Case Study:The Large and the Small of the Measurement of Acoustic Emissions in Flying Aircraft Wings
Aggiornamento: 8 nov 2021
Problem: The Measurement of Acoustic Emissions in a Flying Aircraft Wing Problem Context During flight testing of a commercial aircraft wing there is a requirement to measure acoustic emissions while the aircraft is in flight. The measurements are required to be very accurate; however, there are constraints imposed by the testing environment, which make the use of accurate sensors difficult. In particular, the test aircraft imposes a restriction on the weight and volume of the test equipment that can be used. Before this problem was addressed using TRIZ, two possible approaches had been considered: 1. An electrical sensor was available. This was an excellent system that provided the required accuracy; however, it was too heavy to be used in flight. 2. A much lighter optical sensor was also available; however; this did not provide sufficient accuracy. Discussion Of Problem This is an excellent example of a non - trivial (and hence interesting) problem. There is a desirable output/ characteristic that we need (in this case measurement accuracy) that unfortunately appears to be associated with something harmful, costly or unwanted (in this case, weight). In the language of TRIZ we call this a contradiction. We can express this contradiction as a simple graph, which typically takes this form: As we try to improve one parameter (accuracy) the other (weight) becomes worse, and vice - versa. It would appear that we are constrained to remain on the blue curve, which defines the set of possible compromise solutions available to us. What we would like to be able to do is to move off the blue compromise curve to a more ideal solution, i.e. in the direction shown by the green arrow. To achieve this we need to find a way of resolving the contradiction. The identification and resolution of contradictions is a key element of the TRIZ problem - solving ethos. Inside all interesting problems we invariably find one or more such contradictions. If we can identify these contractions and resolve them we will have devised a high quality solution to our problem – not
merely a better compromise, but an innovative solution that breaks free from the existing constraints and provides a step - change towards an ideal system. In the case of this particular problem we are looking for: A sensor solution that is accurate (like the existing electronic sensor, which is too heavy) and A sensor solution that is light (like the existing optical sensor, which is not accurate enough). Our conceptual contradiction curve looks like this:
Ideally we want a sensor solution that has both good accuracy and good (which, in this case, means low) weight. At first glance (if we stay on the blue curve) we appear to be asking for the impossible; however, it is important to suspend such judgements for the moment, to follow the systematic TRIZ method and allow the possibility that our particular contradiction(s) can be resolved –even if we have no idea of how it might be done. So we accept that it is possible that there is a solution that gives us the benefits we need without the associated costs or harms. With our minds open to the existence of such a solution, we can set out to find it. Tackling the Problem In this case, the Airbus/BAE Systems team decided to use one of the classic tools from the TRIZ toolkit for solving contradictions: the Contradiction Matrix.
TRIZ for Engineers: Enabling Inventive Problem Solving.
As with much of TRIZ, this particular method provides a way of tapping in to the world ’ s experience of problem solving –in this case the world ’s experience of resolving contradictions. The method is a three-step systematic process: Step 1: Identify the contradictions in the problem, and classify them according to the nature of the contradictory system parameters. Step 2: From the TRIZ toolkit, use a statistically derived look - up table (the Contradiction Matrix) to determine which generic Inventive Principles have been successfully used in the past to resolve contradictions of the same generic type as those in our specific problem. Step 3: Take the generic Inventive Principles suggested in Step 2 and apply them to our specific problem. Through this final step it is possible to generate not just one possible solution, but usually a surprisingly large set of candidate conceptual solutions. Step 1: Identifying the Contradictions TRIZ deals with two types of contradictions: Technical Contradictions and Physical Contradictions. A Technical Contradiction is characterized by having different system parameters that constitute the contradiction, such as (in this case) measurement and accuracy. A Physical Contradiction, on the other hand, is characterized by having the contradiction derived from the same system parameter – for example an umbrella needs to be both large (when in use) and not large (when not in use). In this case the BAE/Airbus team identified two Technical Contradictions. Defining contradictions can be tricky and normally in TRIZ we recommend that you try several possibilities (do’ t agonize trying for the one perfectly defi ned contradiction): We want a sensor that is accurate but we don’ t want it to be heavy . For this contradiction we could ask why is it heavy. The answer may be to get enough power. This suggested the possibility of another type of contradiction in the problem: We want a sensor that is accurate but we don’ t want it to require lots of power. The Airbus/BAE team at Filton had identified both these Technical Contradictions:
The Two Technical Contradictions expressed in terms of problem - domain parameters
Step 2: Using the Contradiction Matrix Before the Contradiction Matrix can be used it is necessary to map the specific problem parameters (measurement accuracy, weight and power) onto the generic parameters used by the Contradiction Matrix.
