Abstract:
A method for determining a root cause of a problem in a multiple-element system includes correlating an incoming alarm signal with an element x in a multiple-element system and accessing an implication list comprising a list of all elements upstream of element x. At least one element on the implication list is weighted with data relating to the at least one element. Taking into account the weighting step, a probability is calculated that an element on the implication list comprises a most-probable root cause of the subsequent alarm signal. The identified most-probable root cause of the incoming alarm signal is output.

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application claims priority to provisional patent application 61/117,651, filed Nov. 25, 2008. 
    
    
     STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT 
     This invention was made with Government support under Contract No. N00024-05-C-5346 awarded by United States Navy, Naval Sea Systems Command. The Government has certain rights in this invention. 
    
    
     BACKGROUND OF THE INVENTION 
     1. Field of the Invention 
     The present invention relates to systems and methods for determining a root cause of a problem in a multi-element system. 
     2. Description of Related Art 
     When a problem arises in a large system comprising a large number of elements, a multiplicity of indicators can be triggered. Such indicators can have been tripped by, for example, sensors downstream of an actual, root cause of the problem, thereby potentially masking the real problem. 
     An exemplary, non-limiting example comprises a large, automated naval ship. Particularly in a situation in which staffing has been reduced, it is important to provide an automated process for determining a root cause of an indicated problem in the ship. Other examples, also not intended as limitations, could comprise multi-element electronic systems, nuclear power plants, water treatment plants, power distribution systems, etc. 
     As a set of symptoms may indicate more than one potential root cause, an analysis preferably should establish all known causal relationships between these potential root causes and the problem. Many techniques are known in the art to perform root-cause analysis. For example, Bayesian a priori probabilities have been used to help predict a failed part. Other techniques are known that look for abnormalities in system operations, and that use expert systems to search through failure symptoms and explicit cause-and-effect relationships. Still other techniques use dependencies in the way the system is constructed, and pose queries to earlier systems in a chain of connected systems to determine whether they are still operating. 
     It would be beneficial to provide a root-cause analysis system that can integrate a plurality of disparate systems and determine from data received therefrom one or more root causes of a problem. 
     SUMMARY OF THE INVENTION 
     The present invention is directed to an analysis system for determining a root cause of a problem in a multiple-element system. The analysis system comprises a database that contains a connectivity map for at least some of the system elements, and a location map for at least some of the system elements. 
     Broadly, for a given alarm, the system determines a list of elements that could be suspected of causing the alarm. This list is refined and enhanced based upon a series of hypothesis testing modules. A likely root cause is then determined using an algorithm such as, but not intended to be limited to, a Bayesian inference technique. Over time, results for multiple alarm states are combined in order to refine the analysis and improve root cause determination. 
     In one aspect, an analysis system for determining a root cause of a problem in a multiple-element system comprises a database containing a connectivity map for at least some elements in a multi-element system and an implication list comprising a list of traced elements for an element y correlated with a previously received active alarm signal. 
     A processor in signal communication with the database is adapted for receiving an incoming alarm signal associated with an element x in the multi-element system, element x different from element y. 
     The processor has resident thereon a software system. The software system comprises a connectivity analysis module that is adapted for accessing the connectivity map, tracing all elements upstream of the element x, and creating an implication list therefrom. 
     A calculation module is adapted for receiving results from the connectivity analysis module and for accessing the database. The calculation module is also adapted for determining a set of elements in common with elements from the implication list for element y, and for calculating from the set of elements a probability that a particular system element comprises a root cause of the issuance of the incoming alarm signal. An output module is adapted for outputting at least one of the calculated probabilities, for identifying a most-probable root cause of the incoming alarm signal. 
     Another aspect of the present invention is directed to a method for determining a root cause of a problem in a multiple-element system. The method comprises correlating an incoming alarm signal with an element x in a multiple-element system and accessing an implication list comprising a list of all elements upstream of element x. At least one element on the implication list is weighted with data relating to the at least one element. Taking into account the weighting step, a probability is calculated that an element on the implication list comprises a most-probable root cause of the subsequent alarm signal. The identified most-probable root cause of the incoming alarm signal is output. 
     Yet a further aspect of the present invention is directed to a method for determining a root cause of a problem in a multiple-element system. The method includes correlating an incoming alarm signal with an element x in a multiple-element system and accessing an implication list comprising a list of all elements upstream of element x. At least one element on the implication list is weighted with data relating to the at least one element. Taking into account the weighting step, a probability is calculated that an element on the implication list comprises a most-probable root cause of the subsequent alarm signal. The identified most-probable root cause of the incoming alarm signal is output. 
     Another aspect of the present invention is directed to an analysis system for determining a root cause of a problem in a multiple-element system. The analysis system comprises a database that contains a connectivity map for at least some elements in a multi-element system and an implication list comprising a list of traced elements for an element x. 
     A processor is in signal communication with the database and is adapted for receiving an incoming alarm signal associated with the element x in the multi-element system. The processor is also adapted for receiving data relating to at least one element on the implication list. 
     The processor has resident thereon a software system comprising a calculation module adapted for weighting the set of elements based upon the received element data and for calculating therefrom for each element in the set of elements a probability that a particular system element comprises a root cause of the issuance of the incoming alarm signal. 
     An output module is adapted for outputting at least one of the calculated probabilities, for identifying a most-probable root cause of the incoming alarm signal. 
     It can be seen that the present invention has a multitude of benefits, including enabling staff reductions, accelerating repairs, increasing the effectiveness of repairs, and increasing the accuracy of repairs by enabling the repair of a root-cause element rather than an element that is merely symptomatic. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is an exemplary system diagram for the present invention. 
       FIGS.  2 A, 2 B is a flowchart for an exemplary method of the present invention. 
         FIG. 3  is an exemplary overall software system diagram. 
         FIG. 4  is an exemplary expert system diagram. 
         FIG. 5  is an exemplary implicated equipment list for an alarm. 
         FIG. 6  illustrates an exemplary result of the connectivity analyzer module following the issuance of three alarms. 
         FIG. 7  is an exemplary graph for the temporal analyzer module for use in a weighting factor. 
         FIGS. 8A-8C  are exemplary graphs of the probability of a particular element&#39;s being the root cause of a problem, with abscissa being the element identification number (from 1 to M) and the ordinate being the probability calculated (from 0 to 1). 
         FIG. 8A  represents the time prior to activation, when the analysis has not begun; FIG.  8 B, some activation has occurred, and the analysis has begun;  FIG. 8C , extra activation, analysis complete, root-cause element identified. 
         FIG. 9  is an exemplary output chart. 
     
