Sensors have a key role in industrial production. For example, they can be used for quality and process monitoring or condition-based maintenance. The range of applications is large and is evolving even further, largely due to the increasing use of self-powered wireless sensors for the industrial Internet of Things (IIoT).

Fig.1 Energy converter for linear motion. The energy output at every actuation of the spring is sufficient to transmit 3 sub-messages. Possible applications are miniaturized switches and sensors in building technology and industrial automation.

The majority of sensors in industrial applications are hard-wired and can't be used with moving parts. Furthermore, it is difficult to use them in sealed environments, for example to measure flow, pressure, and temperature of liquids and gases. Although wireless sensors are a good alternative, powering them is an issue. Batteries are used but they must be carefully monitored and replaced periodically. Wireless sensors that are self-powered by harvesting environmental energy are an answer to both problems.

Energy Sources For Self-Powered Wireless Sensors

There are three main sources of energy that can be harvested for wireless sensors.

Kinetic Energy

Different forms of motion such as lateral movement, rotation, or vibration have a long history of being used to generate electrical energy using electromagnetic or piezoelectric harvesters. Electromagnetic energy is generated by changing the magnetic flux through a coil, either by moving a magnet relative to the coil or by changing the flux polarity. This type of kinetic energy harvesting is the technology of choice for mechanical switches and similar applications.

Light Energy

Fig.2 Indoor solar cells designed for use with EnOcean STM sensor modules.

Light can be used to power sensors by means of miniaturized photovoltaic (PV) cells. These are well suited for applications with sufficient illumination (indoor or outdoor) and often used for sensor applications such as temperature, humidity, illumination, or CO2. Energy delivery can be scaled by adjusting the size of the PV cell based on the available space for a given application.

Thermal Energy

Energy can be harvested by using Peltier elements to convert temperature difference to voltage by means of the Sebeck effect. Although the most common use for these elements is to provide cooling when electrical energy is applied, the reverse effect — generating energy based on temperature differences — is used for energy harvesting. The output voltage of Peltier elements depends on the temperature difference and is typically very small (e.g. 20 mV for a 2 °C temperature difference). A DC/DC converter is therefore required to utilize this energy.

Process Monitoring

Fig.3 Wireless radio switches and sensors can be networked and intelligently controlled. Gateways such as KNX, BACnet, or DALI connect the components to other systems.

The aim of any business is to maximize productivity. Industrial productivity can be viewed as the ratio of the value of what is produced to the cost of the the input factors such as time, material, and personnel.

One of the most important requirements for maximizing productivity is to make sure that there is an uniterrupted flow of correctly functioning products. The greater the amount of accurate data you have about each stage of production, the more easily the process can be closely controlled, the better your chances of achieving that goal.

Data can also be used to detect aspects of a process that can be improved by making appropriate changes.

Key to accumulating the relevant data is to have sensors that measure as many of the process variables as possible. The variety of parameters to be monitored should include environmental factors such as temperature, humidity, and air quality; and process factors such as speed, force, pressure, and temperature.

Many of these factors are suitable for automated monitoring by sensors. In practice, however, this has not yet been fully implemented. Some of the reasons for this are the need to invest in new tools, machines, or sensors, and to train personell, as well as the costs of maintenance for the new system. All of these make it difficult to accurately predict the return on investment (ROI).

It would be ideal to have components with integrated sensors that fit directly into existing production processes, and would not require special training, nor generate follow-up maintenance costs.

Data acquisition must take place at the boundary between the tool and the workpiece. Parameters such as feed, contact pressure, surface temperature, vibration, and noise can be recorded and sent for downstream analysis. A challenge here is that the monitoring often has to be carried out at moving and/or difficult-to-access locations. The use of conventional wired sensors would thus be difficult to achieve.

Since they don't need to be hard-wired and don't require external energy sources, compact, wireless self-powered sensors are flexible and relatively easy to integrate into a production process. Since they don't use batteries, maintenance effort and cost is greatly reduced.

Condition-Based Maintenance

Fig.4 Ultra-low-voltage DC/DC converter for powering batteryless EnOcean radio modules by thermal energy.

A fundamental problem of maintenance scheduling is calculating the intervals between each maintenance visit. On the one hand, the time between maintenance visits must be sufficiently short to detect possible deviations before the occurrence of a major problem. On the other hand, maintenance is costly in terms of time, labor, and inactive machines.

A solution would be so-called condition-based or predictive maintenance, based on tracking changes over time for important parameters. A typical example of this is the regulation of the minimum depth of tread on car tires. When the depth of the treads is below the defined limit, it is time to change them.

The main difficulty in implementing condition-based maintenance is the need for continuous monitoring of the object in order to be able to reliably determine the time for necessary maintenance.

It is clear, however, that it would be very difficult to monitor all relevant data. The associated costs would be justifiable only in rare cases. However, it is possible to gain valuable information by monitoring fewer, simpler parameters.

One example is temperature, since wear often leads to higher friction, which in turn, leads to a temperature rise on the machine. Another is sound, because experienced employees can often recognize wear and tear on machines based on changing noise patterns. Vibration also plays a role, particularly in the case of rotating machines. Wireless sensors that can be directly integrated into the machine offer an excellent method for gathering this information.

Self-Powered Radio Sensors Open Up New Possibilities

It is clear that wireless sensors offer decisive advantages for various applications in production. However, these advantages have to be measured against the challenges for powering and maintaining them, particularly when used in places that are difficult to access. Increased sensor maintenance due to battery changes must therefore be carefully considered.

In the industrial sector, kinetic and thermal energy generators are of particular interest. Kinetic energy generators gain energy from movement, for example, by lateral movement (as when a switch is pressed), vibration, or rotation about an axis. Thermal energy generators use temperature differences to generate energy. Combined with a DC/DC converter, temperature differences of only two degrees Celsius can provide usable current. Since the energy produced by such generators is often low, their use requires the optimization of the entire sensor architecture to include efficient measurement methods aand energy-saving wireless solutions.

The Way to The Battery-Free Internet of Things

Wireless sensors, for example, incremental encoders to monitor voltage in rotary chucks or to monitor the tightening torque in torque wrenches are widely used today. In both cases, when changing over to self-powered sensors, the tool remains unchanged in form and mode of operation, thus enabling simple use in existing systems.

The project, Optimized Resource Efficiency in Production through Energy-Energetic Sensor Technology and Interaction with Mobile Users (ESIMA), has developed an energy-efficient compressed-air sensor that simultaneously measures pressure and flow and transmits the data by radio to a base station. The project partners, including Festo, Varta, Daimler, and EnOcean, have integrated this sensor directly into a turbine-generator unit. This can be operated directly with the compressed air used in the production process and provides the necessary energy for supplying the electrical components.

Versatile projects in the area of condition-based maintenance based on monitoring of temperature, vibration or acoustics are in the development stage. These applications are only the beginning of a series of new applications. They show that the use of energy-efficient wireless sensors offers new possibilities for better monitoring of important production parameters.

This article was written by Matthias Kassner, Vice President Product Marketing, EnOcean GmbH, Oberhaching, Hamburg, Germany. For more information, Click Here .


Sensor Technology Magazine

This article first appeared in the September, 2017 issue of Sensor Technology Magazine.

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