Tech Tips April 2005


APRIL 26, 2005




Systems possibly subject to FDA 21 CFR Part 11.


Systems possibly subject to the U.S. Food and Drug Administration's (FDA) 21 CFR Part 11 regulations include:


Stability systems
Toxicology systems
Laboratory robotic systems
Environmental monitoring systems
Laboratory instruments with data acquisition capability
Laboratory information systems
Other data acquisition systems


Case report form systems
Clinical data management systems
Remote data entry systems
Remote data capture systems
Adverse event reporting systems
Other data acquisition systems


Manufacturing execution systems
Maintenance management systems
Calibration management systems
Building management systems
Enterprise resource planning systems
Control and automation systems
Other data acquisition systems


Document management systems
Good practices and other product tracking systems
Standard operating procedure systems
Other data acquisition systems


Dave Harrold, contributing editor


Source: Dave Harrold, 'I'm from the Government and I'm Here to Help You,' Control Engineering, April '02, p. 29.




APRIL 19, 2005




Pneumatic valve selection.


Valves are at the heart of pneumatic control systems, with directional and proportional control valve varieties serving as major choices. Directional control valves (DCVs) are arguably the most frequently used valves. They control the direction of compressed air (or other suitable fluid), for instance, to determine whether a cylinder stroke advances or retracts.


DCVs are identified according to the number of their main connections and possible switching positions. For example, a '3/2 valve' refers to three ports and two switching positions. Besides their function according to ports and switching positions, directional control valves differ in mechanical and functional design. DCV design types include: poppet (ball poppet, flat-seal poppet), spool, flat slide, and rotary slide. Even among these types, other design methods and materials may be used. For example, a spool valve can have sealing rings along its spool or the seals could be housed in the valve body instead. Design features influence the valve's service life, flow rate, actuating elements, actuating forces, size, and price.


While directional valves are used to perform complete switching operations, proportional valves (PVs) regulate pressures and flow rates. Conversion of an input signal into a specific output signal is the most important basic characteristic of proportional valves. PVs normally consist of two elements—a pilot control and a valve unit. Pilot control consists of two 2/2-way pilot valves or a proportional solenoid, and includes the evaluating electronics. The valve unit consists solely of integrated pneumatic functions.


An electrical dc voltage (such as 0-10 V or 0-20 mA current) is applied at the control block connection. Voltage or current then corresponds to a specific pressure to be controlled. Actual pressure at the working port is measured by the integrated pressure sensor and transmitted to the evaluating electronics, which compares actual pressure with desired pressure. The electronics unit then switches the pilot valves according to the pressure deviation and, in turn, the operating positions of the main valve until the desired pressure is obtained.


Proportional DCVs do more


With 'standard' directional control valves, only the individual switching position can be assumed. Proportional directional control valves also permit intermediate positions. This means that apart from the end positions, such as 'open' or 'closed,' intermediate 'slightly open' positions are also possible.


The actuating element for the switching of working positions is a proportional solenoid. When electronically actuated, the solenoid changes the voltage in its coil segments and the position of the control piston changes according to the altered field strengths. As a result, individual air passages simultaneously open or close to varying degrees via the control piston. This not only enables open- or closed-loop control of a cylinder's direction of movement, but also its speed. Here, the valve assumes a so-called throttling function. With a switching frequency of approximately 100 Hz, these valves can achieve extremely high dynamics.


Proportional valves have wide application, such as pneumatically maintaining a constant tension force during the unwinding of lengths of material. Proportional directional control valves have further application in the positioning of cylinders. In such a case, the cylinder is equipped with a displacement encoder, which supplies a feedback signal of the actual piston position. To obtain a specific position, the valve controls volumetric flow into or out of the cylinder.


Frank Langro, product management manager; Frank Latino, valve terminals and electronics product manager, Festo Corp.,


Source: Frank Langro and Frank Latino, 'Pneumatic valve choices,' Back to Basics, Control Engineering, Aug. '04, p. 76.




APRIL 12, 2005




Signal conditioning characteristics and requirements.


Signal conditioning is a basic component of all measurement devices. It converts incoming measurements into a form acceptable to digitization hardware. Signal conditioning not only defines what types of signals the system can accept, but also defines what additional features the system has to offer. Here are some commonly encountered terms and their definitions:


  • Isolation—Isolation provides the protective barrier between digitization hardware and the real world, preventing common-mode voltage or signal spikes from damaging the measurement system. Additionally, channel-to-channel isolation prevents one input signal from arcing to another input channel and back out of the system. Finally, isolation prevents noise producing ground loops, which decrease signal quality. It is required when incoming signals have common-mode voltages higher than (10 volts, or there is a chance for large spikes in the signal.

  • Transducer excitation—Many common sensors require power to generate a signal. These include strain gauges and RTDs. Transducer excitation provides this power so sensors do not require external power sources.

  • Cold-junction compensation—This specific type of signal conditioning is required by thermocouples. Cold-junction compensation removes small voltage errors caused by connecting a thermocouple using terminal blocks made of different metals than the T/C itself. It does this by reading the ambient temperature at the point where the thermocouple connects to the system.

  • Filtering—The filtering process blocks unwanted signal frequencies arising from external noise sources (generators, motors, power lines, etc.) from incoming signals. Proper filtering also prevents anti-aliasing, where higher frequency components of a signal appear as lower frequency components.

