Patent Application
20170097323
Embodiments of the present invention relate generally to monitoring systems, and in particular, to a system and a method for determining crack defects in stationary components of a rotary machine.
Stationary components such as stator vanes are used in rotary machines such as compressors, turbines, engines, and the like. An axial compressor, for example, has a series of stages with each stage including a row of rotor blades and a row of stator blades. The rotor blades increase kinetic energy of a fluid that enters through an inlet of the axial compressor. The stator blades generally convert the increased kinetic energy of the fluid into static pressure through diffusion.
Humidity and high temperature may lead to corrosion of vanes inside a rotary machine. Further, low cycle fatigue and high cycle fatigue during operation of the rotary machine, may lead to stress-corrosion cracking of the vanes. Vanes may be subjected to abnormal resonances or impact of foreign objects. Additionally, the vanes may operate for long hours under different operating conditions such as high speed, high pressure, and high temperature that may affect the health of the vanes. Further, vanes may be subjected to centrifugal forces, vibratory stresses, load of a fluid, or the like. A prolonged increase in stress and fatigue over a period of time may result in crack defects in the vanes of the machine.
Inspection techniques are commonly used to detect cracks and other defects in complex parts and structures. Borescope inspection is one of the commonly used technique for monitoring vanes. Condition based maintenance of machines relies on data obtained from such an inspection. Borescope inspection techniques are dependent on operator skill and thus are very subjective. Most conventional inspection techniques for crack detection involve a static inspection process when the machine is offline. In other words, the techniques require shutdown of the machine.
There is a need for an enhanced system and method for detecting crack defects in real time in stationary components of a rotary machine.
In accordance with one aspect of the present invention, a method is disclosed. The method includes receiving an acoustic signal from an acoustic emission sensor disposed at a predetermined location on a casing of a rotary machine operating in a transient condition. The method further includes applying a signal envelope extraction technique to the acoustic signal to generate a transformed acoustic signal. The method also includes generating an acoustic signature signal based on the transformed acoustic signal and determining a crack defect on a stationary component of the rotary machine based on the acoustic signature signal.
In accordance with another aspect of the present invention, a monitoring system for a rotary machine is disclosed. The monitoring system includes a stationary component disposed within a casing and an acoustic emission sensor disposed at a predetermined location on the casing. The acoustic emission sensor is configured to measure an acoustic signal when the rotary machine is operating in a transient condition. The monitoring system further includes a signal acquisition unit communicatively coupled to the acoustic emission sensor and configured to receive the acoustic signal. The monitoring system also includes a health monitoring unit communicatively coupled to the signal acquisition unit and configured to apply a signal envelope extraction technique to the acoustic signal to generate a transformed acoustic signal. The health monitoring system is further configured to generate an acoustic signature signal based on the transformed acoustic signal. The health monitoring system is also configured to determine a crack defect on the stationary component based on the acoustic signature signal.
These and other features and aspects of embodiments of the present invention will become better understood when the following detailed description is read with reference to the accompanying drawings in which like characters represent like parts throughout the drawings, wherein:
Exemplary embodiments of the present invention include a method and a system for detecting a defect in a stationary component of a rotary machine. The method involves receiving an acoustic signal from an acoustic emission sensor disposed at a predetermined location on a casing of the rotary machine. The acoustic signal is acquired when the rotary machine is operating in a transient condition. A transformed acoustic signal is generated by applying a signal envelope extraction technique to the acoustic signal. An acoustic signature signal is generated by processing the transformed acoustic signal. A crack defect is detected on the stationary component of the rotary machine based on the acoustic signature signal.
As discussed herein, the term “rotary machine” may refer generally to any rotary electrical or mechanical machine. The term rotary machine includes, but is not limited to, an electrical motor, a diesel generator, a gas turbine and a compressor. As discussed herein, the terms “stationary component”, “blade”, “vane”, “foil” may be used interchangeably. The term “vibration mode” refers to inherent axial, flexural and torsional modes of vibrations that are generated in at least one of a stationary component such as a stator vane of the rotary machine at specific resonant frequencies. The term “flexural mode” refers to behavior of at least one of a stationary component subjected to an external load applied perpendicularly to a longitudinal axis of at least one the stationary component. The term “torsional mode” refers to angular vibrations of at least one of a stationary component. The term “acoustic emission” refers to transient elastic waves within at least one of a stationary component, generated due to the rapid release of localized stress energy. Specifically, the acoustic emissions are generated either during the propagation of crack or when the cracked surfaces of a component rub against each other during cyclical flexure and relaxation of the component. The term “acoustic signal” refers to a signal representative of acoustic emission (AE) signals having frequencies between 10 kilohertz (kHz) to 1 megahertz (MHz). The term “crack defect” refers to any defect on a stationary component that may affect the working condition of the rotary machine. The crack defect may be an incipient crack, a crack, or a propagation of crack through the material of a stationary component generated due to stress and strain levels. As discussed herein, the terms “defect” and “crack defect” may be used interchangeably. A defect such as a crack or a propagation of a crack acts as source for acoustic emissions. Additionally, the crack defect can also modify the mechanical resonant frequencies and other characteristics of vibration modes of a corresponding stationary component.