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
     A description of the preferred embodiments of the present invention will now be presented with reference to  FIGS. 1-9 . 
     In an exemplary embodiment, not intended as a limitation on the invention, a system  10  ( FIG. 1 ) and method  100  (FIGS.  2 A, 2 B) are provided for identifying the most likely source(s) of problems on a ship. One of skill in the art will recognize that the system and method are equally applicable to performing root-cause analysis on any complex, multi-element system  11 . 
     An exemplary multi-element system  11  comprises element  1   12 ( 1 ) through element M  12 (M) (see, for example, the element list  23  of  FIG. 5 ). At least some of the elements  12 ( 1 )- 12 (M) are in signal communication with a respective sensor  13 ( 1 )- 13 (M). Each sensor  13 ( 1 )- 13 (M) is adapted to issue an alarm signal  14 ( 1 )- 14 (M) (block  102 ) when a respective element  12 ( 1 )- 12 (M) is sensed to be in a fault condition (block  101 ). Not all elements in the multi-element system  11 , however, are typically equipped with sensors, as illustrated by element  12 ( 3 ). Elements such as element  12 ( 3 ) connect to other elements and can fail in their own right, but not emit an alarm signal themselves. An exemplary such element could comprise a pipe, a cord, or the like. 
     In such a multi-element system  11 , multiple alarms can be issued when the respective elements are not themselves causing a fault, but rather are in a fault condition because of one or more upstream elements that are a root cause of cascading alarm states. 
     The analysis system  10  and method  100  are provided for determining a root cause of a problem in the multiple-element system  11 . The analysis system  10  comprises a processor  15  in signal communication with a database  16  that contains a connectivity map  17  for at least some of the system elements  12 ( 1 )- 12 (M), a location map  18  for at least some of the system elements  12 ( 1 )- 12 (M), a map  19  correlating alarm signals  14 ( 1 )- 14 (M) with their respective system elements  12 ( 1 )- 12 (M), subject-matter-expert data  20 , and failure probability data  21 , the composition and use of which will be discussed in the following. 
     The processor  15  is adapted for receiving an incoming alarm signal (block  103 ), containing an alarm identifier and the time of arrival. The processor  15  accesses the database  16  (block  104 ) for the purpose of accessing the element-to-alarm correlation map  19  to identify the respective system element  12 ( m ) that corresponds thereto (block  105 ). The time of arrival of the incoming alarm signal is also stored (block  106 ). 
     An overall system diagram is provided in  FIG. 3 , in which a software system  22 , which can comprise in an exemplary embodiment an expert system ( FIG. 4 ), is indicated as being resident on the processor  15 . The software system  22  comprises a plurality of modules that perform a plurality of analyses relating to the alarm signal and respective element  12 ( m ). Inherent in the software system  22  are a plurality of algorithms, as will be discussed in the following, that together can be referred to as a “calculation module”  34 , of which a Bayesian inference engine  30  can comprise a part. 
     The connectivity map  17  is accessed (block  107 ) to trace elements upstream of the subject element  12 ( m ) (block  108 ), from which is compiled a list of elements, or implication list (ILE; block  109 ). If other active alarms exist in the system  10 , the compiled ILE is compared with previously determined ILEs for the other elements in an active alarm state, from which common elements can be determined (block  110 ), and a probability value standardized accordingly (block  111 ). The hypothesis behind the connectivity analysis module  24  is that connected element(s) may affect the element(s) issuing the received alarm signals. The first part of the analysis includes implicating all connected elements, all the way back to the “prime mover.” Matching elements are then sought on other ILEs. Each connection or match increases a factor ψ CON  that is used to tally contributions prior to standardization to a [0, 1] range for probability analysis as follows: 
     
