Hardly a week goes by without a plane somewhere in the US making an emergency landing after hitting birds. As these incidents reach record levels, airports are coming up with increasingly imaginative ways of combating them.

Detection using RADAR gets in mention in item 10:

10.The Dutch air force is using a bird detecting radar that could eventually be adopted by civil aircraft. “We’ve known since WWII that radar can see birds, when they were coming across the Channel and they figured it was birds and not German bombers,” says Begier. These bird detecting radars are small and mobile, and technology has come on in the last 10 years, but they can’t yet identify the species or numbers. “The ability to delay a commercial flight with technology that’s not quite there is the problem.”

The above might be referring to the robin radar system.

Source: BBC

Here’s the link

The Irish Aviation Authority have issued the following statement:

1015hrs 10 February 2011: Flight Avia No FLT400C a metroliner SW4 with ten passengers and two crew has crashed at Cork Airport. No details of injuries or fatalities are available. The aircraft made an approach to Runway 17 in low vis conditions (Category 2) and went around and did not land and attempted a second landing on Runway 35. The aircraft then went around a second time and came back for an approach to Runway 17. On the second approach to Runway 17 the aircraft crashed adjacent to Taxiway C. Rescue and Fire crew are in attendance. There is a fire and debris has been scattered onto the runway and over a wide area. The accident will be investigated by the Air Accident Unit of the Dept. of Transport. This is correct at this time and may be amended as more detail becomes available. (source)

My thoughts go out to the friends and family of those involved.

If a system takes 6 minutes to detect an item of FOD, and the next aircraft is due in 4 minutes, then the FOD detection system is completely ineffective at reducing risk.

It’s the sort of argument that people in marketing dream of, not only does it appear to make a lot of sense, but FOD detection time is easy to quantify, and therefore it’s easy to compare across the various systems. Unfortunately, it does not stand up to any form of rigorous analysis. So, let’s take at look at this in more detail, the first thing we need to do is to define the risk from FOD.

What is risk?

It’s often very difficult to quantify risk in any meaningful way, but with FOD it’s actually quite easy. The risk posed by FOD is proportional to the time the FOD object spends on the runway surface (or other airfield surfaces). Of course, the risk from an item of FOD will also depend on exactly where the FOD is found, and what the object is, but, with a large enough data set these two factors should become less important, and then you’re left with the risk from FOD simply being proportional to the time the object spends on the airfield surface.

For example, a single item of FOD on the runway for 1 hour represents the same risk as two items of FOD on the runway for 30 minutes each. It’s even possible to give units, and I’m going to call the units of FOD risk “FOD minutes” (as it’s simply the number of FOD items multiplied by the time on the surface)

An example

Let’s consider a very simple example of a single item of FOD that is on the runway for 3 hrs, and there is no FOD detection system installed. (I’ve assumed the runway is manually checked every 6 hrs, so the mean time FOD will spend on the runway is 3hrs)

• The risk posed by this one item is 1 x 180 mins = 180 FOD minutes

Now let’s add a FOD detection system and see what happens, let’s assume that the FOD detection system has a detection time of 2 minutes.

• The risk posed by this one item is 1 x 2 mins = 2 FOD minutes

But, it gets even better, if there is an aircraft movement every 4 minutes then for any detection time less than 4 min the FOD risk will actually be zero! Unfortunately this hypothetical case is so simple it’s essentially meaningless, this examples makes 3 assumptions:

1. All FOD items originate from the last aircraft that used the runway
2. The risk from FOD is proportional to the detection time
3. The FOD system detects all FOD

Lets deal with each one of these in turn:

1. Assuming that all FOD originates from the previous aircraft is unrealistic, it assumes that there are no other sources of FOD, such as items from ground vehicles, wildlife, litter, broken concrete or tarmac, stones, tools, luggage etc.
2. The risk from FOD is proportional to the time the FOD spends on the surface, this is the detection time plus the retrieval time. The FOD does not magically disappear after it has been detected.
3. No FOD system is 100% effective. Each will have a probability of detection. So there will still be some FOD on the runway which will be found during manual checks.

