Advancements in MOS Sensor Technology, The Soofie® Way

The Soofie® sensors, equipped with metal oxide semiconductor (MOS) technology, offer a promising solution for detecting methane levels with remarkable sensitivity. Harnessing the sensors' full potential hinges on accurately converting MOS output into a methane concentration. This task poses a challenge due to the inherent variability among individual MOS sensors, sparking debates on the practicality of utilizing MOS-based technology compared to Laser Absorption Spectroscopy (LAS). We contend that MOS sensors are highly effective tools for methane detection and site monitoring due to their exceptional responsiveness and high sensitivity, giving them the ability to detect even minor fluctuations in methane concentration levels at a significantly lower cost than the LAS technology.

Each MOS sensor operates uniquely, necessitating a bespoke calibration process to develop precise calibration models tailored to its characteristics. With thousands of Soofie sensors deployed worldwide, automating this calibration was imperative. Automating the calibration process ensures efficiency and facilitates the creation of a global uniform model, thus enabling consistent and high-accuracy methane concentration quantification across diverse sensor installations. This pursuit of standardized calibration methodologies stands as a crucial step towards leveraging MOS sensor technology to its fullest extent in monitoring and mitigating methane emissions on a global scale.

The emissions R&D team has developed a Digital Automated MOS Synchronization Algorithm, which frequently checks the condition of the MOS sensors and calibrates their performance based on the changes in temperatures and relative humidity. The computation behind the scenes minimizes the temperature and relative humidity influence on MOS performance. Following the calibration, the Methane Concentration Model converts the MOS output to Methane in parts per million. This model is derived from physics-based analytics using state-of-the-art estimation techniques.

Here’s an example of how these upgrades combine to enhance sensor performance:

Figure 1. Previous models present a variation in background methane concentration baseline, between 1 to 9 ppm due to MOS Output variability

Figure 2. The new Methane Concentration Model with Digital Automated MOS Synchronization presents a consistent background methane concentration with a baseline between 2.8 to 3.1 ppm

Frequent calibrations of MOS sensors optimize the baseline estimate towards near real-time accuracy by minimizing the effects of environmental variations. In Figure 2, the example from a Soofie experimental site, the Digital Automated MOS Synchronization effectively standardizes the MOS sensor performance for multiple Soofie Sensors on site.

To conclude, the Digital Automated MOS Synchronization Algorithm represents a significant advancement in sensor calibration technology. By effectively standardizing MOS output performance while minimizing the influence of temperature and humidity-induced uncertainties, this algorithm enhances the utility and trustworthiness of MOS sensors. This approach enables us to analyze the sensors as a network rather than as individual units, each with its own unique baseline, aging conditions, and environmental influences. The updated Methane Concentration Model represents a sophisticated approach to converting MOS sensor output into meaningful methane concentration measurements. By combining physics-based analytics with advanced estimation techniques, the model provides accurate and reliable results for continuous monitoring, industrial safety, and air quality assessment.