A Wireless On-line Temperature Monitoring System for Rotating Electrical Machine Sonia Ben Brahim, Ridha Bouallegue, Jacques David, Tan Hoa Vuong & Maria David Wireless Personal Communications An International Journal ISSN 0929-6212 Wireless Pers Commun DOI 10.1007/s11277-016-3808-5
1 23
Your article is protected by copyright and all rights are held exclusively by Springer Science +Business Media New York. This e-offprint is for personal use only and shall not be selfarchived in electronic repositories. If you wish to self-archive your article, please use the accepted manuscript version for posting on your own website. You may further deposit the accepted manuscript version in any repository, provided it is only made publicly available 12 months after official publication or later and provided acknowledgement is given to the original source of publication and a link is inserted to the published article on Springer's website. The link must be accompanied by the following text: "The final publication is available at link.springer.com”.
1 23
Author's personal copy Wireless Pers Commun DOI 10.1007/s11277-016-3808-5
A Wireless On-line Temperature Monitoring System for Rotating Electrical Machine Sonia Ben Brahim1,2 • Ridha Bouallegue1 • Jacques David2 Tan Hoa Vuong2 • Maria David2
•
Springer Science+Business Media New York 2016
Abstract Wireless communication can be a useful method to monitor the electrical machine as it provides the main characteristics of online signal processing. Our contribution in this current paper consists in studying a new system to monitor the rotating electrical machines based on wireless communication. The main objective of this system is to detect the temperature value of the squirrel cage induction machine’s rotor, using the IEEE 802.11 protocol. However, the application of wireless communication inside the rotating electrical machines is not self-evident due to the fact that the electromagnetic compatibility problems between devices isn’t obviously guaranteed. So, in order to obtain a good reliability for wireless communication, the study of the electromagnetic field inside rotating electrical machine is essential. As a first step in this paper, we are going to focus mainly on the flux effect of the rotating electrical machine through the finite element method which offers so much information on the phenomena characterizing the electrical machine operation. This method proves that the high frequency domain transmitter won’t be disturbed by the low frequency existing flux inside the machine. As a second step in this study, the proposed network system design is presented. Then, the communication protocol, the hardware design based on the transmitting chip Roving Networks (RN-171) as
& Sonia Ben Brahim
[email protected] Ridha Bouallegue
[email protected] Jacques David
[email protected] Tan Hoa Vuong
[email protected] Maria David
[email protected] 1
InnoV’COM Laboratory-Sup’Com, University of Carthage, Tunis, Tunisia
2
LAPLACE Laboratory-UMR5213, INPT, Toulouse, France
123
Author's personal copy S. Ben Brahim et al.
well as the software design are illustrated. Finally, the experimental results of the proposed system are investigated to validate its feasibility. Keywords Wireless communication Rotating electrical machines Protocol IEEE 802.11 RN-171 Monitoring Electromagnetic field Finite element method Electrical machine flux
1 Introduction Rotating electrical machines are vital and highly beneficial in the world as they generate the electrical energy used in all sectors of society. Therefore, it is essential to ensure their efficient operation [1]. The monitoring of electrical machine is important to protect motor from unexpected problems [2]. Traditionally, the monitoring system used to be dependent on the use of cables [3]. However, these cables may lead to many disturbances and faults inside electrical machine [4, 5]. To avoid such problems, wireless communication represents a solution for both diagnosis purposes and real time monitoring. Based on wireless data transmission, the research and application of radio monitoring have been on the rise in the recent years. However, in rotating electrical machine, the design of such a system has seldom been reported in literature. So, this paper presents an innovative wireless monitoring system that is to measure the local temperature sensor. This system consists of temperature sensor in the rotor of an electrical machine, computer and wireless communication module based on IEEE 802.11. The wireless communication offers a number of advantages such as a bigger design flexibility and the ease reconfiguration of electrical machines through updates [6, 7]. In fact, the protocol IEEE 802.11 is recommended for this type of application because it enables a better range from the base station, faster connection, and better security [8]. These benefits make wireless communication quite attractive to governmental organization. For the choice of the temperature value, it is mainly due to the fact that it defines the rotating electrical machine lifetime [9]. However, if applied in controlling the rotating electrical machine, wireless communication poses some difficulties because electromagnetic compatibility (EMC) between devices isn’t ensured [10] due to the geometry of the devices, the cramped space, the presence of rotating electromagnetic fields of transmitting module and the flux of rotating electrical machine [11–13]. Thus, it is necessary to study the electromagnetic field inside the electrical machine to obtain a good performance for our monitoring on-line temperature system. In fact, a synthesis on a good compromise between the transmission frequencies, the position of the sensor and the position of the transmitter will make it possible to obtain an optimal solution in term of reliability. In this context, finite element method (FEM) can be used, because it offers so much information on the phenomena characterizing the electrical machine operation [14, 15]. This paper focuses on the implementation of a wireless on-line temperature monitoring system for a squirrel cage induction machine using the wireless communication protocol WiFi (IEEE 802.11). Following the introduction, the related works are presented. Section 3 studies the effect of electromagnetic field. Section 4 outlines the proposed system structure. Section 5 displays the hardware design used for proposed system. Section 6 presents the software design. Section 7 discusses the experimental results of wireless monitoring system inside an electrical machine and demonstrate the feasibility of the communication system.
