified with 5% noise. Finally, the effectiveness of the proposed method was verified experimentally, and the natural frequency of the isolated cable substructure was confirmed to be a highly sensitive damage indicator.
Jilin Hou; Chao Li; Łukasz Jankowski; Yongkang Shi; Li Su; Sheng Yu; Tiesuo Geng. Damage identification of suspender cables by adding virtual supports with the substructure isolation method. Structural Control and Health Monitoring 2020, 28, 1 .
AMA StyleJilin Hou, Chao Li, Łukasz Jankowski, Yongkang Shi, Li Su, Sheng Yu, Tiesuo Geng. Damage identification of suspender cables by adding virtual supports with the substructure isolation method. Structural Control and Health Monitoring. 2020; 28 (3):1.
Chicago/Turabian StyleJilin Hou; Chao Li; Łukasz Jankowski; Yongkang Shi; Li Su; Sheng Yu; Tiesuo Geng. 2020. "Damage identification of suspender cables by adding virtual supports with the substructure isolation method." Structural Control and Health Monitoring 28, no. 3: 1.
Adding a virtual mass is an effective method for damage identification. It can be used to obtain a large amount of information about structural response and dynamics, thereby improving the sensitivity to local damage. In the current research approaches, the virtual mass is determined first, and then the modal characteristics of the virtually modified structure are identified. This requires a wide frequency band excitation; otherwise the crucial modes of the modified structure might be out of the band, which would negatively influence the modal analysis and damage identification. This paper proposes a method that first determines the target frequency and then estimates the corresponding value of the additional virtual mass. The target frequency refers to the desired value of the natural frequency after the virtual mass has been added to the structure. The virtual masses are estimated by tuning the frequency response peaks to the target frequencies. First, two virtual mass estimation methods are proposed. One is to directly calculate the virtual mass, using the frequency‐domain response at the target frequency point only, whereas the second method estimates the mass using a least‐squares fit based on the frequency‐domain response around the target frequency. Both proposed methods utilize merely a small part of the frequency domain. Therefore, an impulse, a simple harmonic, or a narrow spectral excitation can be used for damage identification. Finally, a numerical simulation of a simply supported beam and experiments of a frame structure and a truss structure are used to verify the effectiveness of the proposed method.
Jilin Hou; Zhenkun Li; Łukasz Jankowski; Sijie Wang. Estimation of virtual masses for structural damage identification. Structural Control and Health Monitoring 2020, 27, 1 .
AMA StyleJilin Hou, Zhenkun Li, Łukasz Jankowski, Sijie Wang. Estimation of virtual masses for structural damage identification. Structural Control and Health Monitoring. 2020; 27 (8):1.
Chicago/Turabian StyleJilin Hou; Zhenkun Li; Łukasz Jankowski; Sijie Wang. 2020. "Estimation of virtual masses for structural damage identification." Structural Control and Health Monitoring 27, no. 8: 1.
Damage identification for liquid–solid coupling structures remains a challenging topic due to the influence of liquid and the limitation of experimental conditions. Therefore, the adding mass method for damage identification is employed in this study. Adding mass to structures is an effective method for damage identification, as it can increase not only the experimental data but also the sensitivity of experimental modes to local damage. First, the fundamental theory of the adding mass method for damage identification is introduced. After that, the method of equating the liquid to the attached mass is proposed by considering the liquid–solid coupling. Finally, the effectiveness and reliability of damage identification, based on adding mass for liquid–solid coupling structures, are verified through experiments of a submerged cantilever beam and liquid storage tank.
Jilin Hou; Haiyan Wang; Dengzheng Xu; Łukasz Jankowski; Pengfei Wang. Damage Identification Based on Adding Mass for Liquid–Solid Coupling Structures. Applied Sciences 2020, 10, 2312 .
AMA StyleJilin Hou, Haiyan Wang, Dengzheng Xu, Łukasz Jankowski, Pengfei Wang. Damage Identification Based on Adding Mass for Liquid–Solid Coupling Structures. Applied Sciences. 2020; 10 (7):2312.
Chicago/Turabian StyleJilin Hou; Haiyan Wang; Dengzheng Xu; Łukasz Jankowski; Pengfei Wang. 2020. "Damage Identification Based on Adding Mass for Liquid–Solid Coupling Structures." Applied Sciences 10, no. 7: 2312.
