The Experts below are selected from a list of 13857 Experts worldwide ranked by ideXlab platform

Ronald Gordon Harley - One of the best experts on this subject based on the ideXlab platform.

  • incipient bearing fault detection via motor stator current Noise Cancellation using wiener filter
    IEEE Transactions on Industry Applications, 2009
    Co-Authors: Wei Zhou, Bin Lu, Thomas G. Habetler, Ronald Gordon Harley
    Abstract:

    Current-based monitoring can offer significant economic savings and implementation advantages over traditional vibration monitoring for bearing fault detection. The key issue in current-based bearing fault detection is to extract bearing fault signatures from the motor stator current. Since the bearing fault signature in the stator current is typically very subtle, particularly when the fault is at an incipient stage, it is difficult to detect the fault signature directly. Therefore, in this paper, the bearing fault signature is detected alternatively by estimating and removing nonbearing fault components via a Noise Cancellation method. In this method, all the components of the stator current that are not related to bearing faults are regarded as Noise and are estimated by a Wiener filter. Then, all these Noise components are cancelled out by their estimates in a real-time fashion, and a fault indicator is established based on the remaining components which are mainly caused by bearing faults. Machine parameters, bearing dimensions, nameplate values, and the stator current spectrum distribution are not required in the method. The results of online experiments with a 20-hp induction motor under multiple load levels have confirmed the effectiveness of this method.

  • bearing fault detection via stator current Noise Cancellation and statistical control
    IEEE Transactions on Industrial Electronics, 2008
    Co-Authors: Wei Zhou, Thomas G. Habetler, Ronald Gordon Harley
    Abstract:

    This paper proposes a new approach to detect in situ bearing faults via stator current monitoring. For in situ bearing faults, the characteristic bearing fault frequencies may not exist, particularly at an early stage. In addition, the bearing fault signatures are usually subtle compared to the dominant components in the sampled stator current. Therefore, in this paper, a Noise Cancellation technique is used to suppress those dominant components that are not related to a potential bearing fault. The remaining components, i.e., the Noise-cancelled stator current, are then closely related to the health condition of the bearing. Furthermore, it is observed that under the presence of a bearing fault, the Noise-cancelled stator current displays a significant amount of degrees of uncontrolled variation in its magnitude. The uncontrolled variation is detected by observing the samples falling outside the three-sigma limits on Shewhart's control charts. Therefore, it is possible to detect in situ bearing faults by detecting the variation in magnitude of the Noise-cancelled stator current, as verified by online experiments performed in this paper.

  • incipient bearing fault detection via stator current Noise Cancellation using wiener filter
    IEEE International Symposium on Diagnostics for Electric Machines Power Electronics and Drives, 2007
    Co-Authors: Wei Zhou, Ronald Gordon Harley, Thomas G. Habetler, Bin Lu
    Abstract:

    Current-based monitoring can offer significant economic savings and implementation advantages over traditional vibration monitoring for bearing fault detection. A key issue in current-based bearing fault detection is to extract bearing fault signature from motor stator current. In this paper bearing fault signature in motor stator current is detected by estimating and removing non-bearing fault components via a Noise Cancellation method. In this method, the components of the stator current that are not related to bearing faults are regarded as Noise and are estimated by a Wiener filter. These Noise components are then cancelled by their estimates in a real time fashion and a fault indicator is established based on the remaining components that are related to bearing faults. Machine parameters, bearing dimensions, nameplate values, or stator current spectrum distributions are not required in the method. The results of on-line experiments with a 20-horsepower induction motor have verified the effectiveness of this method.

Wei Zhou - One of the best experts on this subject based on the ideXlab platform.

