Bit-Level Waveform Analysis for DeviceNet Fault Prediction
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Solution Overview
Problem
Existing DeviceNet network diagnostic devices have limited processing power, allowing only frame-level diagnostic information collection, which prevents real-time analysis and fault prediction, and does not provide sufficient detail for bit-level waveform validation, leading to increased maintenance costs and downtime in industrial networks.
Innovation Solution
A network diagnostic device that connects to DeviceNet and Ethernet-based networks, using high-speed analog-to-digital converters and dual microprocessors to analyze bit-level waveform parameters, comparing measurements to established criteria to identify faults and predict failures, offering real-time monitoring and detailed analysis through Individual Measurement Mode and Network Health Mode.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If frame-level diagnostic information is collected using existing diagnostic devices, then device complexity is reduced, but measurement precision and fault detection capability deteriorate
Solution Approach 1:
The patent segments the diagnostic functionality into two distinct parts: a simple passive measurement tool that collects bit-level waveform data with high precision, and a separate processing system that analyzes the collected data. This segmentation allows the measurement device to remain simple while achieving high measurement precision through dedicated hardware components like analog-to-digital converters and waveform analysis circuits.
2Quantity of substance
If frame-level diagnostic information is collected and stored in local memory, then data collection capability is improved, but real-time analysis capability deteriorates
Solution Approach 1:
The patent introduces an intermediary mechanism where collected diagnostic data is transmitted via a network connection to a remote system for analysis. This allows the collection device to continuously gather data without being overwhelmed by processing requirements, while the remote system performs comprehensive real-time analysis, effectively resolving the contradiction between data collection capability and analysis speed.
3Loss of information
If devices are taken off-line to download collected data, then data analysis completeness is improved, but downtime increases
Solution Approach 1:
The patent enables continuous diagnostic data collection and real-time networked transmission of data without requiring the device to be taken offline. The network connection allows data to be continuously analyzed in the background while the industrial network remains operational, eliminating the need for offline data downloads and maintaining continuous production.
4Measurement precision
If bit-level waveform analysis is performed, then fault detection accuracy is improved, but processing power requirements increase
Solution Approach 1:
The patent segments the processing workload by using dedicated hardware components (analog-to-digital converters, waveform analysis circuits) for data acquisition and preprocessing, then transmitting only the essential measured parameters over the network for further analysis. This segmentation reduces the processing power burden on any single device while maintaining high measurement precision through specialized hardware.
Data Source
AI summary
A network diagnostic device is provided, which comprises a passive real-time measurement tool that is useful for, among other things, expediting fault identification, isolation, and repair of a communication network or bus. The device also facilitates prediction of failures by identifying marginal operating conditions. The device analyzes data flowing through the communication network, including through an analysis of variations in bit waveform shape carried by the network physical interconnect media. In one embodiment, an implementation of the network diagnostic device is particularly useful in a DeviceNet-compatible network or, more generally, a Controller Area Network (CAN). The device identifies faults by comparing measurements made on the actual DeviceNet bus with worst-case acceptable criteria. The device interfaces with a remote monitoring computer via an Ethernet compatible medium to display parsed bit-level waveforms, network warnings and errors, as well as an overall network health index.