Recent Publications

  1. Ghafoor I., Tse P.W.*, ‘The design of a non-contact inspection system integrated with the Time of Flight-Based Flaw Detection TOFFD criterion to investigate the structural integrity of the rail track’, Smart Materials and Structures, Article reference: SMS-113975, submitted June 13, 2022.
  2. Ng. K., Ghafoor I. and Tse P., ‘A novel laser-based duffing oscillator system to identify weak ultrasonic guided wave signals related to rail defects’, Optics and Lasers in Engineering, 157 (2022) 107111, May 20, 2022
  3. Khan, M.M.; Tse, P.W.*, Yang J., ‘A novel framework for online remaining useful life prediction of an industrial slurry pump’, Applied Sciences, 2022 12 4389, May 10, 2022.
  4. Masurkar, F., Yelve, N. P. & Tse, P., ‘Nondestructive testing of rails using nonlinear Rayleigh waves’, 17 Apr 2022, (Online published) In: Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science.
  5. Ghafoor, I., Tse, P. W., Munir, N. & Trappey, A. J. C., ‘Non-contact detection of railhead defects and their classification by using convolutional neural network’, Mar 2022, In: Optik. 253, 168607.
  6. Ghafoor, I., Tse, P.W., Munir, N., Trappey, A.J.C. , Non-Contact detection of railhead defects and their classification by using convolutional neural network’, Optik, 253 (2022) 168607 Jan. 17 2022.

Publications (2013-present)

2021

  1. Khan, M.M.; Tse, P.W., Trappey, A.J.C. ‘Development of a Novel Methodology for Remaining Useful Life Prediction of Industrial Slurry Pumps in the Absence of Run to Failure Data’. Sensors 21, 21, 8420. Dec 2021.
  2. Tse P.W.*, Fung C.L., Huang J., Masurkar F., ‘Detection of corrosion in pipes using the torsional guided waves generated by a magneto-strictive sensor mounted on a smart material and series of permanent magnets’, website published paper, www.seam-cndt.com Sept., 2021.
  3. Ghafoor, I., Tse, P.W., Rostami, J. & Ng, K-M., ‘Non-Contact Inspection of Railhead via Laser-Generated Rayleigh Waves and an Enhanced Matching Pursuit to Assist Detection of Surface and Subsurface Defects’. In: Sensors. 21, 9, 20 p., 2994. May 2021.
  4. Tse, P., ‘Summary on Data Logging Activity Conducted on 14th April 2021 at the plant site of Drainage Services Department (DSD) of the SAR Hong Kong Government’, 8 p., 14 Apr 2021.
  5. Tse, W. T. P, ‘The Design and Development of a Software Program for DSD’s Sewage Pump Sensory Data Acquisition, Data Cleaning, Feature Extraction and Signal Analysis’, 12 Apr 2021.
  6. Yang, J. & Tse, P., ‘Sparse representation of complex steerable pyramid for machine fault diagnosis by using non-contact video motion to replace conventional accelerometers’, In: Measurement. 175, 18 p., 109104., Apr 2021
  7. Tse, P.W., ‘The Report of the Analysis and Results Generated from the Third Field Test by Using Guided-wave to Detect Defects Occurred in Condensing Water Pipes that are installed at MTR’s Sai Ying Pun Station’, 20 p., 31 Mar 2021.
  8. Fang, Z., Tse, P.W. & Xu, F., ‘The application of a reflected non-axisymmetric torsional guided wave model for imaging crack-like defects in small-diameter pipes’,  In: Measurement Science and Technology. 32, 3, 035405., Mar 2021.
  9. Tse, P.W., ‘Report on the data from for the experiments conducted on the Big normal pipe partially filled with water (25 Feb. 2021 & Jan. 19, 2021)’, 10 p., 25 Feb 2021.
  10. Tse, P.W., ‘Test report for Inspecting MTR Condensing Pipes Using Guided-wave Inspection Techniques’, 9 p., 29 Jan 2021.
  11. Tse, P.W., ‘Development of Lamb and Rayleigh Wave-Based Nonlinearity Parameters for Estimating the Remnant Life of Fatigued Plate Structures’,  (Online published) European Workshop on Structural Health Monitoring: Special Collection of 2020 Papers . Rizzo, P. & Milazzo, A. (eds.). Springer, Cham, Vol. 1. p. 149-160., (Lecture Notes in Civil Engineering; vol. 127). 11 Jan 2021.