A better example

Let’s create a more realistic example that includes the probability of detection, retrieval time, and assumes that there are sources of FOD other than the previous aircraft. First we have to generate a hypothetical airport, this airport has the following parameters:

1. 300 Items of FOD are found at the airport each year.
2. It takes, on average, 5 mins to retrieve an item of FOD.
3. There are 6 hrs between manual FOD checks.
4. The average time between aircraft movements is 4 mins.
5. 50% of all FOD found came from the previous aircraft.

Now let us also introduce two FOD detection systems that differ only in their probability of detection and their detection time.

• System A: Detection time = 1 min. Probability of detection = 90%
• System B: Detection time = 7 mins. Probability of detection = 95%

So which system is most effective at reducing the risk due to FOD? Well, the probability of detection differs by just 5%, but the detection time for system B is 600% greater than for system A. Not only is it 600% greater, but it’s also greater than the the mean time between aircraft movements.

So, the answer is obvious, isn’t it? Actually, each system reduces the risk from FOD by almost exactly the same amount, down to around 10% of the original risk when no FOD detection system was installed (System A reduces the risk to 13%, and system B to 11.3%). More information is included in the image below.

Click to Zoom

But what if both systems had the same probability of detection and only differed in their detection time? In this case, where both systems have a 95% probability of detection, system A has now reduced the risk from FOD to just 8.2%, and system B remains unchanged at 11.3%. So yes, detection time is a factor. But, a massive reduction in detection time results in a very small reduction in risk.

So, why don’t all the FOD detection systems just reduce their detection time to less than the mean time between aircraft movements?

The fact is that you don’t get something for nothing, and this is true for detection systems. And this is where it starts to get interesting. Each of the systems can probably reduce their detection times, if they wished, but, it would come at a cost, and that cost could be a reduction in probability of detection . And we’ve just seen an example where a system that had a smaller detection time (by 600%), had that advantage wiped out by a system that had a better probability of detection, by just 5%!

This is best explained with an example. Consider a detection system (FOD or not, it doesn’t matter) based on a visible camera system. The system makes detections based on information it receives, and that information is in the form of light entering the camera. Less light, less information, reduced probability of detection. So, what happens when it gets dark? One of two things can happen:

1. The camera collects less light, and the probability of detection reduces
2. The camera stares for longer, i.e. it collects light for longer, and the probability of detection remains constant.

There is a FOD detection system on the market that is based on a visible camera system, and the detection time does indeed increase as it gets dark. Why did they choose to follow option 2 above? why not just follow option 1 and allow the probability of detection to decrease. It’s simple, they realise that probability of detection is far more important that detection time.

So, does this mean that systems with a longer detection time are better?

No, I wish it were that simple, but it’s impossible to compare the trade-off between probability of detection and detection time across systems that are based on different technologies. It’s quite possible that a system based on one form of technology will have a better probability of detection, and a shorter detection time.

Does a reduction in detection time always result in a decrease in probability of detection?

No, it’s possible to reduce detection time while keeping probability of detection constant. When you reduce detection time you’re essentially degrading the quality of the data used to determine the detection, you can still maintain the probability of detection by increasing the system’s sensitivity, but again, you don’t get something for nothing. Increasing the sensitivity will lead to an increase in false alarms, and we’re not talking about a few percent. An increase in the false alarm rate is in itself not a problem, if it means maintaining the probability of detection then you’re still reducing the risk on the runway, which of course is the goal. But, if the false alarm rate is so high that the operator starts to ignore the alarms, that’s when the risk on the runway starts to increase again.

So which system suffers from these trade offs between detection time, probability of detection and false alarm rate?

It doesn’t matter if the FOD detection system uses cameras, radar or lidar, the trade-offs still exist. Actually it doesn’t matter if it’s a FOD detection system or not, it’s fundamental to all detection systems. Radar, cameras (visible, infrared), lidar, human beings, sniffer dogs, or squirrels looking for nuts on the forest floor, they are all detection systems and they all suffer these issues. Lets consider the current FOD detection system used in every airport today, the human being, he drives down the runway at a particular speed trying to detect FOD. Let’s reduce his detection time, it’s easy, ask him to drive twice as fast, unfortunately he now has 1/2 as long to look at each object. So what’s the trade-off in this situation? Typically he will find less FOD (the probability of detection will fall), but what if he has been given strict instructions to find the same amount of FOD (i.e. maintain the probability of detection),  well, he can do that, but  the amount of false alarms will rise. It’s a silly example, but it proves the point.

