Machines and systems hold a great deal of information, which, if properly collected and analyzed, can help systems achieve targeted optimum system performance levels over their life cycle. This phenomenon has been greatly understood but has been seldom applied to leverage the true benefits of predictive maintenance for systems. Theoretical solutions, such as fault detection and diagnosis (FDD), have provided the possibility of tapping information in machines for proactively handling faults and identifying solutions that can reduce the mean time between failures. This capability becomes particularly critical in events where a substantial delay exists between the fault's occurrence and corrective action to prevent excessive damage. The ability to provide an early detection as well as to augment predictive maintenance practices makes FDD valuable. Tangible economic benefits associated with deploying FDD can make it a very attractive solution.

Working along these lines, Italy-based Sensus Machine Intelligence (M. I.) has developed state-of-the-art fault detection, diagnosis and impact (FDDI) solutions for the heating ventilation and air-conditioning sector (HVAC). Sensus Machine Intelligence is a SaaS or software as a service provider, and develops browser-based monitoring and FDDI solutions. Through FDDI, Sensus M. I. is able to manage huge amounts of data that are available from machines and analyze them to provide sought-after decision-making capabilities. FDDI arms service operators with accurate system information from a remote location and provides early detection and diagnosis concerning the machine’s condition, which in turn can be used to carry out necessary actions.

Brian Thompson, founder and CEO, Sensus M. I., tells Sensor Technology, "We firmly believe that the existing data in machines, systems and buildings holds a lot of value. More than often, the inability to interpret useful information leads to inefficient operation, which can be readily resolved by intelligently collecting and analyzing data. It is here that the true value proposition of FDDI lies. We have developed our core competency around the meaningful development of FDDI techniques that bring a myriad of technical as well as business benefits for the building automation domain."

The technique consists of an automated prognostic ability to monitor systems from a remote location. Using a combination of artificial intelligence and thermodynamic rules, the machine data is continuously processed, providing near real-time machine status. An automated learning process fine-tunes the system for each location, machine, and condition. For regions hard-to-wire in buildings, Sensus M. I. uses a ZigBee mesh solution that is directly interfaced with Modbus to deliver sensor and machine programmable logic controller information to an Ethernet gateway, where data is transmitted to remote locations via the Internet without the need of a fixed public IP address at the machine site.

Compared to alarms that are static in nature (often too late with too general information), FDDI alarms are dynamic, adjusting with changing conditions, which gives the user better information to take the corrective action. Contrary to KISS (or keep it simple stupid, a common strategy used to generate static alarms), FDDI is able to handle the continuous information to optimize data management and assist in making decisions. Therefore, it removes the limitations associated with static alarms and provides users with the ability to leverage information for generating an intelligent response. The main drivers for the adoption of FDDI are optimal energy consumption, longer equipment life, reduced maintenance cost, and reduced downtime with higher levels of occupant comfort. Key users of FDDI technology include service organizations, facility maintenance companies, manufacturers, and distributors of components and systems.

Details: Brian Thompson, CEO, Sensus Machine Intelligence, E-mail: b.thompson@sensusmi.com.
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