The Experts below are selected from a list of 285 Experts worldwide ranked by ideXlab platform

Jianji Chan - One of the best experts on this subject based on the ideXlab platform.

  • faulted gear identification of a rotating machinery based on wavelet transform and artificial neural network
    Expert Systems With Applications, 2009
    Co-Authors: Jian-da Wu, Jianji Chan
    Abstract:

    In this paper, a condition monitoring and faults identification technique for rotating machineries using wavelet transform and artificial neural network is described. Most of the conventional techniques for condition monitoring and fault diagnosis in rotating machinery are based chiefly on analyzing the difference of vibration signal amplitude in the time domain or frequency spectrum. Unfortunately, in some applications, the vibration signal may not be available and the performance is limited. However, the Sound Emission signal serves as a promising alternative to the fault diagnosis system. In the present study, the Sound Emission of gear-set is used to evaluate the proposed fault diagnosis technique. In the experimental work, a continuous wavelet transform technique combined with a feature selection of energy spectrum is proposed for analyzing fault signals in a gear-set platform. The artificial neural network techniques both using probability neural network and conventional back-propagation network are compared in the system. The experimental results pointed out the Sound Emission can be used to monitor the condition of the gear-set platform and the proposed system achieved a fault recognition rate of 98% in the experimental gear-set platform.

Jian-da Wu - One of the best experts on this subject based on the ideXlab platform.

  • faulted gear identification of a rotating machinery based on wavelet transform and artificial neural network
    Expert Systems With Applications, 2009
    Co-Authors: Jian-da Wu, Jianji Chan
    Abstract:

    In this paper, a condition monitoring and faults identification technique for rotating machineries using wavelet transform and artificial neural network is described. Most of the conventional techniques for condition monitoring and fault diagnosis in rotating machinery are based chiefly on analyzing the difference of vibration signal amplitude in the time domain or frequency spectrum. Unfortunately, in some applications, the vibration signal may not be available and the performance is limited. However, the Sound Emission signal serves as a promising alternative to the fault diagnosis system. In the present study, the Sound Emission of gear-set is used to evaluate the proposed fault diagnosis technique. In the experimental work, a continuous wavelet transform technique combined with a feature selection of energy spectrum is proposed for analyzing fault signals in a gear-set platform. The artificial neural network techniques both using probability neural network and conventional back-propagation network are compared in the system. The experimental results pointed out the Sound Emission can be used to monitor the condition of the gear-set platform and the proposed system achieved a fault recognition rate of 98% in the experimental gear-set platform.

  • Investigation of engine fault diagnosis using discrete wavelet transform and neural network
    Expert Systems with Applications, 2008
    Co-Authors: Jian-da Wu, Chiu-hong Liu
    Abstract:

    An investigation of a fault diagnostic technique for internal combustion engines using discrete wavelet transform (DWT) and neural network is presented in this paper. Generally, Sound Emission signal serves as a promising alternative to the condition monitoring and fault diagnosis in rotating machinery when the vibration signal is not available. Most of the conventional fault diagnosis techniques using Sound Emission and vibration signals are based on analyzing the signal amplitude in the time or frequency domain. Meanwhile, the continuous wavelet transform (CWT) technique was developed for obtaining both time-domain and frequency-domain information. Unfortunately, the CWT technique is often operated over a longer computing time. In the present study, a DWT technique which is combined with a feature selection of energy spectrum and fault classification using neural network for analyzing fault signal is proposed for improving the shortcomings without losing its original property. The features of the Sound Emission signal at different resolution levels are extracted by multi-resolution analysis and Parseval’s theorem [Gaing, Z. L. (2004). Wavelet-based neural network for power disturbance recognition and classification. IEEE Transactions on Power Delivery 19, 1560–1568]. The algorithm is obtained from previous work by Daubechies [Daubechies, I. (1988). Orthonormal bases of compactly supported wavelets. Communication on Pure and Applied Mathematics 41, 909–996.], the“db4”, “db8” and “db20” wavelet functions are adopted to perform the proposed DWT technique. Then, these features are used for fault recognition using a neural network. The experimental results indicated that the proposed system using the Sound Emission signal is effective and can be used for fault diagnosis of various engine operating conditions.