  • incipient bearing fault detection via motor stator current Noise Cancellation using wiener filter
    IEEE Transactions on Industry Applications, 2009
    Co-Authors: Wei Zhou, Bin Lu, Thomas G. Habetler, Ronald Gordon Harley
    Abstract:

    Current-based monitoring can offer significant economic savings and implementation advantages over traditional vibration monitoring for bearing fault detection. The key issue in current-based bearing fault detection is to extract bearing fault signatures from the motor stator current. Since the bearing fault signature in the stator current is typically very subtle, particularly when the fault is at an incipient stage, it is difficult to detect the fault signature directly. Therefore, in this paper, the bearing fault signature is detected alternatively by estimating and removing nonbearing fault components via a Noise Cancellation method. In this method, all the components of the stator current that are not related to bearing faults are regarded as Noise and are estimated by a Wiener filter. Then, all these Noise components are cancelled out by their estimates in a real-time fashion, and a fault indicator is established based on the remaining components which are mainly caused by bearing faults. Machine parameters, bearing dimensions, nameplate values, and the stator current spectrum distribution are not required in the method. The results of online experiments with a 20-hp induction motor under multiple load levels have confirmed the effectiveness of this method.

  • bearing fault detection via stator current Noise Cancellation and statistical control
    IEEE Transactions on Industrial Electronics, 2008
    Co-Authors: Wei Zhou, Thomas G. Habetler, Ronald Gordon Harley
    Abstract:

    This paper proposes a new approach to detect in situ bearing faults via stator current monitoring. For in situ bearing faults, the characteristic bearing fault frequencies may not exist, particularly at an early stage. In addition, the bearing fault signatures are usually subtle compared to the dominant components in the sampled stator current. Therefore, in this paper, a Noise Cancellation technique is used to suppress those dominant components that are not related to a potential bearing fault. The remaining components, i.e., the Noise-cancelled stator current, are then closely related to the health condition of the bearing. Furthermore, it is observed that under the presence of a bearing fault, the Noise-cancelled stator current displays a significant amount of degrees of uncontrolled variation in its magnitude. The uncontrolled variation is detected by observing the samples falling outside the three-sigma limits on Shewhart's control charts. Therefore, it is possible to detect in situ bearing faults by detecting the variation in magnitude of the Noise-cancelled stator current, as verified by online experiments performed in this paper.

  • incipient bearing fault detection via stator current Noise Cancellation using wiener filter
    IEEE International Symposium on Diagnostics for Electric Machines Power Electronics and Drives, 2007
    Co-Authors: Wei Zhou, Ronald Gordon Harley, Thomas G. Habetler, Bin Lu
    Abstract:

    Current-based monitoring can offer significant economic savings and implementation advantages over traditional vibration monitoring for bearing fault detection. A key issue in current-based bearing fault detection is to extract bearing fault signature from motor stator current. In this paper bearing fault signature in motor stator current is detected by estimating and removing non-bearing fault components via a Noise Cancellation method. In this method, the components of the stator current that are not related to bearing faults are regarded as Noise and are estimated by a Wiener filter. These Noise components are then cancelled by their estimates in a real time fashion and a fault indicator is established based on the remaining components that are related to bearing faults. Machine parameters, bearing dimensions, nameplate values, or stator current spectrum distributions are not required in the method. The results of on-line experiments with a 20-horsepower induction motor have verified the effectiveness of this method.

Bertan Bakkaloglu - One of the best experts on this subject based on the ideXlab platform.

  • a 90 nm cmos 5 ghz ring oscillator pll with delay discriminator based active phase Noise Cancellation
    IEEE Journal of Solid-state Circuits, 2013
    Co-Authors: Seungkee Min, T Copani, S Kiaei, Bertan Bakkaloglu
    Abstract:

