IIoT Sensor Crosspoint Switching for Multi-Sensor Data Collection
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Solution Overview
Problem
Heavy industrial environments face challenges in data collection and utilization due to the complexity of dealing with data from multiple sensors, limiting the effectiveness of 'smart' solutions for optimization and diagnosis.
Innovation Solution
The implementation of methods and systems for continuous ultrasonic monitoring, cloud-based machine pattern recognition, on-device sensor fusion, self-organizing data marketplaces, and AI training based on industry-specific feedback, along with distributed ledgers and self-organizing data collectors, to enhance data collection, processing, and utilization at the edge and in the cloud.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If data is collected by human beings using dedicated data collectors and recorded on media for later analysis, then data can be collected and stored, but the data collection process is time-consuming and returns results on a time scale of weeks or months
Solution Approach 1:
The patent replaces manual data collection and analysis processes with automated electronic systems. Sensors continuously collect data and transmit it via communication networks to remote servers for automated analysis, eliminating the need for human data collectors and media recording. This substitution of mechanical/manual processes with electronic automation dramatically reduces analysis time from weeks/months to near-real-time.
Solution Approach 2:
The patent introduces communication networks and remote servers as intermediaries between sensors and analysts. Data flows from sensors through communication networks to remote servers for processing, enabling continuous data collection and analysis without human intervention at the collection point. This intermediary infrastructure allows rapid data transmission and processing, reducing the time loss associated with manual collection and analysis.
2Adaptability or versatility
If the range of available data is limited in industrial environments, then system complexity is reduced, but smart solutions become less effective for optimization and diagnosis
Solution Approach 1:
The patent implements a universal data collection framework where multiple sensor types (vibration, temperature, pressure, flow, etc.) can be integrated through a common communication network infrastructure. This multi-functional system allows diverse industrial parameters to be collected and analyzed together, enhancing the effectiveness of smart solutions by providing comprehensive data from various sources simultaneously.
Solution Approach 2:
The patent segments the data collection system into independent sensor units that can be distributed throughout the industrial environment. Each sensor independently collects specific parameters and transmits data through the network. This segmentation allows flexible expansion of data availability by adding individual sensors as needed, thereby improving smart solution effectiveness without requiring complete system redesign.
3Reliability
If data from multiple sensors is collected, then monitoring capability is improved, but the complexity of dealing with data increases
Solution Approach 1:
The patent introduces remote servers and communication networks as intermediaries to manage multi-sensor data. Instead of requiring local processing of complex multi-sensor data, the system transmits raw data from multiple sensors through communication networks to centralized remote servers that perform the complex analysis. This intermediary approach maintains high monitoring capability while reducing local data handling complexity.
Solution Approach 2:
The patent extracts the complex data processing function from the local sensor systems and relocates it to remote servers. Sensors are simplified to only perform data collection and transmission, while the complex tasks of data integration, analysis, and interpretation are extracted and performed remotely. This separation reduces device complexity at the sensor level while maintaining comprehensive monitoring capability through remote processing.
Data Source
AI summary
The system generally includes a crosspoint switch in the local data collection system having multiple inputs and multiple outputs including a first input connected to the first sensor and a second input connected to the second sensor. The multiple outputs include a first output and a second output configured to be switchable between a condition in which the first output is configured to switch between delivery of the first sensor signal and the second sensor signal and a condition in which there is simultaneous delivery of the first sensor signal from the first output and the second sensor signal from the second output. Each of multiple inputs is configured to be individually assigned to any of the multiple outputs. Unassigned outputs are configured to be switched off producing a high-impedance state. The local data collection system includes multiple data acquisition units each having an onboard card set configured to store calibration information and maintenance history of a data acquisition unit in which the onboard card set is located. The local data collection system is configured to manage data collection bands.