Th. M. Wolbank

Combination of signal injection and neural networks for sensorless control of inverter fed induction machines

For mechanical sensorless control of inverter-fed induction machines, a satisfactory performance at low speed down to zero fundamental frequency can so far only be achieved by evaluating inherent saliencies of the induction machine. Similar to other sensorless methods based on signal injection, the resulting control signals of the indirect flux detection method by on-line reactance measurement is influenced by every saliency, for example, the saturation based, the slotting, and the anisotropy saliency as well as by load and flux level. Since these influences are extremely dependent on the machine design, they can hardly be calculated in advance and removed by filtering or digital signal processing. However, the possibility of utilizing a neural network for learning the individual dependencies and removing the unwanted influences can provide a very satisfactory result. Since the easy implementation of a neural network does only use a small amount of calculation power, the algorithms can be implemented even in low-cost signal processors. Measurements on mechanical sensorless controlled induction machines present adequate results up to about rated load, depending on the transient electrical behaviour, and with this on the design parameters of the induction machine.

Evaluation and current-response based identification of insulation degradation for high utilized electrical machines in railway application

The demand for condition monitoring systems to prevent a breakdown of electrical machines is continuously increasing. A failure or collapse of the insulation is one of the main reasons for a machine outage, both in the field of high-voltage machines as well as low voltage. Especially at inverter-fed motors, several kinds of stresses due to parasitic phenomena exist and cause decrease of the insulation lifetime. With the method proposed, the evaluation of the stator insulation health condition of inverter-fed motors is possible by analyzing the current sensors transient response after inverter voltage step excitation. The analysis of the transient signal portion gives evidence of a possible change in the insulation system by comparison of the characteristics with the known pattern of the healthy machine transient signal portion. Tests are performed on a 1.4-MW induction machine designed for traction applications. By the availability of taps accessible on the machine terminal, different scenarios to emulate winding insulation degradation are conducted. Additionally, in order to investigate insulation degradation characteristics of the used insulation materials, accelerated aging procedures are applied on specially manufactured stator slot models with form-wound coils. These stator test segments have been aged by different accelerated aging cycles until the failure of the insulation is determined by voltage exposure tests. With additional nondestructive diagnostic measurements, e.g., dissipation factor

Monitoring of partially broken rotor bars in induction machine drives

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Insulation monitoring of three phase inverter-fed AC machines based on two current sensors only

, capacitance, the correlation between these indicator values, the results of the proposed method, and the degradation of the insulation strength until a breakdown are investigated.

Analysis of current reaction on inverter-switching to detect changes in electrical machine's high-frequency behavior

Detection of rotor bar asymmetries in induction machines operated by an inverter can be difficult due to disturbances introduced by the fast switching power devices. Furthermore interference of the fault indicator with control dynamics of the load level lower the accuracy of most detection methods proposed. These disturbances can be avoided if the detection can be realized at standstill of the drive using the inverter as a measurement device. In this paper the sensitivity of a method is analyzed that enables the detection of rotor bar defects at zero load and around standstill. The method is based on the excitation of the machine with voltage pulses generated by the switching of the inverter. Measuring the resulting response of the machine phase currents, the spatial distribution of the transient inductance can be identified with high accuracy. An asymmetry in the rotor bars leads to a distinct change in the spatial distribution of the transient flux linkage and thus also of the transient inductance. The accuracy is such that even partial broken bars can be detected. Measurements on a machine with a specially manufactured copper rotor cage are presented. The resistance of a single bar is stepwise increased by changing the material of the bar from copper to aluminum, brass, and finally steel. It is shown that even the stepwise increase of a single bar resistance before the bar is broken can be clearly detected. It is thus possible to monitor the machine even for a developing rotor defect.

Online detection of insulation degradation in inverter fed drive systems based on high frequency current sampling

The demand of monitoring systems to prevent a breakdown of electrical machines is continuously increasing. Regarding economic issues, usage of system resources and additional components to establish monitoring is restricted. With the method proposed, the evaluation of the stator insulation condition of all three phases is possible using only the two current sensors already available in modern drive systems. The analyses of the transient part of the current response to voltage step excitation give evidence of a possible change in the insulation system. The degradation of the insulation health state is linked with a change in its capacitance, which in turn influences the electrical high frequency properties of the machine and as a consequence the transient part of the current signal resulting from a voltage step. To enable the monitoring of the phase with the missing sensor, a simple summation of all measured currents does not deliver enough accuracy for insulation monitoring. The non-measured phase however, can still be monitored by a special excitation sequence and signal processing without significant deterioration of sensitivity compared to the results if a sensor is available. Further, the influence of temperature and moisture on the proposed method is analyzed.

