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Target Operations. A summary of Target Operation to Date Paul Hodgson The University of Sheffield . T1 Operation Dates. Timing Problem. Calibrations Taken. Target Parameters. Start position: x 1 Start time: t 1 Time beam on: TB 1 Time beam off: TB 2 BCD minimum: x 2
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Target Operations A summary of Target Operation to Date Paul Hodgson The University of Sheffield
T1 Operation Dates Timing Problem Calibrations Taken
Target Parameters Start position: x1 Start time: t1 Time beam on: TB1 Time beam off: TB2 BCD minimum: x2 Time BCD minimum: t2 Strike: s = x2 – x1 Strike time: t = t2 – t1 Acceleration: a = 4s/t2 Run reduction code over the raw data to parameterise Can then plot interesting variables quickly TB1 TB2 x1 x2 t1 t2
BCD Histograms Histogram BCDs for a set value Clear difference between the two distributions Failing target has a much broader spread T2 distribution 3-4 times as broad Can be interpreted as a result of the target “sticking”
BCDs for T1 and T2 In each case the test runs were setup to pulse with a nominal BCD of 19-20 mm Very different appearance for BCD time series plots for T1 and T2 T1 very stable BCD does not vary over time T2 BCD varies strongly over time Plot very “spiky” after ~42k pulses Clear signal for target failure T2 Commissioning Run
Calibration Histograms Fit double Gaussian to BCD by hand Why ? Trying to account for second population usually seen
Calibration Histograms Tricky to automate, usually need to tweak the fit start values by hand to get the fit to converge Obvious 2nd peak More ambiguous case
Is it better to simply fit a single gaussian or do no fit at all and use RMS ?
Another view of the Calibration Double Gaussian fit can pick out second population and gives better resolution for spread
Conclusions • Have a simple method of spotting potential breakdown of the target • This method is partially automated in current target DAQ – Thanks James • Still needs an “experts eye” • Don’t want to define some arbitrary failure value until we see how these measurements evolve