The signal acquisition unit 116 is communicatively coupled to the plurality of acoustic emission sensors 112 and configured to receive at least one acoustic signal 124 when the rotary machine 132 is operating in a transient condition. The term “transient condition” refers to at least one of a start-up condition and a shut-down condition of the rotary machine 132. The start-up condition is indicative of a condition when the rotational speed of the rotary machine 132 is increased from an idle condition to a stable operating speed. The shut-down condition is indicative of a condition when the rotational speed of the rotary machine 132 is decreased from a stable operating speed to the idle condition. During the transient condition, the rotary machine 132 operates at a plurality of rotational speeds thereby exciting a plurality of vibration modes in the vanes 108. When the rotational speed of the rotary machine 132 reaches a critical speed, a vibrational mode corresponding to the critical speed is excited in the vanes 108. As a result, an acoustic signal having an amplitude modulation corresponding to the vibrational mode frequency may be generated depending on whether at least one of the plurality of vanes 108 has a crack defect. During the transient condition, the rotary machine 132 may operate at a plurality of critical speeds. As a result, a plurality of acoustic signals having a plurality of frequencies in a frequency range of 10 kHz to 1 MHz and amplitude modulations corresponding to a plurality of vibrational modes may be generated depending on whether at least one of the plurality of vanes 108 has a crack defect.
The at least one acoustic signal 124 is representative of information about existence of a crack defect in one or more stator vanes 108 disposed within the casing 102. Although “stator vanes” are referenced herein for purposes of illustration, other static structures subject to vibration modes and disposed within the casing 102 may additionally or alternatively be monitored. In one embodiment, the signal acquisition unit 116 is further configured to sample the acoustic signal 124 by processing steps such as noise filtering and signal normalization to enhance the signal content and provide a processed acoustic signal 130 to the health monitoring unit 118. In certain embodiments, when the received acoustic signal 124 has high signal-to-noise ratio, additional processing may not be required and the received acoustic signal 124 is transmitted to the health monitoring unit 118.
The health monitoring unit 118 is communicatively coupled to the signal acquisition unit 116 and configured to receive the processed acoustic signal 130. As illustrated in more detail with respect to
In some embodiments, the health monitoring unit 118 is also configured to process a plurality of acoustic signals 124 to determine a length and a position of the crack defect. In one such embodiment, a resonant frequency of the acoustic signature signal is determined. A length of the crack is obtained from a look-up table based on the value of the resonant frequency. The look-up table may be stored in the memory unit 122 and the values of the look-up table are pre-populated based on historical data and a plurality of observations obtained from experiments or computer simulations. In an alternate embodiment, the length of the crack is obtained by evaluating a mathematical expression as a function of the resonant frequency. In another such embodiment, a source localization technique is used to process the plurality of acoustic signals 124. In one specific embodiment, the source localization technique is a MUSIC (multiple signal classifier) technique. In another embodiment, the source localization technique is an ESPRIT (estimation of signal parameters via rotational invariance technique) technique. In an exemplary embodiment, for each pair of acoustic emission sensors among the plurality of acoustic emission sensors, a time difference of arrival (TDOA) is estimated from the acoustic signals detected by the corresponding pair of acoustic emission sensors. As a result, a plurality of such TDOA estimates for a plurality of pairs of acoustic emission sensors is determined. The position of the crack defect is determined based on a location of the source of the acoustic emission corresponding to the plurality of acoustic signals received from the plurality of acoustic emission sensors. In other embodiments, a triangulation based technique is employed to determine the position of the crack defect.
The processor 120 may include one or more sub-processors having at least one arithmetic logic unit, a microprocessor, a general purpose controller or a processor array to perform the desired computations or execute the computer program. In one embodiment, the functionality of the processor 120 may be limited to tasks performed by the signal acquisition unit 116. In another embodiment, the functionality of the processor 120 may be limited to functions performed by the health monitoring unit 118. The processor 120 is configured to execute a program stored in the memory.
