Event-Driven Data Mining Method for Improving Fault Code Settings and Isolating Faults

摘要

A parameter identification-based fault isolation technique is provided for improving fault code settings and isolating faults. DTCs and PIDs are retrieved from a current serviced vehicle. PID data is obtained from prior serviced vehicles having same vehicle specifications as and under substantially similar operating conditions as the current serviced vehicles. A plurality of clusters is formed using PID data of the prior serviced vehicles using mutual dependence to one another. A joint probability distribution is determined as a function of a mutual dependence of the PID data. PID data is selected of the current serviced vehicle having coherence to the PID of the prior service vehicles. A mutual dependence of the PID data of the current serviced vehicle is projected on onto the corresponding joint probability distribution. An anomaly in the PID data of the current serviced vehicle is detected in response to the probability distribution of parameter identification data being outside of a predetermined variance.