  12. Wei, Y., Wang, J., Tse, P.W. & Wang, Y., ‘Modelling and simulation of nabla fractional dynamic systems with nonzero initial conditions’, In: Asian Journal of Control. 23, 1, p. 525-535., Jan 2021.
  13. Wan, X., Liu, M., Zhang, X., Fan, H., Tse, P. W., Dong, M., Wang, X., Wei, H., Xu, C. & Ma, H., ‘The use of ultrasonic guided waves for the inspection of square tube structures’, In: Structural Health Monitoring. 20, 1, p. 58–73., Jan 2021.
  14. Rostami, J., Masurkar, F., Tse, P., Yelve, N. & Hou, E. Z. Y., ‘An Adaptive Wavelet Library to Detect Surface Defects in Rail Tracks Using a Laser Ultrasonic System’, European Workshop on Structural Health Monitoring: Special Collection of 2020 Papers. Rizzo, P. & Milazzo, A. (eds.). Springer Science and Business Media Deutschland GmbH, Vol. 1. p. 181-189 9 p. (Lecture Notes in Civil Engineering; vol. 127)., 2021.
  15. Fang, Z. & Tse, P. W., ‘Characteristics of Spiral Lamb Wave Triggered by CL-MPT and Its Application to the Detection of Limited Circumferential Extent Defects and Axial Extent Evaluation within Pipes’, In: IEEE Transactions on Instrumentation and Measurement. 70, 9464958., 2021.
  16. Yuan, M., Tse, P. W., Xuan, W. & Xu, W., ‘Extraction of Least-Dispersive Ultrasonic Guided Wave Mode in Rail Track Based on Floquet-Bloch Theory’, In: Shock and Vibration. 2021, 6685450., 25 Feb 2021.

2020

  1. Fang, Z., Tse, P. W. & Xu, F., ‘Characterization of a Partially Covered AM-MPT and Its Application to Damage Scans of Small Diameter Pipes Based on Analysis of the Beam Directivity of the MHz Lamb Wave’, In: IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control. 67, 12, p. 2717-2730., Dec 2020.
  2. Masurkar, F. & Tse, P., ‘Theoretical and experimental evaluation of the health status of a 1018 steel I-beam using nonlinear Rayleigh waves’, In: Ultrasonics. 108, 106036., Dec 2020.
  3. Tse, P. W., ‘A Report on Analyzing the Collected Sensor Data for Sewage Pump Health Monitoring based on Nov. 2020 Collected Data, Site: A Sewage Pumping Facility Plant owned by the Drainage Services Department (DSD), Hong Kong SAR Government’, 43 p., 18 Nov 2020.
  4. Masurkar, F., Ming Ng, K., Tse, P. W. & Yelve, N. P., ‘Interrogating the health condition of rails using the narrowband Rayleigh waves emitted by an innovative design of non-contact laser transduction system’,  (Online published) In: Structural Health Monitoring., 2 Nov 2020.
  5. Wei, Y., Chen, Y., Tse, P. W. & Cheng, S., Analytical and numerical representations for discrete Grünwald–Letnikov fractional calculus, Proceedings 2020 Chinese Automation Congress (CAC 2020). IEEE, p. 2097-2102 9327090. (Proceedings – Chinese Automation Congress, CAC), Nov 2020.
  6. Fang, Z. & Tse, P. W., ‘Methodology for circumferential localisation of defects within small-diameter concrete-covered pipes based on changing of energy distribution of non-axisymmetric guided waves’, In: Applied Acoustics. 168, 14 p., 107416., Nov 2020.
  7. Tse, P. W., ‘Programming PYTHON based Deep Learning Neural Networks as Virtual Instruments for Forecasting the Degradation Trend of Sewage Pump’, 16 Sep 2020.Tse, P. W., ‘y’, 43 p., Sep 2020.
  8. Masurkar, F., Rostami, J. & Tse, P., ‘Design of an innovative and self-adaptive-smart algorithm to investigate the structural integrity of a rail track using Rayleigh waves emitted and sensed by a fully non-contact laser transduction system’, In: Applied Acoustics. 166, 15 p., 107354. Sep 2020.Tse, P. W., ‘y’, 21 Aug 2020.
  9. Hou, E. Z. Y., Rostami, J., Ng, K. M. & Tse, P. W., ‘Experimental Investigation on Choosing a Proper Sensor System for Guided Waves to Check the Integrity of Seven-Wire Steel Strands’, In: Sensors (Switzerland). 20, 18, 25 p., 5025. Sep 2020.
