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sensor within the device, rises or falls above or below the set point. In a more sophisticated
controller, a signal from a measurement system can be used as an input to an ‘‘expert system’’
controller that, through an artificial intelligence algorithm, determines the optimum set conditions
for the process. Mechatronics deals with the interfacing of mechanical and electrical components
with microprocessors, controllers, and measurements. We will discuss some features of mechatronic
systems in detail in Chapter 12.
1.3 EXPERIMENTAL TEST PLAN
An experimental test serves to answer a question, so the test should be designed and executed to
answer that question and that question alone. This is not so easy to do. Let’s consider an example.
Suppose you want to design a test to answer the question, ‘‘What is the fuel use of my new car?’’
What might be your test plan? In a test plan, you identify the variables that you will measure, but you
also need to look closely at other variables that will influence the result. Two important variables to
measure would be distance and fuel volume consumption. Obviously, the accuracy of the odometer
will affect the distance measurement, and the way you fill your tank will affect your estimate of the
fuel volume. But what other variables might influence your results? If your intended question is to
estimate the average fuel usage to expect over the course of ownership, then the driving route you
choose would play a big role in the results and is a variable. Only highway driving will impose a
different trend on the results than only city driving, so if you do both you might want to randomize
your route by using various types of driving conditions. If more than one driver uses the car, then the
driver becomes a variable because each individual drives somewhat differently. Certainly weather
and road conditions influence the results, and you might want to consider this in your plan. So we see
that the utility of the measured data is very much impacted by variables beyond the primary ones
measured. In developing your test, the question you propose to answer will be a factor in developing
your test plan, and you should be careful in defining that question so as to meet your objective.
Imagine how your test conduct would need to be different if you were interested instead in
providing values used to advertise the expected average fuel use of a model of car. Also, you need to
consider just how good an answer you need. Is 2 liters per 100 kilometers or 1 mile per gallon close
enough? If not, then the test might require much tighter controls. Lastly, as a concomitant check, you
might compare your answer with information provided by the manufacturer or independent agency
to make sure your answer seems reasonable. Interestingly, this one example contains all the same
elements of any sophisticated test. If you can conceptualize the factors influencing this test and how
you will plan around them, then you are on track to handle almost any test. Before we move into the
details of measurements, we focus here on some important concepts germane to all measurements
and tests.
Experimental design involves itself with developing a measurement test plan. A test plan draws
from the following three steps:
2
1. Parameter design plan. Determine the test objective and identify the process variables and
parameters and a means for their control. Ask: ‘‘What question am I trying to answer? What
needs to be measured?’’ ‘‘What variables and parameters will affect my results?’’
2 These three strategies are similar to the bases for certain design methods used in engineering system design (1).
6 Chapter 1 Basic Concepts of Measurement Methods
15:40:34 Page 6
sensor within the device, rises or falls above or below the set point. In a more sophisticated
controller, a signal from a measurement system can be used as an input to an ‘‘expert system’’
controller that, through an artificial intelligence algorithm, determines the optimum set conditions
for the process. Mechatronics deals with the interfacing of mechanical and electrical components
with microprocessors, controllers, and measurements. We will discuss some features of mechatronic
systems in detail in Chapter 12.
1.3 EXPERIMENTAL TEST PLAN
An experimental test serves to answer a question, so the test should be designed and executed to
answer that question and that question alone. This is not so easy to do. Let’s consider an example.
Suppose you want to design a test to answer the question, ‘‘What is the fuel use of my new car?’’
What might be your test plan? In a test plan, you identify the variables that you will measure, but you
also need to look closely at other variables that will influence the result. Two important variables to
measure would be distance and fuel volume consumption. Obviously, the accuracy of the odometer
will affect the distance measurement, and the way you fill your tank will affect your estimate of the
fuel volume. But what other variables might influence your results? If your intended question is to
estimate the average fuel usage to expect over the course of ownership, then the driving route you
choose would play a big role in the results and is a variable. Only highway driving will impose a
different trend on the results than only city driving, so if you do both you might want to randomize
your route by using various types of driving conditions. If more than one driver uses the car, then the
driver becomes a variable because each individual drives somewhat differently. Certainly weather
and road conditions influence the results, and you might want to consider this in your plan. So we see
that the utility of the measured data is very much impacted by variables beyond the primary ones
measured. In developing your test, the question you propose to answer will be a factor in developing
your test plan, and you should be careful in defining that question so as to meet your objective.
Imagine how your test conduct would need to be different if you were interested instead in
providing values used to advertise the expected average fuel use of a model of car. Also, you need to
consider just how good an answer you need. Is 2 liters per 100 kilometers or 1 mile per gallon close
enough? If not, then the test might require much tighter controls. Lastly, as a concomitant check, you
might compare your answer with information provided by the manufacturer or independent agency
to make sure your answer seems reasonable. Interestingly, this one example contains all the same
elements of any sophisticated test. If you can conceptualize the factors influencing this test and how
you will plan around them, then you are on track to handle almost any test. Before we move into the
details of measurements, we focus here on some important concepts germane to all measurements
and tests.
Experimental design involves itself with developing a measurement test plan. A test plan draws
from the following three steps:
2
1. Parameter design plan. Determine the test objective and identify the process variables and
parameters and a means for their control. Ask: ‘‘What question am I trying to answer? What
needs to be measured?’’ ‘‘What variables and parameters will affect my results?’’
2 These three strategies are similar to the bases for certain design methods used in engineering system design (1).
6 Chapter 1 Basic Concepts of Measurement Methods