Wireless Sensing with Wireless Vibration Transmitters: Learn more about the four main drivers in the condition monitoring industry that have been pushing the need for sensors to go from wired to wireless.
Condition-based monitoring of rotating equipment assets is a proven method of managing plant reliability and safety that has been practiced for decades. Vibration monitoring is a dominant portion of that. Traditionally, vibration sensors have been installed on the machine, and hard-wired back to a central machinery protection system (e.g. vibration monitor). While reliable, this technique is expensive and therefore usually reserved for large rotating machines; typically steam-driven turbines or large combustion (gas) turbines, deemed “critical” to the plant’s operation. For less critical assets (the so-called balance-of-plant machines), such as centrifugal pumps and compressors, the business case for installing such a condition monitoring system is less clear, or even untenable. The loss of availability of such machines, however, are in some cases no less important to the safe, reliable operation of a plant. There still exists, then, a need to economically condition monitor balance-of-plant machines.
As a solution, wireless vibration sensors have been proposed for over a decade. Many commercial implementations have met with mixed results, for a number of reasons. TE Connectivity (TE) feels that technology and market forces have converged sufficiently, however, to introduce such a wireless sensor.
Industry Drivers
We see at least four drivers shaping this market space:
Driver 1: Ever-increasing demand for data by plant operators at an economical price
Driver 2: Continued electrification has dramatically improved battery performance
Driver 3: The rise of the Internet of Things (IoT) has improved digital radio performance
Driver 4: Edge computing in IoT devices further enhances wireless communications
Driver 1: Ever-increasing demand for data by plant operators at an economical price
As the march towards digitization continues unabated, one lesson that becomes clear is that the demand for data is never satisfied. Supplying this data, however, must be done economically. Condition monitoring of plant assets is no different.
Conventional installations require a multi-conductor, shielded cable to be connected to the sensor installed on the machine and run all the way back to a central machinery protection system. The total cable run length could be hundreds of feet long. Every sensor requires this. With multiple sensors, thousands of feet of cable are required. Further, to meet National Electrical Code® and local plant requirements, typically the first tens of feet of cable from the sensor at the machine is required to be installed in conduit. The remaining length back to the central station is often bundled in larger conduits or cable trays. All of this adds up to expensive labor and materials and it is not easily scalable.
Wireless sensors solve this problem. The wireless gateway is hard-wired back to a central station. But many wireless sensors are handled by a single gateway, thus eliminating the cable and conduit from the machine. Now the single cable from the gateway back to the central station is carrying data from many sensors, not just one. This is an easily scalable architecture, as the gateway can likely handle additional wireless sensors, or an additional gateway could be installed to accommodate an additional double or triple the number of sensors – a task that would be impossible to do the conventional way at the same cost.
Driver 2: Continued electrification has dramatically improved battery performance
Wireless sensors obviously require batteries to perform as expected. The most significant factor in the success or failure of utilizing wireless sensors is the battery’s performance. Having to frequently replace depleted batteries chips away at the economic business case for using wireless sensors, not to mention loss of data while the sensor is left unpowered.
Technological improvements in battery performance have not kept up with other performance improvements in electronics, until recently. The drive for electrification in the transportation sectors (electric vehicles) and aerial drones has dramatically lowered the cost of batteries and improved their performance. Lithium based batteries, still the best technology and preferred choice for wireless applications, has come down in price significantly, from about €1,200 per kWh in 2010 to about €175 per kWh in 2018. The day is not far off when operating an electric vehicle will be cheaper than operating a gas-powered vehicle. Availability of improved battery life makes operation of wireless sensors feasible economically. Going from replacing batteries every few months, to every year, to every two years and beyond suddenly makes operation of wireless sensors cost competitive with wired sensors.
Driver 3: The rise of the Internet of Things (IoT) has improved digital radio
After years of hype, anticipation, and steady uptake, the Internet of Things (IoT) seems poised to cross over into mainstream business use. The number of businesses that use the IoT technologies has increased from 13 percent in 2014 to about 25 percent today. And the worldwide number of IoT-connected devices is projected to increase to 43 billion by 2023, an almost threefold increase from 2018.