  10. Tse, W. T. P., ‘Design of MATLAB based Deep Learning LSTM Neural Networks that can be operated in LabVIEW Virtual Instrument Environment for Predicting Pump Remaining Useful Life’, 21 Aug 2020.
  11. Tse, W. T. P., ‘Preliminary Results on Using Guided Wave Technology to Detect Defects Occurred in Chiller Water Pipes installed at MTR Sai Ying Pun Station (the first onsite test)’, 11 p., 21 Jul 2020.
  12. Tse, P. W., ‘A Report to Request the Installation of an Intelligent and Automatic Health Condition Monitoring System for Sewage Pumps’, 46 p., 23 May 2020.
  13. Tse, P., Masurkar, F. & Yelve, N. P., ‘Estimation of remaining useful life of fatigued plate specimens using Lamb wave‐based nonlinearity parameters’, In: Structural Control and Health Monitoring. 27, 4, e2486.  Apr 2020.
  14. Masurkar, F. & Tse, P., ‘Experimental evaluation of the true intrinsic nonlinearity of rail steel using Rayleigh waves and a new nonlinearity parameter’, Health Monitoring of Structural and Biological Systems IX. Fromme, P. & Su, Z. (eds.). SPIE, Vol. 11381. 12 p. 113811N. (Proceedings of SPIE – The International Society for Optical Engineering; vol. 11381)., Apr 2020.
  15. Tse, W. T. P., ‘The Report of the Second Visit to DSD Sewage Pumps Plant’, 7 p., 6 Mar 2020.
  16. Ng, K. & Tse, P. W., ‘Design of a remote and integrated Sagnac interferometer that can generate narrowband guided wave through the use of laser and effective optics to detect defects occurred in plates’, In: Optics and Laser Technology. 123, 105923., Mar 2020.
  17. Rostami, J., Tse, P. W. & Yuan, M., ‘Detection of broken wires in elevator wire ropes with ultrasonic guided waves and tone-burst wavelet’, In: Structural Health Monitoring. 19, 2, p. 481–494., Mar 2020.
  18. Tse, P. W., ‘A Technical Report for Preparing the Implementation of an Automatic Health Condition Monitoring System for Sewage Pumps’, 28 p., 14 Feb 2020.
  19. Tse, W. T. P., ‘Technology transfer activities made to DSD – FIRST Progress Report – ITS-205-18FX 2020 2’, 7 p., Feb 2020.
  20. Masurkar, F., Tse, P. W. & Yelve, N. P., ‘Theoretical and experimental measurement of intrinsic and fatigue induced material nonlinearities using Lamb wave based nonlinearity parameters’, In: Measurement: Journal of the International Measurement Confederation. 151, 107148., Feb 2020.
  21. XIE, Y., CHEN, S., WAN, X. & TSE, P. W., ‘A Preliminary Numerical Study on the Interactions Between Nonlinear Ultrasonic Guided Waves and a Single Crack in Bone Materials With Motivation to the Evaluation of Micro Cracks in Long Bones’, In: IEEE Access. 8, p. 169169-169182., 2020.
  22. Wei, Y., Liu, D-Y., Tse, P. W. & Wang, Y., ‘Discussion on the Leibniz rule and Laplace transform of fractional derivatives using series representation’, In: Integral Transforms and Special Functions. 31, 4, p. 304–322., 2020.

2019 and before

  1. Masurkar F. and Tse P., ‘Analyzing the features of material nonlinearity evaluation in a rectangular Aluminum Beam using Rayleigh waves: Theoretical and Experimental study’, Journal of Physics Communications, 055002, 3(5), pp 1-23, 2019.
  2. Rostami J., Tse P.* and M. Yuen, ‘Detection of Broken Wires in Elevator Wire Ropes with Ultrasonic Guided Waves and Tone-Burst Wavelet’, Structural Health Monitoring, Manuscript ID SHM-18-0377.R2., Published June 12, 2019.
  3. Wan X., Zhang X.*, Fan H., Tse P., Dong M., Ma H., ‘Numerical Study on Ultrasonic Guided Waves for the Inspection of Polygonal Drill Pipes’, Sensors, 19(9), 2128; Published May 8, 2019.
  4. Tse Y., Cholette M., and Tse P., ‘A multi-sensor approach to remaining useful life estimation for a slurry pump’, Measurement, 139, p. 140-151, June 2019.
  5. Tse P.*, and Fang Z., ‘Novel Design of a Smart and Harmonized Flexible Printed Coil Sensor to Enhance the Ability to Detect Defects in Pipes’, NDT & E International, 103(2019), 48-61, April, 2019.