Structural damage identification plays an important role in providing effective evidence for the health monitoring of bridges in service. Due to the limitations of measurement points and lack of valid structural response data, the accurate identification of structural damage, especially for large-scale structures, remains difficult. Based on additional virtual mass, this paper presents a damage identification method for bridges using a vehicle bump as the excitation. First, general equations of virtual modifications, including virtual mass, stiffness, and damping, are derived. A theoretical method for damage identification, which is based on additional virtual mass, is formulated. The vehicle bump is analyzed, and the bump-induced excitation is estimated via a detailed analysis in four periods: separation, free-fall, contact, and coupled vibrations. The precise estimation of bump-induced excitation is then applied to a bridge. This allows the additional virtual mass method to be used, which requires knowledge of the excitations and acceleration responses in order to construct the frequency responses of a virtual structure with an additional virtual mass. Via this method, a virtual mass with substantially more weight than a typical vehicle is added to the bridge, which provides a sufficient amount of modal information for accurate damage identification while avoiding the bridge overloading problem. A numerical example of a two-span continuous beam is used to verify the proposed method, where the damage can be identified even with 15% Gaussian random noise pollution using a 1-degree of freedom (DOF) car model and 4-DOF model.
Qingxia Zhang; Jilin Hou; Łukasz Jankowski. Bridge Damage Identification Using Vehicle Bump Based on Additional Virtual Masses. Sensors 2020, 20, 394 .
AMA StyleQingxia Zhang, Jilin Hou, Łukasz Jankowski. Bridge Damage Identification Using Vehicle Bump Based on Additional Virtual Masses. Sensors. 2020; 20 (2):394.
Chicago/Turabian StyleQingxia Zhang; Jilin Hou; Łukasz Jankowski. 2020. "Bridge Damage Identification Using Vehicle Bump Based on Additional Virtual Masses." Sensors 20, no. 2: 394.
Damage identification based on modal parameters is an important approach in structural health monitoring (SHM). Generally, traditional objective functions used for damage identification minimize the mismatch between measured modal parameters and the parameters obtained from the finite element (FE) model. However, during the optimization process, the repetitive calculation of structural modes is usually time-consuming and inefficient, especially for large-scale structures. In this paper, an improved objective function is proposed based on certain characteristics of the peaks of the frequency response function (FRF). Traditional objective functions contain terms that quantify modal shapes and/or natural frequencies. Here, it is proposed to replace them by the FRF of the FE model, which allows the repeated full modal analysis to be avoided and thus increases the computational efficiency. Moreover, the efficiency is further enhanced by employing the substructural virtual distortion method (SVDM), which allows the frequency response of the FE model of the damaged structure to be quickly computed without the costly re-analysis of the entire damaged structure. Finally, the effectiveness of the proposed method is verified using an eight-story frame structure model under several damage cases. The damage location and extent of each substructure can be identified accurately with 5% white Gaussian noise, and the optimization efficiency is greatly improved compared with the method using a traditional objective function.
Jilin Hou; Sijie Wang; Qingxia Zhang; Łukasz Jankowski. An Improved Objective Function for Modal-Based Damage Identification Using Substructural Virtual Distortion Method. Applied Sciences 2019, 9, 971 .
AMA StyleJilin Hou, Sijie Wang, Qingxia Zhang, Łukasz Jankowski. An Improved Objective Function for Modal-Based Damage Identification Using Substructural Virtual Distortion Method. Applied Sciences. 2019; 9 (5):971.
Chicago/Turabian StyleJilin Hou; Sijie Wang; Qingxia Zhang; Łukasz Jankowski. 2019. "An Improved Objective Function for Modal-Based Damage Identification Using Substructural Virtual Distortion Method." Applied Sciences 9, no. 5: 971.
Adding virtual masses to a structure is an efficient way to generate a large number of natural frequencies for damage identification. The influence of a virtual mass can be expressed by Virtual Distortion Method (VDM) using the response measured by a sensor at the involved point. The proper placement of the virtual masses can improve the accuracy of damage identification, therefore the problem of their optimal placement is studied in this paper. Firstly, the damage sensitivity matrix of the structure with added virtual masses is built. The Volumetric Maximum Criterion of the sensitivity matrix is established to ensure the mutual independence of measurement points for the optimization of mass placement. Secondly, a method of sensitivity analysis and error analysis is proposed to determine the values of the virtual masses, and then an improved version of the Particle Swarm Optimization (PSO) algorithm is proposed for placement optimization of the virtual masses. Finally, the optimized placement is used to identify the damage of structures. The effectiveness of the proposed method is verified by a numerical simulation of a simply supported beam structure and a truss structure.
