| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0444754 |
| utime |
20240103210154.8 |
| mtime |
20150625235959.9 |
| title
(primary) (eng) |
Probabilistic Inspection of Multimodally Distributed Signals |
| specification |
| page_count |
8 s. |
| media_type |
C |
|
| serial |
| ARLID |
cav_un_epca*0444753 |
| ISBN |
978-1-5108-0712-9 |
| title
|
The 12th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies (CM 2015/MFPT 2015) |
| publisher |
| place |
Oxford, UK |
| name |
The British Institute of Non-Destructive Testing |
| year |
2015 |
|
|
| keyword |
condition monitoring |
| keyword |
probabilistic logic |
| keyword |
binomial opinion |
| keyword |
multimodally distributed signal |
| keyword |
Gaussian mixture |
| author
(primary) |
| ARLID |
cav_un_auth*0212695 |
| name1 |
Ettler |
| name2 |
P. |
| country |
CZ |
|
| author
|
| ARLID |
cav_un_auth*0212696 |
| name1 |
Puchr |
| name2 |
I. |
| country |
CZ |
|
| author
|
| ARLID |
cav_un_auth*0101119 |
| name1 |
Jirsa |
| name2 |
Ladislav |
| full_dept (cz) |
Adaptivní systémy |
| full_dept |
Department of Adaptive Systems |
| department (cz) |
AS |
| department |
AS |
| institution |
UTIA-B |
| full_dept |
Department of Adaptive Systems |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0101175 |
| name1 |
Pavelková |
| name2 |
Lenka |
| full_dept (cz) |
Adaptivní systémy |
| full_dept |
Department of Adaptive Systems |
| department (cz) |
AS |
| department |
AS |
| institution |
UTIA-B |
| full_dept |
Department of Adaptive Systems |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| project |
| project_id |
7D12004 |
| agency |
GA MŠk |
| ARLID |
cav_un_auth*0291242 |
|
| abstract
(eng) |
Condition monitoring of complex systems starts from an inspection of single measured signals. Results of health evaluation for each signal then enter the monitoring framework which uses a special type of probabilistic logic to assess condition of the whole inspected system while respecting its internal structure. A distribution of the involved signal can be multimodal in general. Therefore, a Gaussian mixture is more suitable for its approximation than a single theoretical distribution. The mixture estimated from a sufficiently long record of a particular signal can be used not only for its prediction but also for evaluation of the signal health. However, finding the values in a low probability region does not necessarily indicate bad condition of the signal – it can be interpreted as an increase in the information uncertainty instead. This approach is being tested on industrial data within the running project which aims to develop the novel probabilistic condition monitoring system. |
| action |
| ARLID |
cav_un_auth*0317468 |
| name |
The 12th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies (CM 2015/MFPT 2015) |
| place |
Oxford |
| dates |
09.06.2015-11.06.2015 |
| country |
GB |
|
| reportyear |
2016 |
| RIV |
BC |
| num_of_auth |
4 |
| presentation_type |
PR |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0247505 |
| mrcbC61 |
1 |
| cooperation |
| ARLID |
cav_un_auth*0317469 |
| institution |
COM |
| name |
COMPUREG Plzeň, s.r.o. |
| country |
CZ |
|
| confidential |
S |
| arlyear |
2015 |
| mrcbU63 |
cav_un_epca*0444753 The 12th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies (CM 2015/MFPT 2015) 978-1-5108-0712-9 Oxford, UK The British Institute of Non-Destructive Testing 2015 |
|