Janez Grum - One of the best experts on this subject based on the ideXlab platform.

  • Cracking perception of machine components with Sound Emission during steel quenching
    International Journal of Microstructure and Materials Properties, 2019
    Co-Authors: Franc Ravnik, Janez Grum
    Abstract:

    Quenching and tempering often represent a stage near the end of the manufacturing process of machine components. The purpose of selecting the most suitable quenching parameters and controlling the hardening process is to ensure the required hardness and the residual stresses of a machine part. This paper includes the investigation of certain acoustic events during quenching. The possibility of understanding the relation between a connection during Sound Emission with the wetting kinematic of the quenching agent and a heated specimen with other phenomena during quenching was examined. It was determined that acoustic signals could identify the suitability, i.e.; the quality of the quenching process to ensure better control of the process. The possibility of acoustic signals caused by workpiece deformation and crack formation due to high internal stresses were examined. A comparison of results shows that this possibility can lead to an applicability of controlling the hardening process and quality of steel parts.

  • Sound Emission phenomena analysis at boundary layer during steel quenching
    International Journal of Microstructure and Materials Properties, 2016
    Co-Authors: Franc Ravnik, Janez Grum
    Abstract:

    Mechanical properties after quenching, such as residual stresses and hardenability depend on optimum parameters of a quenching process chosen, and monitoring of the process itself. In order to control the hardening process, one should be able to monitor the quenching process in real time. The paper treats an experimental setup comprising detection of Sound Emission together with some results obtained in the course of quenching process. Due to heat transfer from a specimen to a quenching medium, film boiling and nucleate boiling occur around a heated specimen, which strongly affects Sound-pressure signals emitted from the surface. Sound-pressure signals are shown in 3D diagrams. The analysis of Sound-Emission signals are connected with wettings cinematics and can provide useful information that confirms differences occurring in quenching with different quenching media, different specimen's shapes and under different quenching conditions. They can give useful information and confirm the differences caused by different quenching conditions.

  • Relation between Sound Emission Occurring during Quenching and Mechanical Properties of the Steel after Quenching
    BHM Berg- und Hüttenmännische Monatshefte, 2010
    Co-Authors: Franc Ravnik, Janez Grum
    Abstract:

    Quenching and tempering often represent the final stage in the production of machine components of the manufacturing process. Final mechanical properties, such as residual stress and hardness profiles, depend on optimum parameters of a quenching process and monitoring of the process itself. The paper treats an experimental setup comprising detection of Sound Emission in the course of a quenching process. Due to heat transfer from a specimen's surface to a quenching medium, film boiling and nucleate boiling occur round a heated specimen, which strongly affects quenching. An investigation of Sound Emission in the quenching process was carried out with cylindrical specimens made of chrome-molybdenum heat treatable steel 42CrMo quenched in different quenching media. Sound-pressure signals demonstrated by different amplitudes depending on time at different frequencies are shown in 3-D diagrams. It has turned out that an analysis of Sound-Emission signals can provide useful information that confirms differences occurring in quenching with different quenching media, different specimen's shapes, and under different quenching conditions. Analysis of the quenching results obtained from Sound-Emission signals during the quenching process can be confirmed by variations of residual stresses and hardness in the cross section. The results lead to the applicability of the new approach to the control of the hardening processes of steels.

