Lyza 7000 Used Oil Package (FTIR In-Service Oil Analysis)
Brochures and specifications | 2023 | Anton PaarInstrumentation
Oil condition monitoring using FTIR spectroscopy provides rapid insight into lubricant health, identifying oxidation, nitration, antiwear additives, and contaminants.
Such analyses are vital for predictive maintenance, cost reduction, and environmental sustainability.
The primary aim is to present the Lyza 7000 FTIR spectrometer tailored for used-oil analysis, compliant with key ASTM standards.
It highlights turnkey methods, user customization, and streamlined workflows for lab and field environments.
The system adheres to ASTM methods E2412, D7214, D7412, D7414, D7415, D7418, D7624, and D7844, offering analysis of oxidation, nitration, sulfate, ZDDP, water, fuel contaminants, glycol, and soot.
Analysis completes in under 30 seconds with a signal-to-noise ratio of 55,000:1 and spectral range from 350 to 7,500 cm-1.
Instrument health monitoring includes an integrated humidity sensor with active alerts.
Integration with digital maintenance platforms and IoT for real-time monitoring.
Advanced chemometric models and machine learning to predict lubricant remaining life and failure modes.
Miniaturization and portable FTIR devices for on-site diagnostics across multiple industries.
Lyza 7000 combines compliance, speed, and user-friendly operation to deliver reliable oil condition assessments.
Its flexibility and compact footprint position it as a valuable asset for modern predictive maintenance strategies.
No external references were cited in the original material.
FTIR Spectroscopy
IndustriesEnergy & Chemicals
ManufacturerAnton Paar
Summary
Importance of the Topic
Oil condition monitoring using FTIR spectroscopy provides rapid insight into lubricant health, identifying oxidation, nitration, antiwear additives, and contaminants.
Such analyses are vital for predictive maintenance, cost reduction, and environmental sustainability.
Objectives and Article Overview
The primary aim is to present the Lyza 7000 FTIR spectrometer tailored for used-oil analysis, compliant with key ASTM standards.
It highlights turnkey methods, user customization, and streamlined workflows for lab and field environments.
Used Instrumentation
- Lyza 7000 benchtop FTIR spectrometer with embedded software
- Pyroelectric DLaTGS detector for high sensitivity
- Hermetically sealed optics with gold-coated mirrors and KBr windows
- Permanent cube corner interferometer aligned for stability
- 10.1" PCAP multitouch touchscreen for control
- Optional keyboard, mouse, and barcode reader
Main Results and Discussion
The system adheres to ASTM methods E2412, D7214, D7412, D7414, D7415, D7418, D7624, and D7844, offering analysis of oxidation, nitration, sulfate, ZDDP, water, fuel contaminants, glycol, and soot.
Analysis completes in under 30 seconds with a signal-to-noise ratio of 55,000:1 and spectral range from 350 to 7,500 cm-1.
Instrument health monitoring includes an integrated humidity sensor with active alerts.
Benefits and Practical Applications
- Pre-installed methods enable consistent, standard-compliant testing at the push of a button
- Custom method creation and library expansion streamline specialized analyses
- Embedded data processing eliminates the need for an external PC, saving lab space
- Compact design supports deployment in tight lab environments or field settings
- Intuitive touchscreen interface allows use by operators with minimal training
Future Trends and Potential Applications
Integration with digital maintenance platforms and IoT for real-time monitoring.
Advanced chemometric models and machine learning to predict lubricant remaining life and failure modes.
Miniaturization and portable FTIR devices for on-site diagnostics across multiple industries.
Conclusion
Lyza 7000 combines compliance, speed, and user-friendly operation to deliver reliable oil condition assessments.
Its flexibility and compact footprint position it as a valuable asset for modern predictive maintenance strategies.
Reference
No external references were cited in the original material.
Content was automatically generated from an orignal PDF document using AI and may contain inaccuracies.
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