Analysis of rotor fault detection in inverter fed induction machines at no load by means of finite element method

Adjustable Speed Drives (ASD) are the favorable choice in a fast increasing scope of applications. Although generally highly reliable, continuous condition monitoring of electrical drive systems becomes more and more important, as the adoption of such systems in safety critical applications, like x-by-wire and in the so called more electric aircraft, increases. To fulfill the demand of high efficiency and good return on investment the different drive components are operated at or near their rated values. This fact and additional stress added due to high dynamic operation, fast switching of modern power electronics like IGBT lead to increased risk of drive breakdown. In many applications this is completely unacceptable and has to be compensated by preventive maintenance, fault tolerant operation or continuous condition monitoring and detection of faults in an early stage. A variable speed drive basically consists of three main components - the inverter, the cabling and the machine itself. These components - including their parasitic elements - form a complex impedance system. The proposed method evaluates the transient current reaction on inverter switching. A change in this reaction is correlated to a change in the mentioned complex impedance system, e.g. resulting from degradation of the insulation system. Application of high-frequency current sampling and further signal processing allow a very accurate monitoring of system parameters and even small changes in magnitude and location can be detected. Experimental results proof the applicability of the proposed condition monitoring technique.

Using oversampling techniques to extract ac machine saliency information

The electrical part of modern drive systems usually consists of different components like power electronics, cabling, windings. Each of these components is usually operated at or near its rated values. In addition, high dynamic operation, overload cycles, as well as the fast switching of the power devices puts additional stress on all drive components. As a consequence overall reliability is reduced. Especially in security critical applications a continuous monitoring of the different components is thus necessary. In order to detect possible defects in an early stage or to enable prediction of a developing fault very sensitive measurement and evaluation methods are essential. In this paper a new method is proposed to monitor the state of different drive components like windings insulation, cabling and power electronics very accurately. The method is based on the current sensors available in the inverter in combination with a high frequency sampling. Each change in the switching state of the inverter leads to a transient voltage excitation of the electrical system consisting of power electronics, cabling, machine windings, leading to a step response of the machine current. Assuming a sufficient high sampling rate of the current, the characteristic features of the step response like eigenfrequency, damping rate and steady state value can be calculated and compared. Each of these characteristic values is influenced by the inductances, capacitances and resistances of the system. If for example the inter-turn insulation deteriorates the capacitance changes before the actual breakdown leading to a change in the mentioned characteristic values. Measurement results are presented to verify the applicability to detect changes in the phase winding capacity.

Separation of fundamental wave and transient components of the current signal for machine insulation state monitoring

This paper analyzes a new method for detecting defective rotor bars at zero load and standstill by means of modeling using the finite element method (FEM). The detection method uses voltage pulses generated by the switching of the inverter to excite the machine and measures the corresponding reaction of the machine phase currents, which can be used to identify a modulation of the transient leakage inductance caused by asymmetries within the machine. The presented 2D finite element model and the simulation procedure are oriented towards this approach and are developed by means of the FEM software ANSYS. The analysis shows how the transient flux linkage imposed by voltage pulses is influenced by a broken bar leading to very distinct rotor-fixed modulation, that can be clearly exploited for monitoring. Simulation results are presented to show the transient flux paths. These simulation results are supported by measurements on a specially manufactured induction machine.

Sensitivity analysis of insulation state indicator in dependence of sampling rate and bit resolution to define hardware requirements

Controlling an ac machine without speed or position sensor at zero frequency requires the extraction of its inherent or engineered saliencies. This extraction is currently linked to injected high frequency or transient test signals that are superposed to the fundamental wave. These test signals also affect noise emission, maximum inverter output voltage, and switching frequency. Different methods for an integration of the test signal injection into the fundamental wave excitation have been made, however a full integration in all operating states is still not possible. In this paper a method to extract the necessary saliency information without applying test signals is proposed and analyzed. It is based on oversampling techniques and uses the information that appears in current sensor signals during the switching transients. Different realizations are presented and their performance compared with respect to changes in the operating parameters. It is shown by measurement results that applying the proposed techniques it is possible to obtain the saliency information necessary for speed sensorless control.