In my former posts, I discussed conditions for an Internet of Things (IoT) to become reality. Some of the aspects are still on a wish list. We will see the results only in several years. Nevertheless, there are already concrete developments that take the fast lane in the direction to a real IoT, for instance in the field of energy-harvesting wireless technology. The specific characteristics of this technology enable sensors and actuators to work with an unlimited source of energy harvested from the surrounding environment, making them suitable for many IoT applications where flexibility and maintenance-free operation is highly requested.
Strong power sources are temperature differences, for instance. A difference of just 1°C (1 K) is sufficient to power a wireless sensor. A temperature difference of >10o C allows the operation of more elaborate wireless sensors to monitor and report conditions. The secret behind is an optimized combination of a Peltier element and a DC/DC converter. Standalone Peltier elements only produce very small voltages of about 10 mV per degree Kelvin.
Electronic circuitry connected to this, a sensor module for example, needs a typical supply voltage of 3 V. Therefore, a DC/DC converter is needed to complement the system. An optimized oscillator already starts to resonate upwards of 10 mV input voltage. On 20 mV or more (i.e. about 2K), a useful output voltage of more than 3 V is generated. For a temperature difference of only 7K, approximately 100 μW of energy is generated.
This kind of energy-harvesting principle is particularly interesting for predictive maintenance applications in the industrial sector. In production plants, virtually every unit of industrial machinery generates waste heat. Here, we find perfect conditions for the use of thermal-powered sensors. Typically, the temperature difference between the machine’s heat and the cooler environment provides enough energy to realize a complete autonomous wireless sensor that measures and sends data twice a day. Some might now ask: only twice a day? Yes, this is sufficient for analyzing oscillation of bearings and for monitoring deviations from the normal status and irregularities of measured values. Such sensor systems achieve highly attractive scaling effects.
The measurement prevents unexpected failures and allows a better planning of changing the bearings. In that way, the maintenance intervals are extended, whereas malfunctions, major damage, and thus production downtimes are avoided. That is an important cost benefit, as only one hour of downtime in a paper plant would cost up to $7,000. In addition, the Total Cost of Ownership (TCO) is reduced as service staff is only required when the sensor reports a necessary servicing or repair.
Self-powered sensors positioned at machines can measure data from many different points where power cables or batteries would prove to be a drawback. Batteries last for only a limited time and must therefore be replaced regularly, which is sometimes impossible if the sensor is placed at a point where a change can only be done by stopping the machine. It is out of the question that this would be opposed to a monitoring system which is intended to avoid downtime. In addition, the initial installation time is significantly reduced. The self-powered sensors can flexibly be positioned at the machine. An IP gateway, which can be a plug-in receiver for instance, receives the encrypted wireless signal from the sensors and sends it to a monitoring PC — done. Altogether, such a functioning installation can be completed within 15 minutes or less.
Using energy-harvesting wireless technology, an intelligent predictive maintenance can be realized at affordable costs, even in retrofit projects. It enables the connection of a large number of battery-less, maintenance-free sensors into an IP network that processes data for intelligent and safe conditions monitoring and for a better understanding of technical systems. The best thing: This IoT application is already stepping into reality with field trials in real industrial environments.