  6. Fang Z., and Tse P.*, ‘Demagnetization-based axial magnetized magnetostrictive patch transducers for locating defect in small-diameter pipes by using the non-axisymmetric guided wave’, Structural Health Monitoring, March 5, 2019.
  7. Wang Y., Tse P., Tang B., Qin Y., Deng L., Huang T., and Xu G., ‘Order spectrogram visualization for rolling bearing fault detection under speed variation conditions’, Mechanical Systems and Signal Processing, 122, 580–596, Jan. 2019.
  8. Xu F. and Tse P.*, ‘A method combined refined composite multiscale fuzzy entropy with PSO-SVM for roller bearings fault diagnosis’ (基于精细复合多尺度模糊熵与粒子群优化支持向量机的滚动轴承故障诊断), Journal of Central South University, Dec. 20, 2018.
  9. Xu F., Tse P. and Tse. Y., ‘Roller bearing fault diagnosis using stacked denoising autoencoder in deep learning and Gath–Geva clustering algorithm without principal component analysis and data label’, Applied Soft Computing, volume 73, pages 898-913, Dec. 2018.
  10. Tse P., ‘Novel Fault Diagnosis for Roller Bearing by using Multi Scale Sample Entropy based Clustering’, International Journal of Management and Applied Science (IJMAS)-IJMAS, 4(8), 1-6. August, 2018.
  11. Wang, G., Wei Y.H. and Tse P., ‘Clustering by defining and merging candidates of cluster centers via independence and affinity’, Neurocomputing, NEUCOM-D-18-00702R2, accepted August, 2018.
  12. Wang Y., Tse P., Tang B. Yi Qin, Deng L., Huang T. ‘Kurtogram manifold learning and its application to rolling bearing weak’, Measurement, 127, 533-545, Available online 18 June 2018.
  13. Fang Z., Tse P. and Wei Y., ‘Axial magnetized patch for efficient transduction of longitudinal guided wave and defect identification in concrete-covered pipe risers’, Structural Control and Health Monitoring, Accepted June 11, 2018.
  14. Masurkar F., and Tse P., Yelve N., ‘Investigating the critical aspects of evaluating the material nonlinearity in metal plates using Lamb waves: Theoretical and numerical approach’, Applied Acoustics, accepted June 19, 2018 in-press.
  15. Xu F. and Tse P., ‘Combined DBN in deep learning with AP clustering algorithm for roller bearings fault diagnosis without data label’, Journal of Vibration and Control, 12p., accepted 2018 5 28.
  16. Sun S. and Tse P., ‘Modeling of a horizontal asymmetric U-shaped vibration-based piezoelectric energy harvester (U-VPEH)’, Mechanical Systems and Signal Processing, 114 (2019) 467–485, accepted May 14, 2018, publish Jan. 2019.
  17. Xu F. and Tse P., ‘Automatic roller bearings fault diagnosis using DSAE in deep learning and CFS algorithm’, Soft Computing, pp. 1-12 April 2018.
  18. Wan X., Tse P, Xu G., and Zhang X. Xu G., Zhang, Q.; Fan, H.; Mao, Q.; Dong, M. and; Ma, H., ‘Numerical study on static component generation from the primary Lamb waves propagating in a plate with nonlinearity’, Smart Materials and Structures, 27, 4, 045006, April 2018.
  19. Masurkar F., and Tse P., Yelve N., ‘Evaluation of inherent and dislocation induced material nonlinearity in metallic plates using Lamb waves’, Applied Acoustics, 136 (Feb. 2018) 76–85.
  20. Yelve N., Tse P., Masurkar F., and ‘Theoretical and experimental evaluation of material nonlinearity in metal plates using Lamb waves’, Structural Control and Health Monitoring, 25, 6 e2164, June 2018.
  21. Tse P., Masurkar F., ‘Laser-based guided wave propagation and mode decomposition in detecting the integrity of structural I-beams’, Journal of Computer and Communications, 6(1), 42-55, Jan. 2018.
  22. Wang, G., Peter, W.T. and Yuan, M. Automatic internal crack detection from a sequence of infrared images with a triple-threshold Canny edge detector. Measurement Science and Technology, 29(2), 2018.