  • Amplification/Attenuation—Amplification increases signal amplitude before digitization occurs. Amplification increases the measurement accuracy of small signals and reduces the effects of surrounding noise sources. Attenuation reduces signal amplitude before digitization occurs, increasing the signal input range capabilities of the system.

  • Linearization—Often sensors do not have a linear relationship between their signal value and the physical quantity they are measuring. A thermocouple's nonlinear temperature-to-voltage relationship is a prime example. Linearization maps the relationship between a sensor's signal value and the physical quantity it is measuring so that an incremental change in the physical quantity corresponds to a similar incremental change in the signal. It can be implemented in either the hardware or software component of a system.

  • Multiplexing—Expansion of a measurement system's I/O channel count can be expanded by passing multiple signals to the same digitization hardware. Use of multiplexing techniques allows acquisition of more signals for less money.

  • Bridge completion—This specific type of signal conditioning is used with strain gauges. If a given strain gauge is either quarter-bridge or half-bridge configuration, then the measurement device's signal conditioning must provide the necessary completion resistors to make a full Wheatstone bridge.

  • Shunt calibration—Also used with strain gauges, shunt calibration provides a comparative signal value for a precisely known strain value (load) that can be used to calibrate the measurement system.

  • Switching relays—Both electromechanical and solid-state relays can be used to control whether external system components or equipment receive power or not. Relays use low voltage (ac or dc) to control devices that can require much larger voltages and currents to operate than available in the measurement system. Relays are typically used to control motors, fans, lights, or even other relays.


Electrical characteristics



Low-voltage output Low sensitivity Nonlinear output

Reference temperature sensor (cold-junction compensation) High amplification Linearization


Low resistance (100

Current excitation 4-wire/3-wire configuration Linearization

Strain gauge

Low-resistance device Low sensitivity Nonlinear output

Voltage or current excitation Bridge completion Linearization

Current-output device

Current loop output (4-20 mA typical)

Precision resistor


Resistive device High resistance and sensitivity Very nonlinear output

Current excitation or voltage excitation with reference resistor Linearization

Integrated circuit (IC) temperature sensor

High-level voltage or current output Linear output

Power source Moderate gain

Travis Ferguson, signal conditioning product manager
National Instruments, Austin, Tex


Source: Travis Ferguson, 'Basics of signal conditioning,' Back to Basics, Control Engineering, Oct. '99, p. 136.




APRIL 5, 2005




Defining analog, discrete, and digital.


The green line (top graph) shows an analog variable as it might be recorded on a strip chart. In the middle graph, the blue line shows the same variable discretized to remain constant between sampling intervals. The red line (bottom graph) shows how a computer with three-bit storage reg-isters would digitalize the discretized variable. Its value would be rounded to the nearest integer between 0 and 7.


Unlike the virtual world within a computer, the real world is 'analog.' Real-world variables can change at any time, not just at the end of a scan cycle or sampling interval. Variables measured by a computer are 'discrete.' They remain constant until the next sampling interval, even if real-world values change.


Computer variables are also 'digital,' and are represented by a finite string of digits or bits. 'Digitalization' limits the precision with which an analog variable from the real world can be stored digitally in a computer.


The graphic shows an extreme case of how a computer can misrepresent the values of a real-world variable through discretization and digitalization.


Graphing the discretized variable reflects the general shape of the original real-world variable, but without the smooth curves. Note also that the discretized variable lags behind its analog counterpart, since its value can only change after the analog variable has already changed. The digitalization graph shows how the computer's accuracy is reduced even further because the variable is limited not only by the times when it can change, but the values it can assume.


Fortunately, faster sampling and higher precision storage in today's computers can greatly reduce the effects of discretization and digitalization.


Though fast sampling is usually beneficial, it is not always necessary for a feedback controller to sample a process variable as fast as it can. Likewise, extremely high precision may not help the controller achieve the desired closed-loop performance.


Consider the example in the graphic again, but suppose now that the analog variable represents some pressure, temperature, or flow rate to be controlled. Typically, such real-world variables do not change abruptly. Inertia and friction tend to limit their fluctuations to smooth, continuous curves.


In mathematical terms, such variables are said to have limited bandwidth. That is, the variable looks more like a low-frequency sinusoid than a high-frequency sinusoid. In such cases, the famous Nyquist Theorem states that sampling the variable at rates above a certain cutoff is a waste of computing power. All information required to completely reconstruct the original signal from the sampled data is contained in the samples collected at the cutoff rate. Additional samples resulting from faster sampling won't help the controller gain any more useful information from the sampled signal.


In this example, the analog variable appears very much like a sinusoid that completes two cycles of varying amplitude in about 8 seconds. Signal bandwidth is therefore somewhere around 0.25 cycles per second. The Nyquist Theorem would place the cutoff frequency at twice that value so that a sampling interval of 0.5 samples per second (or one sample every two seconds) would be adequate to glean all of the useful information contained in this signal. Therefore, the sampling rate shown in the discretization graph-one sample per second-should be fast enough.


The case for limiting the precision of the controller's storage to modest levels is easier to make. Real-world process variables are usually corrupted to some extent by measurement noise that limits the accuracy of data even before being sampled and stored. Using high-precision storage registers for the purpose would be overkill.


Vance VanDoren, consulting editor


Source: Vance VanDoren, 'Analog, discrete, digital: deciphered,' Back to Basics, Control Engineering, Nov. '04, p. 68


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