123
Author's personal copy A Wireless On-line Temperature Monitoring System for…
A study of electromagnetic wave propagation characteristics of both stationary and rotating transmitter inside electrical machine is also illustrated to prove the experimental results of wireless monitoring system. Section 8 represents the conclusion.
2 Related Work An electrical machine failure may produce interruptions on production lines, with consequences in product quality, costs and safety [1]. Online monitoring of rotary machines such as induction motors can effectively diagnose electrical and mechanical faults whose origin are in its components. Different methodologies based on current and vibration monitoring have been proposed using wavelet analysis for preventive monitoring of induction motors [16, 17]. Although, it is possible, nowadays, to monitor the state of electrical machine by analyzing its signatures applying the FEM [15], Fast Fourier Transform (FFT) and statistical indicators like neural networks, fuzzy logic algorithms [18, 19]. This technique should be defined with features of online signals to prove its effectiveness. In fact, it is not always possible to identify the type of fault affecting the machine as the analysis of those components has been considered insufficient [19]. Consequently, some alternative methods have been suggested to study the frequencies of the stator phase currents as well as the rotor speed [19, 20]. However, these studies have not considered the possible effects over the frequency magnitudes that may have happened when two of these faults occur simultaneously due to the interactions existing between electrical and mechanical components of the electrical machine, especially the rotor ones which are unattainable. So, it can be summed up that there are countless techniques for diagnosis and prognosis of specific induction motor faults, most of them performed offline, arising the necessity for a generalized technique that allows online multiple fault detection. Despite the considerable effort made in electrical machine condition monitoring, further efforts are required for the development of artificial intelligence that is still in its infancy. Hence, several studies have been realized on the electrical machine control using wireless sensor network, but without being interested in the case of rotating electrical machine [21, 22]. Based on wireless sensor network, Korkua and Lee [21] studied applying the ZigBee for real-time health monitoring of electrical machine. He demonstrated the efficiency and performance of such a system for the monitoring of electric machine in real time. However, it is often required to measure parameters on rotating components as fault detection becomes possible when a measurement parameter exceeds the normal operating range. If applied in controlling the rotating electrical machine, wireless communication poses some difficulties because EMC between devices isn’t necessarily guaranteed. One of the major difficulties comes from the transmitting module’s rotating electromagnetic field. Such a type of difficulties has been dealt through the use of the Tire Pressure Monitoring System (TPMS) which is the automobile tire pressure examination system that alarms the tire flat and the low atmospheric pressure when the automobile is at work and safeguards the traffic safety. A TPMS corresponds to a wireless radio frequency transmission between a transmitter module in each tire of the car and a fixed central receiver. The transmitter, is composed of different electronic sensors (temperature, pressure, acceleration. . .) for the detection of the tire inflation status [23]. Then a graphical display informs the driver about the required pressure and temperature variations. The transmission between the wheel units and the receiver is tricky because of the involvement of different parameters. The rotation
123
Author's personal copy S. Ben Brahim et al.
of the wheel as well as the high number of scatters and reflectors, disturb the radio link budget from the wheel units to the receiver located on the dashboard [24, 25]. In order to improve the transmission quality for direct TPMS communication, many techniques of telecommunications are implemented to reduce the data loss and key parameters affecting wireless data transmission [11]. For electrical machine, it is worth mentioning that the temperature increase over stated limits may lead to the deterioration and reduction of the engine’s lifetime. Thus, it is important to detect the temperature variation of electrical machine’s rotor by studying the temperature value. This paper presents a newly-invented wireless on-line monitoring system aiming to measure the local temperature in the rotor of an electrical machine. Given the above mentioned difficulties faced in applying the wireless communication, this study also focuses on the finite element analysis method which it is used to calculate the electromagnetic flux of induction motor based on Maxwell2D. The simulation results show the accuracy of the modeling method to analyze the influence of electromagnetic flux.