  23. Chen J, Tse P, Zhang H., ‘Integrated optical Mach-Zehnder interferometer-based defect detection using laser generated ultrasonic guided wave’ Optics Letters,Vol. 42, Issue 21, pp. 4255-4258, Nov. 1 2017 
  24. Wan, X., Peter, W. T., Chen, J., Xu, G., & Zhang, Q. Second harmonic reflection and transmission from primary S0 mode Lamb wave interacting with a localized microscale damage in a plate: A numerical perspective. Ultrasonics, 82, 57-71, 2018.
  25. Chen, J., Rostami, J., Peter, W.T. and Wan, X. The design of a novel mother wavelet that is tailor-made for continuous wavelet transform in extracting defect-related features from reflected guided wave signals. Measurement, 110, pp.176-191, 2017.
  26. Rostami J., Tse P., and Fang Z. ‘Sparse and Dispersion-based Matching Pursuit for Minimizing the Dispersion Effect Occurred when Using Guided Wave for Pipe Inspection’, Materials.
  27. Rostami J., Chen J. and Tse P., ‘A Signal Processing Approach with Smooth Empirical Mode Decomposition to Reveal Hidden Trace of Corrosion in Highly Contaminated Guided Wave Signals for Concrete-Covered Pipes’, Sensors, 17(302).
  28. Zhong J., Tse P., and Wei Y., ‘An intelligent and improved density and distance-based clustering approach for industrial survey data classification’, Journal of Expert System with Application, 68, 2017.
  29. Sun S. and Tse P ‘Design and performance of a multimodal vibration-based energy harvester model for machine rotational frequencies’, Applied Physics Letters, 110, 243902 (2017).
  30. Zhong J., Tse P., and Wang D., ‘Novel Bayesian inference on optimal parameters of support vector machines and its application to industrial survey data classification’, Neurocomputing, 211, Oct. 26 2016.
  31. Sun S., Tse P, and Tse YL, ‘An enhanced factor analysis of performance degradation assessment on slurry pump impellers’, Shock and Vibrations, vol. 2017, Article ID 1524840, 13 pages, Jan. 2017. .
  32. Tse P., and Wang D., ‘State space formulation of nonlinear vibration responses collected from a dynamic rotor-bearing system: an extension of bearing diagnostics to bearing prognostics’, Sensors 2017, 17, 369, Feb. 14, 2017.
  33. Tse P. and Zhong J. ‘Smart Data Mining System for Automatically Assessing the Performance in Engineering Asset Management’, International Journal of Computer Science and Electronics Engineering (IJCSEE) 5(1), 2017.
  34. Wei Y.H., Tse P., Du B., and Wang Y., ‘An innovative fixed-pole numerical approximation for fractional order systems’, ISA Transactions, Elsevier Vol. 62, May 2016, pp.94-102.
  35. Wei Y.H., Tse P., S. Cheng, and Wang Y., ‘Adaptive backstepping output feedback control for a class of nonlinear fractional order systems”, Nonlinear Dynamics, 86(2), 2016, 1047–1056. Published online: 27 July 2016.
  36. Tse P and Wang D., ‘Enhancing the abilities in assessing the slurry pumps’ performance degradation and estimating their remaining useful lives by using captured vibration signals’, Journal of Vibration and Control, Sept. 9, 2015.
  37. Wan X., Tse P, Xu G., Tao T. and Zhang Q. ‘Analytical and numerical studies of approximate phase velocity matching based nonlinear S0 mode Lamb waves for the detection of evenly distributed microstructural changes”, Smart Materials and Structures, 25(4) (2016) 045023 (20pp), April 2016.
  38. Wan X., Wang D., Tse P., Xu G., and Zhang Q., ‘A critical study of different dimensionality reduction methods for gear crack degradation assessment under different operating conditions’, Measurement, Vol. 78, 138-150, 2016.
  39. Wan X., Xu G., Zhang Q., Tse P., and Tan H., ‘A quantitative method for evaluating numerical simulation accuracy of time-transient Lamb wave propagation with its applications to selecting appropriate element size and time step’, 64: 25-42, Ultrasonics, Jan, 2016.
  40. Wang D., Tsui K., Tse P., and Zuo M., ‘Principal Components of Superhigh-Dimensional Statistical Features and Support Vector Machine for Improving Identification Accuracies of Different Gear Crack Levels under Different Working Conditions’, Shock and Vibration, Vol. 2015, Article ID 420168, 14 pages, 2015. 
  41. Wang D., W. Guo and Tse P., ‘An enhanced empirical mode decomposition method for blind component separation of a single-channel vibration signal mixture’, Journal of Vibration and Control, Vol. 22(11), June 2016, pp. 2603–2618. 
