PATENT CLAIM ANALYSIS

Application Number: 16053994
Application Type: Utility
Filing Date: 2018-08
Publication Date: 2019-02
Patent Classification: ["702", "183000"]

Abstract:
Disclosed is an apparatus for troubleshooting fault component in equipment and a method thereof. The device includes portions for building a fault-component-sensor Bayesian belief network model by acquiring component state-abnormal and data of fault maintenance of the equipment, and for calculating probabilities of actual component abnormality when a sensor connected with an component detects component abnormality based on the model; and arranging the probabilities in a descending order to obtain the arranged probabilities of actual component abnormality, and the top-arranged component being the one to be troubleshot first. Namely, a relational expression among the fault, the component and the sensor may be systematically built by adopting the method or the apparatus provided by the present disclosure, and the most-likely-failing component in an equipment may be quickly detected according to the expression, thereby improving troubleshooting efficiency.

Claim (Index 12):
The method of  claim 9 , wherein before the step 4, the method further comprises:\n judging whether the first probability of an component is greater than a first threshold value and whether the component is connected with each of the plurality of the sensor, obtaining a first judgment result; connecting each of the plurality of sensors with the component, if the first judgment result shows that the first probability of the component is greater than the first threshold value and the component is not connected with each of the plurality of sensors; maintaining connection between the component and the plurality of sensors, if the first judgment result shows that the first probability of the component is no larger than the first threshold value or the component is connected with the plurality of sensors; updating the fault-component-sensor Bayesian belief network model based on the first judgment result; and calculating the actual probability of component abnormality when the component is detected abnormal by the plurality of the sensor connecting to the component based on the updated fault-component-sensor Bayesian belief network model.

Metadata:
- Claim Count in Document: 32.0
- Percentile: 96.0
- Lexical Diversity: 1.90789
- Patent Class: 702.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['09758891', '14909788', '15823116', '13336153', '11868245']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2138216995198255
- 35 USC 102 Novelty (BERT): 0.5060365780450043
- Combined Prediction Score: 0.2430431873723434
- Mean Citation Score: 186.220998
- Max Citation Score: 203.27025
- Similarity Product: 114.1460133679658

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test