3 The Effect of the Rotating Electrical Machine Flux Using FEM The squirrel cage induction motor, is the main workhorse of the industry due to its simplicity, good operating characteristics, ease of use and low manufacturing cost. It is used in many industrial processes, converting electrical energy to mechanical energy, maximizing their efficiency minimizes the environmental impact [1]. Like any other electrical motor, it contains two main parts, namely a rotating part: a rotor and a stationary part: a stator. The rotor is connected to the mechanical load through the shaft. The squirrel cage induction motor used in this work is presented in Fig. 1. Our objective is to analyze the magnetic flux inside the rotating electrical machine. This can be achieved through the finite element method. Based on the geometry and the material properties of an electrical machine, the FEM gives detailed information about nonlinear effects of the machine. This modeling approach is able to obtain a precise and a full description of an electrical machine [15].
Fig. 1 Squirrel cage induction motor components
123
Author's personal copy A Wireless On-line Temperature Monitoring System for…
The analytical resolution of Maxwell equations is difficult. So, it would be more helpful to use the software based on the FEM method such as: Flux 2D/3D, Maxwell2D/3D, Magnet, COMSOL [26, 27] which make it possible to analyze the electromagnetic field inside electrical machine. We suggest using Maxwell2D [12]. There are three steps involved in finite element analysis [15]. • Definition of geometrical parameters and construction of 2-D model. • Definition of physical parameters such as regions, materials etc. • Construction of electric circuit model. Table 1 shows the main parameters of the simulated machine. Based on the basic definition of the electrical machine parameters, electromagnetic response for rotor rotation is simulated. Magnetic flux lines generated by the alternating current are shown in Figs. 2 and 3. In the electrical machine surface, these lines keep constant. Figures 2 and 3 show that the flux lines in the shaft have an insignificant value compared to those existing between the rotor and stator. Figure 4 illustrates the simulation results of the field distribution with color progression in the stator, the rotor and the shaft respectively. It shows that the distribution of the B field in the shaft has a low amplitude value compared to which in the stator and the rotor [12]. It is quite interesting to study the spectrum analysis of flux distribution inside rotating electrical machine. The spectrum analysis of flux distribution is shown in Fig. 5. It shows that the spectrum of flux has a low amplitude value, equal to 0.46 Wb and operating at low frequency 50 Hz [12]. The simulation results help us to demonstrate that when the speed is equal to 1500 r/s our transmitter working at a high frequency 2.4 GHz domain will not be disturbed by the existing flux placed inside the machine operating at low frequency 50 Hz [12]. The FEM analysis provides a good support to select the frequencies of the transmission and prove the transmitter location choice.
4 The Proposed Network System Structure This work aims at the on-line detection of the rotor temperature of an electrical machine. In this case, a wireless on-line temperature monitoring system, which comprises a transmitter mounted on a rotating component and a fixed receiver, is used to measure the rotor temperature. Thus, the proposed architecture for implementing the described system is shown in Fig. 6. The objective of this work is to show that the considered system for the monitoring of temperature is based on the IEEE 802.11 protocol. The choice of technology depends on Table 1 Induction machine parameters
Parameters
Values
Output power
2.27 kW
Rated voltage
110 V
Speed
1500 rpm
Frequency
50 Hz
Number of stator slots
24
Number of rotor slots
28
123
Author's personal copy S. Ben Brahim et al.
Fig. 2 Flux lines in the induction machine
Fig. 3 Flux lines in the shaft of the induction machine
services offered, and the needs of the designer network. Some parameters such as power, speed, range, cost and safety must be taken into account. In our system, high power external calculation proves non-essential advantage compared to ZigBee or Bluetooth.
123
Author's personal copy A Wireless On-line Temperature Monitoring System for…
Fig. 4 Field distribution in the induction machine
Fig. 5 The spectrum Analysis of the flux in rotating electrical machine
Furthermore, this system should be with minimal configuration and low cost. Also, the need for a user access point can be found in the IEEE 802.11 protocol. WiFi Benefits can help us the final decision to use it as a base platform in our system.
123
Author's personal copy S. Ben Brahim et al.
