1. PSE comprehensive system for on-line continuous
monitoring of rotating machinery

2. 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

3. 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”.
PredictiveOnLine measures the gap or angle between the Voltage and Current curves. The fluctuations between these two curves are analysed to produce the Failure factors and Alerts.

4. 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.

5. Phase Angle Machine Condition Assessment instrumentation (eight machines installation)

6. PAD failure signatures Loose motor foundations
This is an example of a loose foundation which affects all of the mechanical components of this fan.

7. Pre crystallizer. PAD failure signatures
This is an example of a loose foundation which affects all of the mechanical components of this fan.

8. Stirred reactor Failure Factor trend
PAD failure factor signatures
Stirred reactor Failure Factor trend
This is an example of a loose foundation which affects all of the mechanical components of this fan.

9. Phase Angle Fractal
Fractal plots are one of many diagnostic tools utilized in the analysis of failure development.

10. Phase Angle Fractal 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.

11. Phase Angle Fractal
Figure 7
The fractal in Figure 7 has an elliptical form. This form is associated with some initial abnormality in the bearing.

12. Phase Angle Fractal
Figure 8
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.

13. Phase Angle Fractal
Figure 10
The disruption of the fan journal bearings was associated with growing fractal asymmetry.

14. Phase Angle Fractal
Figure 10
Figure 10 shows the trend of the fractal diameters ratio in the course of bearing disruption.

15. Multi Disciplinary Signal Processing

16. Diagnostics Prognostics Engineering Report
iReporter
Diagnostics Prognostics Engineering Report
ereporter

17. Prognostics case story

18. iDiagnosticsWare functionality
On Line Trend analysis

19. iReporter
Machine Status Report

20. THIS DEVICE WILL FAIL IN 8days ± 1 day!
PSE - Predictive Maintenance - Technology Summary
THIS DEVICE WILL FAIL IN 8days ± 1 day!
CAN YOU BE THAT PRECISE?
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
CMMS – Computerised Management Maintenance System
DCS – Distributed Control System
SCADA - supervisory control and data acquisition

21. 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 warnings
OTHER CLIENT/ PSE INTERFACES
Pi Historian and other archives
CMMS, DCS, SCADA

22. 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

23. Predictive vs Preventive Maintenance
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

24. 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 Sensors indicating the performance of specific electricity generation processes and/or machine failures.
Automatic trend tracking and the early discovery of minor disturbances in the monitored processes and/or equipment
Prognosis of time when a tag or a Software Sensor value reaches a threshhold value.

25. iReporter PredictiveOnLine employs an Intelligent User Interface
presenting the results of the remote diagnostics & prognostics
of the monitored objects.
It includes;
animated icons symbolizing the status of a monitored object
the signatures and trends of key diagnostics indicators
related to the detected abnormality,
the abnormality root cause,
the time remained to reaching a threshold, etc.

26. Disturbance Growth Prognostics:
iDiagnosticsWare- performance analytics tool
Disturbance Growth Prognostics:
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 “SEVERE”
conditions

27. Power Station Management Assistant
Operation Schedule

28. Direct link to emergency shutdown PLC through RS485
Compressor protection
Direct link to emergency
shutdown PLC through RS485
bus or dry contacts

29. 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

30. Failures detected pumps
Impeller imbalance
Blocked impeller
Cavitations
Misalignment
Bearing abnormalities,
Loose foundation
Resonance problem
Sub-optimal operation and others..

31. 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.