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# User Rev Content
1 sguazz 1.1 \section{Integration Tests}
2     \label{sec:Tests}
3    
4     The CMS tracker has been designed to survive at ten years of LHC operation, with little or no chance
5     for maintenance. Its various components have been tested during the production
6     to meet stringent quality requirements. Few important problems have been spotted and
7     solved.\\
8 sguazz 1.2 During the TIB/TID integration all the operations have been monitored step by step by a chain of tests
9 carlo 1.4 aimed at a final control of the components just after the installation described here.
10     A verification of the
11     shell overall quality and functionality in conditions similar to the final ones
12     has been later performed during the so-called burn-in tests~\cite{ref:burnin}.
13     The step by step tests are of particular importance
14 sguazz 1.1 because in most cases it is very difficult and in some cases even dangerous
15     to replace a single faulty component when it is embedded in a fully equipped shell.
16    
17     \subsection{Test Setup}
18     \label{sec:TestSetup}
19 sguazz 1.2 The integration started well before the tracker
20 sguazz 1.1 final data acquisition hardware and software
21 sguazz 1.2 were available to the Collaboration. Integration tests thus had to
22     rely on prototype DAQ hardware and peripherals and software versions
23     that has been frozen to ensure consistent conditions during the
24     integration activities time-span, except few minor upgrades and bug
25     fixes.
26 sguazz 1.1
27     \subsubsection{Hardware}
28     Here a brief account of the hardware used in DAQ for the integration
29     is given (see Fig.~\ref{fig:integration daq}).
30     \begin{figure}
31     \centering
32     \includegraphics[width=\textwidth]{Figs/integrationDAQ.pdf}
33     \caption{Hardware used for the integration DAQ.
34     \textbf{On the left:}
35     \textbf{1:} The analog opto-electrical converter.
36     \textbf{2:} Optical lines from the AOHs inside the (yellow) ribbon.
37     \textbf{3:} The signal is converted to electric.
38     \textbf{On the right:}
39     \textbf{1:} The signal converted to electric goes to FEDs through 2-poles LEMOs.
40     \textbf{2:} TSC provides trigger and clock to FEC through an (orange) optical fibre and
41     \textbf{3:} to FEDs though 4-poles LEMOs.
42     \textbf{4:} FEC also implements the 2-way communication towards CCUs and modules through a
43     (yellow) fibre ribbon.}
44     \label{fig:integration daq}
45     \end{figure}
46    
47 sguazz 1.2 \begin{description}
48 carlo 1.4 \item[TSC] The Trigger Sequencer Card or TSC~\cite{ref:tsc} generate the
49 sguazz 1.2 40~MHz clock for the entire system and triggers as well, either
50     internally via software or by accepting external inputs. It has up to four
51 carlo 1.3 electrical clock/trigger outputs, enough to drive the FEDs used during the
52     integration, and an optical clock/trigger output for the FEC.
53     The TSC may also generate the reset and calibration signal that are
54 sguazz 1.2 also encoded on the clock/trigger line.\\
55 carlo 1.4 \item[FED] The analog-to-digital conversion is done by special PCI FEDs,
56     %~\cite{bib:fedpci},
57 sguazz 1.1 with electrical differential analog input, mounted on
58     PCI carrier boards and installed in an industrial PC.
59 carlo 1.3 The opto-electrical conversion of the analog signals coming from the module under test
60     is done externally by a 24-channel unit.
61 sguazz 1.1 A setup containing 3 FEDs, with the electro-opical converter, is able
62 carlo 1.4 to readout 48 APV25; this is equivalent to 12 single sided modules
63 sguazz 1.2 %(four complete strings)
64     or four double sided modules assemblies.
65     %(one string plus one module).
66     These figures are
67     pefectly suited for the tests during the integration.\\
68 carlo 1.4 Since the readout of the data from the APV25s is not
69 carlo 1.3 synchronous with the L1 trigger, a crucial capability of the FED is the
70 sguazz 1.2 \textit{header finding}, i.e. the automatical tagging of the
71 carlo 1.4 analog data stream from APV25 pairs with respect to the idle
72     signals at its inputs. This is possible since the APV25s embeds the
73 sguazz 1.2 analogue data stream within a {\em digital frame} made up of a leading
74 carlo 1.3 digital header and a trailing tick-mark.