  • Sound Emitted at Boundary Layer During Steel Quenching
    Strojniški vestnik, 2009
    Co-Authors: Franc Ravnik, Janez Grum
    Abstract:

    Quenching and tempering often represents the final stage in the manufacturing process of machine parts. The choice of optimum parameters of a quenching process and monitoring of the process itself ensures the achievement of the specified hardness and residual stress in the surface layer of the machine component. A hardening process can be controlled by selecting different quenching parameters (quenching media, its temperature, specimen temperature, ...). In order to control the hardening process, one should be able to monitor the quenching process in real time. This paper treats an experimental setup comprising detection of Sound Emission and some of the results obtained during the quenching process. Due to the heat transfer from the specimen to the quenching medium, film boiling and nucleate boiling occur around the heated object, which strongly affects quenching. Bubble formation, their development and implosions, and disappearing around the surface causes Sound Emission whose intensity depends on the intensity of the bubbles' oscillation and the speed of their disappearing, i.e. on the quenching process. Sound-pressure signals demonstrated by different amplitudes depending on time, at different frequencies, are shown in 3D diagrams. It was established that an analysis of Sound Emission signals can provide useful information that confirms the differences occurring in quenching with different quenching media and under different quenching conditions. Analyses of Sound Emission demonstrated that Sound Emission during quenching process can be used for monitoring the hardening process. Analysis of the quenching results and Sound Emission signals during the process itself confirm the applicability of the new approach to the controlling ofsteel quenching.

Chiu-hong Liu - One of the best experts on this subject based on the ideXlab platform.

  • Investigation of engine fault diagnosis using discrete wavelet transform and neural network
    Expert Systems with Applications, 2008
    Co-Authors: Jian-da Wu, Chiu-hong Liu
    Abstract:

    An investigation of a fault diagnostic technique for internal combustion engines using discrete wavelet transform (DWT) and neural network is presented in this paper. Generally, Sound Emission signal serves as a promising alternative to the condition monitoring and fault diagnosis in rotating machinery when the vibration signal is not available. Most of the conventional fault diagnosis techniques using Sound Emission and vibration signals are based on analyzing the signal amplitude in the time or frequency domain. Meanwhile, the continuous wavelet transform (CWT) technique was developed for obtaining both time-domain and frequency-domain information. Unfortunately, the CWT technique is often operated over a longer computing time. In the present study, a DWT technique which is combined with a feature selection of energy spectrum and fault classification using neural network for analyzing fault signal is proposed for improving the shortcomings without losing its original property. The features of the Sound Emission signal at different resolution levels are extracted by multi-resolution analysis and Parseval’s theorem [Gaing, Z. L. (2004). Wavelet-based neural network for power disturbance recognition and classification. IEEE Transactions on Power Delivery 19, 1560–1568]. The algorithm is obtained from previous work by Daubechies [Daubechies, I. (1988). Orthonormal bases of compactly supported wavelets. Communication on Pure and Applied Mathematics 41, 909–996.], the“db4”, “db8” and “db20” wavelet functions are adopted to perform the proposed DWT technique. Then, these features are used for fault recognition using a neural network. The experimental results indicated that the proposed system using the Sound Emission signal is effective and can be used for fault diagnosis of various engine operating conditions.

Franc Ravnik - One of the best experts on this subject based on the ideXlab platform.

  • Cracking perception of machine components with Sound Emission during steel quenching
    International Journal of Microstructure and Materials Properties, 2019
    Co-Authors: Franc Ravnik, Janez Grum
    Abstract:

    Quenching and tempering often represent a stage near the end of the manufacturing process of machine components. The purpose of selecting the most suitable quenching parameters and controlling the hardening process is to ensure the required hardness and the residual stresses of a machine part. This paper includes the investigation of certain acoustic events during quenching. The possibility of understanding the relation between a connection during Sound Emission with the wetting kinematic of the quenching agent and a heated specimen with other phenomena during quenching was examined. It was determined that acoustic signals could identify the suitability, i.e.; the quality of the quenching process to ensure better control of the process. The possibility of acoustic signals caused by workpiece deformation and crack formation due to high internal stresses were examined. A comparison of results shows that this possibility can lead to an applicability of controlling the hardening process and quality of steel parts.

