SENSORS & SENSING SYSTEMS FEATURE
risk of significant measurement spikes being missed if they occur between samples?
• In transmitting data across communication networks, there is always a chance that a data packet may be delayed, received multiple times, or lost. How significant will any of these events be to the process being analysed or controlled?
SO, WHICH IS BEST? Recovering data from sensors into IoT systems involves a balance of measurement performance, transmission speed, security, power, range and cost. Therefore it may not come as a big surprise to learn that there is no ‘best’ solution. Wired systems typically offer the best levels of resilience and speed of acquisition, but
“The inherent flexibility of IoT systems means that the required data measurements evolve over time, requiring strategies to integrate pre-existing measurement points with new ones”
ADDITIONAL CONSIDERATIONS FOR WIRELESS SYSTEMS If the digitised information is to be transmitted onwards using a wireless solution, there are other things that must be considered: • How will power be provided to the remote device? Simple devices may be able to operate from internal batteries for an acceptable period, but many wireless devices may still need cables to be laid to provide power and so not completely avoid the costs of wiring.
• How immune is the radio technology to interference? How secure are the transmissions from eavesdropping, or from malicious actors blocking signals, or impersonating devices to provide false information?
• Do the radios operate in controlled, licenced airspace, or do they use licence-free frequencies? If the latter, how is transmission to be guaranteed against accidental disruption by other systems operating in the same frequencies?
• What are the ongoing costs of the communications provision? The costs of wired systems are normally limited to the capital cost (Capex) of purchasing and installing the equipment, but many radio-based systems involve an ongoing operational expense (Opex), for example for cellular service provision.
• Can reliability be improved by adopting systems with radio diversity with the chosen technology (i.e. automatic routing of signals via multiple path options, for example as found in ‘mesh’ systems)?
• What is the working range of the wireless technology in the environment it will be installed? Theoretical ‘line of sight’ maximum distances can be significantly longer than real world ‘practical’ distances, especially if transmitters are located in buildings, valleys or underground. Similarly, environments where there is a lot of movement of large metal assets (e.g. forklift trucks) and/or water filled objects (ego human beings) can cause difficulties due to the constantly changing radio absorption, reflection and interference profile.
• What public or shared infrastructure (e.g. cellular networks) will the data have to transit across to reach its destination. How is access control performed, and data privacy ensured?
these are increasingly becoming matched by newer fieldbus-based systems. For lower speed applications, wireless systems can offer a fast and cost-effective way to add further measurement points within an existing installation, provided they are able to operate effectively within the environment in which they are operating. They can be especially useful in overlay applications, where data is recovered from select points within existing installations, and the existing systems are not easily interfaced to third party systems. Things get more complicated when considering
geographically remote data acquisition. The best technology to apply will depend not only on the factors outlined above, but also upon how many data points exist at the location. With a small
number of sensors, it may be sensible to use native radio-based sensors such as those designed for networks such as NB-IoT, LoRa or SigFox. If more sensors are present, then it is more likely that some form of input aggregating edge device, accepting inputs from all sensors but passing the resulting digitised values back through a single radio channel, will be a more effective solution. This is especially true in cases where the edge device has intelligence, enabling it to provide front end filtering and transformation of the raw sensor data prior to transmission, effectively not transmitting low value repetitive data but instead transmitting significant events which implicitly have higher value as actionable information…. but that’s another article. In many cases, the question should not be a
case of ‘either-or’. Often, the best results are achieved by mixing technologies, optimising for each measurement point as you go. Advantech offers a range of wired and wireless sensor interfaces as both standalone devices and integrated within industrial computers and gateways. Covering the full range of available technologies including hardwired, fieldbus, serial, networked and radio via LTE, NB-IoT, mesh, and LoRaWAN, the company can help determine the ideal combination of devices to deploy in any application.
Advantech
www.advantech.com
HIGH PERFORMANCE MINI SMART SENSORS
SICK has launched the W4F family of photoelectric smart sensors, with class- leading detection options and application-specific optics in the same, rugged, 16x 40 x 12mm housing. Each features SICK’s BluePilot push-turn pinpoint alignment and on-sensor status display. Resilient to bright ambient light, the versatile W4F smart sensors multiply intelligent machine integration options for almost any application, no matter how tight the available mounting space. The W4F family comprises eight sensor types, split into the Optical
Experts and Optical Standard range. Among the W4F Optical Experts is the new SICK W4F MultiSwitch with two separate switching points, together with a distance measurement output in mm. It is therefore possible, e.g. to reliably detect a pack both when it is upright or lying on its side using just one sensor, or to enable a robot arm to travel more quickly by allowing it to stop in two steps. Using distance measurement, an automated response can be designed to alert when products drift away from a pre-set detection position on a conveyor, or to measure the width of a roll of paper. Another highlight is the new foreground suppression sensor optic, capable of reliably detecting
low, flat objects less than one 1mm in depth on a conveyor, even if they are highly reflective. The W4F ForegroundSuppression sensor excels when detecting flat products, even if dark and glossy. The W4F V-Optic has a V-focused light beam, designed to achieve exceptional accuracy when detecting mirror-reflective or completely transparent products such as glass panes. Low-remission, or tiny components such as solar wafers are detected reliably, as well as objects as thin as a single fuse wire. The W4F DoubleLine upgrades SICK’s MultiLine technology adding more power and performance to
detect components that have uneven surfaces, recesses, holes, perforations, grids or grooves. Even when faced with dirt, vibrations or high temperature, the W4F is designed to self-monitor and will continue to deliver precise results even under tough conditions. The W4F Optical Standards sensors have already proven themselves in the field as space-saving
and high-performing all-rounders. The through-beam photoelectric sensor has a long sensing range of up to 8m, while the photoelectric retro-reflective sensor extends up to 5m. Together with two photoelectric proximity sensors with background suppression, the Optical Standards achieve exceptionally reliable object detection.
SICK / DESIGNSOLUTIONS
www.sick.co.uk DESIGN SOLUTIONS | MAY 2021 17
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