Failure cause classification apparatus
Selection of sensors requires the knowledge of individual sensors mounted on a target machine and the knowledge of mechanical features of the machine. In the past, experts having mechanical knowledge selected the sensors. The present invention involves analyzing sensor data at e of machine failure, extracting features from the sensor data regarding each failure cause, and comparing the extracted features so as to clarify the difference between the sensor data about the failure causes and present an operator with the clarified difference thereby to support sensor selection. The invention makes it possible to select more simply than before the sensors considered effective for classifying failure causes. For example, the sensors deemed effective for classifying failure causes without mechanical knowledge can be selected.
1. A failure cause classification apparatus comprising:
a processing part; and
a failure database, wherein:
the failure database stores machine failure causes of vehicles in relation with sensor data of the vehicles,
the sensor data include at least one of an accelerator position, an engine speed and a temperature, and
the processing part is configured to:
learn failure features from the sensor data stored in the failure database;
based on a result of learning, obtain similar failure features from among the failure features of at least two machine failure causes;
compare the similar failure features obtained; and
obtain an influence value serving as an index for selecting a sensor effective for classifying the machine failure causes based on a result of comparing, wherein:
the influence value includes an effectiveness value indicating whether a candidate sensor is effective for classifying the machine failure causes; and
a selection screen for selecting sensors, wherein the selection screen displays a sensor selection part that displays the influence value and sensor identifications and allows the candidate sensor to be selected.
2. The failure cause classification apparatus according to claim 1 , wherein the influence value further includes a reliability value indicating whether the influence value is reliable.
3. The failure cause classification apparatus according to claim 2 , wherein the reliability value is a function of the number of sensor data used for evaluating the effectiveness value.
4. The failure cause classification apparatus according to claim 3 , wherein the influence value includes classification performance indicating percentage of the machine failure causes classified correctly by the selected sensor among all classified machine failure causes.
5. The failure cause classification apparatus according to claim 1 , wherein the selection screen displays the classification performance and updates the displayed classification performance in accordance with the sensor selected by the sensor selection part.
6. The failure cause classification apparatus according to claim 5 ,
wherein the selection screen displays images indicative of the candidate sensors; and
wherein the selection screen changes a method by which the images are displayed in accordance with the influence value.
7. The failure cause classification apparatus according to claim 6 , wherein the selection screen displays machine failure causes and, when a specific machine failure cause is selected from the displayed machine failure cases, changes the display of the influence value in accordance with the selected machine failure cause.
8. The failure cause classification apparatus according to claim 6 , wherein the selection screen has a function of changing the display of the influence value in accordance with a specific image when the specific image is selected from among the images.
9. The failure cause classification apparatus according to claim 8 , wherein the selection screen displays a history of the influence value in the past.
10. The failure cause classification apparatus according to claim 9 , wherein the selection screen displays a history of the images previously selected.