  • Sound Emission phenomena analysis at boundary layer during steel quenching
    International Journal of Microstructure and Materials Properties, 2016
    Co-Authors: Franc Ravnik, Janez Grum
    Abstract:

    Mechanical properties after quenching, such as residual stresses and hardenability depend on optimum parameters of a quenching process chosen, and monitoring of the process itself. In order to control the hardening process, one should be able to monitor the quenching process in real time. The paper treats an experimental setup comprising detection of Sound Emission together with some results obtained in the course of quenching process. Due to heat transfer from a specimen to a quenching medium, film boiling and nucleate boiling occur around a heated specimen, which strongly affects Sound-pressure signals emitted from the surface. Sound-pressure signals are shown in 3D diagrams. The analysis of Sound-Emission signals are connected with wettings cinematics and can provide useful information that confirms differences occurring in quenching with different quenching media, different specimen's shapes and under different quenching conditions. They can give useful information and confirm the differences caused by different quenching conditions.

  • Relation between Sound Emission Occurring during Quenching and Mechanical Properties of the Steel after Quenching
    BHM Berg- und Hüttenmännische Monatshefte, 2010
    Co-Authors: Franc Ravnik, Janez Grum
    Abstract:

    Quenching and tempering often represent the final stage in the production of machine components of the manufacturing process. Final mechanical properties, such as residual stress and hardness profiles, depend on optimum parameters of a quenching process and monitoring of the process itself. The paper treats an experimental setup comprising detection of Sound Emission in the course of a quenching process. Due to heat transfer from a specimen's surface to a quenching medium, film boiling and nucleate boiling occur round a heated specimen, which strongly affects quenching. An investigation of Sound Emission in the quenching process was carried out with cylindrical specimens made of chrome-molybdenum heat treatable steel 42CrMo quenched in different quenching media. Sound-pressure signals demonstrated by different amplitudes depending on time at different frequencies are shown in 3-D diagrams. It has turned out that an analysis of Sound-Emission signals can provide useful information that confirms differences occurring in quenching with different quenching media, different specimen's shapes, and under different quenching conditions. Analysis of the quenching results obtained from Sound-Emission signals during the quenching process can be confirmed by variations of residual stresses and hardness in the cross section. The results lead to the applicability of the new approach to the control of the hardening processes of steels.

  • Sound Emitted at Boundary Layer During Steel Quenching
    Strojniški vestnik, 2009
    Co-Authors: Franc Ravnik, Janez Grum
    Abstract:

    Quenching and tempering often represents the final stage in the manufacturing process of machine parts. The choice of optimum parameters of a quenching process and monitoring of the process itself ensures the achievement of the specified hardness and residual stress in the surface layer of the machine component. A hardening process can be controlled by selecting different quenching parameters (quenching media, its temperature, specimen temperature, ...). In order to control the hardening process, one should be able to monitor the quenching process in real time. This paper treats an experimental setup comprising detection of Sound Emission and some of the results obtained during the quenching process. Due to the heat transfer from the specimen to the quenching medium, film boiling and nucleate boiling occur around the heated object, which strongly affects quenching. Bubble formation, their development and implosions, and disappearing around the surface causes Sound Emission whose intensity depends on the intensity of the bubbles' oscillation and the speed of their disappearing, i.e. on the quenching process. Sound-pressure signals demonstrated by different amplitudes depending on time, at different frequencies, are shown in 3D diagrams. It was established that an analysis of Sound Emission signals can provide useful information that confirms the differences occurring in quenching with different quenching media and under different quenching conditions. Analyses of Sound Emission demonstrated that Sound Emission during quenching process can be used for monitoring the hardening process. Analysis of the quenching results and Sound Emission signals during the process itself confirm the applicability of the new approach to the controlling ofsteel quenching.