Discrete instruments

The GPIB or IEE-488 cable is a bidirectional serial cable carrying module addressing information lines as well as signal and housekeeping lines. It can be used to send and collect information from different instruments on a cable bus. It is often used in instrumentation to automate a series of discrete instrument modules connected through a system controller. 

Discrete instruments may be designed to analyze samples for one analyte at a time. These are the so-called batch instruments, or single-channel analyzers. See Figure 23.3. However, those that analyze the samples in parallel, that is. 

Automatic analytical systems are of two general types (liscreie analyzers and continuous jUnv analyzers occasionally, the two arc amibined. In a discrete instrument. individual samples are maintained as separate entities and kept in separate vessels throughout each... 

Because discrete instruments use individual containers, cross-coniamination among samples is totally eliminated. On the other hand, interactions among samples are always a concern in continuous flow systems, particularly as sample throughput increases. Here, special prccaution.s are required to minimi/.c sample contamination. 

Figure 24.9. Output response behavior of discrete instruments, t, — sampling dead-time = t2 — h = ti — ts = ta = analytical deadtime = h — tz = h — ti = ts + ta < ta < It, + 2ta, where ta is the total measurement dead-time. Courtesy of the Foxboro Company.

Response spectrum recorders are not supplied as discrete instruments. A permanently installed response spectrum analyzer provides more complete information than that provided by response spectrum recorders. Data from the strong motion accelerometers are fed into the response spectrum analyzer to produce earthquake spectra immediately following an earthquake. The response spectrtun analyzer is located in the Reactor Service Building with readout both there and in the Control Room. This system achieves the intent of Regulatory Guide 1.12, Revision 1. (Ref. 13)... 

During the inspection of an unknown object its surface is scanned by the probe and ultrasonic spectra are acquired for many discrete points. Disbond detection is performed by the operator looking at some simple features of the acquired spectra, such as center frequency and amplitude of the highest peak in a pre-selected frequency range. This means that the operator has to perform spectrum classification based on primitive features extracted by the instrument. 

Numerical simulations offer several potential advantages over experimental methods for studying dynamic material behavior. For example, simulations allow nonintrusive investigation of material response at interior points of the sample. No gauges, wires, or other instrumentation are required to extract the information on the state of the material. The response at any of the discrete points in a numerical simulation can be monitored throughout the calculation simply by recording the material state at each time step of the calculation. Arbitrarily fine resolution in space and time is possible, limited only by the availability of computer memory and time. 

If static capacitors are employed this can be achieved by using several capacitors arranged in units (banks) which can be switched in or out as required. This variation can only be carried out in discrete steps. In the case of the A.C. machine (the synchronous condenser), it is possible to obtain a continuous variation. The switching of the equipment can be carried out by an operator or automatically in response to the output from a power factor-sensing instrument. 

The start of the solid-state electronic industry is generally recognized as 1947 when Bardeen, Brattain, and Shockley of Bell Telephone Laboratories demonstrated the transistor function with alloyed germanium. The first silicon transistor was introduced in 1954 by Texas Instruments and, in 1956, Bell Laboratories produced the first diffused junction obtained by doping. The first-solid state transistor diodes and resistors had a single electrical function and were (and still are) known as discrete devices. 

Other analyzers such as the Gilford Automated Enzyme Analyzer and the LKB-8600 Reaction Rate Analyzer analyze discrete samples one at a time. These instruments provide kinetic analyses, digital data reduction at the time each sample is analyzed, and excellent electronic and optical characteristics. Recently, Atwood has developed kinetic enzyme analyzers which require only 9 seconds for measuring an enzyme activity, using highly stable and sensitive electronic circuits (12). This short read out time allows a large number of samples to be processed by one instrument in an automated mode. 

In Section 42.2 we have discussed that queuing theory may provide a good qualitative picture of the behaviour of queues in an analytical laboratory. However the analytical process is too complex to obtain good quantitative predictions. As this was also true for queuing problems in other fields, another branch of Operations Research, called Discrete Event Simulation emerged. The basic principle of discrete event simulation is to generate sample arrivals. Each sample is characterized by a number of descriptors, e.g. one of those descriptors is the analysis time. In the jargon of simulation software, a sample is an object, with a number of attributes (e.g. analysis time) and associated values (e.g. 30 min). Other objects are e.g. instruments and analysts. A possible attribute is a list of the analytical... 

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