Method for alerting of an event affecting a physical system

A non-transitory computer readable medium having stored thereon a computer program comprising instructions for performing a method for determining new occurrences of an event of a physical system to be manufactured in the course of designing a model of the physical system on a Computer-Aided Design (CAD) system, the event being a cause of an incident of the physical system, the method comprising:

• obtaining a first set and a third set of past events of the physical system, each past event comprising several attributes, at least one of the several attributes being a structured attribute and at least one of the several attributes being an unstructured attribute, each attribute being a symbol associated with data, the symbol characterizing a parameter of the physical system, the data associated with at least one attribute having been measured by a probe;
• training a context sensitive auto-encoder with the third set of past events, the context sensitive auto-encoder being trained to take as input a vectorized event and to provide as output a signature of the event, the signature of the event being a compression of the event that contains as much as possible of the information necessary to reproduce the event;
• obtaining a signature for each past event of the first set by:
• vectorizing each past event, the vectorizing comprising converting unstructured attributes into a number of numerical attributes;
• and
• applying the trained context sensitive auto-encoder to each vectorized past event;
• obtaining a new event comprising several attributes, the new event being a cause of an incident of the physical system, data associated with at least one attribute of the new event having been measured by a probe;
• computing a signature of the new event by:
• vectorizing the new event;
• and
• applying the trained context sensitive auto-encoder to the vectorized new event;
• computing a similarity measure between the signature of the new event and each signature of each past event of the first set;
• determining a plurality of past events closest to the new event, the plurality of past events having the highest similarity measures, the plurality of past events thereby forming a second set of past events, the number of the plurality of past events closest to the new event being predefined by a user;
• computing a score of relevance for each structured attribute of each of the events of the second set, the computing comprising, for each structured attribute:
• obtaining a distribution of values of the structured attribute on the second set;
• obtaining a distribution of values of the structured attribute on the first set;
• and
• comparing the distributions of values;
• and
• generating a set of attributes by selecting the structured attributes of each of the events of the second set having the greater scores of relevance.

A system comprising:

• a processor coupled to a memory, the memory having recorded thereon a computer program for determining new occurrences of an event of a physical system to be manufactured in the course of designing a model of the physical system on a Computer-Aided Design (CAD) system, the event being a cause of an incident of the physical system, that when executed by the processor causes the processor to be configured to:
• obtain a first set and a third set of past events of the physical system, each past event comprising several attributes, at least one of the several attributes being a structured attribute and at least one of the several attributes being an unstructured attribute, each attribute being a symbol associated with data, the symbol characterizing a parameter of the physical system, the data associated with at least one attribute having been measured by a probe;
• train a context sensitive auto-encoder with the third set of past events, the context sensitive auto-encoder being trained to take as input a vectorized event and to provide as output a signature of the event, the signature of the event being a compression of the event that contains as much as possible of the information necessary to reproduce the event;
• obtain a signature for each past event of the first set by the processor being configured to:
• vectorize each past event, the vectorizing comprising converting unstructured attributes into a number of numerical attributes;
• and
• apply the trained context sensitive auto-encoder to each vectorized past event;
• obtain a new event comprising several attributes, the new event being a cause of an incident of the physical system, data associated with at least one attribute of the new event having been measured by a probe;
• compute a signature of the new event by the processor being configured to:
• vectorize the new event, and
• apply the trained context sensitive auto-encoder to the vectorized new event;
• compute a similarity measure between the signature of the new event and each signature of each past event of the first set;
• determine a plurality of past events closest to the new event, the plurality of past events having the highest similarity measures, the plurality of past events thereby forming a second set of past events, the number of the plurality of past events closest to the new event being predefined by a user;
• compute a score of relevance for each structured attribute of each of the events of the second set, the computing comprising, for each structured attribute, by the processor:
• obtain a distribution of values of the structured attribute on the second set;
• obtain a distribution of values of the structured attribute on the first set;
• and
• comparing the distributions of values;
• generate a set of attributes by selecting the structured attributes of each of the events of the second set having the greater scores of relevance.