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Transcript of 2 Predictive Systems Engineering, Ltd Predictive Systems Engineering Diagnostics/Prognostics...
PSE comprehensive system for on-line continuous monitoring of rotating machinery
2 Predictive Systems Engineering, Ltd
Predictive Systems Engineering Diagnostics/Prognostics
Predictive Maintenance Phase Angle/current analysis Vibration Acoustic
Mitigating risk of production interruptions
Automating diagnostics Automating prognostics Automate detection of mechanical and electrical condition Cloud computing Multi-technology approach Integrating diagnostics with CMMS and archive systems
Zero unexpected equipment failures objective Reduced operation losses and maintenance expenditures
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Phase Angle Diagnostics
Voltage
Current
Small variations in the Phase Angle “t” are analysed by PredictiveOnLine proprietary diagnostics. The results indicate the condition of various components in the drive train as well as the electrical condition of the motor. See next slide for an analysis of the frequencies of Phase Angle “t”.
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Phase Angle Machine Condition Assessment
•Mechanical disturbances in rotating equipment causes small
fluctuations in the moment on the shaft. •The Phase angle of an AC electrical motor is proportional to the
moment on the shaft. •The analysis of the phase angle fluctuations allows PSE to detect and
recognize the mechanical disturbances in the rotating machinery
driven by the electrical motor. •PSE has developed and patented a method for this diagnostics. Its
advantage is that sensors (current transformer) are located in the
motor electrical cabinet and not on the monitored machine itself. •Phase Angle technology is valuable for machinery which is difficult
to access, for low speed machinery, or for machines
operating in harsh environments. •The most important issue is the technology viability. The testing
provided by Mitsui Chemical, Japan, has shown that Phase Angle
Diagnostics is much more sensitive than vibration analysis.
This makes it valuable for all rotating equipment.
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Phase Angle Machine Condition Assessmentinstrumentation (eight machines installation)
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PAD failure signatures Loose motor foundationsPAD failure signatures Loose motor foundations
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PAD failure signatures PAD failure signatures
Pre crystallizer.
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PAD failure factor signatures PAD failure factor signatures
Stirred reactor Failure Factor trend
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Phase Angle Fractal Phase Angle Fractal
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Phase Angle Fractal a useful diagnostic signature Motor torque changes in course of shaft revolution. The analysis of these changes is helpful for diagnostics of electromechanical and mechanical failures in rotating equipment. It is done by building Phase Angle Fractals, which are the polar diagrams of motor torque as a function of rotor angle position. It is an accumulated diagrams obtained in the course of a number of shaft revolutions. The form of a fractal signals machine health conditions.
Phase Angle Fractal Phase Angle Fractal
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Phase Angle Fractal Phase Angle Fractal
The fractal in Figure 7 has an elliptical form. This form is associated with some initial abnormality in the bearing.
Figure 7
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Phase Angle Fractal Phase Angle Fractal
Figure 8 was registered very close to stirrer outage shows the unstable movement of the shaft inside bearings disclosed by an increased value of fractal dispersion.
Figure 8
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Phase Angle Fractal Phase Angle Fractal
The disruption of the fan journal bearings was associated with growing fractal asymmetry.
Figure 10
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Phase Angle Fractal Phase Angle Fractal
Figure 10 shows the trend of the fractal diameters ratio in the course of bearing disruption.
Figure 10
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Multi Disciplinary Signal Pro-cessing
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Diagnostics Prognostics Engineering Report
ereporter
iReporter
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Prognostics case story
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iDiagnosticsWare functionality
On Line Trend analysis
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Machine Status Report
iReporter
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PSE - Predictive Maintenance - Technology Summary
THIS DEVICE WILL FAIL IN 8days ± 1 day! CAN YOU BE THAT PRECISE?
THIS DEVICE WILL FAIL IN 8days ± 1 day! CAN YOU BE THAT PRECISE?
