Report: K-nearest neighbors matching applied to SNS accelerator pulses

Rebecca Seviour; Miha Rescic

Report: K-nearest neighbors matching applied to SNS accelerator pulses

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Abstract

SNS collects beam current data associated with a machine trip. There are 3 categories of pulses recorded: the pulse before the trip, the tripping pulse and the rst pulse that successfully passes through the machine as the machine recovers from error.
This report describes an analysis where the K-nearest neighbors (K-NN) approach is applied to SNS pulse data as an attempt to classify pulses as one of the above mentioned categories: pre-trip pulse (bad) and post-trip pulse (good).

Original language	English
Publication status	Unpublished - 18 Jan 2018

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title = "Report: K-nearest neighbors matching applied to SNS accelerator pulses",

abstract = "SNS collects beam current data associated with a machine trip. There are 3 categories of pulses recorded: the pulse before the trip, the tripping pulse and the rst pulse that successfully passes through the machine as the machine recovers from error. This report describes an analysis where the K-nearest neighbors (K-NN) approach is applied to SNS pulse data as an attempt to classify pulses as one of the above mentioned categories: pre-trip pulse (bad) and post-trip pulse (good).",

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AU - Seviour, Rebecca

AU - Rescic, Miha

PY - 2018/1/18

Y1 - 2018/1/18

N2 - SNS collects beam current data associated with a machine trip. There are 3 categories of pulses recorded: the pulse before the trip, the tripping pulse and the rst pulse that successfully passes through the machine as the machine recovers from error. This report describes an analysis where the K-nearest neighbors (K-NN) approach is applied to SNS pulse data as an attempt to classify pulses as one of the above mentioned categories: pre-trip pulse (bad) and post-trip pulse (good).

AB - SNS collects beam current data associated with a machine trip. There are 3 categories of pulses recorded: the pulse before the trip, the tripping pulse and the rst pulse that successfully passes through the machine as the machine recovers from error. This report describes an analysis where the K-nearest neighbors (K-NN) approach is applied to SNS pulse data as an attempt to classify pulses as one of the above mentioned categories: pre-trip pulse (bad) and post-trip pulse (good).

M3 - Other report

BT - Report: K-nearest neighbors matching applied to SNS accelerator pulses

ER -

Report: K-nearest neighbors matching applied to SNS accelerator pulses

Abstract

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