Six months ago, I wrote about ‘Finding DIMES’ as we kicked off a new EU-funded project to develop an integrated measurement system for identifying and tracking damage in aircraft structures. We are already a quarter of the way through the project and we have a concept design for a modular measurement system based on commercial off-the-shelf components. We started from the position of wanting our system to provide answers to four of the five questions that Farrar & Worden  posed for structural health monitoring systems in 2007; and, in addition to provide information to answer the fifth question. The five questions are: Is there damage? Where is the damage? What kind of damage is present? How severe is the damage? And, how much useful life remains?
During the last six months our problem definition has evolved through discussions with our EU Topic Manager, Airbus, to four objectives, namely: to quantify applied loads; to provide condition-led/predictive maintenance; to find indications of damage in composites of 6mm diameter or greater and in metal to detect cracks longer than 1mm; and to provide a digital solution. At first glance there may not appear to be much connection between the initial problem definition and the current version; but actually, they are not very far apart although the current version is more specific. This evolution from the idealised vision to the practical goal is normal in engineering projects.
We plan to use point sensors, such as resistance strain gauges or fibre Bragg gratings, to quantify applied loads and track usage history; while imaging sensors will allow us to measure strain fields that will provide information about the changing condition of the structure using the image decomposition techniques developed in previous EU-funded projects: ADVISE, VANESSA (see ‘Setting standards‘ on January 29th, 2014) and INSTRUCTIVE. We will use these techniques to identify and track cracks in metals ; while for composites, we will apply a technique developed through an EPSRC iCASE award from 2012-16 on ‘Full-field strain-based methods for NDT & structural integrity measurement’ .
I gave a short briefing on DIMES to a group of Airbus engineers last month and it was good see some excitement in the room about the direction of the project. And, it felt good to be highlighting how we are building on earlier investments in research by joining the dots to create a deployable measurement system and delivering the complete picture in terms of information about the condition of the structure.
Image: Infra red photograph of DIMES meeting in Ulm.
The INSTRUCTIVE and DIMES projects have received funding from the Clean Sky 2 Joint Undertaking under the European Union’s Horizon 2020 research and innovation programme under grant agreements No. 685777 and No. 820951 respectively.
The opinions expressed in this blog post reflect only the author’s view and the Clean Sky 2 Joint Undertaking is not responsible for any use that may be made of the information it contains.
The moral of this story is don’t travel with me. Last week, I wrote about my train being delayed by someone pulling the emergency handle before we got to the end of the platform in Liverpool [see ‘Stopped in Lime Street’ on June 26th, 2019]. Four days later, I was once again on a late afternoon train to London waiting for it to leave Lime Street station. This time we didn’t even get started before the train manager announced that a road vehicle had hit a bridge between Crewe and Liverpool; and, so we were being held in Liverpool for an unknown period of time. I sent a message to my family telling them about the delay and one, an engineer, replied that I was ‘hitting the low frequency failure modes on the service quality pareto’. The Pareto principle is also known as the 80/20 principle. I first encountered it when I was working at the University of Sheffield and the Vice-Chancellor, Professor Gareth Roberts, used it to describe the distribution of research output in academic departments, i.e., 80% of research was produced by 20% of the professors. In service maintenance, it is assumed that 80% of service interruptions are caused by 20% of the possible failure modes. Hence, if you can address the correct 20% of failure modes then you will prevent 80% of the service interruptions, which is an efficient use of your resources. The remaining, unaddressed failure modes are likely to occur infrequently and, hence, can be described as low frequency modes; including passengers pulling emergency handles or people driving vehicles into bridges.
How do you drive into a bridge and block the main railway lines between London and the north-west of England? Perhaps the driver was using their smart phone which was not smart enough to warn them of the impending collision with the bridge. So, there’s a new product for someone to develop: a smartphone app that connects to dashboard camera in your vehicle and warns you of impending collisions, or better still just drives the vehicle for you. Yes, I know some vehicles come with all of this installed but not everyone is driving the latest model; so, a retro-fit system should sell well and protect train passengers from unexpected delays caused by road vehicles damaging rail infrastructure.
By the way, the 14:47 to London magically became the 15:47 to London and left on time!
It is a late, slightly muggy, summer afternoon and I am sitting at the window in the last carriage of a train waiting for it to leave Liverpool for London. So far, it has been a busy day with meetings in the morning at the University’s facility at Daresbury followed by a couple on the main campus before I walked down to Lime Street station. I stopped for a bite to eat as I travelled from Daresbury to Liverpool; but I am hungry again, so I have a sandwich that I bought in the station. However, I don’t like to unpack and start eating until the train starts moving, just in case I am on the wrong train or we have to change trains. Finally, the train starts to move and as it builds up speed I reach for my sandwich. Suddenly it stops. My carriage has not even reached the end of the platform. Station staff appear outside my window talking into their radios. What’s happened? Did the train hit someone? I thought there was a small thud just before we stopped. But the station staff seem unflustered. Wouldn’t there be more urgency about their movements if there was a casualty? We sit in silence for ten minutes before the train starts to move again and the train manager announces that someone pulled the emergency handle because they decided that wanted to get off the train. Why did they want to get off the train? Did they realise they were trapped on the train to London with someone who was pursuing them? Was it a police officer who realised that their quarry had jumped off the train just before it set off? Or, have I been reading too many Eric Ambler stories (see ‘The Mask of Dimitrios‘ or ‘Journey into Fear‘) involving train journeys across Europe? Maybe it was someone who just decided that they didn’t want to go London after all and didn’t care about inconveniencing several hundred people or paying the fine for improper use of the emergency handle. But that seems unlikely too or perhaps not… I contemplate these options as the train accelerates towards London and I munch my sandwich. It reminds me of a quote from Gillian Tett (in the FT Weekend on June 17/18, 2017) about people believing they have a ‘God-given right that they should be able to organise the world around their personal views and needs instead of quietly accepting pre-packaged options’.
As engineers, we like to draw simple diagrams of the systems that we are attempting to analyse because most of us are pictorial problem-solvers and recording the key elements of a problem in a sketch helps us to identify the important issues and select an appropriate solution procedure [see ‘Meta-representational competence’ on May 13th, 2015]. Of course, these simple representations can be misleading if we omit parameters or features that dominate the behaviour of the system; so, there is considerable skill in idealising a system so that the analysis is tractable, i.e. can be solved. Students find it especially difficult to acquire these skills [see ‘Learning problem-solving skills‘ on October 24th, 2018] and many appear to avoid drawing a meaningful sketch even when examinations marks are allocated to it [see ‘Depressed by exams‘ on January 31st, 2018]. Of course, in thermodynamics it is complicated by the entropy of the system being reduced when we omit parameters in order to idealise the system; because with fewer parameters to describe the system there are fewer microstates in which the system can exist and, hence according to Boltzmann, the entropy will be lower [see ‘Entropy on the brain‘ on November 29th, 2017]. Perhaps this is the inverse of realising that we understand less as we know more. In other words, as our knowledge grows it reveals to us that there is more to know and understand than we can ever hope to comprehend [see ‘Expanding universe‘ on February 7th, 2018]. Is that the second law of thermodynamics at work again, creating more disorder to counter the small amount of order achieved in your brain?