This level of uptake is both a result and an impetus of the developing technologies that underpin the IoT. For one, technological advancement means that IoT technology will become easier to implement, opening the door for a wider variety of companies to benefit from IoT applications. Indeed, although large enterprises began to invest their sizable resources in IoT technologies years ago, the beneficiaries of this latest wave of IoT maturity will be small and medium-size enterprises. While they may not have the means to execute bespoke implementations, they can still invest in easy-to-use IoT solutions.
For a wireless vibration sensor, a perhaps obvious application of Edge computing is calculating the FFT (Fast Fourier Transform) of a sampled vibration waveform at the sensor itself. In a conventional system, the raw vibration waveform would be sent to the central station (as an analog signal) and the FFT calculated there. With Edge computing, the FFT can be calculated in the sensor and the processed data sent back. Rather than sending back raw vibration signals, this reduces bandwidth overhead and usage of battery power. But this is only a simple example. Ultimately much more computing could be done at the sensor. Given the appropriate algorithms, the sensor could “learn” about the machine it is installed on and when it is running well and when it is not. The building blocks are in place for a truly smart condition-monitoring vibration sensor.
LoRaWANTM is emerging as the most promising of the low power wide area networks (LPWANs) available.
Utilizes sub-gigahertz unlicensed radio spectrum
Ultra-low power that extends battery life
Long range between sensor and gateway (5 km or greater depending on local conditions)
Flexible deployment and able to penetrate deep in mixed environments
Allows data to be sent asynchronously (only sent when necessary), further extending battery life
Driver 4: Edge computing in IoT devices further enhances wireless communication
Many years ago, Gordon Moore famously predicted that performance in digital devices would double approximately every 18 months (known as Moore’s Law). This prediction has generally held true, to the point where there is now tremendous computing power in the palm of your hand, or in your wearable device (e.g. smart watch). This has enabled Edge computing; the ability to process data at or near the end of the network (the “edge” of the network), rather than send that data in raw form all the way back to a central station to be processed there.
Technological advancements have enabled embedded devices to communicate with sensors and other assets in a simple, effective and cost-effective way. Thanks to embedded software platforms, these devices can collect data and transfer them via the Internet: these are typical functionalities of IoT gateways. The role of cloud computing and cloud-based data centers is crucial here: they provide remote connectivity to and remote management of OT infrastructures and a place for data storage and analytics to trigger important business decision. Nonetheless, cloud computing has three main limits: latency, connection and costs.
Mission-critical applications require hundreds or thousands of parameters to be constantly monitored, thus generating increasingly larger data flows to be sent to the cloud. Response time from data centers has been reduced with technological advancements, but it could be not sufficient for some applications that require immediate feedback.
Connection issues may arise in some IoT applications. Imagine you have to manage a fleet of locomotives equipped with sensors and intelligent devices that constantly send data about the vehicle status and position. During the journey, vehicles can travel across mountain or remote areas where Internet connection is bad, or even areas without Internet. Devices must keep managing those insights and provide response to trigger critical issues or malfunctions even without remote support.
The number of intelligent devices and smart sensors is constantly increasing: maintaining such device infrastructures is becoming more and more expensive, due to the fact that huge amount of data have to be transferred to central data center via the Internet. Bandwidth-related costs can be even higher in cellular networks. Moreover, data coming from the field could have not been filtered at the source, thus loading data centers with unnecessary and redundant information.
Edge computing is the ability to provide secure computing and storage capabilities at the edge along with data analytics, filtering, aggregation, routing and device management in the field. Edge computing provides advanced management functionalities where data is produced, thus reducing latency, connection issues and infrastructure costs. Integration with cloud platforms becomes an additional feature for a more complete, end-to-end infrastructure management.
About TE Connectivity
With these market drivers at play, TE Connectivity designed the model 8911 wireless proof of concept vibration sensor. The 8911 satisfies plant operators demand for machine condition data, with an easily scalable wireless architecture. With a built-in LoRa™ radio and using the LoRaWANTM protocol to communicate back to a wireless gateway, the 8911 achieves up to a 10-year battery life depending on the sampling rate. The 8911 can be installed in a complex plant environment with little worry about signal integrity issues; and Edge computing ability to calculate processed machine data. The 8911 wireless vibration sensor is the condition-monitoring sensor you need for your 21st Century plant.
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