The memory unit 122 is configured to be accessed by at least one of the signal acquisition unit 116, the health monitoring unit 118, and the processor 120. In an exemplary embodiment, the memory unit 122 may include one or more memory modules. The memory unit 122 may be a non-transitory storage medium. For example, the memory unit 122 may be a dynamic random access memory (DRAM) device, a static random access memory (SRAM) device, flash memory or other memory devices. In one embodiment, the memory unit 122 may include a non-volatile memory or similar permanent storage device, media such as a hard disk drive, a floppy disk drive, a compact disc read only memory (CD-ROM) device, a digital versatile disc read only memory (DVD-ROM) device, a digital versatile disc random access memory (DVD-RAM) device, a digital versatile disc rewritable (DVD-RW) device, a flash memory device, or other non-volatile storage devices. In one specific embodiment, a non-transitory computer readable medium may be encoded with a program to instruct at least one processor to perform functions of one or more of the signal acquisition unit 116 and the health monitoring unit 118.
The method further involves determining a crack defect on a stator vane of the rotary machine based on the acoustic signature signal as represented in step 708. In one embodiment, a plurality of samples of the acoustic signature signal is compared with a predetermined threshold value. If samples of the acoustic signature signal are greater than the predetermined threshold value, a peak value in the acoustic signature signal is detected. The peak in the acoustic signature signal is indicative of a crack defect in one or more of the stator vanes. In an embodiment involving a plurality of acoustic signature signals, crack defect is independently determined from each of the plurality of acoustic signature signals. The determined data related to the detection of crack defect may be combined to determine a robust decision pertaining to the detection of the crack defect. In another embodiment, the data related to the crack defect may be indicative of a plurality of crack defects in one or more of the stator vanes.
In an exemplary embodiment, determining the crack defect involves determining at least one of a length and a position of the crack defect, based on the acoustic signature signal. Determining the length of the crack defect involves determining a resonant frequency corresponding to the acoustic signature signal. The length of the crack defect is obtained from a look-up table, using the resonant frequency. In another embodiment, a plurality of acoustic signals is obtained from a plurality of acoustic emission sensors disposed at a plurality of predetermined locations on the casing of the rotary machine. In such an embodiment, determining a position of the crack defect involves processing a plurality of acoustic signals from the plurality of acoustic emission sensors disposed at a plurality of predetermined locations on the casing of the rotary machine. The location of the crack defect is determined based on a source localization technique. In one embodiment, the source localization technique is a triangulation technique based on at least three acoustic signals. In another embodiment, a time difference of arrival (TDOA) is determined corresponding to a pair of acoustic signals from the plurality of acoustic signals. A plurality of such TDOA estimates is obtained corresponding to the plurality of pairs of acoustic signals, from the plurality of acoustic signals. The location of the crack defect is obtained based on the plurality of TDOA estimates. In one embodiment, the position of the crack defect is determined based on the plurality of transformed acoustic signals. In another embodiment, the position of the crack defect is determined based on the plurality of acoustic signature signals.
Disclosed embodiments facilitate detection of crack defects in-situ in stationary components such as stator vanes in rotary machines. Monitoring presence and growth of crack defects on the stator vanes is enabled by signal processing of acoustic emission signals obtained from acoustic emission (AE) sensors disposed on the casing. The exemplary inspection techniques for crack detection can be performed in real time when the machine is operating. In other words, the exemplary technique does not require shutdown of the machine.
It is to be understood that not necessarily all such objects or advantages described above may be achieved in accordance with any particular embodiment. Thus, for example, those skilled in the art will recognize that the systems and techniques described herein may be embodied or carried out in a manner that achieves or improves one advantage or group of advantages as taught herein without necessarily achieving other objects or advantages as may be taught or suggested herein.
While the technology has been described in detail in connection with only a limited number of embodiments, it should be readily understood that the specification is not limited to such disclosed embodiments. Rather, the technology can be modified to incorporate any number of variations, alterations, substitutions or equivalent arrangements not heretofore described, but which are commensurate with the spirit and scope of the claims. Additionally, while various embodiments of the technology have been described, it is to be understood that aspects of the specification may include only some of the described embodiments. Accordingly, the specification is not to be seen as limited by the foregoing description, but is only limited by the scope of the appended claims.
| Number | Date | Country | Kind |
|---|---|---|---|
| 5323/CHE/2015 | Oct 2015 | IN | national |
