Michal Orkisz

Integrating hundred's of products through one architecture - the industrial IT architecture

During the last few years, software product line engineering has gained significant interest as a way for creating software products faster and cheaper. But what architecture is needed to integrate huge amounts of products, from different product lines? This paper describes such an architecture and its support processes and tools. Through cases, it is illustrated how the architecture is used to integrate new --- and old --- products in such diverse integration projects as vessel motion control, airport baggage handling systems, pulp&paper and oil&gas, in a very large organization. However, in a large organization it is a challenge to make everyone follow an architecture. Steps taken to ensure global architectural consistency are presented. It is concluded that a single architecture can be used to unify development in a huge organization, where the distributed development practices otherwise may prohibit integration of various products.

Slip estimation of a large induction machine based on MCSA

This paper presents a newly developed algorithm for a large induction machine rotor slip estimation. The proposed algorithm is based on spectrum analysis of the stator current. The main idea is to find the best fit of spectrum components to the operating parameters. Motor slip is the result of the presented algorithm. Numerical calculations show that the method yields very accurate results and can be an important part of machine monitoring systems. Specially the presented method successfully deals with the slip estimation of a large machine with relatively small slip, for which very often standards methods may fail.

Determination of peak locations and amplitudes for automated interpretation of spectra

Exact determination of the position and magnitude of peaks in a spectrum is essential to interpreting a spectrum, especially for automating the process. Algorithms such as FFT provide values at regular intervals, whose spacing is determined by the length of the acquired signal. If the time-domain signal length does not contain a whole number of periods, the peak position falls between two spectral values. Neither the exact position nor the amplitude are apparent from the spectrum. A method is presented here for computing a correction to both the location and the amplitude of the local maximum in the spectrogram to significantly improve the estimated location and frequency of the peak location. The computational complexity is constant time per peak, thus it can be employed in low computational power and embedded systems. Corrections for signal length and zero-padding are also included. Examples of the application of this method are presented and its accuracy vs. other methods is discussed.

Practical Approach to Condition Monitoring of MV Drives

In modern plants one encounters a combination of very intelligent assets, traditional simple but critical assets, as well as access to process control and automation system. All existing information should be combined in order to optimize life cycle management of assets and thus to reduce maintenance costs and improve process/asset performance. This need determines some basic features of modern condition monitoring systems. Large drives are frequently used to power critical equipment, thus maintaining them in good running order is essential. In the process of performing their control function, drives collect and produce large quantity of data, which can be used in condition monitoring context.

Visual modeling of condition monitoring systems

In this paper a graphical approach for Condition Monitoring Systems (CM) based on Model Driven Architecture is presented; in particular, the software application “Smart Monitoring Agent” or SMA. This graphical approach starts from the idea of modeling, applying and visualizing non-hierarchical relations. The presented method makes use of well-defined data models that take the solution to a superior level of configurability, using only graphical tools. Finally it is explained how this approach enables the flexible knowledge exchange between condition monitoring experts and software engineers.

Selected data analysis techniques for equipment monitoring using drive's control signals

Variable speed drives are becoming the method of choice for powering AC motors in many industrial applications. They allow for flexible speed control, substantial energy savings, and reduced stress during motor start-up, all of which lead to lower lifecycle costs for the shaft line. Modern drives, in order to perform their controlling function, are equipped with sensors, hardware and software to measure or compute a number of signals (for example, current, torque, speed, frequency, power, flux, etc.). This data is available and can be used for diagnostic purposes. These signals can be analyzed for their spectral content, used for monitoring the operating point, for examining cyclic processes, etc. The data is freely available, but the format, quality and quantity are determined by the hardware. Furthermore, variable speed drives change the output frequency to follow desired process parameters. This work presents selected methods for handling these difficulties and turning them to our advantage. Some examples of these methods application to industrial data are presented. These results prove that a variable speed drive can be a valuable source of diagnostic data not only for the drive itself, but also for the entire driven process.

Remaining useful life assessment via residual generator approach - a SOH virtual sensor concept

Based on analytical redundancy, specific set of residuals are designed to be sensitive to each component fault. The residual set may then represent as a measure of the loss of performance of the component in the system and thus, reflect the state of health of the component. The dynamic evolution of the residual can be considered as an image of the evolution of the component health, and can be modeled as the response of the component to the stress factors and the natural aging. The residual represents a degradation virtual sensor. Based on this prediction related to the various stress factors, the range of possible values of the remaining useful life (RUL) of the component can be predicted. The main contribution of the proposed paper is to present a new approach for RUL estimation based on a State Of Health degradation virtual sensor design. The range of values of the RUL can supply downstream applications for decision aids in maintenance or control. For illustration, the proposed approach was applied to the RUL prediction of actuators in a function of stress factors.

The effect of change in DC link series resistance on the AC/AC converter operation: Power converters embedded diagnostics

Nowadays health and condition monitoring of the particular elements of the industrial system is a standard requirement. This also applies to power converters which are becoming more and more critical and important parts of the automation systems. That brings an important need for the appropriate solutions for internal diagnostics methods. One of the most important elements of the voltage source converter circuit is the DC capacitor(s). In many of the proposed and available methods the health state of the DC bus capacitor is described by monitoring the equivalent series resistance. This paper presents the method for monitoring the DC link capacitor aging effects. Additionally the article examines the possibility of using the emerging changes in the frequency spectrum of the converter currents for the DC link deterioration. The results are obtained from simulations.

Analysis and remedies for torsional oscillations in rotating machinery

In the context of operation of rotating machinery vibrations are inevitable. Consequences of long-term operation under cyclic loads are often catastrophic, as the fatigue stress of machinery elements may lead to breakdowns. It is well known that the level of vibrations should be minimised either by passive design of the system or by active damping efforts. The work presented in this paper is motivated by an analysis of the problem observed at a gas compression industrial plant where observed anomalies are believed to be a common problem within the industry. The torsional vibrations observed in the compressor unit data, collected with DriveMonitor™, are subject of investigations. Such oscillations may always originate from process disturbances, however in the considered industrial case study vibrations are caused by mechanical resonance. To investigate the system behaviour interaction between the variable speed drive and mechanical system are looked into on the laboratory scale test rig. Investigations carried out there provide a valuable insight into a system dynamics. A justification of the observed signal features through physical analysis of the system is also given. The active damping of oscillations is also implemented on the laboratory hardware. The subsequent stages required during hardware implementation include data acquisition, system identification, analysis and active damper implementation. The excellent results confirm effectiveness of the implemented methodology.

Diagnostic signal analysis using distribution of frequency gaps between spectral peaks

Many monitoring and diagnostics algorithms are based on analyzing the spectra of signals, such as vibrations, electrical currents and voltages, torques, etc. Often the analysis involves determining exact peak locations and looking at relations between various peak groups, such as harmonic trains or sidebands. These relationships can be more telling than the actual peak locations. Manual examination is aided by graphic tools for plotting the spectra, with features such as harmonic and sideband cursors. Automated analysis often relies on methods such as cepstra, or autocorrelation. This paper presents advantages of using another method: histograms of inter-peak gaps. In contrast to methods that operate on the whole spectrum (such as autocorrelation), this method relies on finding a discrete number of peaks and exploring the distribution of gaps between them. In particular, a histogram of frequency differences between all peak pairs is constructed. The paper presents details of this method, discusses its strong and weak points, and provides examples of its application to actual data: vibration and acoustic signals involving bearing defects, as well as a motor supply current.