So why do some vendors still insist that their system is better just because they have a shorter detection time?

Unfortunately, it’s our fault. We like comparing numbers, it’s easy, system A has a shorter detection time than system B, therefore I’m going to buy system A. The best analogy I can make is with digital cameras. The number of megapixels a camera has is still used by many people as the factor that most influences which camera they buy. It’s easy to compare this parameter across various cameras. But, much like detection systems, there is a trade off, if the digital camera sensor size remains constant, then as the number of pixels is increased, each pixel has to be made smaller, and unfortunately this tends to increase the noise in the system, and this can result in reduced image quality. And comparing the image quality from different cameras is much harder than comparing the number of megapixels they have. It’s very similar to FOD detection systems, comparing detection time is easy, but comparing the probability of detection, or false alarm rate is not.

To sum up, I’m not saying that detection time is not important, I’m just saying that it’s not as important as it would first appear (and there are far more important parameters to consider). Always remember that the goal of a FOD detection system is to reduce the risk from FOD, it’s not to have the shortest detection time, or the lowest number of false alarms. And to the person (who didn’t  leave their name, position, company, or a usable email address) who asked “Did you neglect the timing requirement[detection time] when you did your system design???[sic]”, I have one question for you, “did you only consider the detection time when you designed/bought your system?” if the answer is Yes, then all I can say to you is “Oops”

I disagree with you, how do I comment? Is an anonymous email the best method?

Ummm….let me think about this….no, an anonymous email is not the preferred method. I’m aware that not everyone is familiar with a blog style website, so here are some basic instructions for anyone who wishes to comment on this article.

At the bottom of this article (and every article on this website) is a section entitled Leave a Reply, this is where comments should be left. It’s public, it allows others to see the comments, which I believe is useful, especially if they have similar comments. If someone has an issue with a particular assumption I’ve made, such as “50% of FOD originates from the previous aircraft”, please remember that this is not supposed to represent an average value, or a value for a particular airfield. If you have some real data for the airport values used above then please use the spreadsheet (link at the end of this article), do the calculation for your particular airport, include your system’s detection time and probability of detection and include your results in the Leave a Reply section.

If you discover an error in the calculation itself then let me know in the Leave a Reply section, I’m human, mistakes happen. The spreadsheet is available for anyone to download, it’s completely open, there are no hidden or protected fields. Please feel free to check the calculations yourself (build on the original calculation if you wish, add other airfield surfaces, change the risk for each surface, add a probability of detection for the manual checks etc). I have nothing to hide, and I’m a fan of transparency. If you are really uncomfortable with your comments being public then feel free to use the Contact Form, but my personal preference is that we keep any discussions public.

The Spreadsheet

Since starting to write this article the spreadsheet has grown and become more involved than was originally planned. It now includes the ability to input data for 3 FOD detection systems, and also allows the user to select which action is taken when FOD is detected, i.e. to close the runway and retrieve, or to continue operations and retrieve. The spreadsheet is provided, as is.

Download the Spreadsheet (FOD risk v2)

I’d like to hear from people who have considered purchasing a FOD detection system, but have, for one reason or another, decided not to proceed. If you would like to contribute then please use the contact form and get in touch. All communication will be strictly confidential.

Here’s an extract:

Since the Concorde accident, four automatic systems have been developed and have been evaluated by the FAA’s Center of Excellence for Airport Technology at the University of Illinois. All four met FAA criteria, and are each eligible for Airport Improvement Program (AIP) funding, effective October 1. One major airport in the Northeast is understood to have ­submitted its AIP application already.

Read the full article here.

The patent basically describes a number of monitoring devices located alongside a runway, where the monitoring device:

includes at least one of a video camera, single-frame camera, infrared camera, high definition camera, Light Detection and Ranging device.

The detection is then done by comparing a baseline image to the current image:

at least one monitoring device generates baseline image data associated with a first condition, generates other image data associated with at least a second condition and the at least one processor compares the image data associated with the conditions to determine whether foreign object debris is present in the at least one runway area

The system then generates an alert if an unacceptable runway condition is detected:

wherein the unacceptable runway condition may include at least one of, vehicle traffic congestion outside acceptable tolerances, presence of an unacceptable amount of ice, presence of fire, and presence of foreign object debris.

