Acid number in insulating, transformer and turbine oils

Importance of the Topic

The acid number (AN) of insulating, transformer and turbine oils is a key quality parameter that reflects the presence of acidic degradation products. Maintaining low and stable AN values is essential to prevent corrosion, prolong equipment lifetime and ensure reliable operation under voltage stress.

Objectives and Study Overview

This application note describes a fully automated photometric titration method for the determination of AN in insulating, transformer and turbine oils according to ASTM D974, ISO 6618 and IP 139. The aim is to demonstrate how an Optrode-equipped titrator improves endpoint detection, precision and reliability compared to manual color-indicator titrations, especially for colored samples.

Methodology and Instrumentation

Samples of oil are weighed into a titration vessel and dissolved in a solvent mixture of toluene, isopropanol and water. A p-naphtholbenzein indicator is added. Titration is performed with 0.01 mol/L KOH in isopropanol. The Optrode photometric sensor monitors absorbance at 610 nm and a breakpoint evaluation of the titration curve defines the endpoint. A blank determination is conducted under identical conditions without sample.

Used Instrumentation

• OMNIS Sample Robot S Pick&Place
• OMNIS Advanced Titrator (no stirrer)
• OMNIS Dosing Modules and Cylinder Units (50 mL, 10 mL, 2 mL)
• Analogue Measuring Module
• Rod Stirrer and EFTE Propeller, 20 mm
• Optrode Photometric Sensor (610 nm)

Main Results and Discussion

Repeated titrations of three oil samples yielded total acid numbers of 0.005, 0.047 and 0.550 mg KOH/g with relative standard deviations of 0.00 %, 0.12 % and 1.18 % (n=3). These figures demonstrate excellent precision and low sample-to-sample variability. Automated endpoint detection removed subjective interpretation, ensuring consistent results even for darker oil matrices.

Benefits and Practical Applications

• Enhanced precision and reproducibility compared to manual titrations
• Reliable endpoint detection for colored or turbid oil samples
• Reduced operator bias and consistent measurement conditions
• Streamlined workflow with automatic cleaning and blank correction
• Applicable to routine QA/QC in transformer, turbine and insulating oil analysis

Future Trends and Opportunities

Further developments may include integration of inline titration for real-time monitoring, advanced sensor technologies for multiwavelength detection, AI-driven endpoint algorithms and miniaturized flow-through systems. These innovations will enhance data quality, reduce solvent consumption and enable proactive maintenance strategies in power and industrial operations.

Conclusion

The fully automated photometric titration method with an Optrode sensor offers significant improvements in precision, reliability and operator independence for acid number determinations in oils. Adherence to ASTM D974, ISO 6618 and IP 139 ensures compliance with industry standards and supports robust quality control in electrical and mechanical equipment maintenance.

References

• ASTM D974: Standard Test Method for Acid and Base Number by Color-Indicator Titration
• ISO 6618: Animal and vegetable fats and oils — Determination of acid value and acidity
• IP 139: Determination of total acid number (TAN) using potentiometric titration