Maciej Orman

A signal processing approach to bearing fault detection with the use of a mobile phone

According to statistics, bearings are the most often failing elements of low voltage motors. At the same time diagnostics of rolling element bearings constitutes a well-established part of the rotating machinery condition monitoring domain. In many cases however the cost of installing a high-end accelerometer based bearing condition monitoring system, which is currently the most common approach in the industry, might be difficult to justify on non-critical machinery due to potentially long payback period on the investment. This text investigates the possibility of performing condition monitoring of rolling element bearings based on acoustic signals recorded by a standard, easily accessible mobile phone. The main difficulty in using mobile phone-embedded microphone for rotating machinery diagnostic purposes is the fact that the frequency response of the mobile phone microphone is very poor below 200Hz. The results presented in this text seem to indicate that with an appropriate signal processing approach, it is possible to indicate the presence of faults in the bearings.

Usage of acoustic camera for condition monitoring of electric motors

The paper presents a method of analysis of electric motors based on acoustic measurements. Acoustic signals were measured by microphones arranged in circular shape array called acoustic camera. Measurements by acoustic camera allow localization of sound source and by that separate sounds of interests from background noise can be obtained. Typically acoustic camera measurements are accompanied by a photography associated with acoustic measurement scene which is used for mapping of sound sources on the monitored area. As a reference, acoustic analysis is compared with vibration measurements. Vibration signals were measured by piezoelectric accelerometers and data collector dedicated for condition monitoring of electric motors. As presented in the result section, acoustic analysis appears as a valuable technique for condition monitoring of electric motors even in noisy industrial environment.

Condition monitoring of electric motors based on magnetometer measurements

Using micro-sensors in industrial applications is of great interest due to their small size, low-cost and little power consumption. However, the harsh environmental conditions encountered in an industrial environment have so far hindered the widespread use of, for example, MEMS-based sensors. Such sensors are particularly suited for mobile condition monitoring of industrial machinery as short time placement and operation of these sensors is typically unproblematic for many monitoring applications. In this paper we use a miniature triaxial geomagnetic sensor for condition monitoring of low voltage motors. The performance of the magnetometer is studied under conditions encountered in industry. Furthermore the magnetometer is used to measure magnetic fields of an electric motor in a healthy state and in case of a broken rotor bar. By frequency analysis of this data it is demonstrated that the magnetometer measurements can be employed to distinguish between these motor conditions.

Bearing fault detection with the use of acoustic signals recorded by a hand-held mobile phone

It is well know that bearings are the most often failing elements of electric motors. Percentage of bearing failures vs. other failures is even more significant for the case of low voltage motors. At the same time diagnostics of rolling element bearings constitutes a well-established part of the rotating machinery condition monitoring domain. In many cases, however, the cost of installing a high-end accelerometer-based bearing condition monitoring system, which is currently the most common approach in the industry, might be difficult to justify on non-critical machinery due to potentially long payback period of the investment. Therefore, still the very first diagnostic is often performed by human ear and the assessment of the nature of the emitted sound. Considering an example of electric motors, it is typically the abnormal or excessive sound that is first recognized by the operators as the indicator of faulty motor operating condition. This text investigates the possibility of performing condition monitoring of rolling element bearings based on acoustic signals recorded by a standard and easily accessible mobile phone. The main difficulty in using mobile phone-embedded microphone for rotating machinery diagnostic purposes is the fact that the frequency response of the mobile phone microphone is very poor (below 200 Hz) where typically the bearing fault frequencies lie. The results seem to indicate that given an appropriate signal processing approach is taken, it is possible to indicate the presence of faults in the bearings.

Low cost, hand held acoustic camera

The work described in this paper focuses on the design of a low cost, hand held acoustic camera. The novel process of creating the camera has been entirely engineered in ABB Ltd. Even though the creation of the acoustic camera with the use of 3D printing techniques may come at the cost of slightly decreased accuracy of the measurements, when compared with the commercially available solutions, however this is entirely acceptable in many applications. Additionally the costs saving related with the in-house manufacturing adds to the attractiveness of such an approach. The paper aims to present that with the advent of new technologies e.g. 3D printing it becomes possible for simple-design tools capable of delivering high quality results to be created by virtually anyone.

A novel non-invasive method for detection of static rotor eccentricity in an induction machine

This paper presents a newly developed algorithm for evaluating the health of an induction machine. The proposed algorithm allows for motor eccentricity detection on the basis of impedance spectrum analysis. The proposed method is based on a concept of performing the analysis in the frequency spectrum of the impedance for each power phase. The biggest advantage of the method lies in the fact that it exploits the information contained in both the current and the voltage signals. An experimental verification seems to be supporting the proposed method as an effective diagnostic tool for the detection of the static eccentricity of the rotor.

On the detection of missing magnetic wedges using impedance analysis

In this paper, a method for detecting missing magnetic wedges in induction motors supplied both direct-online and via variable-speed-drive is presented. The proposed algorithm is based on spectrum analysis of an impedance calculated using measured stator current and voltage signals. The main idea of proposed algorithm is to first normalize current and voltage signals in order to remove variations due to non-stationary operating conditions. Once normalized, the signals are processed to obtain the frequency spectrum of the impedance for each power phase and, subsequently, specific differences between phases are analyzed to identify faults. To verify these algorithms three induction motor cases were examined. Two were supplied direct-on-line and one supplied by variable-speed-drives. In the case of direct-online-supply one of the motors was known to be healthy and the other was known to have missing magnetic wedges while in the case of variable-speed-drive-supply one motor was known to have missing magnetic wedges. Measurements were recorded and processed using an ABB portable condition monitoring tool dedicated for electric motors. Experimental investigations show that the method successfully identifies defective cases.

Vibration, Sound and Thermal Analysis as a Condition Monitoring Methods for Electric Motors

This paper presents a comparison of different measurement techniques for condition monitoring of electric motors. Results are presented for vibration, acoustic and thermal analysis. Vibration signals were measured by piezoelectric accelerometers, acoustic by microphones and temperature data was collected by an infrared camera. Two induction motor cases were examined – healthy motor case and combination of static eccentricity with soft foot case. Vibration monitoring is a well known technique used in condition monitoring and in this work vibration measurements were used as a reference signal for assessment of the value of acoustic and thermal measurements. As presented in result section both acoustic analyses as well as thermal images appear as valuable techniques for condition monitoring of electric motors. All the measurements where conducted in an industrial environment.