Here’s a quote from a recent press release:

We have at length discussed the viability of the patented product and technology and the fact that there are very few competitors in this market and none with the kind of product licensed to Secure. To my knowledge none of the competition holds patents on their products and Secure’s license provides Secure with an advantage and product which we believe is superior to the competition.

I must admit that I find the above statement quite surprising, especially the comment regarding the competitions lack of patents, and the fact that their “product is superior”. As far as I’m aware they don’t have a product, they have a patent that describes a general process, I don’t think you can really compare an actual product against a patent, not in any meaningful way anyway. The slide below dated July 2010 details the current state of their “product”.

(see full presentation)

I don’t want to say too much about this, but if you’re interested then please visit their website.

Links:

• Patent (PDF)
• Diversified Secure Ventures Corp Homepage
• Presentation

…well, there isn’t, but I firmly believe there should be.

I’ve just read through the new FAA draft Circular on FOD Management, and it discusses the fact that it’s the responsibility of everyone to report FOD if they come across it. I believe that if you want people to do something, especially if it’s not their main role, you have to:

• make the function quick and easy to perform, and
• offer an incentive.

And let’s get one thing straight, asking a contractor who’s working airside to visit an office on the far side of the airfield to locate and complete a FOD reporting form does neither of these, it’s definitely not quick, and there’s no incentive. Actually it’s more likely to get them into trouble with their boss as they’d have to explain why they’d not been doing their job for the last 30 minutes!

The first thing you have to do is to give the person who found the FOD a method of recording the event then and there, because if they plan to leave it until the end of their shift then it’s not going to get done at all, and I’m not talking about a new device for them to carry around all day, because they won’t carry it. You have to take advantage of the fact that it’s very likely that they’re carrying a small recording device with them anyway, and yes, if you haven’t already guessed from the mock poster above, I’m talking about a smartphone.

There are 3 reasons why  smartphones are perfect for recording FOD finds:

• they have cameras
• they have GPS
• they can transmit data

The apps function would be very simple with the help of mobile testing services, take a picture of the FOD, select a category (wildlife, tools etc), and assign a risk (low, medium, high), that’s it. The image would be tagged with the location via GPS,and the data would then be sent to a central database. Once the FOD find has been recorded, the app could then give the location of the nearest FOD bin, or supply the phone number of the FOD manager.

Provide an incentive

Even if something is quick and easy to do people still need an incentive to do it. If the user who downloads the app also has to register, then any FOD finds they record will be registered against them, and then it’s simply a case of offering some form of reward, e.g. entry into a monthly prize draw. The more FOD they record the more likely they are to win.

Make it global

One of the advantages of this concept is that once a user has downloaded the app and registered as a user, it could be used on any airfield in the world, the GPS data would be all that’s required to identify the airfield, and this location information would then supply custom information back to the user i.e. the phone number of the FOD manager and the location of the FOD bins (or any FOD procedures that are unique to the airfield)

It’s all about the sharing

Where would all this FOD information go? I would strongly suggest to a single, centrally (FAA?) managed database. Airports could be given access via a website to the data collected from 100’s of airports, this data could then be used to generate better targeted FOD procedures.

If you have any thoughts on this concept then please leave a comment in the comments section below, or get in touch via the contact form.

The engines on a French Concorde are to be examined as the first move in a £15m project aiming to get the supersonic passenger jet back in the air.

The article goes on to state:

It is hoped the jet will be able to fly as part of the opening ceremony of the 2012 London Olympics.

The verdict from the trial is expected on December 6th .

The blue ice runway is groomed by the camp staff using commercial lightweight snow ploughs and blowers (which could be shipped in by Dash 7 aircraft). When the wind is favourable, and the conditions good, a runway 1.2 km in length and 50 m wide is possible. However, operations are often hampered by much lighter winds causing knee high snow drifts which reduce contrast. The runway is marked by flags and large colourful bin bags to improve contrast for approaching planes.

Given the fact that they’re using bin bags to improve the contrast for pilots, I think they probably have a few key items to purchase before splashing out on a FOD detection system!

Click to zoom