Pipeline Sensor Network Using Segmented LPRF Nodes
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Solution Overview
Problem
Monitoring of long and remote oil pipelines is challenging due to their inaccessible locations and the need for efficient, real-time data collection and communication of asset tracking information, which is crucial for business operations, environmental, and health safety reasons.
Innovation Solution
A sensor network system comprising low power radio frequency (LPRF) devices with standards-based radios, remote sensor interfaces (RSIs), and gateways that form class-based networks along pipelines to collect and transmit data on pipeline conditions, including leaks, tampering, and environmental factors, using solar power and satellite or cellular communication for external data transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional monitoring systems are used for long pipelines, then coverage area is large, but real-time data collection capability deteriorates due to inaccessible locations and transmission delays
Solution Approach 1:
The monitoring system is divided into distributed sensor nodes placed at intervals along the pipeline, each independently collecting and processing local data. This segmentation enables real-time monitoring at multiple locations simultaneously without requiring centralized access to the entire pipeline, resolving the contradiction between coverage area and real-time data collection capability.
Solution Approach 2:
Wireless communication infrastructure acts as an intermediary between the distributed sensors and the central monitoring system. This intermediary enables real-time data transmission from inaccessible pipeline locations to remote monitoring centers, eliminating transmission delays while maintaining comprehensive coverage.
2Measurement precision
If comprehensive sensor deployment is implemented, then monitoring accuracy improves, but system complexity increases
Solution Approach 1:
Multiple sensor types (temperature, pressure, flow rate, leak detection) are merged into integrated monitoring nodes that automatically process and correlate data from all sensors. This merging approach improves monitoring accuracy through comprehensive data collection while reducing system complexity by eliminating the need for separate processing systems for each sensor type.
Solution Approach 2:
The monitoring nodes are designed as universal, multi-functional units that can perform multiple measurement and communication functions simultaneously. Each node serves as both a sensor array, a data processor, and a wireless communicator, reducing overall system complexity while maintaining comprehensive monitoring capabilities.
3Productivity
If continuous monitoring is implemented, then real-time detection capability improves, but energy consumption increases
Solution Approach 1:
The sensor nodes employ periodic sampling and event-driven communication, transmitting data only when threshold violations occur or at scheduled intervals rather than continuously. This periodic action maintains real-time detection capability for critical events while dramatically reducing energy consumption compared to continuous transmission.
Solution Approach 2:
The monitoring system incorporates autonomous decision-making at each node, where sensors automatically trigger communications only when anomalies are detected. This self-service approach enables continuous monitoring of critical parameters while minimizing energy consumption by keeping nodes in low-power states during normal operation.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables continuous, real-time monitoring and event-driven data propagation along pipelines, improving response times and reducing operational costs by providing accurate and timely information to relevant parties, while ensuring network redundancy and security through multi-designation paths and solar-powered devices.
Implementation Method 1
The sensor network may be powered by solar panels
Implementation Method 2
A sensor network for monitoring a pipeline may be implemented using low power radio frequency (LPRF) devices with standards-based radios
Data Source
AI summary
A sensor network for monitoring utility power lines comprises a sensor disposed for monitoring utility power lines, the sensor capable of acquiring data related to the utility power lines and communicating sensor data; a first remote sensor interface (RSI) comprising a data communications device capable of receiving the sensor data communicated from the sensor, and transmitting data relating to the received sensor data; and a data communications device capable of receiving the data transmitted by the first RSI and transmitting data related to the sensor data directly or indirectly to a network external to the sensor network. The sensor network comprises a common designation network.