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Launch HN: Orbiter (YC W20) – Autonomous data monitoring for non-engineers

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Re: Launch HN: Orbiter (YC W20) – Autonomous data monitoring for non-engineers

#41

Earlier quoted context omitted.

I think some sort of anomaly detection would be useful in your case. There are a bunch of libraries floating about, I remember at least Netflix[1], Yelp and Datadog talking about them. There appears to be a really good links page available too[1]. You can also learn a lot from Forecasting Principles and Practice , which is free online[2] I have previously pitched using a kind of SPC-for-metrics approach, with Nelson…

thanks for the links. We only create an alert if there is a problem the operator can solve, otherwise there is no point in waking them up at 3 AM, so if anything our thresholds are set as loose as possible instead of as tight as possible. However there are many instances where the operator could be alerted earlier that the machine operation is abnormal. For example the stator windings are rated for operation up to 15…

I agree with focusing on actionable alerts during on-call hours. You might be able to have some kind of scheduled change in sensitivity.

One thing I've wondered in the past year is whether fuzzy logic would be useful. Your example is a really good case of linguistic variables -- "lightly loaded", "a long time", "normal temperature" and so on. These can be assembled into rules or tables that should fire more sensibly than exact threshold values.

Re: Launch HN: Orbiter (YC W20) – Autonomous data monitoring for non-engineers

#42
post #39

I work on power stations which normally have about 1000 monitored variables per turbine-generator and another 500 for the plant in general. So typically 2500 for a two unit plant. Alarms are generated if a variable exceeds a threshold, or a binary variable is in the wrong state. Is Orbiter something that would benefit power plants?

Out of curiosity, since I'm interested in industrial monitoring: would you mind telling a bit more about the monitoring infrastructure, esp. how often are those metrics collected and what data protocols are involved in the process?

I only know from my own experience and I’m essentially self taught, so I don’t know what industry norms are only what has worked for me and my customers.

The instruments and controlled devices are wired to a PLC such as Allen Bradley control logix or Schneider electric m580. The PLC generally reads the inputs, executes the program, and updates the outputs every 10ms. HMI software running on a computer such as inductive automation ignition, vtscada, wonderware, citect, etc reads data from the PLC to display to the operator and record for history. Protocols are often modbus or common industrial protocol (CIP) which is also called, or some flavor of it, the ridiculous name of Ethernet/IP, but that’s the kind of shit you get in industrial automation.

I generally set the HMI software to record my 2500 values once per second.

During testing it is common to use a data acquisition system that can sample even much faster than the PLC runs, eg 1 kHz.

Re: Launch HN: Orbiter (YC W20) – Autonomous data monitoring for non-engineers

#43

Earlier quoted context omitted.

I think some sort of anomaly detection would be useful in your case. There are a bunch of libraries floating about, I remember at least Netflix[1], Yelp and Datadog talking about them. There appears to be a really good links page available too[1]. You can also learn a lot from Forecasting Principles and Practice , which is free online[2] I have previously pitched using a kind of SPC-for-metrics approach, with Nelson…

thanks for the links. We only create an alert if there is a problem the operator can solve, otherwise there is no point in waking them up at 3 AM, so if anything our thresholds are set as loose as possible instead of as tight as possible. However there are many instances where the operator could be alerted earlier that the machine operation is abnormal. For example the stator windings are rated for operation up to 15…

You should take a look at http://riemann.io
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