Fluctuations, baseline variations

Detector sensitivity is one of the most important properties of the detector. The problem is to distinguish between the actual component and artifact caused by the pressure fluctuation, bubble, compositional fluctuation, etc. If the peaks are fairly large, one has no problem in distinguishing them however, the smaller the peaks, the more important that the baseline be smooth, free of noise and drift. Baseline noise is the short time variation of the baseline from a straight line. Noise is normally measured "peak-to-peak" i.e., the distance from the top of one such small peak to the bottom of the next. Noise is the factor which limits detector sensitivity. In trace analysis, the operator must be able to distinguish between noise spikes and component peaks. For qualitative purposes, signal/noise ratio is limited by 3. For quantitative purposes, signal/noise ratio should be at least 10. This ensures correct quantification of the trace amounts with less than 2% variance. The baseline should deviate as little as possible from a horizontal line. It is usually measured for a specified time, e.g., 1/2 hour or one hour and called drift. Drift usually associated to the detector heat-up in the first hour after power-on. 

Inlet and outlet check valves ensure a one-way solvent flow. Problems arise when the plunger must be pulled back to refill the chamber to ready itself for the next stroke (Fig. 9.3). The pressure drops until the plunger starts forward again. This results in pulsation, which causes variations in solvent delivery flow and, more importantly, variation in pressure to the column. The column acts as a pressure dampener, which can easily seen by watching baseline fluctuation of a system with and without a column in place. 

Noise present in the detector signal may have two components, long-term noise and short-term noise. The former causes a slow baseline wander measured over a 1 h period and may be attributed to fluctuations in temperature, column stationary phase bleed, flow rate variation, or pneumatic leaks. Short-term noise is observed as small, sharp spikes of shorter duration than component peaks and usually arises in the detector. Most integrators smooth the signal so that noise is not apparent unless a direct plot mode is selected. It is important to establish the mean noise level, the baseline, in order to determine the limit of detection. The time period of a peak is most conveniently described by the peak width at half height and the noise, N, is measured as the variation between maxima and minima of the noise peaks over the time period. The contribution of noise to the total component signal should be less than 1% (Figure 5.17). 

Number of phases indicates the complexity of the MUP and the degree of misalignment between SFAPs. In neurogenic diseases, polyphasic MUPs arise due to slow conduction velocity in immature nerve sprouts or slow conduction velocity in reinnervated but still atrophied muscle fibers. Variation in muscle fiber size also causes polyphasic MUPs in myopathic diseases. To prevent noisy baseline fluctuations from affecting the count of MUP phases, a valid baseline crossing must exceed a minimum absolute amplitude criterion. 

Careful and sufficient benthic baseline data accumulation is required to evaluate their variations of fluctuation ... 

The purpose of the Measure phase is to develop an understanding of the current conditions of the process problems and issues by identifying numerical data that provides the best measurement of the current performance. This data is used to establish baseline measurement used to track and measure the project progress. The measurements developed must be relevant to identify and measure the source of variation in the process. Variation is a measurement of the fluctuation over time of the data. It is essential in determining process improvement. 

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