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Status of the ZEUS Expert System ZEX 

 Ulf Behrens
   DESY-ZEUS

 Mariusz Flasinski
 Jagellonian University Cracow

Lars Hagge 
DESY-ZEUS

Janusz Jurek 
Jagellonian University Cracow

Kars Ohrenberg 
DESY-ZEUS
  • Paper (Postscript)
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                    Abstract

    A. Description of ZEX

    The ZEUS detector is controlled and read out by a highly parallel distributed online system. An expert system helps to increase both efficiency and reli- ability of experiment operation while reducing the required efforts and expertise of the shift crew. The task of the expert system is to detect anomalous behavior in any part of the experiment, to trace errors to their origin, and to recover or help to recover the system as quick as possible.

    ZEX is based on the commercial expert system shell RTworks. The large number of human experts in the ZEUS environment requires the knowledge to be stored in an intuitive way, and extending the knowledge base has to be possible without expert system experts. A rule based system was considered to be the only appropriate way of knowledge storing. Experience of this way of keeping the knowledge of human experts available will be discussed.

    ZEX is put on top of existing systems, and the layered structure of ZEX reflects the structure of the online system:

    • a slow control sub-expert-system monitors the basic hardware of the experiment. It surveys the states of power supplies, racks, crates, photomultipliers, temperature and radiation sensors, cooling, etc. Based on this information, it decides if efficient data taking is possible, and proposes what to do to regain an acceptable state.
    • a data quality sub-expert-system tries to ensure a high quality of the data written to tape. It monitors the beam quality and background rates, and it checks the data from the major components for miscalibration, dead channels, etc.
    • a data flow sub-expert-system surveys the data taking. It monitors the central components of the data acquisition system (ie front-end systems, trigger stages, data storage task) for data rates, deadtime, response times etc.
    • at the top level, ZEX is combining the information about the subsystems to an overall system understanding.

    For the 1995 data taking period, ZEX is tuned to speed up the procedure of expanding and modifying the knowledge of the system, thus enabling fast reactions to changes in the run conditions, and preparing ZEX to handle short-term conditions in the ZEUS environment (eg crate failures).

    B. Impact on future experiments

    In a fast-changing environment like a HEP experiment, where experts are not always available at the location of the experiment and are frequently changing their positions, an expert system provides a central knowledge repository, which makes information available to anybody whenever (maybe also wherever) it is needed. Parts of the experiment operation (eg data acquisition operation, readout configuration etc) can even be automated with an ES.

    A mandatory condition for successful operation is the availability of monitoring information from and access to the different detector parts, their readout and the trigger system. It is thus beneficial to incorporate an expert system already at very early stages into the experiment design (protocols, network layout etc).

    Knowledge engineering and artificial intelligence are branches of computer science which are mostly alien to high-energy physicists. It should thus be considered to involve computer scientists into the design and development of expert systems in HEP. 

    
Name:           Ulf Behrens
Institution:    DESY
                Notkestr.85
                22603 Hamburg
EMAIL address:  behrens@x4u.desy.de
Telephone:      ++49-40-8998 2709
FAX:            ++49-40-8998 3092
Authors:        Ulf Behrens (DESY-ZEUS),
                Mariusz Flasinski (Jagellonian University Cracow),
                Lars Hagge (DESY-ZEUS),
                Janusz Jurek (Jagellonian University Cracow),
                Kars Ohrenberg (DESY-ZEUS)