1. Introduction
Energy remains the fundamental requirement for the industrial and residential sectors [
1]. Global energy consumption is expected to have an alarming growth by 2030, shown in
Figure 1. Among them, the pumping system (especially centrifugal pumps) contributes the major electric loads installed around the globe, contributing ~22% [
2]. This is due to the huge availability of energy savings opportunities and various research outcomes suggested for increasing energy efficient pumping system [
3]. A review of various energy efficient enhancement centrifugal pumping systems concludes the maximum savings of approximately 5% to 50% can be achieved. This expectation can be made possible by introducing variable frequency drives with proper control methods [
4].
Due to the inevitable usage of pumps [
5], the supervision on the reliability and fault occurrence of the pumping system is highly significant. The major components of a pumping system consist of a pumping liquid, pump unit, piping, suction, and the delivery setup. The major faults include cavitation and water hammering caused due to the inefficient operation of pumps and piping arrangements in a pumping system. The commercial and industrial loads insist enhancement of energy efficiency [
6,
7] that leads to the drastically increased usage of Variable Frequency Drives (VFDs) for pumping applications. It reduces the energy consumption along with the regulation of variable flow rate demand of the pumping system [
8,
9]. Conversely, current/voltage harmonic distortions are generated by installing such nonlinear loads (VFDs).
VFDs are preferred for centrifugal pumps to enhance energy efficiency and reduce the occurrence of faults. Fault diagnosis at an early stage is identified by using vibration-based investigation methods [
10,
11]. The transient impulse of the motor bearings and rotor faults are diagnosed using wavelet transform (WT) techniques [
12]. The signal-based techniques exhibit better performance than the model-based techniques for estimating faults [
13,
14]. Advanced learning techniques involve developing algorithms that enable the drives to learn, classify between the given categories [
15,
16], and predict the future states [
17,
18]. Detection of pump faults like cavitation can be performed by using pump acoustics [
5]. The nature of individual power quality parameters varies with the change in pressure, the severity of fault, and the region of operation [
19,
20,
21]. The existing fault detection techniques involve the usage of pump parameters like flow rate and pressure to determine the occurrence of pump cavitation and water hammering; this requires additional sensors. To overcome the shortcomings of the currently available research, the experimental investigation of power quality parameters was proposed to estimate the cavitation and water hammering in a centrifugal pumping system. The change in such power quality parameters, vibration details of normal operation, and simulated fault conditions are recorded as the testing inputs for validating the performance of the study.
In this research, the effectiveness of the fault identification is performed through experimental power quality measurements in a parallel pumping system. Estimating pump defects at an early stage will help perform suitable primitive measures and significantly increase the life of the system. The cascade setup is subjected to various pressure set points, the delivery valve is maintained in a partially closed position, and the response is observed for various set pressure values. The power quality variations are voltage, current, respective Total Harmonic Distortion (THDs), power, power factor, and energy. The power quality variations were observed and recorded for the equidistant set pressure values. Also, the best operating region, in terms of energy efficiency, is suggested using the power quality results. The vibration signal and power quality measurement from the pump is used to estimate and classify faults automatically. The training data is obtained by varying the pressure from 0.1 to 0.5 bar. Also, the cascade pumping system is experimented and validated, in terms of power quality and the efficiency for set pressure, with using observed results.
The article is organized as follows. Firstly, in
Section 2, the industrial cascade pumping experimental setup and modeling equations and curves are discussed. In
Section 3, the power quality and pump vibration results are presented for a cascade pumping system during normal and abnormal conditions for fault identifications in the cascade pumping system. In
Section 4, the experimental vibration, FFT, and power quality signatures are highlighted for cavitation and water hammering. Moreover, the results portraits the significant variation in the power quality and vibration parameters for normal and abnormal pump operating region. It is followed by the conclusion in
Section 5.
3. Experimental Test with Cascaded Industrial Variable Frequency Drives Pumping System
The experimental results of motor parameters for the pressure set points of 0.1, 0.3, and 0.5 bar were recorded through the hardware interfacing platform (dSPACE and MCT 10), as shown in
Figure 5. Significant motor control parameters like speed, motor current, set reference, voltage, frequency, power drawn, and feedback (actual pressure) were monitored and recorded. From the waveform, variable speed pump (pump 1) is initiated at the beginning of the process. Since pump 1 alone is unable to deliver the required set pressure (0.3 bar), an additional pump (pump 2) is staged on to run at the rated speed. However, pump 1 starts from the minimum speed limit, and accelerates gradually to reach the pressure set point.
