System and method for integrating a plurality of diagnostic...

Data processing: generic control systems or specific application – Generic control system – apparatus or process – Having protection or reliability feature

Reexamination Certificate

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Details

C702S179000, C714S025000, C714S026000, C382S141000, C382S157000

Reexamination Certificate

active

06473659

ABSTRACT:

FIELD OF THE INVENTION
The present invention relates generally to fault diagnosis and more particularly to integrating a plurality of diagnostic related information in order to facilitate detection and identification of a fault and recommend a service or control action for a machine experiencing a failure, a fault condition, or symptoms of an incipient failure condition or mode.
BACKGROUND OF THE INVENTION
In either an industrial or commercial setting, a malfunctioning machine can impair a business severely. Thus, it is essential that a malfunctioning machine be repaired quickly and accurately. For example, during a malfunction of an imaging machine such as an ultrasound, a computed tomography (CT), or a magnetic resonance imaging (MRI) machine, a field engineer is called in to diagnose and repair the machine. Typically, the field engineer will look at multiple sets of information generated from the imaging machine. For example, there is an error log generated from the imaging machine which contains sequences of events that occurred during both routine operation as well as during any malfunction situation. The error log represents a “signature” of the operation of the machine and can be used to correlate malfunctions. In addition, there are a series of phantom images and clinical images generated from the imaging machine. Other information includes the imaging machine's operative parameters (e.g., power, temperature, etc.) and waveform data generated from running a system performance test.
Using their accumulated experiences at solving imaging machine malfunctions, the field engineer looks through the multiple of information and tries to find any symptoms that may point to the fault. The field engineer then tries to correct the problem that may be causing the machine malfunction. If there is only a small amount of information to evaluate, then this process will work fairly well. However, if there is a large amount of information to process as is usually the case for large complex devices, it will be very difficult for the field engineer to diagnose a fault with accuracy and completeness. In this case, the field engineer will request the help of a service engineer located at a remote site for assistance in evaluating the information and thus diagnosing the most likely cause of the malfunction. Typically, the service engineer retrieves all of the information obtained from the imaging machine. At the remote site, automated tools specific to each of the imaging machine information type are available to the service engineer. The service engineer then runs a series of automated analysis and diagnosis tools to evaluate the information obtained from the imaging machine. Each of the automated analysis and diagnosis tools generates a list of recommendation(s) for diagnosing the condition for the malfunction. The service engineer analyzes the list of recommendations from the multiple tools and uses their accumulated experience at solving imaging machine malfunctions to find the most likely cause for the fault. The service engineer then recommends a particular fix action to the field engineer.
A problem with this approach is that there is no predefined execution strategy for selecting the specific analysis and diagnosis tools and executing them. A predefined execution strategy is needed because some of the analysis and diagnosis tools are more effective than others at solving a given system malfunction. Without a predefined execution strategy, it is difficult for the service engineer to determine the most likely cause for the fault. Another problem with this approach is that the recommendations generated from the analysis and diagnosis tools sometimes overlap or conflict with each other. A methodology is needed to resolve such conflicts so that the final recommendations of fault conditions are in fact the most likely actual fault and the corrective service or control action recommended is accurate. Therefore, there is a need for a system and method that can integrate knowledge from various sources of information in order to quickly detect and identify a fault, and recommend a service or control action for a machine experiencing a failure, a fault condition, or symptoms of an incipient failure condition or mode.
SUMMARY OF THE INVENTION
This invention is able to quickly detect and identify a fault, and recommend a service or control action for a machine experiencing a failure, a fault condition, or symptoms of an incipient failure condition or mode by using a diagnostic router and an integrator. The diagnostic router collects a plurality of diagnostic related information for the machine from a multiple of sources and generates a current incident record therefrom. The integrator finds approved incident records from an approved incident record database that most closely match the current incident record. A recommended service action or fix is generated by the integrator to bring the machine to a normal operating state or mode. The integrator resolves any conflicting information in order to a unique recommendation.
In accordance with this invention, there is provided a system and method for integrating a plurality of information from a multiple of sources. In this invention, there is a site specific database containing site specific information for a machine. A plurality of diagnostic related information is obtained from the machine. A diagnostic router collects site specific information for the machine from the site specific database and the plurality of diagnostic related information and generates a current incident record therefrom. An approved incident record database contains a plurality of approved incident records obtained from a plurality of machines. An integrator finds approved incident records from the approved incident record database that most closely match the current incident record.


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