Fig. 6 Wireless temperature monitoring architecture
The rotating transmitter consists of the temperature sensor, the wireless transmission module, the transmitting antenna, the signal conditioning module and the power supply module. The rotating transmitter is encapsulated as a whole reliably. The temperature parameter is processed. The components of the fixed receiver are: the receiving antenna, the wireless receiving module, the display module and the data process module [12]. A second step which is the opposite direction of the monitoring is the controlling state. That consists in determining the smooth running of the electrical machine. With these two steps, our system has a bidirectional channel of wireless communication inside the electrical machine [13].
5 Hardware Design 5.1 Transmitting Chip RN-171 The hardware architecture is based on the transmitting chip RN-171. It is a standalone complete Transmission Control Protocol/Internet Protocol (TCP/IP) wireless networking module. It incorporates a 2.4 GHz radio, 32-bit Scalable Processor ARChitecture (SPARC processor), TCP/IP stack, real-time clock, crypto accelerator, power management, Central Processing Unit (CPU) and analog sensor interfaces [28]. The RN171-EK module is chosen for our system because it is very simple to implement inside the rotating electrical machine. It is also perfect for mobile wireless applications like our system due to its small form factor and extremely low power consumption. The RN-
123
Author's personal copy A Wireless On-line Temperature Monitoring System for…
171-EK is based on the Roving Networks RN-171 module. In addition, the analog sensor inputs can be used to interface the temperature sensors. Table 2 shows the detailed specifications for the RN-171 module [29]. Figure 7 shown the RN-171-EK evaluation board components [29]. The RN-171 operates in two modes [29]: • Data transfer mode (default). • Control mode. In data transfer mode, the RN171 module is essentially considered a data channel. When the module receives data via Wi-Fi, it removes the headers TCP / IP and transmits the user data to the Universal Asynchronous Receiver Transmitter (UART). By default, the RN 171 module is in data transfer mode. To switch to the control mode, a sequence must be sent to: $. Once activated the module can be configured to using simple American Standard Code for Information Interchange (ASCII) commands. Figure 8 shows an application interface for data transfer modes, and control mode [29].
5.2 LM35 This is a precise integrated circuit where the output voltage is linearly proportional to the temperature in Celsius. The advantage of LM35DZ is that it is not necessary to subtract a high constant voltage from the output to obtain the Centigrade scale. This chip requires no external calibration to achieve an accuracy of 10:04 C at ambient temperature and 8=10 C over the entire temperature range. The device draws only 56 lA voltage sources in the range 4–30 V so it has very low self-heating less than 0.1 C in still air, as it draws only 60 lA from its supply. The LM35 operates in the range 0–100 C [30].
6 Software Design 6.1 Communication Design: The Frame Structure of System Network Protocol IEEE 802.11 is a set of standards for computer communications in a Wireless Local Area Network (WLAN), developed by the Institute of Electrical and Electronics Engineers (IEEE) Local Area Network/ Metropolitan Area Network (LAN/MAN) Standards Committee (IEEE 802). The scope of these standards is to define one Medium Access Control (MAC) and several PHYsical layer (PHY) specifications for wireless connectivity for fixed or moving stations. IEEE 802.11b, is an amendment to the IEEE 802.11 wireless networking specification that extends throughput up to 11 Mbit/s using the same 2.4 GHz band [31]. Table 2 General characteristics of the RN-171 module
Parameters
RN-171
Temperature
40 to ? 85 C
Resolution
14 bits ¼ 12 lV
Conversion time
35 ls
Frequency range
2.402–2.480 GHz
Transmission rate
1–11 Mbps for 802.11b et 6–54 Mbps for 802.11g
123
Author's personal copy S. Ben Brahim et al.
Fig. 7 RN-171-EK evaluation board [29]
Fig. 8 Application interface for data transfer modes and command mode [29]
The 802.11 standard defines the frames exchanged format. Each frame consists of a MAC header, a variable length frame body and a Frame Check Sequence (FCS) , which contains an IEEE 32-bit Cyclic redundancy check (CRC). The general MAC frame format is depicted in Table 3.
123
Author's personal copy A Wireless On-line Temperature Monitoring System for…
The MAC header comprises several elds [31]: • Frame Control: consists of several subfields and ags that contain relevant information for stations in power save mode. It also includes information about the frame type, fragmentation, etc. • Duration/ID: vary with frame type, but it is usually set to the time (in s) required to complete the current transmission. • Address Fields: used to identify the source address, the destination address, the transmitting station (STA) address and receiving STA address. The contents of the address fields are dependent upon the values of the To Distribution System (DS) and From DS ags in the Frame Control field. • Sequence Control: used to number an MAC Service Data Unit (MSDU) and to identify fragments of a given MSDU
6.2 Software Flowchart of Receiver After the system initialization, a listen socket will be created. Once the listening socket is created, the receiver will be in waiting request connection status. In case of a connection, a service socket will be created. This service socket receives the data packet from the emitter over the User Datagram Protocol (UDP) or the TCP. Then, these data will be processed. After, monitoring is done on the received data by applying the algorithms defined for electrical machine, the server will display on the computer screen, the received data and all messages from the monitoring algorithms. Finally, the service will be closed. These different steps are summarized in the flowchart plotted in Fig. 9.
