Digitization of a Secondary Pump Condition-based ...
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Digitization of a Secondary Pump Condition-based Monitoring System
NIST Center for Neutron Research
Reactor Operations and Engineering Group
By:
Abdullah Weiss
NIST Advisors:
Dagistan Sahin, PhD
Marcus Schwaderer2 0 1 8 N I S T S u m m e r
U n d e r g r a d u a t e R e s e a r c h F e l l o w s h i p
G r a n t N u m b e r : 7 0 N A N B 1 8 H 0 7 0
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BackgroundAbdullah Weiss
โข B.S. in Mechanical Engineering at Texas A&M University-Kingsville
โข Upcoming PhD in Nuclear Engineering student at Texas A&M University
Katie Behnert
โข Collaborator on the project (led the physical lump of the project)
โข Upcoming Senior in Nuclear Engineering at Penn State University
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Project Background
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โข NCNR generates neutrons via a fission nuclear reactorโข ๐ท๐ท2๐๐ moderated and cooled
โข cooled via ๐ป๐ป2๐๐ in a secondary loop
https://www.ncnr.nist.gov/summerschool/ss07/bob_williams.pdf
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Condition-based Monitoring (CBM)
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โข The primary form of predictive maintenance for machinery
โข Monitors different conditions:โข Vibration, Temperature, etc..โข Via noise analysis
โข Evaluates health of machinery using:โข Time-history plotsโข Frequency spectra
โข Can provide financial savings through predictive measures
Pump
Vibration Sensor
TOO MUCH VIBRATION!Something must be wrong!
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Monitored conditions in our CBM System
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Temperature (simple one)
โข If the temperature of the bearing exceeds a set-limit, then you should investigate.
Vibrations (complex one)
โข Raw vibration history-plot reveals a severity measure of the vibrations
โข FFT spectrum reveals specific faults including:โข Cavitationโข Mechanical Loosenessโข Misalignmentโข Turbulenceโข Oil Whirl Instabilityโข Etc..
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Vibrations Analysis Literature
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https://www.engineersedge.com/vibration/vibration_severity_chart_13658.htm
For Raw Data Assessment
For Filtered Data Spectra Assessment
H. P. Bloch and F. K. Geitner, Machinery Failure Analysis and Troubleshooting: Practical Machinery Management for
Process Plants. (4th ed.) .
Analyze multiples of pump operating
frequency
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CBM System
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Courtesy of Katie Behnert
โข Sensors installed on the following axes:
โข Tangential
โข Radial
โข Axial
AccelerometerTransmitter
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Sensor Locations
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Axial (Ch. 0) Radial (Ch. 1) Radial (Ch. 2) Tangential (Ch. 3)
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CBM Connections Schematic
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๐๐๐ฝ๐ฝ๐ฝ๐ฝ๐ฝ๐ฝ๐ฝ๐ฝ = 6.4236%
๐๐๐ป๐ป๐ป๐ป๐ป๐ป๐ป๐ป = 1.3457%
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CBM Connections Box
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High-Level Architecture of Software
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Plot
โขData is displayed in a frequency plot
Find Peaks
โขSignificant peaks are picked by the program
Auto Spectrum
Calculation
โขFiltered data undergoes an auto spectrum calculation to further filter signal
Fast-Fourier Transform
โขVectorized data is passed through FFT to filter the noise
PC/MATLAB
โขDigital signal is converted to vectorized data
DAQ
โขConverts analog signal to digital signal
Transmitter
โขAmplifies Analog Signal
Sensor
โขVibrationsโขAnalog Signal
Vibration Data Flow
Plot
โขData is displayed in a time plot
PC/MATLAB
โขDigital signal is converted to vectorized data
DAQ
โขConverts analog signal to digital signal
Sensor
โขTemperatureโขAnalog Signal
Temperature Data Flow
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High-Level Architecture of Software
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High-Level Architecture of Software
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Vibrations Data Acquisition
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โข Utilized a NI USB-4432 DAQ deviceโข 5 BNC input channels (only 4 are used)โข 200 kS/s (10 kS/s used)โข Sensitivities set in MATLAB
โข Performed 5 batches of DAQ (5 seconds each)โข Average is utilized
โข Represents an average over every โ30โ seconds.
