35 results about "Diagnostic reasoning" patented technology

A method for distributed diagnostic reasoning is provided. The method includes establishing a computing node monitoring the operation of a component of a complex system and populating at least one of a processor and the memory of the computing node with one or more standardized executable application modules (SEAMs) and a workflow service. The method further includes creating a configuration file in combination with several SEAMS to create a distributed diagnostic reasoner (DDR) associated with the component. The method also comprises installing the configuration file in the computing node for execution by the processor; and initializing the one or more SEAMS, the configuration file and the workflow service, wherein the workflow service facilitates data flow between the one or more SEAMS and the static data associated with a fault condition resident in the configuration file.

The invention discloses a time-varying reliability evaluation method for a mechanical system based on a dynamic Bayesian network. The time-varying reliability of mechanical systems is calculated by using the Sterling information update formula and Monte Carlo simulation. Beneficial effects of the invention: Bayesian network provides a graphical representation method of knowledge, which can describe the causal probability relationship between node variables in a directed graphical manner, which can be used for uncertainty knowledge expression, causal reasoning and diagnostic reasoning Wait. The reasoning of the Bayesian network can effectively identify the weak links of the system reliability; its graphical display makes the relationship between the components in the mechanical system more intuitive and clear, and the dynamic Bayesian network technology is applied to the time-varying reliability of the mechanical system Evaluation, analysis of the multi-state and failure correlation of the mechanical system, to improve the theoretical support for improving the performance and reliability of the mechanical system.

The invention discloses a data-driven self-adaptive multi-layer flow model equipment diagnosis method, which combines the better accuracy based on the data-driven method and the better interpretability based on the multi-layer flow model method, and overcomes the traditional The fixed abnormal alarm threshold in the multilayer flow model method is easy to cause missing alarms, which leads to wrong diagnosis results. Based on the data-driven equipment status classification and identification results, the abnormal alarm threshold of the multi-layer flow model is adaptively adjusted, and the current equipment status is further confirmed through the multi-layer flow model anomaly detection and diagnostic reasoning to enhance the reliability of equipment fault diagnosis. The equipment diagnosis method has important scientific research value and engineering application value.

The invention discloses an overhead power transmission line running state assessment method based on a bidirectional Bayesian network. The method can be used for conducting a real-time assessment on the running state of an overhead power transmission line. According to the method, a Bayesian network structure for the assessment of the running state of the power transmission line is constructed with various factors which influence the running state of the power transmission line serving as a condition attribute set and the running state of the line serving as a decision attribute, a conditional probability table is obtained according to sample training, and by utilizing the bidirectional reasoning technology dedicated to the Bayesian network, the running state of the line can be judged by means of causal reasoning, and the hidden danger of the state can also be recognized by means of diagnostic reasoning; when an assessment error exists, a self-feedback system can be used for conducting early warning and correction, an assessment database, the network structure and parameters can be modified dynamically in real time so as to be adapted to an update, and therefore healthy running of the power transmission line is truly guaranteed.

The invention discloses a method for diagnosing a compressor-associated failure based on a Bayesian network. Based on a three-layer Bayesian diagnosis network of working condition operation, failure and symptom, a simple and intuitive graphic mode is used for expatiating the complicated causality and conditional relation between the failure, the reason and the symptom thereof, performing diagnostic reasoning under a finite, incomplete and uncertain information condition and completely describing the probability of the system failure, so qualitative information and quantitative information canbe integrated, the function of fully utilizing multi-source information is realized, and the testing sample size for performing the failure diagnosis is reduced by fully utilizing the priori information and historical information of a specific diagnosis object; and the accuracy and the efficiency for the failure diagnosis can be greatly improved by establishing a proper Bayesian diagnosis networkand determining a rational prior probability.