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J. Sens. Sens. Syst., 7, 267-280, 2018
https://doi.org/10.5194/jsss-7-267-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Regular research article
16 Apr 2018
Temperature estimation of induction machines based on wireless sensor networks
Yi Huang and Clemens Gühmann TU Berlin, Chair of Electronic Measurement and Diagnostic Technology, Sekr. EN13, Einsteinufer 17, 10589 Berlin, Germany
Abstract. In this paper, a fourth-order Kalman filter (KF) algorithm is implemented in the wireless sensor node to estimate the temperatures of the stator winding, the rotor cage and the stator core in the induction machine. Three separate wireless sensor nodes are used as the data acquisition systems for different input signals. Six Hall sensors are used to acquire the three-phase stator currents and voltages of the induction machine. All of them are processed to root mean square (rms) in ampere and volt. A rotary encoder is mounted for the rotor speed and Pt-1000 is used for the temperature of the coolant air. The processed signals in the physical unit are transmitted wirelessly to the host wireless sensor node, where the KF is implemented with fixed-point arithmetic in Contiki OS. Time-division multiple access (TDMA) is used to make the wireless transmission more stable. Compared to the floating-point implementation, the fixed-point implementation has the same estimation accuracy at only about one-fifth of the computation time. The temperature estimation system can work under any work condition as long as there are currents through the machine. It can also be rebooted for estimation even when wireless transmission has collapsed or packages are missing.
Citation: Huang, Y. and Gühmann, C.: Temperature estimation of induction machines based on wireless sensor networks, J. Sens. Sens. Syst., 7, 267-280, https://doi.org/10.5194/jsss-7-267-2018, 2018.

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We focus on the implementation of monitoring algorithms for the induction machine in WSNs. As there are restrictions on the sensor node, such as low cost, low power, weak calculation and small memory size, the algorithm should be simple and efficient. The model-based method is used for the temperature estimation algorithm development. The experiments prove that the KF algorithm implementation is suitable for real-time temperature estimation on a wireless sensor node.
We focus on the implementation of monitoring algorithms for the induction machine in WSNs. As...
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