Data Acquisition Device (DAQ)
The AbdullAh GuArAnTee:
Program will always update in no more than 30 seconds
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Vibrations Data Processing
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โข Raw data โ Fast-Fourier Transform (fft command in MATLAB) โ Filtered dataโข Computes the Discrete-Fourier transform using a built-in MATLAB FFT algorithm:
โข ๐๐ ๐๐ = โ๐๐=1๐๐ ๏ฟฝ๐๐ ๐๐๐๐๐๐๐๐๐๐๐๐๐๐
๐๐๐๐๐๐โ1 (๐๐โ1) โ ๐๐๐๐ = ๐๐
โ2๐๐๐๐๐๐ = ๐๐๐๐๐๐ ๐๐๐๐ ๐๐ ๐๐๐๐๐๐๐๐๐๐ ๐๐๐๐ ๐ข๐ข๐๐๐ข๐ข๐๐๐ข๐ข
โข Creates a complex vector of data
โข ๐ด๐ด๐ข๐ข๐๐๐๐๐ด๐ด๐ด๐ด๐๐๐ด๐ด๐๐๐๐๐ข๐ข๐ด๐ด = ๐น๐น๐น๐น๐น๐น ๐๐๐๐๐๐ ๐๐๐๐๐๐๐๐ ๏ฟฝ ๐๐๐๐๐๐๐๐ ๐น๐น๐น๐น๐น๐น ๐๐๐๐๐๐ ๐๐๐๐๐๐๐๐๐ฟ๐ฟ๐ฟ๐ฟ๐๐๐๐๐๐๐ฟ ๐๐๐๐ ๐๐๐ฟ๐ฟ๐ฟ ๐๐๐๐๐๐๐๐๐๐๐๐
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Vibrations Data Peaksโ Finder
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โข Based on a user-defined RPM (for each channel), the conditioner function:1. looks for a frequency that matches the vane-pass frequency (VPF) within a certain accuracy
โข ๐๐๐๐๐๐ = ๐ ๐ ๐ ๐ ๐ ๐ 60 ๐ ๐ ๐ ๐ ๐ ๐
๐๐๐๐๐๐ร ๐๐๐ฃ๐ฃ๐๐๐๐๐ฟ๐ฟ๐ฃ๐ฃ
2. finds the corresponding amplitude (principle peak)3. circles the point
โข Based on the principle peak, the same conditioner function:1. finds peaks @ VPF multiples (0.5X, 1X, 1.5X, 2.5X, 3X, 4X โฆ. 10X)2. leaves x at each point
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Vibrations Data Peaksโ Finder
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Vibrations Automatic Fault Detector (Conditioner)
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Mechanical Loosenessโข โPossible Loosenessโ: There are too many โxโ marks (> 3 โxโ marks).
โข โLooseness detectedโ: There are too many โxโ marks, and one of them has an amplitude higher than the principle peak.
Misalignmentโข โPossible Misalignmentโ: The โ2X peak is between 50% and 150% of the principle peakโs
amplitude.
โข โMisalignment detectedโ: The โ2X peak is more than 150% of the principle peakโs amplitude.
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Vibrations Automatic Fault Detector (Cont.)
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Oil Whirl Instabilityโข โPossible Oil Whirl Instabilityโ: A peak at 0.2X to 0.8X is greater than the principle peak.
Flow Turbulenceโข โPossible Flow Turbulenceโ: There are several random low-frequency peaks that have an
amplitude that of at least 4% of the principle peakโs amplitude.
Cavitationโข โPossible Cavitationโ: There are several random high-frequency peaks that have an
amplitude of at least 8% of the principle peakโs amplitude.