       
         
           
             
               
                 
                   
                     
                       P 
                       CON 
                     
                     ⁡ 
                     
                       ( 
                       m 
                       ) 
                     
                   
                   = 
                     
                   ⁢ 
                   
                     P 
                     ⁡ 
                     
                       ( 
                       
                         
                           Equipment_m 
                           ⁢ 
                           _is 
                           ⁢ 
                           _root 
                           ⁢ 
                           _cause 
                         
                         | 
                         Connection_data 
                       
                       ) 
                     
                   
                 
               
             
             
               
                 
                   = 
                     
                   ⁢ 
                   
                     
                       
                         ψ 
                         CON 
                       
                       ⁡ 
                       
                         ( 
                         m 
                         ) 
                       
                     
                     
                       
                         argmax 
                         
                           m 
                           ∈ 
                           
                             M 
                             CON 
                           
                         
                       
                       ⁢ 
                       
                         
                           ψ 
                           CON 
                         
                         ⁡ 
                         
                           ( 
                           m 
                           ) 
                         
                       
                     
                   
                 
               
             
           
         
       
     
     where ψ CON  is the number of times element m is referenced in connection chains; m is the element identifier, having a range of mε[1, M CON] , assumed to be labeled sequentially; and M CON  is the maximum number of elements in this connection set. 
     In an embodiment, at least one of the software system modules is executed, preferably substantially simultaneously, to refine the ILE and inform a possible root cause solution. 
     In case of an emergency or some other potentially hazardous event, real-time data  33  are input into the processor  15  (block  112 ). The location map  18  is accessed by a hazardous compartment analysis module  32  (block  113 ), which operates under the hypothesis that an element&#39;s residing in a hazardous compartment may make the element more likely to fail. The hazardous compartment module determines whether any element on the ILE is in a hazardous compartment (block  114 ). If so, a factor ψ HCL  is increased for that element by a predetermined factor, for example, 0.5 (block  115 ). Energy (a value) in ψ HCL  indicates that the associated element is located in a hazardous compartment. Thus, if the element is not in a hazardous compartment, ψ HCL =0. 
     The HCL calculations and standardizations can proceed as follows: 
     
       
         
           
             
               
                 
                   
                     
                       P 
                       HCL 
                     
                     ⁡ 
                     
                       ( 
                       m 
                       ) 
                     
                   
                   = 
                     
                   ⁢ 
                   
                     P 
                     ⁡ 
                     
                       ( 
                       
                         
                           Equipment_m 
                           ⁢ 
                           _is 
                           ⁢ 
                           _root 
                           ⁢ 
                           _cause 
                         
                         | 
                         HCL_data 
                       
                       ) 
                     
                   
                 
               
             
             
               
                 
                   = 
                     
                   ⁢ 
                   
                     
                       
                         ψ 
                         HCL 
                       
                       ⁡ 
                       
                         ( 
                         m 
                         ) 
                       
                     
                     
                       
                         argmax 
                         
                           m 
                           ∈ 
                           
                             M 
                             CON 
                           
                         
                       
                       ⁢ 
                       
                         
                           ψ 
                           HCL 
                         
                         ⁡ 
                         
                           ( 
                           m 
                           ) 
                         
                       
                     
                   
                 
               
             
           
         
       
     