    Ring oscillators (ROs) provide a low-cost digital VCO solution in fully integrated PLLs. However, due to their supply Noise sensitivity and high Noise floor, their applications have been limited to low-performance applications. The proposed architecture introduces an analog feed-forward adaptive phase-Noise Cancellation architecture that extracts and suppresses phase Noise of ROs outside the PLL bandwidth. The proposed technique can improve the phase Noise at an arbitrary offset frequency and bandwidth, and, after initial calibration for gain, it is insensitive to process, voltage, and temperature variations. An experimental fractional PLL, with a loop bandwidth of 200 kHz, is utilized to demonstrate the active phase-Noise Cancellation approach. The Cancellation loop is designed to suppress the phase Noise at 1-MHz offset by 12.5 dB and reference spur by 13 dB with less than 17% increase in the overall power consumption at 5.1-GHz frequency. The measured phase Noise at 1-MHz offset after Cancellation is ${-}$ 105 dBc/Hz. The proposed RO-PLL is fabricated in 90-nm CMOS process. With Noise Cancellation loop enabled, the PLL consumes 24.7 mA at 1.2-V supply.

  • a 90nm cmos 5ghz ring oscillator pll with delay discriminator based active phase Noise Cancellation
    Radio Frequency Integrated Circuits Symposium, 2012
    Co-Authors: Seungkee Min, T Copani, S Kiaei, Bertan Bakkaloglu
    Abstract:

    Ring-oscillators provide a low-cost digital VCO solution in fully integrated PLLs, but due to their supply Noise sensitivity and high Noise floor, their applications have been limited. A fully integrated feed-forward, delay-discriminator based adaptive Noise-Cancellation architecture that improves phase Noise characteristic of ring-oscillators outside the PLL bandwidth is presented. Proposed technique can improve the phase Noise in an arbitrary offset frequency and bandwidth, and it is insensitive to process and temperature variations. The proposed Cancellation loop suppresses the phase Noise at 1 MHz offset by 12.5dB and reference spur by 13dB, with 3.7mA power consumption. The measured phase Noise at 1 MHz offset is −105 dBc/Hz. The proposed PLL is fabricated in 90 nm CMOS with current consumption of 24.7 mA with the Cancellation technique enabled from a voltage supply of 1.2 V.

Thomas G. Habetler - One of the best experts on this subject based on the ideXlab platform.

  • incipient bearing fault detection via motor stator current Noise Cancellation using wiener filter
    IEEE Transactions on Industry Applications, 2009
    Co-Authors: Wei Zhou, Bin Lu, Thomas G. Habetler, Ronald Gordon Harley
    Abstract:

    Current-based monitoring can offer significant economic savings and implementation advantages over traditional vibration monitoring for bearing fault detection. The key issue in current-based bearing fault detection is to extract bearing fault signatures from the motor stator current. Since the bearing fault signature in the stator current is typically very subtle, particularly when the fault is at an incipient stage, it is difficult to detect the fault signature directly. Therefore, in this paper, the bearing fault signature is detected alternatively by estimating and removing nonbearing fault components via a Noise Cancellation method. In this method, all the components of the stator current that are not related to bearing faults are regarded as Noise and are estimated by a Wiener filter. Then, all these Noise components are cancelled out by their estimates in a real-time fashion, and a fault indicator is established based on the remaining components which are mainly caused by bearing faults. Machine parameters, bearing dimensions, nameplate values, and the stator current spectrum distribution are not required in the method. The results of online experiments with a 20-hp induction motor under multiple load levels have confirmed the effectiveness of this method.

  • bearing fault detection via stator current Noise Cancellation and statistical control
    IEEE Transactions on Industrial Electronics, 2008
    Co-Authors: Wei Zhou, Thomas G. Habetler, Ronald Gordon Harley
    Abstract:

    This paper proposes a new approach to detect in situ bearing faults via stator current monitoring. For in situ bearing faults, the characteristic bearing fault frequencies may not exist, particularly at an early stage. In addition, the bearing fault signatures are usually subtle compared to the dominant components in the sampled stator current. Therefore, in this paper, a Noise Cancellation technique is used to suppress those dominant components that are not related to a potential bearing fault. The remaining components, i.e., the Noise-cancelled stator current, are then closely related to the health condition of the bearing. Furthermore, it is observed that under the presence of a bearing fault, the Noise-cancelled stator current displays a significant amount of degrees of uncontrolled variation in its magnitude. The uncontrolled variation is detected by observing the samples falling outside the three-sigma limits on Shewhart's control charts. Therefore, it is possible to detect in situ bearing faults by detecting the variation in magnitude of the Noise-cancelled stator current, as verified by online experiments performed in this paper.