75     %The peculiarity of the PCI FED
76     %with respect to the VME FED that will be used in the experiment, other than having electrical inputs
77     %instead of optical ones, is the timing system: the VME FED is able to
78     %perform the header finding on each input channel independently; the PCI FED has
79     %this capability only on the first channel of the eight available
80     %and assumes that the all input signals are synchronised.
81     %This makes the PLL-based time alignment procedure of crucial
82     %importance in a setup with PCI FEDs. Furthermore, PCI FEDs are not
83     %able to insert a programmable delay on their inputs and thus
84     %it is important that the clock/trigger connections from the TSC to
85     %FEDs have all the same delay. Last, PCI FEDs cannot perform an online
86     %pedestal subtraction and zero suppression (they cannot run in
87     %Processed Raw data nor in Zero Suppression mode).
88 sguazz 1.2 \item[FEC] The special FEC used during the integration is the {\em FEC
89     mezzanine} also installed into a PC on a PCI carrier. It supports
90     the optical trigger/clock provided by the TSC and features an
91     optical output directly connected to DOHs on the DOHM.
92     \end{description}
93    
94 sguazz 1.1
95     \subsubsection{Software}
96 carlo 1.3 The software used to carry out integration tests is
97     based on the CMS general data acquisition framework
98     %{\em TrackerOnline}, the CMS
99     %tracker implementation of a more general software,
100     named xDAQ~\cite{ref:xdaq}.
101     % which is the official CMS DAQ framework.
102 sguazz 1.2 In place of a database as in the
103     experiment version, the integration version of TrackerOnline uses a set of
104 carlo 1.3 xml files for all the configurations needed to perform a test run.
105     A description of the xml configuration files follows.
106 sguazz 1.2 %, i.e. all the parameters needed by the devices and the
107     %software involved in the test run,
108     %\begin{figure}[bth!]
109     %\centering
110     %\includegraphics[width=\textwidth]{Figs/fecmodulexml_2.pdf}
111     %\caption{An example of data contained in fec.xml and module.xml files for one module.
112     %Part of the data is not shown for simplicity.}
113     %\label{fig:fecmodulexml}
114     %\end{figure}
115 carlo 1.3 The hardware and software configuration of the DAQ is written into the file
116     named daq.xml. It reflects the setup used for the test and has to be rarely changed
117     during the integration procedures. The system settings uploaded, and
118     read back for verification, by the FEC are contained into fec.xml.
119 carlo 1.4 The data decoding map (i.e., information needed to map each FED input to an
120     APV25 pair of a specific module) is written into module.xml.
121 carlo 1.3
122     %\begin{description}
123     %\item[Configuration of the DAQ hardware and software, daq.xml] The hardware
124     % and software configuration of the DAQ is written in a single xml file, which
125     % reflect the setup used for the test and has to be rarely changed
126     % during the integration procedures.
127     %\item[Configuration of the control system, fec.xml] The most important
128     % part of this configuration section is the settings the FEC must
129     % upload to the modules and AOHs and in general any configurable
130     % $I^2C$ device, before starting the data
131     %taking. Altough these settings are not specifically
132     % related to the control system, it is duty of the control system to
133     % write them to the devices' $I^2C$ registers and read them back for verification.
134     %\item[Configuration of the readout, module.xml] All other information needed by the DAQ to
135     %rearrange data coming from the FEDs is in module.xml that allows each
136     %FEDs input channel to be mapped to an APV pair of a specific module as
137     %identified by ring, CCU and $I^2C$ addresses (i.e. the correspondance
138     %between readout coordinates and Control System coordinates);
139 sguazz 1.2 %Each row corresponds to an APV
140     %pair, an AOH laser, an optical fibre and a FED input.\\
141     %The second table of module.xml reassembles the information on a module basis.
142     %Here all the active modules are listed, with a row for every module.
143     %The Control System coordinates are repeated both in module.xml and fec.xml,
144     %so that they can be used as a pivot between the 3 tables.\\
145 carlo 1.3 %\end{description}
146 sguazz 1.2
147     The tasks performed by the integration software are the following:
148     execution of the commissioning runs needed to optimal adjust of the
149     module parameters (preparation of fec.xml and module.xml); execution
150     of the test runs with complete and automated logging; fast analysis
151     for immediate feedback; archival of xml configuration files to log the
152     test conditions; archival of the raw data.
