Wireless Monitoring of Induction Machine Rotor Physical Variables

Abstract

Abstract:With the widespread use of electric machines there is a growing need to extract information from the machines to optimize their control systems and maintenance management.The present work shows the development of an embedded system to perform the monitoring of an squirrel cage induction motor rotor physical variables. The system comprises: circuit to acquire desirable rotor variable(s) value(s) and send it to the computer; a rectifier and power storage circuit that besides converting an alternating current in continuous also store energy for a certain amount of time to wait the motor engine shutdown; and magnetic generator that harvest energy from rotating field to power the circuits mentioned above. The embedded system is set on the rotor, making it difficult to power the system because it is rotating, problem solved with the construction of the magnetic generator eliminating the need of using batteries or collector rings and send data to the computer using a wireless NRF24L01 module. For the proposed system validation a temperature sensor (DS18b20) was used, variable known as the most important when identifying the need for maintenance and control systems. Tests were made getting satisfactory results proving the viability of using sensors on the rotor.

Fault Diagnosis of Induction Machines in Transient Regime Using Current Sensors with an Optimized Slepian Window

“…which is valid for any type of fault. For example, ρ f ault can be computed from (1), (2) and 3for the detection of rotor broken bar, mixed eccentricity and bearing faults, respectively. In the following sections the proposed approach has been applied to the diagnosis of rotor broken bars, as in [9,11,13,15,32,74], without any loss of generality.…”

“…Ensuring their proper functioning is essential to keep the production processes running [1]. Thus, the early detection of induction machine (IM) faults and the machine condition prognosis are crucial to reduce maintenance costs [2] and to avoid costly, unexpected shut-downs [3]. Fault diagnosis via the current analysis in the frequency domain has become a common method for machine condition evaluation because it is non-invasive, it requires a single current sensor, either a current transformer, a Hall sensor, or a magnetoelectric current sensor [4], and it can identify a wide variety of machine faults [5,6].…”

“…. , (2) and bearing faults generate components of frequencies f bear [20][21][22] f bear = | (1 ± k f 0 ) | k = 1, 2, 3 . .…”

“…In [27] the recursive undecimated wavelet packet transform (RUWPT) is used to isolate and to compute the RMS value of the components produced by a broken bar fault, using an extremely low sampling frequency (224 Hz) and a small number of current samples (1024 samples). Other approaches rely on tracking the evolution of the fault harmonics in the time-frequency domain, looking for characteristic patterns of each type of fault, as indicated by (1), (2) and (3); this technique allows the detection of different types of faults, even in the case of mixed faults, with the instantaneous presence of two faults, such as broken rotor bars in the presence of the intrinsic static eccentricity; as [28] states, rotor bars breakage causes the static eccentricity and it is possible that two faults occur simultaneously. TMCSA techniques have been developed in the technical literature using different time-frequency (TF) signal analysis tools [9,29], such as the discrete wavelet transform (DWT) [15,[30][31][32][33][34][35][36], the discrete wavelet packet transform (DWPT) [37], the discrete harmonic wavelet transform (DHWT) [38], the continuous wavelet transform (CWT) [39,40], the complex CWT [41,42], and the Wigner-Ville distribution (WVD) [43,44], among others.…”

Internet of things based industrial environment monitoring and control: A design approach

“…The utilized sensor for gathering the gas temperature is DS18B20, which is a precise, digital sensor, produced by Dallas Semiconductor Company and it uses a 1-wire protocol for communication with the microcontrollers. The sensor has the capability of temperature sensing and the analogue to digital (ADC) data conversion [16,17]. Its measurement range is from -55 C o to +125 C o with high precision reaches to 0.0625 C o and expanded measurement uncertainty of ±0.5 C o , however, the measured temperature value can be shown in 9 to 12 bits [18,19].…”