Grms 加速度平方根值.doc

Calulating Grms(Root-Mean-Square Acceleration) It is very easy to describe the Grms (root-mean-square acceleration, sometimes written as GRMS or Grms or grms or grms) value as just the square root of the area under the ASD vs. frequency curve, which it is. But to physically interpret this value we need to look at Grms a different way. The easiest way to think of the Grms is to first look at the mean square acceleration. 其实是很容易来描述这个Grms（根均方加速）作为只是平方根值下的房间隔缺损与频率曲线但是，从上解释这个值，我们需要不同的方式Grms。最简单的方法思考Grms加速度均方。 Mean-square acceleration is the average of the square of the acceleration over time. That is, if you were to look at a time history of an accelerometer trace and were to square this time history and then determine the average value for this squared acceleration over the length of the time history, that would be the mean square acceleration. Using the mean square value keeps everything positive. 均方加速在一段时间内加速平方的平均值。也就是说，如果你要在一个加速度时间历程看跟踪并正视这段时间的历史，然后确定的平均值为这个当时的历史长度的平方的加快，这将是均方加速。使用均方值保持一切积极。 The Grms is the root-mean-square acceleration (or rms acceleration), which is just the square root of the mean square acceleration determined above. 在克这个瑰宝是根均方加速（或有效值加速），这仅仅是对上述决定的加速度均方的平方根。 If the accelerometer time history is a pure sinusoid with zero mean value, e.g., a steady-state vibration, the rms acceleration would be .707 times the peak value of the sinusoidal acceleration (if just a plain average were used, then the average would be zero). If the accelerometer time history is a stationary Gaussian random time history, the rms acceleration (also called the 1 sigma acceleration) would be related to the statistical properties of the acceleration time history (you may have to refresh your probability and statistics knowledge for this): 如果加速度时间历程，是一个纯正弦波的平均值为零，例如，一个稳态振动，加速度的RMS将0.707倍的正弦加速度（如果只是一个普通的平均使用了峰值，然后将平均是零）。如果加速度时间历程，是一个平稳高斯随机时间的历史，均方根加速度（也称为1西格马加速）将有关的加速度时程（即统计特性可能需要刷新您的概率和统计知识这一点） 68.3% of the time, the acceleration time history would have peaks that would not ex