The technical indicators for evaluating the quality of an X-ray fluorescence spectrometer are multiple and comprehensive. The main concern and emphasis of users is the range of analysis elements, which are what we usually call analyzable elements, the length of analysis, and the accuracy. The importance of technical indicators ultimately depends on the purpose of the application.
Myth 1: One-sided pursuit of high indicators. Buying an instrument can't wait to test all the elements in the periodic table. When it's actually applied, just measure a few elements.
For industrial analysis, the type of sample being analyzed is deterministic, even single, and the requirements for the results are also determined. In particular, some companies may test one or two samples, one or two elements forever, and even simply describe the content of the elements as not more than one. The pursuit of indicators far above these requirements is actually a waste of resources. For example, the control analysis of most cement plants only uses calcium and iron. For the control of the rate value, it is necessary to measure calcium, iron, silicon and aluminum. For the whole analysis, it is required to increase the elements such as Na, Mg, S and K, and tens of thousands of calcium. The iron meter can meet the control requirements. For example, the multi-element analyzer that requires about 100,000 yuan for the silicon aluminum can be tested. The multi-element analyzer can fully meet the requirements of the four major elements of the rate control. Accuracy and speed requirements require a small multi-channel X-ray fluorescence spectrometer of approximately one million yuan. Due to the certainty of the sample to be analyzed, the empirical coefficient method is the most effective analysis method. If the standard-free method must be pursued, the effect of the empirical coefficient method cannot be achieved. Originally, the measured elements are deterministic, and the number is limited. The fixed track can solve the problem, blindly pursuing the variable path, both costing more, and sacrificing stability and analysis time; as far as the energy dispersive X-ray fluorescence spectrometer is concerned The number of roads is not as good as possible. So before buying an X-ray fluorescence spectrometer, be sure to know what you are buying and then determine the model.
Myth 2: One-sided pursuit of accuracy.
Whenever we talk about the performance of the instrument, it is often the first time to judge whether the result is accurate or not, and in daily applications, a lot of energy will be used to judge the instrument "impossible", the most common is the chemical analysis. For the result." Accuracy is important, but as an industrial analysis, precision must not be ignored. The first thing to focus on is the precision problem. That is to say, the same sample should be measured multiple times, and the results should have good consistency. The difference from the mean is small enough. As for the difference between the measured value and the true value, it is often a systematic deviation and can be mathematically corrected. This makes it understandable that you measure the same element of the same sample twice, with a result of 1 and a result of 2, and how do you report the results?
Myth 3: Do not pay attention to stability and reproducibility.
The so-called stability refers to the standard deviation of the same sample continuously measured multiple times (usually 21 times), and the reproducibility is the consistency between the results of re-measurement after a longer interval of the same sample. These two indicators are key indicators of industrial analytical instruments. The results of industrial analysis are mainly used for control and parameter adjustment of production processes. The relative changes of analytical results are directly related to process control and regulation. Accurate measurements of relative changes are based on stability and repeatability.
Myth 4: The shorter the analysis time, the better.
X-ray measurement is a statistical measurement of random events, which is determined by statistical laws. The absolute amount of counting depends on the measurement time and directly determines the size of the measurement error. A sufficiently long measurement time is a prerequisite for measurement accuracy, in order to ensure measurement. Accuracy must have sufficient measurement time.
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