MSO-X 6004A信封检测器功能在哪里?

由于设计和成本原因，Infiniviision示波器（包括MSOX6000）不具备Infiniium示波器的所有处理能力。
通过将2个函数串联在一起，始终可以在Infiniium上创建包络函数。
“真实”包络检测器（也称为晶体检测器）是二极管和电容器。
在Infiniium上，您使用了'绝对值'功能，然后使用低通滤波器来执行相同的操作。
一旦用户定义函数可用，我就编写了一个MATLAB函数来做同样的事情，添加了缩放。
Infiniium SW的最新版本增加了一个“Envelope”功能（也称为Amplitude Demodulation），它使用希尔伯特变换进行同样的操作。
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安捷伦论坛在“可用”的基础上进行监控，并不一定是解决技术问题的最快方式。



     以下为原文

  By design, and for cost reasons, the Infiniviision scopes, including the MSOX6000, don't have all of the processing capability as the Infiniium scopes.

It was always possible to create an envelope function on the Infiniium by stringing 2 functions together. A 'real' envelope detector (also called a crystal detector) is a diode and a capacitor. On an Infiniium, you used the 'Absolute Value' function, followed by a low-pass filter to do the same thing.

Once User-Defined Functions were available, I wrote a MATLAB function to do the same thing, adding in scaling.

The latest versions of Infiniium SW have added an 'Envelope' function (also called Amplitude Demodulation) which uses a Hilbert Transform for the same thing.

Al

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嗨Al谢谢你的重播。
你建议的方法有一个重要的流程：包络的幅度减小（它看起来像原始峰值的75％）我在这个网络上找到了Matlab的包络函数示例。
http://www.mathworks.com/help/dsp/examples/envelope-detection-1.html#zmw57dd0e10317第一种方法使用Squaring和Low Pass-Filtering它在某种程度上类似于你的建议。
第二种方法使用希尔伯特变换查看两种方法，我不会惊讶你不喜欢使用它们。
他们正在处理资源匮乏。
它完全矫枉过正。
我会建议更简单的方法。
如果我是正确的，你已经有找到边缘的功能。
您甚至可以定义要使用的边缘。
如果您发现所有边缘（或峰值）都高于零并连接它们，那么您就会有信封。
如果不起作用，则需要构建专用搜索功能。
1.搜索将叹息从+更改为 - 的所有值以查找零交叉2.搜索负值（负包络）的每对正值（正包络）之间的最大值（或峰值）。
一旦你达到顶峰，连接它们，你就会有信封。
如果你只处理它在屏幕上显示的数据（1000点左右），即使非常慢的CPU也不应该有任何问题。
我甚至不会使用“Real”作为某些开关（特别是二极管基座），由于视频泄漏（脉冲DC偏移），您可能会出现明显的失真。如果使用“Real”，您将会遇到更大的混乱。
在测量切换时间之前，有一种方法可以消除视频泄漏。
1.你输入内存视频泄漏波形2.你从显示的脉冲波形中减去视频泄漏波形3.创建信封4.测量切换时间问候，Mirek



     以下为原文

  Hi Al

Thank you for the replay.

The method that you suggest has one significant flow: 
The amplitude of the envelop is reduce (it look like 75% of the original peak value)

I found on this web the envelop functions example for Matlab.
http://www.mathworks.com/help/dsp/examples/envelope-detection-1.html#zmw57dd0e10317

The first method use Squaring and Low Pass-Filtering
It is in some way similar what you suggest.

The second method use Hilbert Transform

Looking on both methods, I ma not surprise that you do not like to use them. They are processing resource hogs. It total overkill.

I will suggest much simpler approach.

If I am correct you already have function to find edges. You can even define which edge you like to used. If you find all edges (or peaks) above Zero and connect them you have envelop.

If that not work you will need to build dedicated search function.
1. Search for all values that change the sigh from + to - to find Zero crossing
2. Search maximum (or peaks) values between each pair of positive values (positive envelop) of negative values (negative envelop). Once you have the peak, connect them, and you have envelop.  
If you will deal with data that it shows on the screen only (1000 point or so), even very slow CPU should not have any problem do the job.

I will not even use “Real" as some switches (especially diode base) you may have significant distortion due to video leakage (pulse DC offset). If you use "Real”, you will have even bigger mess.

There is a way to remove video leakage before measuring switching time.
1. You put in memory video leakage waveform
2. You subtract video leakage waveform form displayed pulse waveform
3. Create envelop
4. Measure Switching time   

Regards,

Mirek

正如我所说，最简单的算法是模拟具有“绝对值”（或方形）函数的晶体检测器，然后是低通滤波器，ADDING IN SCALING。
滤波器的输出将具有正确的形状，并且曲线下的面积将与整流信号相同，但是，必要时，幅度将是错误的并且需要被校正。
包括我在内的其他人都尝试过你的算法。
找到峰值，特别是在存在噪声的情况下，可能会出现问题。
在峰值之间进行插值可能在算法上具有挑战性。
确定脉冲的开始和结束位置，以及开始和结束计算的位置，增加了额外的复杂程度。
滤波器和希尔伯特变换方法都经过了广泛的优化，可以非常快速地运行。
它们已经被证明是正确的，并且在信封测量过程中不会出现任何不连续性导致问题的风险。
我不确定你对“视频泄漏”的讨论在哪里进入讨论。
我已经多次对多个客户进行了切换时间测量，他们对我对问题的分析以及我得到的结果非常满意。
如果您编写实现算法的代码，请务必发布。
我很高兴看到您是否找到了我错过的内容... Al免责声明：为了获得更可靠的响应，您应该考虑致电当地的Keysight技术呼叫中心。
Keysight论坛在“可用”的基础上进行监控，并不一定是解决技术问题的最快方式。



     以下为原文

  As I said, the simplest algorithm is to emulate a crystal detector with an 'absolute value' (or square) function, followed by a low-pass filter, ADDING IN SCALING. The output of the filter will have the correct shape, and the area under the curve will be the same as the rectified signal, but, of necessity, the amplitude will be wrong and needs to be corrected.

Other people, including me, have tried your algorithm. Finding the peaks, especially in the presence of noise, can be problematic. Doing the interpolation between the peaks can be algorithmically challenging. Determining where the start and end of the pulse are, and thus where to start and end the calculations, adds an additional level of complexity.

Both the filter and the Hilbert transform method have been extensively optimized, and can run very quickly. They have been proven to be correct, and don't run the risk of any discontinuities causing problems during the measurements on the envelope.

I am not sure where your discussion of 'video leakage' enters into the discussion.

I have made the switching time measurement many times, at multiple customers, and they have been very happy with my analysis of the problem, and the results I have gotten for them.

If you write some code implementing your algorithm, be sure to post it. I would  be happy to see if you found something I missed...

Al

Disclaimer: For more reliable response, you should consider calling your local Keysight Technical Call Center. The Keysight Forums are monitored on an "as available" basis, and aren't necessarily the fastest way to get technical questions answered.