     The location analysis module  25  operates under the hypothesis that elements on other ILEs in the same location as an element on the present ILE may have an effect on the element being considered. The location analysis module  25  accesses the location map  18  (block  116 ) and determines whether any of the ILE elements are located proximate each other (block  117 ). If so, a factor is increased for that element by a predetermined factor, as above (block  118 ), and the probability factor is standardized in similar fashion as for the CON analysis (block  119 ). 
     Subject-matter experts (SMEs) can also be consulted for encoding their knowledge into the system  10 , for example, in an SME data sector  20  in the database  16 . These data can also be useful in performing root-cause analysis. 
     The working hypothesis is that an SME may know to check other elements if a particular alarm occurs. The expert system  22  has an SME module  26  that accesses the SME data sector  20  (block  120 ) to ascertain whether other elements should be implicated based on the input alarm data (block  121 ). If so, a factor ψ SME (m) used in calculating root-cause probability in increased (block  122 ). 
     Examples of such an increase in the factor ψ SME (m) are as follows: If bearing1 has a high-temperature alarm, then increase the probability of oil_pump4 by 0.5. Or, if equipmentType is “bearing” and alarmType is “temp high” and connectionList has equipmentType “oilPump” having name “OilPump” then increase the probability of “OilPump” by 0.5. 
     Further, additional elements can be added to the ILE pursuant to SME knowledge that were not originally included pursuant to the results of the connectivity analysis module  24 . As an example, if in the above example “oil_pump4” were not already on the ILE, it could be added using SME knowledge, and given a ψ SME  value of 0.5. 
     Another module in the expert system  22  comprises a temporal analysis module  27 . The temporal analysis module  27  takes as input the times of arrival of the incoming alarm signals and compares the time of arrival with those having been received for other active alarms. The hypothesis under which this module  27  operates is that alarms occurring near in time to the current alarm may be related to the cause of the current alarm. 
     The temporal analysis module  27  finds alarms that are close in time (block  123 ) and weights them for closeness (block  124 ), P TEM =weight. The element with the highest P TEM  is determined in each close alarm (block  125 ). Information in the found-element data is updated (block  126 ), and the element is added to the implication list  23 , appropriately weighted (block  127 ). Thus an element not originally on the ILE pursuant to the results of the connectivity analysis module  24  can be added to the ILE. An exemplary weighting method is illustrated in the graph of  FIG. 7 , using the equations:
 
 P   TEM   =P   TEM (Δ t )= p ( m |time)
 
 P   TEM (Δ t )=
 
0,Δt≦a
 
(Δ t−a )/( b−a ), a&lt;Δt≦b;  
 
1,− b&lt;Δt≦ 0;
 
( c−Δt )/ c, 0 &lt;Δt;  
 
where a&lt;0; b&lt;0; c&gt;0; a&lt;b&lt;c.
 
     In a fault/alarm module  28 , the implication list  23  is checked to see if an element thereon has a fault or alarm status (block  128 ). If so, the factor P FLT =1 (block  129 ); otherwise, P FLT =0 (block  130 ). An associated weight is used to control the actual value (block  131 ). 
     A failure probability module  29  operates by accessing the failure probability data sector  21  on the database  16  (block  132 ), which is based upon prior reliability maintainability analysis data. The probability that an element will fail at all is P RMA , and is given as the probability of failure according to predetermined data, for example, manufacturer data or condition-based-maintenance data that can provide data useful in estimating a remaining useful life of the element. For example, a predetermined time span could be set, such as within 4600 hours (one month) (block  133 ). This factor can be substituted in an alternate embodiment with condition-based-maintenance data from a mission readiness element for adaptive accuracy. 
     The processor  15  uses an algorithm, preferably a Bayesian inference engine  30 , although this is not intended as a limitation, that is adapted for receiving results from one or more of the connectivity  24 , the location  25 , the temporal  27 , SME  26 , fault/alarm  28 , and failure probability analysis  29  modules. The Bayesian inference engine  30  determines therefrom a probability that a system element comprises a root cause of the issuance of the incoming alarm (block  134 ), and all alarms are analyzed and updated with the receipt of new data. Using the following definitions: 
     m=equipment ID 
     A=alarm ID 
     P CON =P CON (m)=P(A|m) CON =contribution to root cause from connection data 
     P LOC =contribution to root cause from location data 
     P SME =contribution to root cause from SME data 
     P HCL =contribution to root cause from hazard compartment list data 
     P TEM =contribution to root cause from temporal data 
     P FLT =contribution to root cause from fault/alarm data 
     P RMA =probability that element will fail 
     P TOT =P(m|A) TOT =probability that element m is the root cause of alarm A the calculations proceed as follows: 
     
