Li, Jianchun

Dynamic-based damage identification using neural network ensembles and damage index method

Dackermann, U., Li, J., & Samali, B. (2010) · Advances in Structural Engineering

Structural Health Monitoring TechniquesInfrastructure Maintenance and Monitoring

Cited by 66

A comparative study of using static and ultrasonic material testing methods to determine the anisotropic material properties of wood

Dackermann, U., Elsener, R., Li, J., & Crews, K. (2016) · Construction and Building Materials

Wood Treatment and PropertiesUltrasonics and Acoustic Wave Propagation

Cited by 59

Identification of member connectivity and mass changes on a two-storey framed structure using frequency response functions and artificial neural networks

Dackermann, U., Li, J., & Samali, B. (2013) · Journal of Sound and Vibration

Structural Health Monitoring TechniquesMachine Fault Diagnosis Techniques

Cited by 55

Wavelet packet energy–based damage identification of wood utility poles using support vector machine multi-classifier and evidence theory

Yu, Y., Dackermann, U., Li, J., & Niederleithinger, E. (2019) · Structural Health Monitoring

Structural Health Monitoring TechniquesUltrasonics and Acoustic Wave Propagation

Cited by 54

Condition Assessment of Foundation Piles and Utility Poles Based on Guided Wave Propagation Using a Network of Tactile Transducers and Support Vector Machines

Dackermann, U., Yu, Y., Niederleithinger, E., Li, J., & Wiggenhauser, H. (2017) · Sensors

Ultrasonics and Acoustic Wave PropagationStructural Health Monitoring Techniques

Cited by 33