6.3 The Process of Sending Data The principle of operation of the transmitter is described as follows: we begin with system initialization and the acquisition of the rotating rotor’s temperature of the electrical machine. Then, the module sends a connection request to the server. In case of success, the data will be transmitted to the server in a package via the desired protocol (TCP or UDP). These steps are illustrated in the flowchart in Fig. 10.
6.4 Debugging and Programming The transmitter module RN-171 is programmed and controlled from a console with a simple ASCII command language (TeraTerm). Indeed, TeraTerm is a language used to send the configuration commands to the module via a UART interface. It also allows the display of he information transmitted from the module. For the receiver, the monitoring
Table 3 Data frame format [31] Bytes 2
2
6
6
6
2
6
0–2312
4
Frame control
Duration/ID
Address 1
Address 2
Address 3
Seq. control
Address 4
Frame body
FCS
123
Author's personal copy S. Ben Brahim et al. Fig. 9 The flowchart of server [34]
parameters of the electric machine on the computer are received from the transmitter using the Java software and Matlab.
7 Experimental Results Given the low magnetic flux on the shaft and the sufficient space provided inside it, we have placed the transmitter RN-171-EK in the shaft while LM35 is placed in the rotor. However, an auto transformer is required for the set up in order to vary the voltage, enabling the rotating velocity’s variation. Figure 11 shows the configuration performed on the RN-171 module. The measurement system components are shown in Fig. 12. The module RN-171 sends the value of the General Purpose Input/Output (GPIO) and sensor pins to the server automatically. The data arrives as 18 bytes of ASCII hex data in the format (2 bytes GPIO; channel 0 thru 7 sensor data) [32]. For wireless communication posting and UDP broadcast packets, the module shifts the reading by 4 bits resulting in a 16-bit number. The sampling of the actual voltage requires taking the 16-bit number [32].
123
Author's personal copy A Wireless On-line Temperature Monitoring System for… Fig. 10 The flowchart of transmitter [34]
The temperature values are recorded in a step of 1sec for a total of 18 received temperatures values. Thus, the received temperature curves are obtained by recording temperature values and corresponding time. Figure 13 shows the resulting string sent to the server. The received rotor’s temperature curves are demonstrated in Fig. 14. This experiment shows the possibility of both measuring a parameter inside an electric machine and sending acquired data to a receiver outside the machine using a wireless transmission. The detection of the signal means that the transmission is neither disturbed by the devices’ metal enclosure nor by the radiated electromagnetic noise of the rotating electrical motor [12]. It is observed that the higher the speed, the higher the variation temperature. As for the stationary transmitter, no variation has been noticed both inside and outside the machine, proving that the temperature variation results mainly from the antenna rotation. The detected temperature value makes it possible the rotating electrical machine monitoring since fault detection is realizable when a measurement parameter exceeds the normal operating range. An experiment proving the temperature variation was carried on. It consists in measuring the electromagnetic wave propagation characteristics in rotating electrical machine.
123
Author's personal copy S. Ben Brahim et al.
Fig. 11 Configuring the RN-171-EK module in TeraTerm
Fig. 12 Measurement setup inside electrical machine
A continuous wave signal at a frequency of 2.4 GHz was transmitted from the rotating transmitter to the fixed receiver outside electric machine. The transmitting module is located in the shaft to check whether we can detect the signal inside the motor and the
123
Author's personal copy A Wireless On-line Temperature Monitoring System for…
Fig. 13 Received frame from RN-171 placed inside electrical machine
Fig. 14 Temperature variation
effect of electromagnetic field inside the rotating electrical machine on the signal transmission as shown in Fig. 15. For this study, the experimental results are achieved by using the spectrum analyzer and locating the RN-171-EK module in the rotating electrical machine. That required an antennae connected to the spectrum analyzer [12, 33]. As shown in Fig. 16, the received power range is from 22:62 dBm at 30 to 28:49 dBm at 150 inside the electrical machine compared to 23:2 dBm in the stationary environment.
123
Author's personal copy S. Ben Brahim et al.
