Management of Big Data in the Sensor Industry

Brett Sargent, Chief Technology Officer and VP/GM of Products and Solutions at LumaSense Technologies, Inc., talks to AZoSensors about the management of Big Data in the sensor industry.

You’ve recently presented at two back-to-back conferences on data analytics. What were the main points covered during your presentations?

The main points covered in the presentation were:

1. The Grid is not Smart by just putting smart meters at the end point of the grid. The infrastructure on a global basis is old, very old. Many components are 40+ years old at this point. While having smart meters at the end may enable pricing options such as Time of Use and Demand Response, it does not help with sustainable and reliable electricity flow from Generation to the end user. You lose your smart meter…you are back in the 1980’s.  You lose your grid…welcome to the 1880’s.
2. The grid is getting pushed harder and harder. The number of significant power outages have increased significantly over the past few years…growing from 76 in 2007 to 307 in 2011. The average age of a transformer in North America is over 40 years old.
3. With such an aged grid, you really have 2 choices on what you can do:
   1. Build new infrastructure to help with growing electrical demand and replace the aged infrastructure. This is met with huge obstacles such as a lack of budget, NIMBY (Not in my backyard), BANANA (Build Absolutely Nothing Anywhere Near Anyone), aged workforce, etc.
   2. Make things last longer – do things to extend the life of existing assets on the electrical grid.  This is a more viable solution…and can be accomplished through the addition of Sensors.
4. The new approach and the right approach is SLEx (Substation Life Extension), where you approach a substation and evaluate the assets and then outfit the substation as needed in order to extend the life of the substation to the point at which you can upgrade, replace, etc.
5. However, when you put a high number of sensors in place to enable SLEx…then you also step into the pit of Big Data. A high number of sensors in a substation can drive Big Data where you can have 3-5 Gb/sec of data coming out of a substation, overwhelming a utility and crushing the bit pipe used to carry data.
6. To avoid this, utilities should embrace Intelligent Sensing At The Edge, which will keep the data storage and analytics close to the sensor head and then use the “report by exception” philosophy in order to send information back to the utility on an as needed basis, instead of flowing all of the data continuously back to the utility. The data is not lost or misplaced…just stored near the asset being monitored and available to be analyzed as needed.

What are your views on Big Data for Big Substations and the challenges this brings for the utility companies?

Big Data has a different definition to different people, based on Volume, Velocity, Variety and Veracity of the data coming at them. The definition of Big Data for Google will be different then it is for a utility customer. Big substations need a large number of sensors in order to monitor and keep track of the assets that are located at that substation. This will bring 3-5 Gb/sec of data out of a substation that is almost impossible to handle effectively. So where do you process the data? The options are:

1. At the Edge
2. In the Cloud
3. In the Server (at HQ).

Each has pros and cons, but keep in mind the further you move data, the more likely it is something will go wrong or the data will get hacked, lost, corrupted, etc.  It also costs more money in order to move data a greater distance. Factors to consider where you process the data include:

1. Cost
2. Bandwidth – which is the most important
3. Security – NERC CIP
4. Stability/Reliability
5. Integrity
6. Size of Network.

Sensors are needed. They create big data. The challenge is to know where you are going to process this big data and how you are going to handle it. The most cost effective way is to do intelligent “sensing at the edge”.

How do sensors help enhance the generation, transmission, and distribution levels to improve a smart grid and how do LumaSense plan on taking on this challenge for its end-users?

Sensors enable SLEx…Substation Life Extension. With sensors, a wide variety of things can be accomplished, including:

1. Condition Based Maintenance
2. Safe Dynamic Loading
3. ICR – Intelligent Component Replacement
4. Maximizing Asset Performance
5. Safe Life Extension
6. Improved Safety
7. Smart Workforce Deployment
8. Forensic and Diagnostic Analysis
9. Probabilistic Risk Assessment.

The part of LumaSense is to provide quality sensing solutions that will enable SLEx and can handle Big Data the right way so as not to kill the customer.

How do you see the industry changing with handling Big Data from a sensor manufacturer perspective?

Sensors are here to stay. From my perspective, there will be an increase in the amount of sensing technology used in data as data is king, and harnessing data will give you a competitive advantage. Sensor manufacturers need to make it easy for the customer, providing data quickly, accurately and in a format that can be easily integrated and allow for M2M and automation, which is the ultimate end goal.  

You mention ‘Intelligence Sensing at the Edge’; can you explain what you mean by this and how this relates to the latest trend in the industry?