For some problems this mapping of real - world problem - domain parameters onto the 39 parameters used by the matrix can be a little tricky –the matrix parameters are generic, and a certain amount of thought and careful consideration may be necessary to map the 'real world ’problem parameters to the ‘ Matrix ’ generic parameters. In this particular case it was not very difficult to arrive at an appropriate mapping as:
Parameter 28 = Measurement accuracy matched well, as did
Parameter 1 = Weight of a moving object and
Parameter 21 = Power
The full description of each of these parameters is:
1 Weight of moving object The mass of the object in a gravitational field. The force that the body exerts on its support or suspension.
28 Measurement accuracy The closeness of the measured value to the actual value of a property of a system. Reducing the error in a measurement increases the accuracy of the measurement.
21 Power The time rate at which work is performed. The rate of use of energy. Improving Parameter Worsening Parameter We want this to get better but we don ’ t want this to get worse Measurement accuracy Weight of moving object
Thus the two real - world contradictions, when mapped onto Matrix parameters become: 1. Measurement accuracy vs. Weight of moving object 2. Measurement accuracy vs. Power Each of these contradictions are used with the Contradiction Matrix to obtain suggested Inventive Principles.
Improving Parameter Worsening Parameter
We want this to get better but we don ’ t want this to get worse
Measurement accuracy Weight of moving object
These two parameters are used to cross - index the Contradiction Matrix to obtain the following four Inventive Principles that (statistically) have been found to be the most successful ways of obtaining better measurement accuracy without getting worse weight (for moving objects):
Measurement Accuracy vs. Weight of Moving Object
32 Colour Change
35 Parameter Change
28 Replace Mechanical System
Improving Parameter Worsening Parameter
We want this: but we don ’ t want this:
Measurement accuracy Power (i.e. we don ’ t want to have to provide lots of power)
In this case the Contradiction Matrix suggests the following three inventive principles:
Measurement Accuracy vs. Power
3 Local Quality
32 Colour Change
Step 3: Apply the Suggested Inventive Principles
Having derived some suggested generic Inventive Principles, the team’ s next task was to apply them to their particular problem. This is part of a recurring theme in TRIZ: we take our specific problem, generalize it in order to access known generic solutions and then finally apply the general solution to our specific problem.
Principle 32 Colour Change
A – Change the colour of an object or its external environment Use safe lights in a photographic darkroom Use colour - changing thermal paint to measure temperature Thermochromic plastic spoon Temperature - sensitive dyes used on food product labels to indicate when desired serving temperature has been achieved Electrochromic glass Light - sensitive glasses Camouflage Dazzle camouflage used on World War I ships Employ interference fringes on surface structures to change colour (as in butterfl y wings, etc)
B – Change the transparency of an object or its external environment Use photolithography to change transparent material to a solid mask for semiconductor processing Light - sensitive glass Smoke - screen
C – In order to improve observability of things that are difficult to see, use coloured additives or luminescent elements Fluorescent additives used during UV spectroscopy UV marker pens used to help identify stolen goods Use opposing colours to increase visibility –e.g. butchers use green decoration to make the red in meat look redder
D – Change the emissivity properties of an object subject to radiant heating Use of black and white coloured panels to assist thermal management on space vehicles Use of parabolic refl ectors in solar panels to increase energy capture
As Inventive Principle 32 Colour Change was suggested by the Contradiction Matrix twice, i.e. it was suggested by both of the two contradictions that were considered, the team gave particular attention to this as a solution trigger for their problem. The next task for the team was therefore to understand the Colour Change Inventive Principle. This was important – the names of the 40 Inventive Principles are just convenient labels and it is important to appreciate the full definition of each principle before attempting to apply it. In the case of Colour Change, the definition (together with some examples) is: At this point in the problem - solving process appropriate problem domain and technology domain knowledge is important. The fi nal solution that the team derived from this principle was to use of an electro - chromatic material to convert the signal from the electric sensor into a colour change that could be interrogated by an optical fibre. The team was able to quickly identify a suitable material that was already being used for adaptive camouflage applications.
TRIZ pointed them quickly towards the right solution. Once we have identifi ed the problems and uncovered the contradictions then we can use the TRIZ 40 Principles to help us locate all the relevant solutions. The unique power of TRIZ is that it includes such simple solution lists –all the freely available 40 ways/concepts the world knows to quickly solve problems containing contradiction
TRIZ for Engineers: Enabling Inventive Problem Solving, First Edition. Karen Gadd.
© 2011 John Wiley & Sons, Ltd. Published 2011 by John Wiley & Sons, Ltd. ISBN: 978-0-470-74188-7