Open-source kit supports predictive maintenance - Embedded.com

Open-source kit supports predictive maintenance

The Intelligent Condition Monitoring Box (iCOMOX) is an open-source development platform for condition-based monitoring of equipment, assets, and industrial facilities. The goal of the board is to monitor operating conditions at the equipment surface to identify potential failures and reduce the risks associated with equipment operation and maintenance. Condition-based monitoring extends equipment operating life while minimizing unplanned downtime and maintenance costs. The open-source platform thus advances the goal of Industry 4.0 automation to increase production efficiency through digital solutions.

Predictive maintenance for Industry 4.0

Predictive maintenance is a true strategy, supported by intelligent IoT sensors and embedded control solutions that offer advanced business models to create additional value between company and customer and achieve significant maintenance cost savings. Sensors can be used to monitor key equipment continuously, and production data can be recorded and wirelessly transmitted in real time to the cloud for predictive-maintenance analysis to optimize flow and enhance security. Consulting firm McKinsey & Co. estimates that effective use of predictive maintenance in factories can reduce downtime by up to 50% and save 10% to 40% on equipment maintenance costs.

Predictive-maintenance environments include a platform to model, simulate, test, and deploy the solution. The tools include industrial data integration and analysis algorithms to detect patterns in machine data and root-cause–analysis tools to determine the corrective action to be taken.

Vibration, temperature, and pressure are just some of the parameters that can indicate equipment status and identify potential failures (Figure 1). Monitoring techniques are normally used on equipment such as compressors and pumps.


Figure 1: Vibration frequency analysis for fault detection (Image: Analog Devices)

Because vibration is the most common symptom of imbalance, misalignment, and other anomalies, predictive maintenance is often based on vibration analysis of rotating machinery. Temperature sensors, meanwhile, monitor critical machine parts to detect changes in operating conditions.

Oil particle sensors monitor the level of particle contamination in lubrication systems; an increase in the number of particles can indicate machinery wear and tear. And current sensors monitor the power consumption of machine components. A typical application is monitoring the current consumption of a motor to gauge wear.


Figure 2: Predictive maintenance (Image: Bosch)

In addition to sophisticated industrial sensors, the implementation of a predictive maintenance model requires control technologies (often through production control software). The acquired data is sent to a programmable logic controller (PLC) via IO-Link or other control systems, with the aim of intelligently managing current and future machine operations (Figure 2). Let’s review the Shiratech iCOMOX board in collaboration with Arrow.

Board details

The elegantly presented iCOMOX kit provides two devices: the real board and the control hub (dongle) for SmartMesh wireless communication. The connection cable for firmware upgrade and the support structure for optimal mounting are included (Figures 3 and 4).


Figure 3: The iCOMOX kit
(Image: EE Times Europe)


Figure 4: The card (top) and the wireless hub for SmartMesh control (Image: EE Times Europe)

The platform is equipped with vibration, magnetic-field, temperature, and audio sensors (Figure 5). It provides a wide dynamic range and an exceptional signal-to-noise ratio (SNR) for vibration analysis. In addition, it enables noise-emission detection and current analysis in motors to avoid overheating. SmartMesh communication enables low-power wireless communications. The board offers the ability to configure warning and alarm levels for each sensor. A compact form factor and CE and FCC certification round out the features.


Figure 5: Arrangement of sensors and components on the iCOMOX board
(Image: Shiratech)

At the heart of the system is an Analog Devices ADuCM4050 ultra-low-power Arm Cortex-M4F processor with integrated power management through SensorStrobe technology. The MCU also has a collection of digital peripherals, SRAM and built-in flash memory, and an analog subsystem that provides clocking, reset, and power management capabilities. An analog-to-digital conversion (ADC) subsystem is provided with a 12-bit successive approximation register (SAR) ADC and a 1.8-Msps, eight-channel converter for data acquisition (Figure 6).


Figure 6: Block diagram of the ADuCM4050 (Image: Analog Devices)

The Arm Cortex-M4F processor, with up to 52-MHz performance and 512 KB of built-in flash with error correction code (ECC), offers an optional 4-KB cache for less active power and 128 KB of system SRAM with parity. The ADuCM4050 features cryptographic hardware that supports Advanced Encryption Standard (AES)-128 and AES-256 with Secure Hash Algorithm (SHA)-256 and the following modes: electronic code book (ECB), block encryption (CBC), counter (CTR), and block encryption (CCM/CCM).


Figure 7: Block diagram of the ADXL356 vibration sensor (Image: Analog Devices)

The vibration sensor is an Analog Devices ADXL356 with a low-noise microelectromechanical system (MEMS) accelerometer (Figure 7). The IC offers excellent long-term stability from –40°C to 125°C. A Bosch BMM150 three-axis magnetic-field sensor provides absolute spatial orientation and motion vectors with high accuracy and dynamics.

Infineon Technologies’ IM69D130 is a high-performance digital MEMS microphone that uses Infineon’s Dual Backplate MEMS technology to provide a dynamic range of 105 dB and output linearity of up to 130 dBSPL (Figure 8). The results are crystal-clear audio signals, extended reception distance, and sensitivity to both soft and loud signals — from whispered speech to rock concerts.


Figure 8: The IM69D130 digital microphone (Image: Infineon Technologies)

The temperature sensor used in the platform is Analog Devices’ ADT7410, with ±0.5°C accuracy and 16-bit resolution. It measures temperatures ranging from –55°C to 150°C.

The board offers data sharing and management through SmartMesh networks via the dongle and Analog Devices’ LTC5800. The LTC5800-IPM system-on-chip, with a highly integrated, low-power radio design from Dust Networks and a 32-bit Arm Cortex-M3 microprocessor, allows the SmartMesh IP networking software to be run. The LTC5800-IPM SoC integrated into the board features a chip power amplifier (PA) and transceiver so that decoupling the power, crystals, and antenna with matching circuits is all that is required to create a complete wireless node.

>> Continue reading about supported connectivity and firmware in the complete article on our sister site, EE Times Europe.

 

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