Fig. 15 Measurement setup [12]
Fig. 16 Received power inside rotating electrical machine [12]
So, even if the motor carcass was closed, the signal can be detected by the receiver due to the machine geometry. There is variation in the received power linked to the rotating transmitter itself added to disturbances related to the flux and the noise of the rotating electrical motor. So, to boost the monitoring system performance, it is advisable that these procedures be considered: • Locating the transmitter on the shaft. • Adopting a high carrier frequency of 2400 MHz.
123
Author's personal copy A Wireless On-line Temperature Monitoring System for…
• Installing the rotating transmitter as close as possible to the shaft so as to reduce the signal fluctuation and fading rate. • Ensuring that the transmitting antenna is placed outside the metallic stator, far from the rotor. It should also be noted that an induction motor is driven by an inverter, variable voltage, variable rotating velocity and variable frequency which may emit high frequency noise. This noise can disturb the wireless communication system. So, to improve the proposed system reliability, many studies of the electromagnetic wave propagation characteristics in rotating electrical machine are required [33]. It is worth mentioning that, in order to determine and evaluate the wireless transmission performance of a radio monitoring system, frame error statistic measurements must carried out in rotating electrical machine.
8 Conclusion The use of wireless communication for rotating electrical machine was the main contribution of this paper. The application of the wireless system helped to reduce the complexity of wired connections. This system proved to be more flexible and self-organizing with low-cost and low power consumption. In this work, an analysis and a synthesis on a good compromise between the position of our transmitter and the frequencies of the transmission would make it possible to get an optimal solution of the link budget both in term of rate and reliability. In this context, the FEM analysis was used for magnetic field study. For this study, the finite element analysis method was used to calculate the electromagnetic flux of induction motor based on Maxwell2D. The simulation results showed the accuracy of the modeling method to analyze the influence of electromagnetic flux. We noted that our transmitter working at a high frequency domain would not be disturbed by the existing flux placed inside the machine operating at low frequency. So far, the results of this work have been encouraging as the system enabled us to demonstrate the possibility of such a concept. These results, however, showed a temperature variation due to the antenna rotation. This variation represented one of the signal fading effects of the transmitter rotation. Moreover, an induction motor is driven by an inverter, variable voltage and variable frequency which may emit high frequency noise that could disturb the wireless communication system. The analysis of the FEM provided a good support to prove the transmitters location choice and select the frequencies of the transmission. Our experiment in monitoring the rotating electrical machine made the possibility of achieving much improvement. By performing more signal integrity and reliability testing, further potential development could be realized. This can even involve multiple sensors and real time diagnostic and prognostic algorithms allowing a robust health monitoring system applied simultaneously on various machines. The electromagnetic wave propagation measures allow us to locate all signal fading effects resulting from the transmitter rotation. Therefore, it is essential that we study the methods of improving wireless data transmission performance in rotating environments to avoid the variation inconvenience in order to enhance the communication system reliability and obtain optimum parameters. Acknowledgments This work was supported in part by the Innov’COM Laboratory of Higher School of Telecommunication, University of Carthage Tunisia and LAPLACE Laboratory of the National Polytechnic Institute of Toulouse France.
123
Author's personal copy S. Ben Brahim et al.
