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Fault Detection Diagnostics for HVAC from ASHRAE Guideline 36 sequences in Python Pandas

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my-weekend-fdd-hobby

Welcome, this has been my experience studying Fault Detection Diagnostics (FDD) for HVAC from ASHRAE Guideline 36 sequences in Jupyter Labs with Python & Pandas. The purpose is for learning and pseudo code development that can then be pontentially used on actual AFDD systems. Each ASHRAE Guideline 36 Fault Condition will be representded in unique IPython notebook

  • The Goal is to cover each of the 15 Faults in seperate IPython notebooks:

fc_tables1 fc_tables2

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【MIT License】

Copyright 2021 Ben Bartling

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

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