Beneath the waves

How a simple test can reveal invaluable data

Published:  26 March, 2015

By Steve Smith

Whilst we attempt to keep diagnosis as non-intrusive as possible during the initial vehicle evaluation, there comes a point when we have to go further armed with the knowledge obtained during the assessment and the customer interview, often referred to as the 'golden hour'.

We know we have a host of test equipment and test procedures at our disposal to make informed decisions based on results obtained but the skill is knowing what test to apply and when.

Here, I would like to discuss a relatively non-intrusive and simple test to a typical engine management sensor that can reveal far more than was ever imagined. Using PicoScope to capture a Crankshaft sensor signal, we can evaluate:

? The formation of the signal for irregularity (damaged teeth)

? The amplitude of our signal to confirm sensor and circuit integrity

? Engine RPM

? Acceleration and deceleration of the crankshaft relative to combustion (misfires)

? Cylinder balance

? Compression events

Figure 1

Using the identical crankshaft signal waveform we can now apply a Maths Channel to reveal even more. Let's first calculate RPM. Our crankshaft pick-up ring has 36 teeth with 2 missing as a TDC reference. Whilst in reality we have 34 teeth, we must include the missing teeth in our formula for accurate RPM results. To explain further how the maths channel can display RPM, we need to look at the theory below:

? Frequency is measured in Hz (Cycles per second)

? We are looking at the frequency of the engine speed signal in Hz's but require RPM

? RPM = FREQUENCY (Hz) X 60

PicoScope measures the frequency of 36 teeth of the crankshaft sensor pick-up (one crankshaft revolution) and multiplies this value by 60 (seconds) to obtain RPM: 36 Teeth of our crankshaft pick up are equal to = Hz x 60

The Maths Channel formula for RPM is written as follows: "60/36*freq(A)"

With your captured waveform on screen:

1.    Select "Tools>Maths Channels" and then Create.

2.    Click on Advanced and type "60/36x" in the formula box.

3.    Now click on the freq button. When "freq( )" appears in the formula box, put your cursor in-between the two brackets "( )" and type A, the whole formula will look like "60/36*freq(A)"

Click Next and choose any colour you prefer for your RPM maths channel. In the units section, type "Engine Speed" in the long name box and "RPM" in the short name box. In the range select box it is best to set a manual override for the actual range you require (in the example below I have selected 0 RPM to 1,000 RPM) and finally click Finish. Enable the box next to your created Maths Channel and click OK. A new 2nd Maths Channel will appear and will plot the RPM of the channel you have requested.

Figure 2

? Engine speed (RPM)

? The reduction in crankshaft speed during compression and acceleration after combustion (misfire indication)

? The overall uniformity of the maths channel reveals good cylinder balance (engine run)

? Uniform cylinder compressions (engine run or cranking)

? Actual TDC is not aligned with engine position reference point (2 missing teeth ­- A common misconception)

As a basic indication of airflow, using the formula below we can estimate MAF for any normally aspirated engine speed (assuming a WOT):

? 3,000 RPM / 60 = 50 Rev per second (Hz)

? For each engine revolution of our 4- cylinder engine we have 2 x intake strokes

? Therefore 50 rev per second / 2 = 25 intake strokes per second

PicoScope calculates the RPM but now incorporates the additional formula to account for two intake strokes and a 1.8 litre engine. Once again select Tools>Maths Channels and then Create. Click on Advanced and type the exact formula as above for RPM 60/36*freq(A) but now add /60/2*1.8. The whole formula looks like "60/36*freq(A)/60/2*1.8".

Figure 3

One test on one wire, utilising one PicoScope channel has revealed eight critical pieces of information about our engine run condition. The technician can now make an informed decision on the next step through the diagnosis based on the documented evidence above.

FIGURE 1

FIGURE 2

FIGURE 3

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