Intelligent Sensing at the Edge is moving the processing of data and the true intelligence related to data analytics close to the sensor head, thus saving the “bit pipe” from being crushed and allows for quicker decisions and less risk to the data integrity. With the advent of Big Data, it is clear that people need to know the “exception” to things…looking for abnormalities in things and not just have tons of data pour over them.

Intelligent Sensing at the Edge is the philosophy of doing the analysis and storage of data close to the sensing point, and only reporting back information by exception. It is the enabler to the next level of automation…which is Machine to Machine (M2M).

What sophisticated sensors will enable SLEx to gather critical information relating to the health of power assets?

There are a wide variety of sensors that are in the market to collect the data necessary to enable SLEx. Many of them are sensing technologies that have been done manually for years and now will be put online continuously for monitoring (like Dissolved Gas Analysis (DGA) for transformer and load tap changer oil or SF6 gas composition).

One of the largest sensing technologies that will come about in implementation is thermal imaging that is performed online continuously instead of 1-2 times per year with portable thermal imagers. Sensing external component temperature with thermal imagers is one of the best methods of diagnostics for electrical components that are non-obtrusive and non-destructive. There are also many other sensors in the market that are becoming available as well, such as RF Leakage Current, Online Partial Discharge, RF Acoustic Emissions and online Frequency Response Analysis (FRA).

LumaSense have a range of advanced thermal imaging cameras. Among this range is the Rel Rad – a new category of thermal imaging. How does this new range work?

Today in the market there are two types of thermal imagers…radiometric (those where every pixel reads temperature accurately) and non-radiometric (which provides a thermal image that shows temperature relatively…but not accurately and not calibrated to anything). I have introduced a new category called Rel Rad (short for Relatively Radiometric) that incorporates the use of one or more pyrometers in conjunction with a non-radiometric camera so that the image is relative to the accurate pyrometers. A pyrometer can be a single pixel measurement or have a small spot size, but it is very accurate. This creates a new category of temperature measurement between radiometric (rad) and non-radiometric (non-rad).

A perfect use of Rel Rad would be to measure something where you need to know the temperature accurately and you are interested in the uniformity of temperature across the object that you are measuring.  Things like ladel preheat or any type of preheat or annealing process.

What are the main benefits of Rel Rad?

The main benefit of Rel Rad is to bridge the proverbial gap of pyrometers and imaging cameras. For years, people have used pyrometers for accurate spot temperature measurement successfully. However, the assumption when using pyrometers is that the whole object you are measuring (or the relevant areas) is uniform in temperature. This is normally not the case. So the next step used to be going to thermal imagers that are fully radiometric. This requires a larger monetary investment and sometimes a sudden process change.

Rel Rad allows an interim step, where you can get more information by bringing in a non-radiometric camera driven by accurate temperature measurement found with the pyrometers. The perfect bridge and Rel Rad can use existing installed pyrometers, which is more cost effective and does not take away the comfort that customers have enjoyed with their pyrometers.

How do you think intelligence sensing at the edge will evolve over the next 5 years?

Two things are coming in the future that Intelligent Sensing at the Edge will be the enabler for:

1. The Internet…people call it the Internet of Things…Cisco is now referring to it as the Internet of Everything. Everything will ultimately get connected to the internet. Intelligent sensing will get us closer to this reality.
2. M2M – Machine to Machine. Intelligent Sensing at the Edge will be a great enabler to this and allows for machines to talk to machines more quickly and more rapidly than ever before.

Where can we find further information on how your sensor technology can help enable SLEx and optimize asset performance?

Visit my blog or You Tube videos to learn more.

About Brett Sargent

Brett Sargent is currently Chief Technology Officer and VP/GM of Products and Solutions at LumaSense Technologies, Inc., which is based in Silicon Valley.  His current responsibilities include driving the vision and technical direction of LumaSense and he leads the design engineering, application engineering, product management and marketing teams.  Prior to this role, Brett was VP of Sales at LumaSense for 5 years.

Brett has over 20 years of energy and industry experience including leadership roles at DuPont, Lockheed Martin, Exelon Nuclear and General Electric, where he was Global Sales Leader for the GE Energy T&D Products division. Brett has held leadership roles in design engineering, product management, sales, marketing, operations, supply chain and quality.

Brett is Six Sigma Black Belt certified and a graduate of the Naval Nuclear Power School. Brett holds a B.S. in Electrical Engineering from Widener University, an M.S. in Nuclear Engineering from Rensselaer Polytechnic Institute and an MBA in International Business from Georgia State University.