Using Drone Data to Create a Digital Twin
Digital twins allow asset owners, engineers, inspectors and designers to not only understand the current condition of assets and infrastructure through remote digital inspection, but digital twins allow them to understand changes over time, which leads to accurate predictions of function and degradation into the future. With this information owners are able to create accurate maintenance, cost, and expected asset life cycle modelling for their organizations. Industries are dealing with potentially trillions of dollars of infrastructure and assets, the amount of savings in both cost and time due to this emerging technology is going to be truly massive. We are currently at the start of a new wave in the processes of collecting data, modeling, categorizing, and predicting the future for all assets.
In order to create a fully accurate digital twin, companies will rely on several types of technologies to build a comprehensive model of their assets. The technology will include specialized sensors depending on what is important to the specific client; this can range from LiDAR to RGB to Thermal or Infrared and a number of other sensor technologies. Another important consideration is a platform to carry the sensor. Ground based sensors and drones will supply a fully comprehensive solution to model the entire asset’s external condition and in some cases even internal.
In this article we will be exploring exactly what digital twins are and how drones are being used to capture the required data.
What Is a Digital Twin?
A digital twin is a complex virtual model of a physical object, think of a digital twin as a true model of reality. There are a number of data sets important to collect on the asset depending on the assets physical characteristics. (1) Size and dimensions of the asset, (2) Surface color of the asset, (3) Surface temperature of the assets, (4) thickness of an assets external shell (5) Collection date of the asset. Digital twins make it possible to understand how a physical asset is performing in the present but how it will perform in the future.
How Data Analysis and AI can Accurately Produce Custom Reports and Auto Notifications Based on Your Specific Assets’ Condition
Once a digital twin has been created AI software can be programmed to create custom inspection algorithms that can be used to quickly identify any variable in the data you choose. From identifying rust to cracks, heat stress, wall thickness and even dimensional changes. Imagine having a report created in a matter of minutes that pinpoints any rust spots or insulation damaged on a 100-mile pipe rack without having to go to the field and inspect manually.
Once your initial digital twin is created a second digital twin can be created after a set amount of time has passed. This can be at any time interval you choose; monthly, quarterly, yearly, etc.
Here is the best part, having two digital twins modeled at separate times allows for comparative analysis of the condition of these two assets, so any changes to these assets can be identified and logged for review. As an example, if you inspected a brand new vessel immediately after initial construction and inspected the asset a year later the two data sets are compared and changes between the two assets are identified and logged. This gives you the ability to manage and control the changes throughout your entire asset portfolio over time.
Furthermore, AI conditions can be set to categorize stress levels to each change in the asset identified; Low Priority, Medium Priority, High Priority, Immediate Priority, which in turn can be used to create work orders.
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Current and Upcoming Industries Relying on Digital Twins
While NASA began using digital twins to run simulations of spacecraft, the technology has gained traction across a wide variety of industries and fields.
NASA began using digital twins in 2010, creating the concept within four parts:
- Physical object or process;
- Digital product;
- Data moving from the physical object to the digital twin;
- Information taken from the digital and applied to the physical environment.
Digital twins will transform the energy sector. A small list of common assets that will be incorporated into a digital twin solution include pipelines, solar farms, wind turbine fields, oil refineries and many more. Energy companies must maintain their assets regularly, making the switch from manual inspection to a digital twin solution a no-brainer, especially when assets are valued into the hundreds of billions of dollars. At this scale even a small cost saving is massive. Just imagine having digital access to all your company’s assets that allow you to inspect, review, monitor, and compare changes over time, all without having to travel to the field. This allows users to see the asset’s conditions, forecast performance based on data collection and improve optimization from a central location.
Digital twins will transform the infrastructure sector. A few infrastructure assets that will be incorporated into a digital twin solution include highways and roads, dams and bridges, waterways, and many more. Private and public infrastructure must maintain their assets regularly, making the switch from manual inspection to a digital twin solution a no brainer when hundreds of billions of dollars are at stake.
How Can Drone Data Be Used to Make a Digital Twin?
Drones are capable of providing multiple datasets used to create an accurate, detailed digital twin. They make it easier to capture the data safely and quickly and are fully capable of attaching any sensor type to them. Drones give you the ability to capture any datasets anywhere. The possibilities are endless.
A subset of different sensor types are listed below along with their specific capabilities:
RGB – Is used to collect Red Green and Blue electromagnetic color characteristics of each pixel of information associated with the asset.
Thermal or Infrared – Is used to collect the radiometric surface temperature of the asset, thereby giving you access to specific heat temperature levels throughout the surface of the asset.
LiDAR – Is used to collect high accuracy, high precision dimensions of assets allowing accurate measurements in space.
Multispectral – Collects 5 different bands in the electromagnetic spectrum leading to more data to analyze.
Hyperspectral – Hyperspectral sensors measure energy in narrower and more numerous bands than multispectral sensors but collect a much larger data set.
Ultrasonic – Measures the thickness dimensions of the external ‘wall’ of the asset.
These six different sensor types will revolutionize the digital twin space. It’s not if this will be the future, it’s when. We are looking forward to all the new use cases owners, engineers, and inspectors will discover over the course of the next decade.
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