  42. Esmaeili M., Oskouei A., Mirhadizadeh S., Tse P., and Hoshyar N. ‘Prediction of hydrodynamic bearing performance based on effective parameters by neural network’, International Journal of Engineering and Management Science, Vol. 7(2), April 15, 2016. 
  43. Ng S., Cabrerab J., Tse P., Chen A., and Tsui K., ‘Distance-based Analysis of Dynamical Systems Reconstructed from Vibrations for Bearing Diagnostics’, Nonlinear Dynamics, Vol. 80(1-2), 147-165, April 2015.
  44. Zhang Q., Tse P., Ruana D. and Xua G., ‘Remaining Useful Life Estimation for Mechanical Systems Based on Similarity of Phase Space Trajectory’, Expert Systems with Application, 42 (2015) 2353–2360, on-line Nov. 4 2014. 
  45. Wang D., and Tse P., ‘Prognostics of slurry pumps based on a moving-average wear degradation index and a general sequential Monte Carlo method’, Mechanical Systems and Signal Processing, vol. 56-57 (2015) 213-229.
  46. Wang D. Sun S. and Tse P., ‘A General Sequential Monte Carlo Method based Optimal Wavelet Filter: a Bayesian Approach for Extracting Bearing Fault Features’, Mechanical Systems and Signal Processing, vol. 52-53 (2015) 293-308, Accepted July 7, 2014. Online August, 2014.
  47. Tse, Y and Tse P., ‘A low-cost and effective automobile engine fault diagnosis by using instantaneous angular velocity evaluation’, Special Issue in International Journal of Strategic Engineering Asset Management (IJSEAM), July 25, 2014 Vol. 2, No.1, pp.2 -21.
  48. C. Shen, D. Wang, Y. Liu, g F. Kon, and Peter W. Tse. “Recognition of rolling bearing fault patterns and sizes based on two-layer support vector regression machines”, Smart Structures and Systems, 13(2014) pp. 453-471. 
  49. S. Ng, Peter W. Tse and K. Tsui, ‘A One-Versus-All Class Binarization Strategy for Bearing Diagnostics of Concurrent Defects’, Sensors 14 (2014) pp. 1295-1321.
  50. C. Shen, F. Liu, D. Wang, A. Zhang, F. Kong and Peter W. Tse. ‘Doppler transient modeling based on Laplace wavelet and spectrum correlation assessment for locomotive bearing fault diagnosis’, Sensors, 13(2013) pp.15726-15746.
  51. J. Hu and Peter W. Tse, ‘A relevance vector machine-based approach with application to oil sand pump prognostics’, Sensors, 13(2013) pp.12663-12686.
  52. D. Wang, C. Shen and Peter W. Tse, ‘A novel adaptive wavelet stripping algorithm for extracting the transients caused by bearing localized faults’, Journal of Sound and Vibration, 332(2013), pp. 6871-6890.
  53. Y. Tse and Peter W. Tse, ‘A low-cost and effective automobile engine fault diagnosis by using instantaneous angular velocity evaluation’, Special Issue in International Journal of Strategic Engineering Asset Management, to appear.
  54. Chuan Li and Peter W. Tse, Fabrication and testing of an energy-harvesting hydraulic damper, Smart Materials and Structures, 22 (2013)  065024.
  55. Peter W. Tse and D. Wang, “The design of a new sparsogram for fast bearing fault diagnosis Part 1 of the two related manuscripts that have a joint title as “Two Automatic Vibration-based Fault Diagnostic Methods using the Novel Sparsity Measurement – Parts 1 and 2”, Mechanical Systems and Signal Processing, 40(2013) pp. 499-519.
  56. Peter W. Tse and D. Wang, “The automatic selection of an optimal wavelet filter and its enhancement by the new sparsogram for bearing fault detection Part 2 of the two related manuscripts that have a joint title as “Two Automatic Vibration-based Fault Diagnostic Methods using the Novel Sparsity Measurement – Parts 1 and 2”, Mechanical Systems and Signal Processing, 40 (2013), pp. 520-544. 
  57. Peter W. Tse, Xiaojuan Wang, Characterization of pipeline defect in guided-waves based inspection through matching pursuit with the optimized dictionary, NDT & E International, 54 (2013) pp.171-182.
  58. C Shen, D Wang, F Kong, PW Tse, “Fault diagnosis of rotating machinery based on the statistical parameters of wavelet packet paving and a generic support vector regressive classifier”, Measurement 46 (2013), pp. 1551-1564.