References 1. Hubert, C. I. (1991). Electric machines: Theory, operational, applications, adjustment, and control. New York: Macmillan Publshing Company. 2. Habetler, T. G., Harley, R. G., Tallam, R. M., Lee, S. B., Obaid, R., & Stack, J. (2002). Complete current-based induction motor condition monitoring: Stator, rotor, bearings, and load. In 8th IEEE international power electronics congress CIEP. 3. Tavner, P. J. (2008). Reviw of condition monitoring of rotating electrical machines. The Institution of Engineering and Technology (IET) in Electric Power Applications, 2(4), 215–247. 4. Khalid, A., & Nawaz, A. (2014). Sensor less control of DC motor using Kalman filter for low cost CNC machine. In The first international conference on robotics and emerging allied technologies in engineering (iCREATE), Islamabad. 5. Tashakori, A., & Ektesabi, M. (2013). A simple fault tolerant control system for hall effect sensors failure of BLDC motor. In 8th IEEE conference on industrial electronics and applications (ICIEA). 6. Mahulkar, V., McKay, S., Adams, D. E., & Chaturvedi, A. R. (2009). System-of-systems modeling and simulation of a ship environment with wireless and intelligent maintenance technologies. IEEE Transaction on Systems, Man and Cybernetics, Part A, Systems and Humans, 39(6), 1255–1270. 7. Larios, D., Barbancho, J., Rodriguez, G., Sevillano, J. L., Molina, F. J., & Leon, C. (2012). Energy efficient wireless sensor network communications based on computational intelligent data fusion for environmental monitoring. The Institution of Engineering and Technology (IET) in Communications, 6(14), 2189–2197. 8. Yang, Y., Marina, M., & Bagrodia, R. (2006). Experimental evaluation of application performance with 802.11 PHY rate adaptation mechanisms in diverse environments. In International conference on wireless communication and networking conferece (WCNC). 9. Ganchev, M., Umschaden, H., & Kappeler, H. (2011). Rotor temperature distribution measuring system. In 37th Annual conference on IEEE Industrial Electronics Society (IECON). 10. Pande, D. C. (1999). Electromagnetic compatibility problems in mobile communication systems. In International conference on electromagnetic interference and compatibility. 11. Leng, Y., Dong, W., Peng, S., Ge, X., Nga, G. J., & Sheng, L. (2012). Study on electromagnetic wave propagation characteristics in rotating environments and its application in tire pressure monitoring. IEEE Transaction on Instrumentation and Measurement, 61(6), 1765–1777. 12. Ben Brahim, S., Bouallegue R., David J., & Vuong, T. H. (2015). Wireless communication to monitor the rotating electrical machines. In 23rd International conference on Software Telecommunications and Computer Networks (SoftCOM). 13. Ben Brahim, S., Vuong, T. H., David, J., Bouallegue, R., & David, M. (2015). Feasibility study of wireless communication for the double fed inductin machine. In 12th International conference on fuzzy systems and knowledge discovery (FSKD). 14. Aileen, J., Nagarajan, S., & Rama Reddy, S. (2011). Detection of broken bars in three phase squirrel cage induction motor using finite element method. In International conference on emrging trends in electrical and computer technology (ICETECT). 15. Zaabi, W., Bensalem, Y., & Trabelsi, H. (2014). Fault analysis of induction machine using Finite Element Method (FEM). In 15th International conference on sciences and techniques of automatic control and computer engineering (STA). 16. Daviu, J. A., Rodriguez, P. J., Guasp, M. R., Sanchez, M. P., & Arkkio, A. (2009). Detection of combined faults in induction machines with stator parallel branches through the DWT on the startup current. Elsevier on Mechanical Systems and Signal Processing, 23(7), 2336–2351. 17. Riera, G. M., Antonino, D. J. A., Pineda, S. M., Puche, P. R., & Perez, C. J. (2008). A general approach for the transient detection of slip-dependent fault components based on the discrete wavelet transform. IEEE Transactions on Industrial Electronics, 55(12), 4167–4180. 18. Salah, M., Bacha, K., & Chaari, A. (2013). Stator current analysis of a squirrel cage motor running under mechanical unbalance condition. In 10th International conference on systems, signals and devices (SSD). 19. Gomez, F. A. J., Sobczyk, T. J., & Weinreb, K. (2015). Influence on rotor broken bar fault diagnosis of mechanical torque pulsations by means of FFT. In 10th International symposium on diagnostics for electrical machines, power electronics and drives (SDEMPED). 20. Cupertino, F., Vanna, E., Salvatore, L., & Stasi, S. (2004). Analysis techniques for detection of Induction Motor broken rotor bars after supply disconnection. IEEE Transactions on Industry Applications, 40(2), 526–533. 21. Korkua, S. K., & Lee, W. J. (2009). Wireless sensor network for performance monitoring of electrical machine. In ON north american power symposium (NAPS).