153     %\begin{figure}
154     %\centering
155     %\includegraphics[width=.9\textwidth]{Figs/integration_package.pdf}
156     %\caption{Scheme of the integration software.
157     %\textit{Arrows}: a relation.
158     %\textit{Gears}: an application.
159     %\textit{Mouse:} an interactive application.
160     %\textit{Sheet}: a file.}
161     %\label{fig:integration_package}
162     %\end{figure}
163     %Figure~\ref{fig:integration_package} shows a scheme of the relations between all the software
164     %components that will be described, the local files and the remote database.
165 carlo 1.3 This is achieved by using a specific set of components of integration
166     data acquisition software as summarized in the following.
167 sguazz 1.2 \begin{description}
168     \item[FecTool.]
169     FecTool is GUI based front-end to two standalone
170 carlo 1.3 applications: FecProfiler
171 sguazz 1.2 and ProgramTest, aimed to ease the creation of the device
172     description.
173     FecProfiler is able to detect
174     the devices connected to the CCUs and builds the fec.xml file needed by
175     TrackerOnline. FecTool takes care of checking that thedetected devices
176 carlo 1.4 corresponds to expected ones, i.e., per module, 4 or 6 APV25s, one
177 sguazz 1.2 PLL, one AOH, and so on. ProgramTest allows the ring functionalities,
178     i.e. the redundancy, to be deeply tested.
179    
180     The geographical identity of the strings under test must be
181     entered to allows for verification from FecTool of the matching
182     between the DCU Hardware Id read from each
183     module and the one declared in the module database. This
184     consistency check is crucial to spot possible errors in recording the
185     location where a module is mounted during the assembly. If the check
186     is passed, the fec.xml description file needed to go forth with
187     integration tests can be created.
188     %Hence tests proceed with the data
189     %readout from modules, which rely on .
190     \item[The Integration Package.]
191 carlo 1.3 %TrackerOnline as any xDAQ implementation requires an expert user as
192     %many run-specific parameters must be set and there is no input
193     %validation.
194 sguazz 1.2 %\begin{figure}
195     %\centering
196     %\includegraphics[width=0.35\textwidth]{Figs/FedGuiMain.png}
197     %\caption{Main GUI window.}
198     %\label{fig:fedgui}
199     %\end{figure}
200 carlo 1.3 The integration setup is made more user-friendly by a special {\em
201 sguazz 1.2 Integration Package}, a GUI based front end that interacts with
202 carlo 1.3 the data aquisition program to automatically set all relevant parameters
203     and to harvest all data at the end
204 sguazz 1.2 of a run. The package is organized as a finite state machine by which
205     the user can cycle between the various states, i.e. the following integration test steps:
206 sguazz 1.1 \begin{enumerate}
207 carlo 1.3 \item Daq initialisation (only once);
208 sguazz 1.2 \item choice of the the desired run;
209 carlo 1.3 \item execution of the run via Daq program;
210 sguazz 1.2 \item on run completion (i.e. after a given number of events), stop
211     data taking and execution of the fast data analysis;
212     \item presentation of the run outcome on summary GUIs;
213     \item on positive validation from the user, data are stored together
214     with run logs and data quality flags;
215     \item in case of commissioning runs, on positive validation from the
216     user, fec.xml and module.xml are updated accordingly to be used from
217     now on.
218 sguazz 1.1 \end{enumerate}
219    
220 sguazz 1.2 %For every required run, the integration package shows the TrackerOnline output
221     %through some GUIs, so that the user can acknowledge the outcome of the run and give the approval
222     %for archiving the data or, in case of a commissioning run, for updating the parameter set.\\
223     %The TrackerOnline software computes the new parameter set for each commissioning run
224     %(except for the ``find connection'' run, as we'll see below) and writes
225     %it locally as a fec.xml file, which is retrieved by the integration package at need.\\
226     A main integration database has been setup for centralized archiving purposes,
227     was also installed. For later reference, if needed, the data analysis
228     can also be run on the archived files with validation outputs made
229     available through a web interface.
230     \end{description}
231 sguazz 1.1
232     \subsection{Test Description}
233     \label{ref:test-description}
234    
235 sguazz 1.2 Each run type that can be choosen by the user corresponds to a
236     commissioning run or to a test run, as described below.