  59. Wei Guo, Peter W. Tse, A novel signal compression method based on optimal ensemble empirical mode decomposition for bearing vibration signals, Journal of Sound and Vibration, 332 (2013), pp.423-441.
  60. C. Shen, Q. He, F. Kong, and P. W. Tse, “A fast and adaptive varying-scale morphological analysis method for rolling element bearing fault diagnosis”, Journal of Mechanical Engineering Science, 227(2013), pp.1362–1370.
  61. Dong Wang, Peter W.Tse, Kwok Leung Tsui, “An enhanced Kurtogram method for fault diagnosis of rolling element bearings”, Mechanical Systems and Signal Processing, 35(2013), pp.176–199.

Previously Selected Publications (2012 and before)

  1. D. Wang, Peter W. Tse ,”A new blind fault component separation algorithm for a single-channel mechanical signal mixture”, Journal of Sound and Vibration 331 (2012), pp.4956–4970.
  2. D. Wang, Peter W. Tse and Y. Tse, “A morphogram with the optimal selection of parameters used in morphological analysis for enhancing the ability in bearing fault diagnosis” Measurement Science and Technology 23 (2012) 065001 (15pp).
  3. W. Guo, Peter W. Tse , A. Djordjevich, “Faulty bearing signal recovery from large noise using a hybrid method based on spectral kurtosis and ensemble empirical mode decomposition” Measurement 45 (2012) pp. 1308-1322.
  4. F. Di Maio , J. Hu, Peter W. Tse, K. Tsui, E. Zio, and M. Pecht, ‘Ensemble-approaches for clustering health status of oil sand pumps”, Expert Systems with Applications, 39(5), Apr 2012, pp. 4847-4859.
  5. W. Guo, M. Hua, Peter W. Tse, and A. Mok, “Process Parameters Selection for Laser Polishing DF2 (AISI O1) by Nd:YAG Pulsed Laser Using Orthogonal Design”, International Journal of Advanced Manufacturing Technology, 59, Aug 2011, pp. 1009-1023.
  6. Peter W. Tse, X. Liu , Z. Liu, B. Wu, C. He, and X. Wang, “An Innovative Design of Using Flexible Printed Coil for Magnetostrictive-based Longitudinal Guided Wave Sensor in Steel Strand Inspection”, Smart Materials and Structures. 20 (2011) 055001, May 2011. (Featured article). 
  7. X. Wang, Peter W. Tse and A. Dordjevich, “Evaluation of pipeline defect’s characteristic axial length via model-based parameter estimation in ultrasonic guided wave-based inspection” Measurement Science and Technology 22 (2011) 025701 (13pp).
  8. D. Wang, Peter W. Tse, W. Guo and Q. Miao, “Support vector data description for fusion of multiple health indicators for enhancing gearbox fault diagnosis and prognosis” Measurement Science and Technology 22 (2011) 025102 (13pp).
  9. S. Savovic, A. Djordjevich, Peter W. Tse, and D. Krstic, “Radon diffusion in an anhydrous andesitic melt: a finite difference solution”, Journal of Environment Radioactivity, 102(2), 2011, Feb 2011, pp. 103-106.
  10. S. Savovic, Djordjevich A., Peter W. Tse, and D. Nikezic, “Explicit finite difference solution of the diffusion equation describing the flow of radon through soil”, Applied Radiation and Isotopes, 69(1), Jan 2011, pp. 237-240.
  11. S. Savovic , A. Djordjevich, Peter W. Tse, J. Zubia, J. Mateo, and M. Losada, “Determination of the width of the output angular power distribution in step-index multimode optical fibers” Journal of Optics. (Optics has been renamed to Journal of Optics A-pure and applied optics, 12(11), Nov 2010, pp. 1-5. 
  12. A. Djordjevich, S. Savovic, Peter W. Tse, B. Drljaca, and A. Simovic, “Mode coupling in strained and unstrained step-index glass optical fibers”, Applied Optics, 49(27), Sep 2010, pp. 5076- 5080.
  13. X. Wang, Peter W. Tse, C. Mechefske and M. Hua, “Experimental investigation of the reflection in guided wave-based inspection for the characterization of pipeline defects”, the Journal of NDT&E International, Vol.43(4), 2010, pp.365-374.
  14. J. Rafiee, M. Rafiee, Peter W. Tse,, “Application of Mother Wavelet Functions for Automatic Gear and bearing Fault Diagnosis”, Expert Systems with Applications, 37(6), Jun 2010, pp. 4568-4579. 