123
Author's personal copy A Wireless On-line Temperature Monitoring System for… 22. Omar, M. Q., Widad, I., Mokhtar, M., Inzarulfaisham, A. R., & Miskam, M. A. (2013). Embedded active RFID with WSN for machine condition monitoring. In IEEE conference on wireless sensor (ICWISE). 23. Brzeska, M., Pontes, J., Chakam, G. A., & Wiesbeck, W. (2007). RF Design characterization and modeling of tire pressure sensors. In The second European conference on antennas and propagation. 24. Cheikh, M., David, J., Tartarin, J. G., Kessler, S., & Morin, A. (2009). RF source characterization of Tire Pressure Monitorng System. In European conference on wireless technology (EuWIT). 25. Tartarin, J. G., Cheikh, M., Kessler, S., Morin, A., & David, J. (2010). Efficient time diversity evaluation for direct tire pressure monitoring system. In 71st Conference on vehicular technology(VTCSpring). 26. Zaabi, W., Bensalem, Y., & Trabelsi, H. (2015). Analysis of induction motor with stator winding shortcircuit fault by finite element model. International Journal of Scientific Research and Engineering Technology, 3(3), 53–58. 27. Sprooten, J., & Maun, J. C. (2009). Influence of saturation level on the effect of broken bars in induction motors using fundamental electromagnetic laws and finite element simulations. IEEE Transactions on Energy Conversion, 24(3), 557–564. 28. Microchip. RN-171 Data Sheet (2014). 29. Microchip. RN-171-EK Data Sheet (2014). 30. Liu, C., Ren, W., Zhang, B., & Lv, C. (2011). The application of soil temperature measurement by lm35 temperature sensors. In International conference on electronic and mechanical engineering and information technology (EMEIT). 31. Villegas, E. G. (2009). Self-optimization of radio resources on IEEE 802.11 networks. Thesis in Telematics Department Universitat Politecnica de Catalunya (UPC). 32. Microchip. (2014). WiFly command reference, advanced features and applications. 33. Ben Brahim, S., Bouallegue, R., David, J., & Vuong, T. H. (2015). Electromagnetic wave propagation characteristics of rotating antenna in electrical machine. In 11th International conference on wireless communication and mobile computing (WiCOM). 34. Ben Brahim, S., Bouallegue, R., David, J., Vuong, T. H., & David, M. (2016). Design and implementation of wireless sensor network node for rotating electrical machine. In The twenty-first IEEE symposium on computers and communications (ISCC).
Sonia Ben Brahim Received the B.S. degree in 2009 from National Engineering School of Gabes, Tunisia, and M.S. degree in 2011 from Higher School of Communication of Tunis (SUP’COM). Her research interests focus on mobile and wireless communications, wireless sensor network, embedded system, implementing and studying the use of wireless communication for rotating electrical machine.
123
Author's personal copy S. Ben Brahim et al. Ridha Bouallegue Received the Ph.D degrees in electronic engineering from the National Engineering School of Tunis. In Mars 2003, he received the Hd.R degrees in multiuser detection in wireless communications. From September 1990 He was a graduate Professor in the higher school of communications of Tunis (SUP’COM), he has taught courses in communications and electronics. From 2005 to 2008, he was the Director of the National engineering school of Sousse. In 2006, he was a member of the national committee of science technology. Since 2005, he was the laboratory research in telecommunication Director’s at SUP’COM. From 2005, he served as a member of the scientific committee of validation of thesis and Hd.R in the higher engineering school of Tunis. His recent research interests focus on mobile and wireless communications, OFDM, OFDMA, Long Term Evolution (LTE) Systems. He’s interested also in spacetime processing for wireless systems and CDMA systems.
Jacques David Was born in France in 1946. He received the Ph.D. degree in electronics from the University of Toulouse, Toulouse, France, in 1974 and the Doctor in Sciences Degree from the National Polytechnic Institute of Toulouse, in 1984. He is currently a Professor of electrical engineering at the National Polytechnic Institute of Toulouse (ENSEEIHT). Since 1971, he has been working at the Electronics Laboratory of ENSEEIHT and his primary interest is in the field of electromagnetic wave propagation with applications in the electromagnetic compatibility domain and wavematter interaction.
Tan Hoa Vuong Received the Ph.D. degree in electronics from the University of Toulouse, Toulouse, France. He is currently a manager in electronics department of IPST-CNAM at the National Polytechnic Institute of Toulouse (ENSEEIHT). His research interests focus on antenna engineering, microwave, radio propagation, aeronautical engineering and electromagnetic wave propagation with applications in the electromagnetic compatibility domain and wave-matter interaction.
123
Author's personal copy A Wireless On-line Temperature Monitoring System for… Maria David Received the Diploma of Engineer degree from the Technical University of Gdansk, Poland, in 1970, and the Ph.D. and ‘‘Docteur d’E´tat’’ degrees from the Institut National Polytechnique of Toulouse, Toulouse, France, in 1979 and 1988, respectively. She is a Professor and Head of the Electrical Engineering and Automatic Control Department at Ecole Nationale Superieure d’Electrotechnique, d’Electronique, d’Informatique, d’Hydraulique et des Telecommunications (ENSEEIHT), Toulouse. Her present research activities at Laboratoire Plasma et Conversion d’Energie (LAPALCE), are in the domain of the controls and observations of Multi-Converters/MultiMachines especially applied in the several embedded systems such as: aeronautic, vehicular, railway and naval
123