237 sguazz 1.1
238 sguazz 1.2 \begin{description}
239     \item[Find connections.] This commissioning run is used associate each
240     FED input channel to a module. The procedure, repeated in sequence
241     for all AOHs laser drivers, consists of switching on only a given
242 carlo 1.3 AOH laser driver at a time while checking the signal on all the FED inputs. If
243 sguazz 1.2 the difference of the signal seen on a FED channel is above
244     a given threshold, the connection between that laser and input channel is tagged and stored
245     in module.xml.
246     \item[Time alignment.]
247     This commissioning run measures the appropriate delays to be later set
248     in the PLLs delay registers.
249     Doing so the different delays in the control and
250     readout chain are compensated, the clock arrives to the modules
251 carlo 1.4 synchronously, with a skew of the order of a few ns, and the APV25s
252 sguazz 1.2 signal are properly sampled by the FEDs. This requires also the clock
253     to all the FEDs to be synchronous, but this is guaranteed
254     by using cables equal in length between the TSC and the FEDs.\\
255 carlo 1.3 The time alignment run uses the periodic tick mark signal issued by
256 carlo 1.4 the idle APV25s every 70 clock cycles. The APV25 signals are sampled by FEDs in
257 sguazz 1.2 scope mode, i.e. without waiting for an header but continously,
258 carlo 1.3 sampling the inputs at the full clock frequency as with a 40~MSample/s
259 sguazz 1.2 scope. The measurement is repeated after all the PLL delays are
260 carlo 1.3 increased by the minimum delay step, 25/24~ns. After 24 such cycles the
261 carlo 1.4 idle APV25 output and thus the tick mark signal also are measured with
262 carlo 1.3 an effective 960~MSample/s scope.
263 sguazz 1.1 \begin{figure}
264     \centering
265     \includegraphics[width=.6\textwidth]{Figs/tickmark.pdf}
266     \caption{A tick mark sampled during a time alignment. The raising edge and the sampling point
267     are marked. In the picture are reported only those samplings around the tick mark, while
268     during the time alignment an interval of $1\,\mu\mathrm{s}$ is scanned.}
269     \label{fig:tick}
270     \end{figure}
271 carlo 1.4 The time differences between the variuos APV25 tick marks are a
272 sguazz 1.2 measurement of the relative delays introduced by the connections and
273     can be used to compute the optimal delay to be set on each PLL for compensation.
274 sguazz 1.1 The tick mark raising edge $t_R$ time is measured by taking the time corresponding to the highest
275     signal derivative (see Fig.~\ref{fig:tick}).
276     The best sampling point is considered $t_R+15\,\mathrm{ns}$, to avoid
277 sguazz 1.2 the possible overshoot.
278     %[???This is important also later, when measuring the analogue data frame, as
279     %it allows measuring the signal coming from each strip after transient effects due to the signal
280     %switching between strips are over.???]\\
281     At the end of the procedure, all proposed adjustments to PLL delay
282     values are proposed to the user. If accepted the delays are written in
283     fec.xml. If the setup is correctly aligned in time, a further time
284     alignment procedure should not propose delay corrections greater than
285     $\sim 2$ns.
286 carlo 1.3 %It is worth noticing that by the time alignment procedure all APVs are
287     %made sampling synchronously, since in the integration setup AOH fibres
288     %and ribbons are all equal in length. This is not important during
289     %integration quality checks, as no external signal is ever measured,
290     %but it would be so in trying to detect ionising particles.
291 sguazz 1.2 \item[Laser Scan.] By this commissioning run a scan of any bias and
292     gain value pair is done to determine the optimal working point for
293     each AOH.
294     The procedure requires a sucessfull time alignment since again tick marks are
295     sampled but in this case changing gain and bias values.
296     %
297 sguazz 1.1 \begin{figure}[t!]
298     \begin{center}
299     \subfigure[The sampled tick mark top and baseline as a function of the laser driver's bias.]
300     {
301     \label{fig:gainscan_basetop}
302     \includegraphics[width=.45\textwidth]{Figs/gainscan_basetop.pdf}
303     }
304     \hspace{5mm}
305     \subfigure[The corresponding tick mark height for a given gain.]
306     {
307     \label{fig:gainscan_range}
308     \includegraphics[width=.45\textwidth]{Figs/gainscan_range.pdf}
309     }
310 carlo 1.4 \subfigure[A pictorial representation of a tick mark as produced by the APV25s (dotted)
311 sguazz 1.2 and as transmitted by the lasers (solid) when the laser driver's bias is too
312     low (left), correct (centre) or too high (right), with the subsequent signal saturation.]