Jilin Hou; Zhenkun Li; Qingxia Zhang; Runfang Zhou; Łukasz Jankowski. Optimal Placement of Virtual Masses for Structural Damage Identification. Sensors 2019, 19, 340 .
AMA StyleJilin Hou, Zhenkun Li, Qingxia Zhang, Runfang Zhou, Łukasz Jankowski. Optimal Placement of Virtual Masses for Structural Damage Identification. Sensors. 2019; 19 (2):340.
Chicago/Turabian StyleJilin Hou; Zhenkun Li; Qingxia Zhang; Runfang Zhou; Łukasz Jankowski. 2019. "Optimal Placement of Virtual Masses for Structural Damage Identification." Sensors 19, no. 2: 340.
This research proposes a damage identification approach for storage tanks that is based on adding virtual masses. First, the frequency response function of a structure with additional virtual masses is deduced based on the Virtual Distortion Method (VDM). Subsequently, a Finite Element (FE) model of a storage tank is established to verify the proposed method; the relation between the added virtual masses and the sensitivity of the virtual structure is analyzed to determine the optimal mass and the corresponding frequency with the highest sensitivity with respect to potential damages. Thereupon, the damage can be localized and quantified by comparing the damage factors of substructures. Finally, an experimental study is conducted on a storage tank. The results confirm that the proposed method is feasible and practical, and that it can be applied for damage identification of storage tanks.
Jilin Hou; Pengfei Wang; Tianyu Jing; Łukasz Jankowski. Experimental Study for Damage Identification of Storage Tanks by Adding Virtual Masses. Sensors 2019, 19, 220 .
AMA StyleJilin Hou, Pengfei Wang, Tianyu Jing, Łukasz Jankowski. Experimental Study for Damage Identification of Storage Tanks by Adding Virtual Masses. Sensors. 2019; 19 (2):220.
Chicago/Turabian StyleJilin Hou; Pengfei Wang; Tianyu Jing; Łukasz Jankowski. 2019. "Experimental Study for Damage Identification of Storage Tanks by Adding Virtual Masses." Sensors 19, no. 2: 220.
To improve the identification sensitivity of local damages in pipelines, we propose an added virtual mass method thatprevents adding real masses to the pipeline. First, we develop a method of adding virtual masses to pipelines based on the virtual distortion method (VDM). Second, a frequency response to the added mass is constructed using the excitation and acceleration responses. The quantity of mass and the corresponding selected natural frequency with high sensitivity are both determined by the analyzing the sensitivity of the relationship between mass and natural frequency. Finally, the degree of damage can be accurately identified by adding virtual masses on the substructure of the pipeline combined with sensitivity and frequency. Using numerical simulations and experiments, we verify the feasibility of the added virtual mass method for the identification of damages to pipeline structures.
Dongsheng Li; Dang Lu; Jilin Hou. Pipeline Damage Identification Based on Additional Virtual Masses. Applied Sciences 2017, 7, 1040 .
AMA StyleDongsheng Li, Dang Lu, Jilin Hou. Pipeline Damage Identification Based on Additional Virtual Masses. Applied Sciences. 2017; 7 (10):1040.
Chicago/Turabian StyleDongsheng Li; Dang Lu; Jilin Hou. 2017. "Pipeline Damage Identification Based on Additional Virtual Masses." Applied Sciences 7, no. 10: 1040.
This paper proposes a frequency-domain method of substructure identification for local health monitoring using substructure isolation method (SIM). The first key step of SIM is the numerical construction of the isolated substructure, which is a virtual and independent structure that has the same physical parameters as the real substructure. Damage identification and local monitoring can be then performed using the responses of the simple isolated substructure and any of the classical methods aimed originally at global structural analysis. This paper extends the SIM to frequency domain, which allows the computational efficiency of the method to be significantly increased in comparison to time domain. The mass-spring numerical model is used to introduce the method. Two aluminum beams with the same substructure are then used in experimental verification. In both cases the method performs efficiently and accurately.
Jilin Hou; Łukasz Jankowski; Jinping Ou. Frequency-Domain Substructure Isolation for Local Damage Identification. Advances in Structural Engineering 2015, 18, 137 -153.
AMA StyleJilin Hou, Łukasz Jankowski, Jinping Ou. Frequency-Domain Substructure Isolation for Local Damage Identification. Advances in Structural Engineering. 2015; 18 (1):137-153.
Chicago/Turabian StyleJilin Hou; Łukasz Jankowski; Jinping Ou. 2015. "Frequency-Domain Substructure Isolation for Local Damage Identification." Advances in Structural Engineering 18, no. 1: 137-153.