# US 11,897,527 B2 · Automated positive train control event data extraction and analysis engine and method therefor

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- Number: US 11,897,527 B2
- Document ID: US11897527B2
- Status: Granted
- Kind: B2
- Application number: 18/065,149
- Filed: 2022-12-13
- Published: 2023-10-19
- Granted: 2024-02-13
- Earliest claimed: 2022-04-14
- Assignees: BNSF Railway Company
- Applicants: BNSF Railway Company
- Inventors: Scott Alan Neal, Jr.; Siju Pallimolel Kuriakose
- Web page: https://patentgrep.com/patent/US11897527B2

## CPC

- B61L 15/0058: {On-board optimisation of vehicle or vehicle train operation}
- B60T 8/1705: {for rail vehicles}
- B61L 15/0094: {Recorders on the vehicle}
- B61L 27/57: for vehicles or trains, e.g. trackside supervision of train conditions
- B60T 2270/406: Test-mode; Self-diagnosis
- B61L: GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC (brakes or auxiliary equipment B61H, B61K; point or crossing construction E01B)
- B60T: VEHICLE BRAKE CONTROL SYSTEMS OR PARTS THEREOF; BRAKE CONTROL SYSTEMS OR PARTS THEREOF, IN GENERAL (electrodynamic brake systems for vehicle, in general B60L; brakes per se, i.e. devices where braking effect occurs, including ultimate brake actuators, F16D); ARRANGEMENT OF BRAKING ELEMENTS ON VEHICLES IN GENERAL; PORTABLE DEVICES FOR PREVENTING UNWANTED MOVEMENT OF VEHICLES; VEHICLE MODIFICATIONS TO FACILITATE COOLING OF BRAKES

## Abstract

A system and method for automating workflow and performing root cause analysis for enforcement events is presented. The system can enable accurate detection of an enforcement event and identifies the root cause of such events. The system can provide a user with an interface to monitor the enforcement event by collecting a list of data characterizing the enforcement event, as well as analyze the data to evaluate what is the root cause of the enforcement event. The system can extract critical information from train system logs of the train using an extraction model to generate a window of activity providing an analysis model with a comprehensive scope to analyze the enforcement event. The system can give the user robust and accurate information of the root cause of the enforcement event.

## Claims

### Claim 1

A system for extracting data and performing root cause analysis of data structures, comprising:
a memory having a database with train system logs; and
a processor operably coupled to the memory and capable of executing machine-readable instructions to perform program steps, the program steps comprising:
receiving a message having message data corresponding to train policy enforcement events;
determining whether the message data is unstructured;
transforming unstructured message data to structured data using one or more factors;
organizing the structured data according to one or more of the factors;
extracting data from the structured data;
analyzing the extracted data using an analysis model to generate an analysis result;
assigning, via the analysis model, an alert ID to the analysis result; and
sending a synopsis corresponding to the unique ID or the alert ID to a user.

### Claim 2 (depends on 1)

The system of claim 1, wherein the factors include message length, message payload, an employee name, an employee ID, an employee role on the train, the policy enforcement type, a location of the train.

### Claim 3 (depends on 1)

The system of claim 1, the program steps further comprising:
creating, via the analysis model, a high-level classification for the train event, if the analysis result does not include the root cause.

### Claim 4 (depends on 1)

The system of claim 1, the program steps further comprising:
analyzing the extracted data using a defect detection analysis model;
if a defect is detected, classifying the root cause as the defect; and
if the defect is not detected, analyzing the extracted data using a historical analysis model.

### Claim 5 (depends on 4)

The system of claim 4, wherein the historical analysis model is based on historical data such as previous engineer interactions, system component responses, and situational behavior.

### Claim 6 (depends on 1)

The system of claim 1, wherein either structured data or unstructured data include train system log data.

### Claim 7 (depends on 6)

The system of claim 6, wherein the data is extracted using data manipulation practices.

### Claim 8 (depends on 1)

The system of claim 1, wherein the analysis model comprises a decision tree model, a classification model, or a clustering model.

### Claim 9 (depends on 1)

The system of claim 1, wherein the data is extracted using a regular expression.

### Claim 10 (depends on 9)

The system of claim 9, wherein the regular expression includes a sequence of characters that define a search pattern.

### Claim 11

A method of extracting data and performing root cause analysis of data structures, comprising:
receiving a message having message data corresponding to train policy enforcement events;
determining whether the message data is unstructured;
transforming unstructured message data to structured data using one or more factors;
organizing the structured data according to one or more of the factors;
extracting data from the structured data;
analyzing the extracted data using an analysis model to generate an analysis result;
assigning, via the analysis model, an alert ID to the analysis result; and
sending a synopsis corresponding to the unique ID or the alert ID to a user.

### Claim 12 (depends on 11)

The method of claim 11, wherein the factors include message length, message payload, an employee name, an employee ID, an employee role on the train, the policy enforcement type, a location of the train.

### Claim 13 (depends on 11)

The method of claim 11, further comprising:
creating, via the analysis model, a high-level classification for the train event, if the analysis result does not include the root cause.

### Claim 14 (depends on 11)

The method of claim 11, further comprising:
analyzing the extracted data using a defect detection analysis model;
if a defect is detected, classifying the root cause as the defect; and
if the defect is not detected, analyzing the extracted data using a historical analysis model.

### Claim 15 (depends on 14)

The method of claim 14, wherein the historical analysis model is based on historical data such as previous engineer interactions, system component responses, and situational behavior.

### Claim 16 (depends on 11)

The method of claim 11, wherein either structured data or unstructured data include train system log data.

### Claim 17 (depends on 16)

The method of claim 16, wherein the data is extracted using data manipulation practices.

### Claim 18 (depends on 11)

The method of claim 11, wherein the analysis model comprises a decision tree model, a classification model, or a clustering model.

### Claim 19 (depends on 11)

The method of claim 11, wherein the data is extracted using a regular expression.

### Claim 20 (depends on 19)

The method of claim 19, wherein the regular expression includes a sequence of characters that define a search pattern.