313     {
314     \label{fig:laserscan}
315     \includegraphics[width=.9\textwidth]{Figs/laserscan.pdf}
316     }
317 sguazz 1.1 \caption{Plots computed during a gain scan run.}
318     \end{center}
319     \end{figure}
320 sguazz 1.2 %
321 carlo 1.3 For each trigger sent to FEDs, the tick mark is sampled twice and all other samplings fall
322 sguazz 1.2 on the baseline. The tick mark's top samples are used to estimate the higher limit of the signal
323     for a given gain/bias setting pair and the baseline samples provide an estimate of the lower limit.
324     For each gain setting the tick mark top samples and the baseline samples are measured as a
325     function of the bias, as shown in Fig.~\ref{fig:gainscan_basetop}. For
326     each bias setting their difference is the tick mark height, shown in Fig.~\ref{fig:gainscan_range},
327     that represents the dynamic range as a function of the bias.\\
328     The best bias setting for a given gain setting is taken as the one maximising the tick mark height keeping
329     the maximum and minimum not saturated, as pictorially represented in Fig.~\ref{fig:laserscan}.
330     The same measurement is done for each possible gain setting.
331     The best laser gain setting is the one providing an overall gain of
332     the optical chain as close as possible to the design one, 0.8~\cite{ref:gain}.
333     The overall gain is estimated from the slope of the curves of
334     Fig.~\ref{fig:gainscan_basetop} in their central section.
335     After the run is completed a set of values are proposed to the
336     user. Abnormal gain values may indicate a problem either on the AOH or
337     on the fibre and are investigated.
338     \item[VPSP Scan.]
339     This commissioning run is devoted to optimise the pedestal of
340 carlo 1.4 the APV25, i.e. the average output level in absence of any signal, with
341 sguazz 1.2 respect to the dynamical range of the FEDs. This level is managed by a
342 carlo 1.4 specific APV25 register, know as {\em VPSP}, which controls a voltage
343 sguazz 1.2 setting within the deconvolution circuitry. The procedure consists of
344     a scan of VPSP values while acquiring data frames from modules in the
345 carlo 1.3 standard way.
346     %%, i.e. trigger sent to the modules and FEDs in
347     %%``header finding'' mode.
348     In the final tracker operation the optimal VPSP setting correspond to a pedestal baseline placed
349     around 1/3 of the available dynamic range. This is a good compromise to keep
350 sguazz 1.2 the baseline not too close the lower saturation value while leaving a good
351     range for particle signals, corresponding to $\sim 6$ MIP.
352 carlo 1.3 During the integration tests the only important point is to keep the baseline
353     away from the saturation levels; in such a way the module noise measurements will
354     not be affected by the wrong common mode subtractions which are present in case
355     of events with baseline saturation.
356 sguazz 1.2 At the end of the run a set of values are proposed to the user for
357 carlo 1.3 approval and in case written in the relevant xml file.
358 sguazz 1.1 \begin{figure}
359     \begin{center}
360 carlo 1.3 %\subfigure[Strip pedestals of a module in ADC counts vs.\ strip number.]
361     \subfigure[]
362 sguazz 1.1 {
363     \label{fig:saturationpedestal}
364     \includegraphics[width=.45\textwidth]{Figs/saturation_pedestal.pdf}
365     }
366     \hspace{5mm}
367 carlo 1.3 %\subfigure[Strip noise of a module in ADC counts vs.\ strip number.]
368     \subfigure[]
369 sguazz 1.1 {
370     \label{fig:saturationnoise}
371     \includegraphics[width=.45\textwidth]{Figs/saturation_noise.pdf}
372     }
373 carlo 1.4 \caption{Pedestal (left) and noise (right) vs. strip number for a 6 APV25 module.