  15. V. Sotiris, Peter W. Tse, and M. Pecht, “Anomaly detection through a bayesian support vector machine”, IEEE Transactions on Reliability, 59(2), Jun 2010, pp.277-286.
  16. Y. Li, Peter W. Tse , X. Yang and J. Yang, “EMD-based fault diagnosis for abnormal clearance between contacting components in a diesel engine”, Mechanical Systems and Signal Processing, 24(1), Jan 2010, pp. 193-210. 
  17. J. Rafiee and Peter W. Tse, “Use of autocorrelation of wavelet coefficients for fault diagnosis”, Mechanical Systems and Signal Processing, 23(5), Jul 2009, pp. 1554-1572. (The second most downloaded paper as of Sep 2009).
  18. C. Chan and Peter W. Tse, “A novel, fast, reliable data transmission algorithm for wireless machine health monitoring”, IEEE Transactions on Reliability (invited special section), 58, No. 2, Jun 2009,pp. 295-304. 
  19. Peter W. Tse, and X. Wang, “Semi-quantitative analysis of defect in pipelines through the use of technique of ultrasonic guided waves”, Key Engineering Materials, 413-414, Special Volume – Damage Assessment of Structure VIII., May 2009, pp. 109-116. 
  20. J. Rafiee, Peter W. Tse, A.Harifi, and M. Sadeghi, “A novel technique for selecting mother wavelet function using an intelligent fault diagnosis system”, Expert Systems with Applications, 36(3P1), Apr 2009, pp.4862-4875. 
  21. Y. Li, Peter W. Tse, and X. Wang, “Recovery of vibration signal based on a super-exponential algorithm”, Journal of Sound and Vibration, 311, Issues 1-2, Mar 2008, pp. 537-553.
  22. Peter W. Tse, S. Gontarz., and W. Wang, “Enhanced eigenvector algorithm for recovering multiple sources of vibration signals in machine fault diagnosis”, Mechanical Systems and Signal Processing, 21, No. 7, Oct 2007, pp. 2794-2813. 
  23. W. Wang, Peter W. Tse, and J. Lee, “Remote machine maintenance system through internet and mobile communication”, International Journal of Advanced Manufacturing Technology, 31, No. 7-8, Jan 2007, pp. 783-789. 
  24. Z. Peng, F. Chu, Peter W. Tse, “Singularity analysis of the vibration signals using wavelet modulus maxima method”, Mechanical Systems and Signal Processing, 21, Issue 2, Feb 2007, pp. 780-794. 
  25. Peter W. Tse, J. Zhang, and X. Wang, “Blind-source-separation and blind equalization algorithms for mechanical signal separation and identification”, Journal of Vibration and Control, 12, Issue 4, Apr 2006, pp. 395-423. 
  26. Z. Peng, Peter W. Tse, and F. Chu, “An improved Hilbert – Huang transform and its application for vibration signals snalysis”, Journal of Sound and Vibration, 286, Aug 2005, pp. 187-205. (Awarded as one of the most read and cited articles in year 2006).
  27. Z. Peng, Peter W. Tse, and F. Chu, “A comparison study of improved Hilbert-Huang transform and wavelet transform: application to fault diagnosis for rolling bearing”, Mechanical Systems and Signal Processing, 19(5), Sep 2005, pp. 974-988. (Ranked first of the top 25 articles in the review list with bibliography).
  28. W. Yang and Peter W. Tse, “An advanced strategy for detecting impulses in mechanical signals”, Journal of Vibration and Acoustics – Transactions of the ASME, 127 (3), Jun 2005, pp. 280-284.
  29. J. Wang, Peter W. Tse, L. He, R. Yeung, “Remote sensing, diagnosis and collaborative maintenance with web-enabled virtual instruments and mini-Servers”, International Journal of Advanced Manufacturing Technology, 24(9-10), Nov 2004, pp. 764-772.
  30. Peter W. Tse, W. Yang, and H. Tam, “Machine fault diagnosis through an effective exact wavelet analysis”, Journal of Sound and Vibration, 277(4-5), Nov 2004, pp.1005-1024. 
  31. K. Ip, Peter W. Tse and H. Tam, “Extraction of patch-induced Lamb waves using a wavelet transform”, Smart Material and Structures, 13(4), Jun, 2004, pp.861-872 (ISSN 0964-1726). 
  32. W. Lai, Peter W. Tse, G. Zhang, and T. Shi, “Classification of gear faults using cumulants and the radial basis function network”, Mechanical Systems and Signal Processing, 18(2), Mar 2004, pp. 381-389.