       
         
           
             
               
                 
                   
                     P 
                     TOT 
                   
                   = 
                     
                   ⁢ 
                   
                     P 
                     ⁡ 
                     
                       ( 
                       
                         m 
                         | 
                         A 
                       
                       ) 
                     
                   
                 
               
             
             
               
                 
                   = 
                     
                   ⁢ 
                   
                     P 
                     ⁡ 
                     
                       ( 
                       
                         
                           Equipment_m 
                           ⁢ 
                           _is 
                           ⁢ 
                           _root 
                           ⁢ 
                           _cause 
                         
                         | 
                         Alarm 
                       
                       ) 
                     
                   
                 
               
             
             
               
                 
                   = 
                     
                   ⁢ 
                   
                     
                       
                         
                           
                             P 
                             ⁡ 
                             
                               ( 
                               
                                 Alarm 
                                 | 
                                 
                                   Equipment_m 
                                   ⁢ 
                                   _is 
                                   ⁢ 
                                   _root 
                                   ⁢ 
                                   _cause 
                                 
                               
                               ) 
                             
                           
                         
                       
                       
                         
                           
                             P 
                             ⁡ 
                             
                               ( 
                               
                                 Equipment_m 
                                 ⁢ 
                                 _is 
                                 ⁢ 
                                 _root 
                                 ⁢ 
                                 _cause 
                               
                               ) 
                             
                           
                         
                       
                     
                     
                       P 
                       ⁡ 
                       
                         ( 
                         Alarm 
                         ) 
                       
                     
                   
                 
               
             
           
         
       
     
     But, since the element is in the alarm state:
 
 P (Alarm)=1
 
Thus:
 
 P   TOT   =P (Alarm|Equipment —   m _is_root_cause) P (Equipment —   m _is_root_cause)
 
     The posterior probability that an element is the root cause is denoted as P TOT , which is found for each element m on the ILE. P TOT  is equal to a conditional probability term multiplied by a prior probability term P RMA  as follows: 
     
       
         
           
             
               P 
               TOT 
             
             = 
             
               
                 [ 
                 
                   
                     ( 
                     
                       
                         
                           w 
                           TEM 
                         
                         ⁢ 
                         
                           P 
                           TEM 
                         
                       
                       + 
                       
                         
                           w 
                           CON 
                         
                         ⁢ 
                         
                           P 
                           CON 
                         
                       
                       + 
                       
                         
                           w 
                           HCL 
                         
                         ⁢ 
                         
                           P 
                           HCL 
                         
                       
                       + 
                       
                         
                           w 
                           LOC 
                         
                         ⁢ 
                         
                           P 
                           LOC 
                         
                       
                       + 
                       
                         
                           w 
                           SME 
                         
                         ⁢ 
                         
                           P 
                           SME 
                         
                       
                       + 
                       
                         
                           w 
                           FLT 
                         
                         ⁢ 
                         
                           P 
                           FLT 
                         
                       
                     
                     ) 
                   
                   6 
                 
                 ] 
               
               ⁢ 
               
                 P 
                 RMA 
               
             
           
         
       
     
     where the weights W TEM , W CON , W HCL , W LOC , W SME , and W FLT  temper the contributions. The element m having the maximum P TOT (m) is reported as the most likely root cause (block  135 ). Various patterns may emerge that implicate the element producing the original alarm. 
     Output from the analysis (block  136 ) may be transmitted to an output device  31  in signal communication with the processor  15 , and may take any of several forms, as will be appreciated by one of skill in the art. For example, in  FIGS. 8A-8C  are depicted a series of graphs prior to analysis ( FIG. 8A ), with analysis begun ( FIG. 8B ), and with analysis complete ( FIG. 8C ). The abscissa provides the element ID number, and the ordinate the probability that a given element is the root cause of the problem. 
     Another output form is given in  FIG. 9 , wherein a number of symbols represents the probability that a certain element is the root cause of the problem. 
     As will be understood by one of skill in the art, the above-described system  10  and method  100  are preferably iterative. As each new piece of data (e.g., a change in the hazardous compartment condition) and/or alarm is received (block  137 ), the root-cause analysis is recalculated and refined. 
     Having now described the invention, the construction, the operation and use of preferred embodiments thereof, and the advantageous new and useful results obtained thereby, the new and useful constructions, and reasonable mechanical equivalents thereof obvious to those skilled in the art, are set forth in the appended claims.