CMMS – Computerised Management Maintenance SystemDCS – Distributed Control SystemSCADA - supervisory control and data acquisition
Predictive Maintenance
Assets
PSE
• Monitor rotating machinery; pumps , compressors, fans, gearboxes, mills, etc
• Scheduling and Planning made easy and effective with PSE Predictive Maintenance
• Integrate PSE with CMMS, SCADA, DCS, Pi Historian etc
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PSE - Predictive Maintenance - Technology Summary
PSE 's- CLOUD CONDITION MONITORING SOFTWARE
· iDiagnosticsWare – automates failure diagnostics
· Cloud Server Software:
· eReporter – user friendly web based alerts, reports, analysed data
· eExpert – online access to remote expert assistance
· ePredictor – automated failure prediction report
SENSOR NETWORK
· Phase Angle, current and voltage sensors
· Smart wireless 3D accelerometers
· Acoustic sensors
· Zigbee and power line communication
· Cell phone data connection modems
CLOUD ACCESS
· Diagnostics & prognostics
· Monitoring reports
· Remote expert
· SMS and email warnings
OTHER CLIENT/ PSE INTERFACES
· Pi Historian and other archives
· CMMS, DCS, SCADA
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Cost Benefit of PSE
Cost Benefit Diagnostics - Chemical Plant Israel
· US$210,000 annual savings from extending their maintenance cycle from 12 to 14 months
· Payback time on initial cost of PSE – 1.1 months
· PSE currently monitors the reactor stirrer
Cost Benefit Prognostics - Power Plant NY
• One day of downtime equals $600,000 revenue loss
• Payback time on initial cost of PSE preventing one day of downtime – 4.4 hours.
• PSE is currently monitoring critical pumps and compressors
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Benefits of Predictive Maintenance
Maintenance costs reduced by 50%Unexpected failures reduced by 50%Repair time reduced by 60%Parts inventory reduced by 30%MTBF increased by 30%Uptime increased by 30%
Source: Plant Engineer's Handbook – R Keith Mobley – 2001
Predictive vs Preventive Maintenance
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Diagnostics prognostics software
Principle Functionality:
On line signal processing related to steady state and transitive processes
System customization by self-learning monitored machine / process behavior at baseline conditions.Aggregation of different tags into Software Diagnostics Sen-sors indicating the performance of specific electricity genera-tion processes and/or machine failures.Automatic trend tracking and the early discovery of minor dis-turbances in the monitored processes and/or equipmentPrognosis of time when a tag or a Software Sensor value reaches a threshhold value.
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iReporter
PredictiveOnLine employs an Intelligent User Interface presenting the results of the remote diagnostics & prog-
nostics of the monitored objects.
It includes; animated icons symbolizing the status of a monitored objectthe signatures and trends of key diagnostics indicators
related to the detected abnormality,the abnormality root cause, the time remained to reaching a threshold, etc.
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iDiagnosticsWare statistically analyzes the Diagnostics Software
Sensor Trends and detects small changes related to machine health or
process abnormalities
Afterwards, it builds a statistical model of the trend and forecasts when
the trend reaches the thresholds related to “ALERT” or “SE-VERE”
conditions
Disturbance Growth Prognostics:
iDiagnosticsWare- performance analytics tool
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Power Station Management Assistant
Operation Schedule
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Compressor protection
Direct link to emergencyshutdown PLC through RS485 bus or dry contacts
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Failures detected compressors
Compressor valve flutter: spectral analysis of motor current and phase angle.
Compressor valve leakage: ultra sound probes installed on the cylinder heads.
O-rings wear: thermodynamic analysis of temperatures before and after cylinders.
Shaft bearings malfunctions: ultra sound probes
Loose foundation: vibration analysis.
Rod wear: spectrum analysis of motor current & phase angle and vibration analysis
Short windings in electrical motors: Unbalance of motor current
VFD improper performance: spectral analysis of voltage SINEs in three phases
Rotor-stator gap problems: Phase Angle fractals
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Failures detected pumps
Impeller imbalanceBlocked impellerCavitationsMisalignmentBearing abnormalities,Loose foundationResonance problemSub-optimal operation and others..
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Process Plant Equipment monitored
Steam and Gas Turbines
Boilers Feed Pumps
Air and gas compressors
Electrical motors
Generators
Mills
Condensers
Heat exchangers
Vacuum Pumps, etc.