374 carlo 1.3 The pedestals of strips after strip \#{}640 are low, approaching to the bottom of the
375     dynamic range. Their noise is therefore altered with respect to the not saturated
376     channels.}
377 sguazz 1.1 \label{fig:saturation}
378     \end{center}
379     \end{figure}
380 sguazz 1.2 The VPSP scan is not sistematically performed during the integration,
381     since the default VPSP setting is adequate in most of the
382     cases. Nevertheless, VPSP optimal values change considerably within
383 carlo 1.4 the APV25 population and are strongly temperature dependent and is
384 carlo 1.3 rather common to have a stuation in which the pedestal of few readout
385 sguazz 1.2 channels approaches to the lower edge of dynamic range
386     (Fig.~\ref{fig:saturationpedestal}) resulting in a lower RMS (see
387     Fig.~\ref{fig:saturationnoise}). The VPSP scan allows for this issue to be
388     fixed.
389     \item[Pedestal and Noise Run.]
390     This is the main run type for qualifying the performances during
391     the integration. Tipically a bias of 400V is applied to the modules
392     under test to check for any possible overcurrent or breakdown.\\
393     Triggers are sent to the modules and FEDs work in ``header finding'' mode.
394     All the analogue frames from the modules are collected two analyses
395     are performed on these data: online, by the TrackerOnline
396 carlo 1.4 software; offline, in a way very similar to the final experiment algorythms.
397     %by using algorythms of the ORCA package~\cite{bib:orca}, the CMS
398     %reconstruction package at that time, now replaced by CMSSW.
399 sguazz 1.1 The average value of the signal read on each strip is an estimate of
400     its pedestal, while the RMS is a good estimate of its noise, provided that the noise itself
401     is Gaussian, which is true to a first approximation. This value is often referred to as
402 sguazz 1.2 \textit{raw noise}, as opposed to the \textit{common-mode subtracted
403     noise} (or CMN). The latter is the RMS computed after having
404     subtracted the {\em common noise}, i.e. the correlated noise-like fluctuation
405 carlo 1.4 common to a given group of channels (tipically an entire APV25).
406     The common mode noise subtraction method implemented in
407 sguazz 1.2 TrackerOnline is similar to that performed by the final FEDs.\\
408 carlo 1.3 Because of the difference in gain between the various
409 carlo 1.4 optical links, noise comparison between different APV25 pairs requires a
410 carlo 1.3 normalization. This procedure relies on the digital
411 carlo 1.4 headers whose amplitude, being the same on each APV25, is used to
412 sguazz 1.2 estimate of the relative gain of optical links so to apply an
413     appropriate correction. In such a way noise and gain are
414     simultaneously measured provided that the signal is not saturation both on low and high values.
415     The normalisation factor is chosen so as to bring the normalised
416     header height to 220 ADC counts, as measured in quality controls
417     during the module production. This allowed the scaled measurements to be easily
418 carlo 1.3 compared with those done during module production tests~\cite{ref:modtest}.\\
419     At the end of the run, pedestal and noise profiles and distributions
420 sguazz 1.2 are shown to the user.
421 sguazz 1.1 \begin{figure}[t!]
422     \centering
423     \includegraphics[width=0.6\textwidth]{Figs/noiseprofile.pdf}
424     \caption{Noise profile of a TIB Layer 3 module. X axis represent the strip index
425     and y axis represent the noise in ADC counts (or ADC count equivalent for the
426     normalised noise).}
427     \label{fig:noiseprofile}
428     \end{figure}
429 sguazz 1.2 Figure~\ref{fig:noiseprofile} shows an example of the noise output:
430     the normalised raw noise and CMN and the uncalibrated CMN
431 sguazz 1.1 for each strip are plotted against the strip index. The first 256 strips belong to the
432 carlo 1.4 first APV25 pair and are multiplexed to a single optical line and the strips from 257 to 512
433     belong to the second APV25 pair. It can be noted here that the
434 carlo 1.3 raw noise without normalisation reflecs the different gain of
435     optical links, this is corrected by the normalisation procedure.\\
436 sguazz 1.2 If validated by the user, data are packed along with
437 sguazz 1.1 possible comments and sent to the central archive system, where they are processed
438 sguazz 1.2 again and made available on a web page.
439     %The system also automatically recognises where
440     %the modules where mounted by checking their DCU Hardware Id (which is written in the fec.xml file)
441     %in the construction database, this information is stored in the test table of
442     %the integration database and allows to build a geographical table of mounted modules with
443     %a link to a page containing all the tests performed for each module.\\
444     \end{description}
445 sguazz 1.1
446     %%%%%%% aggiunta C.G.
447 sguazz 1.2 The basic run types and tests described above are appropriately
448     combined according to the devices and/or the group of devices under test.
