September presentation: background on best practices for pH measurement

Jay Mershon, Analytical Business Manager for Endress+Hauser, provided a well received and informative presentation on pH measurement at the September 21 evening meeting of the Philadelphia ISA section. About 25 attended the meeting, held at Rumsey Electric in Conchohocken.

Mershon began by noting that making this measurement is often troublesome with many factors that can adversely affect accuracy. He said that the frequency of cleaning and calibrating probes (in that order) depends entirely on the specifics of an installation. Additionally the probes may have a lifetime of only six months–even less for high temperature installations. The response time of the measurement can degrade with conditions, making online control of pH difficult. The measurement is temperature dependent; compensation usually takes place in the transmitter.

As described by Mershon, the measurement usually consists of a pH sensitive glass electrode, a reference electrode, and a high impedance voltmeter. The pH electrode, solution measured, and reference electrode complete an electric circuit. The difference in the potentials between the pH and reference electrodes is a millivolt signal proportional to pH. At the neutral pH of 7, the signal is 0 mV. The circuit generates about -59 mV per pH level, which ranges from 2 (acid) to 12 (alkaline). Mershon pointed out that most processes run between 4 and 10 pH. Measurements at the extreme levels are better made with conductivity probes.

Near the end of the talk, Mershon introduced a new technology developed by Endress+Hauser for transferring the signal from the probe. Called Memosens, the technology converts the measured pH value to a digital signal and transfers it inductively to the transmitter. This technique, now available from multiple vendors, eliminates many of the problems often associated with pH measurements, including moisture, corrosion, cabling, ground loops, and noise. The technique can also transmit stored calibration, sensor, and process data to facilitate predictive and preventive maintenance.

 


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