  • incipient bearing fault detection via stator current Noise Cancellation using wiener filter
    IEEE International Symposium on Diagnostics for Electric Machines Power Electronics and Drives, 2007
    Co-Authors: Wei Zhou, Ronald Gordon Harley, Thomas G. Habetler, Bin Lu
    Abstract:

    Current-based monitoring can offer significant economic savings and implementation advantages over traditional vibration monitoring for bearing fault detection. A key issue in current-based bearing fault detection is to extract bearing fault signature from motor stator current. In this paper bearing fault signature in motor stator current is detected by estimating and removing non-bearing fault components via a Noise Cancellation method. In this method, the components of the stator current that are not related to bearing faults are regarded as Noise and are estimated by a Wiener filter. These Noise components are then cancelled by their estimates in a real time fashion and a fault indicator is established based on the remaining components that are related to bearing faults. Machine parameters, bearing dimensions, nameplate values, or stator current spectrum distributions are not required in the method. The results of on-line experiments with a 20-horsepower induction motor have verified the effectiveness of this method.

Seungkee Min - One of the best experts on this subject based on the ideXlab platform.

  • a 90 nm cmos 5 ghz ring oscillator pll with delay discriminator based active phase Noise Cancellation
    IEEE Journal of Solid-state Circuits, 2013
    Co-Authors: Seungkee Min, T Copani, S Kiaei, Bertan Bakkaloglu
    Abstract:

    Ring oscillators (ROs) provide a low-cost digital VCO solution in fully integrated PLLs. However, due to their supply Noise sensitivity and high Noise floor, their applications have been limited to low-performance applications. The proposed architecture introduces an analog feed-forward adaptive phase-Noise Cancellation architecture that extracts and suppresses phase Noise of ROs outside the PLL bandwidth. The proposed technique can improve the phase Noise at an arbitrary offset frequency and bandwidth, and, after initial calibration for gain, it is insensitive to process, voltage, and temperature variations. An experimental fractional PLL, with a loop bandwidth of 200 kHz, is utilized to demonstrate the active phase-Noise Cancellation approach. The Cancellation loop is designed to suppress the phase Noise at 1-MHz offset by 12.5 dB and reference spur by 13 dB with less than 17% increase in the overall power consumption at 5.1-GHz frequency. The measured phase Noise at 1-MHz offset after Cancellation is ${-}$ 105 dBc/Hz. The proposed RO-PLL is fabricated in 90-nm CMOS process. With Noise Cancellation loop enabled, the PLL consumes 24.7 mA at 1.2-V supply.

  • a 90nm cmos 5ghz ring oscillator pll with delay discriminator based active phase Noise Cancellation
    Radio Frequency Integrated Circuits Symposium, 2012
    Co-Authors: Seungkee Min, T Copani, S Kiaei, Bertan Bakkaloglu
    Abstract:

    Ring-oscillators provide a low-cost digital VCO solution in fully integrated PLLs, but due to their supply Noise sensitivity and high Noise floor, their applications have been limited. A fully integrated feed-forward, delay-discriminator based adaptive Noise-Cancellation architecture that improves phase Noise characteristic of ring-oscillators outside the PLL bandwidth is presented. Proposed technique can improve the phase Noise in an arbitrary offset frequency and bandwidth, and it is insensitive to process and temperature variations. The proposed Cancellation loop suppresses the phase Noise at 1 MHz offset by 12.5dB and reference spur by 13dB, with 3.7mA power consumption. The measured phase Noise at 1 MHz offset is −105 dBc/Hz. The proposed PLL is fabricated in 90 nm CMOS with current consumption of 24.7 mA with the Cancellation technique enabled from a voltage supply of 1.2 V.