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Human-machine Interface (A Channel tab)
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Phase Analysis
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โข Used for further verification of faults such as misalignment, soft foot, etc.โฆโข Utilizes phase angle difference
โข Compares two channels (A & B):โข Cross-Spectrum:
โข ๐๐๐ด๐ด๐ด๐ด๐ด๐ด = ๐๐๐๐๐น๐น ๐ด๐ด ๏ฟฝ ๐๐๐๐๐น๐น ๐ต๐ต
โข Displays phase angle of ๐๐๐ด๐ด๐ด๐ด๐ด๐ด:โข ๐๐ = tanโ1 ๐ ๐
๐ ๐ โ ๐๐๐ด๐ด๐ด๐ด๐ด๐ด = ๐ ๐ + ๐ข๐ข ๐๐
โข angle() command in MATLAB
โข Finds phase angle difference between signals from channels A and B.
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Human-machine Interface (Phase Analysis tab)
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Vibrations Severity Detector (RawConditioner)
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Average Raw Vibrations (every โ30 seconds):0 โ 0.005 in/s Extremely Smooth0.005 โ 0.01 in/s Very Smooth0.01 โ 0.02 in/s Smooth0.02 โ 0.04 in/s Very Good0.04 โ 0.08 in/s Good0.08 โ 0.16 in/s Fair0.16 โ 0.32 in/s Slightly Rough0.32 โ 0.64 in/s Rough> 0.64 in/s Very Rough
https://www.engineersedge.com/vibration/vibration_severity_chart_13658.htm
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Temperature Conditioner (RawConditioner)
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โข Using set temperature limits (๐น๐น๐๐๐๐๐๐, and ๐น๐น๐ฟ๐๐๐๐๐ฟ):
โข ๐น๐น๐ฃ๐ฃ๐ฟ๐ฟ๐๐๐ฃ๐ฃ๐๐๐๐ โฅ ๐น๐น๐ฟ๐๐๐๐๐ฟ | ๐น๐น๐ฃ๐ฃ๐ฟ๐ฟ๐๐๐ฃ๐ฃ๐๐๐๐ โค ๐น๐น๐๐๐๐๐๐ โ ๐น๐น๐ฃ๐ฃ๐ฟ๐ฟ๐๐๐ฃ๐ฃ๐๐๐๐
โข T๐ฟ๐๐๐๐๐ฟ > ๐น๐น๐ฃ๐ฃ๐ฟ๐ฟ๐๐๐ฃ๐ฃ๐๐๐๐ > ๐น๐น๐๐๐๐๐๐ โ ๐น๐น๐ฃ๐ฃ๐ฟ๐ฟ๐๐๐ฃ๐ฃ๐๐๐๐
Pump
Temp SensorT
TOO HIGH!
TOO LOW!
Just Right
(:
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Human-machine Interface (Summary Tab)
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Human-machine Interface (Settings tab)
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Output File
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โข Generated every hourโข .csv fileโข 20 โ 25 MBโข Each channelโข FFT data with the peaksโ frequenciesโข Enables further manual analysis
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Sensitivity Analysis & Observations
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โข Performed to pick reasonable sensitivities (V/g) for the channelsโข Average in/s at various sensitivitiesโข Referenced to transmittersโ valuesโข Best-fit functions & trial-error revealed appropriate sensitivities for channels
โข Different Sensitivity for each channelโข Channels should have same sensitivityโข Calibration needed
โข โ Sampling rate โก โ in/s
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Conclusion
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โข A working CBM system was developed and implemented successfully
โข A corresponding custom software was developed and implemented successfully
โข Documentation (including a manual) were put together for the software analysis
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Future Work
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โข Calibrate accelerometers
โข Improve GUI
โข Installation of CBM system on primary pumpsโข Additional Noise Analysis Applications:
โข Crack detection (for fuel channels analysis)โข Power Noise
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Acknowledgements
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Muhammad Afridi, PhD
Richard Allen
Scott Arneson
Julie Borchers, PhD
Heather Chen-Mayer, PhD
Joseph Dura, PhD
Steven Fick, PhD
Sam MacDavid
Mitchell Stansloski, PhD, PE
Danyal Turkoglu, PhD
All of the members of Reactor Ops and Engineering at the NCNR
NIST Research Library
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Acknowledgements
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Acknowledgements
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Marcus Schwaderer, MBA, COR II, PM II
Daฤistan ลahin, PhD Katie Behnert, National Golf Champion (GoogleMe)
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Q/A
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