449     \begin{description}
450     \item[Single Module.] After a module is mounted, its basic
451     functionalities can be tested. In particular, a fast test on the
452     I$^2$C communication permits possible
453     electrical problems to be spotted in the module front-end electronics,
454     in the AOH or in the mother cable. For mother cable and AOH this is of
455     particular importance: an AOHs can be practically tested only
456     after the corresponding modules is mounted and this is the first
457     test which can spot possibly broken fibres; similarly for the MC, it
458     is very important to perform the test of as soon as possible. In
459     fact, a safe removal and replacement of either an AOH or the MC is a
460     difficult intervention possibly requiring the dismounting of many
461 carlo 1.3 modules already put in place. \\
462     Since the
463 sguazz 1.2 I$^2$C test FecTool checks the identity of the components with respect
464 carlo 1.3 to the construction database an alarm issued in case of mismatch.
465     The results of the tests can then be
466 sguazz 1.2 monitored through a web page.
467     \item[String]
468     When the third and last module or double sided assembly is mounted on
469     a string, all the commissioning runs described above are performed
470     just after the I$^2$C communication tests. The ``Find
471 carlo 1.3 connections'' run allows for the devices accessibility to be checked.
472 sguazz 1.2 Afterwards a ``Time Alignement'' run, a ``Laser scan'' run and
473 carlo 1.3 finally a ``Pedestal and Noise'' run with bias voltage at 400V are performed. The
474 sguazz 1.2 ``Laser scan'' run is done limiting the laser gain to the lower value
475     which is found to be enough for the integration setup needs.
476     \item[Control Ring and Redundancy.]
477     The control electronics can be fully tested only after complete
478     assembly of a shell. This last test forsees a check of the correct
479     operation of the ring and of the redundancy circuitry. A failure on a
480     CCU or a control cable can be immediatly spotted as it causes the
481     interruption of the ring; the communication with the other components
482     is then checked using ProgramTest. Finally the test of redundancy
483     circuitry is performed by-passing each CCU one by one and verifying
484     the correct response of the ring. The test is successful only if both
485     the primary and secondary circuits of the DOHM are working correctly
486     and if the CCUs are connected in the right order to the DOHM ports.
487 sguazz 1.1 %%%%%%%% fine aggiunta C.G.
488 sguazz 1.2 \end{description}
489 sguazz 1.1
490     \section{Safety of operations}
491     The integration procedure posed many possible problems in the safety of operations,
492     from the routing of optical fibres to the handling of modules and each of these items
493     were addressed to minimise the risk of an accident. \\
494     For example
495     as the integration setup could not make use of the shell cooling system,
496     temperature measurements on the most sensible devices were done
497     to be sure not to damage any components when the system is powered up.\\
498     The component with the most stringent requirement on temperature is the AOH
499     and in particular the optical coupling of the pig-tail fibres to lasers.
500    
501     \begin{figure}[t!]
502     \centering
503     \includegraphics[width=.5\textwidth]{Figs/ir.pdf}
504     \caption{IR picture of and AOH seen from below (laser side)
505     taken after a laser scan when bias and gain are maximum. The lasers reach a temperature
506     of $40^\circ \mathrm{C}$, while the highest recorded temperature $48^\circ \mathrm{C}$,
507     on the hybrid.}
508     \label{fig:ir}
509     \end{figure}
510    
511     An infrared camera has been used to monitor the temperature during the integration
512     tests. Figure~\ref{fig:ir} show a shot taken just
513     after a laser scan performed on one string of double-sided modules.
514     This run proved to be the most thermal
515     stressing among the commissioning run performed, because at its end
516     all laser drivers have the maximum gain and the highest bias possible with a complete
517     signal saturation.\\
518     For this test a double-sided layer has been used. In this case the modules have
519     two back-to-back hybrids
520     and thus a higher power dissipation density with respect to the single-sided ones;
521     furthermore the AOH are equipped with three lasers.\\
522     Even in the most stressing condition and after a few minutes of settling,
523     the highest measured temperature on the lasers was $\sim 40^\circ \mathrm{C}$
524     (while it was $48^\circ \mathrm{C}$ on the hybrid).
525 carlo 1.4 These are safe temperatures~\cite{ref:lasertemp}
526 sguazz 1.1 thus the integration tests could be performed without problems.