The valve positions can be kept either at fully or partially open condition. In the study, the valve position is maintained in the partially opened condition, and the rated voltage is applied across the point of common coupling (PCC). The experimentation is performed by taking five equidistant pressure set points: 0.1, 0.2, 0.3, 0.4, and 0.5 bar. The pressure gauge reading is monitored by the internal cascade control algorithm as it tries to reach the pressure set point. It is accomplished by varying the speed of the pump 1 and turning ON/OFF pump 2 and pump 3. For waveform analysis purpose three pressure levels—0.1, 0.3, and 0.5 bar—are considered. The operational state (ON/OFF) of the motor–pump is defined in
Table 2. Pump 1 alone operates at a lower pressure set point of 0.1 bar, and pumps are added into operation when the pressure set point increases.
When the available net positive suction head value (NPSHA) is lower than the required net positive suction head value (NPSHR) the centrifugal pump exhibits cavitation. The NPSHR was provided by the pump manufacturer, and the NPSHA is calculated from pump system parameters like friction loss, atmospheric pressure, and static head. The water hammering occurs whenever there is a sudden increase in pressure change, i.e., sudden closure/opening of valves that causes severe damage to the pipes. To realize water hammering in the real-time experimental setup, electric valve actuators in the delivery side were used. These electronic controlled valves have a much smaller time constant for the sudden closure of the valve and opening at the same to induce water hammering in the pumping system. In this research we have not considered the fault condition with both water hammering and cavitation at the same instant, and the vibration measurement details are provided to confirm that the pump and piping systems are operated safely when realizing water hammering.
4. Experimental Power Quality Signatures
The effectiveness of the proposed methodology is calibrated by testing a practical industrial pumping setup with variable speed drives. The results and inference obtained for various operating pressure are plotted for estimating the pumping parameters. Power quality is the capability of electrical equipment to operate in the preferred region without influencing the operation of adjacent equipment connected to the common electrical bus. As the pumps in industry are put into service, the variations in loading/demand cause voltage fluctuations. Hence, for various pressure values (0.1, 0.3, and 0.5 bar) the instantaneous measure of three-phase voltage and current has been observed through WinPQ software (PQBox-200), as shown in
Figure 6. The power drawn by the pump driven by VFD is at its maximum when it is operated at a low-pressure set point (say 0.1 bar). When other pumps are staged at higher set pressure (for 0.3 bar) the contribution due to variable speed pump (pump 1) is lower. The contribution of pump 1 still reduces when the pressure set point is further increased to a higher value, i.e., 0.5 bar (see
Table 3).
When the primary VFD-operated pump is not sufficient to produce the required set pressure additional pumps are turned ON, with the VFD-controlled pump put back to its minimum operating speed. During such a transition of pumps, the steady-state voltage value remains unchanged. The total current drawn by the cascade pump setup experiences a spike for a momentary period when the additional pumps are added. The power factor during steady-state conditions reduces when the pressure reference increases from 0.1 bars to 0.5 bar. As the load on the pump increases when the pressure is set to 0.5 bar from 0.1 bar, the energy consumed and power drawn also increase. The power drawn during full load capacity fluctuates less when compared with the power drawn at a pressure at 0.1 bar. The steady-state current THD in
Table 4 is found to be reducing desirably as the pressure reference increases. For the pressure set values of 0.1 bar, 0.3 bar, and 0.5 bar the current THDs attained are in the range of 100, 25 to 30, and 10 to 20 percent, respectively. The shape of the current drawn in
Figure 6 becomes sinusoidal from nonsinusoidal as the loading of the pumping setup is approached towards its maximum capacity. Thus, when the pumping setup is operated near to its full load capacity, the current THD reduces.
The harmonic spectrum obtained through experimentation shows that the mentioned harmonic orders are having higher magnitudes. Among them, the 5th harmonic remains dominant, as shown in
Figure 7. The harmonic orders for the six pulse VFDs (Diode Bridge) are expressed through Equation (6).
The vibration meter (VIB-15) was mounted on the pump impeller casing to acquire the vibration details (i.e., acceleration, velocity, and displacement) of the centrifugal pump. The sensitivity of acceleration, velocity, and displacement for the vibration meter is 0.1 g, 0.2 mm/s, and 10 microns, respectively. The input signals are recorded through a 24-bit analog input channel at a sampling rate of 70 kHz. An FFT analysis of the acceleration signal was performed to attain the time–frequency pattern. The study is performed for various operating points with normal and faulty conditions as shown in
Table 5. The vibration and FFT signal of the normal defect-free pump and water hammering is noisy when compared with the normal defect-free pump, as shown in
Figure 8.
Various power quality parameters measured for the pressure setpoint of 0.5 bars under normal defect-free condition were recorded as shown in
Figure 7. The measurements are repeated 10 times and the average value is taken to ensure recording accuracy. The error tolerance and uncertainty of fault detection are restricted to 5%. The faults are simulated in the real-time pumping setup, and the test data (voltages, currents, pressure, flow rate, and speed) is obtained for different pressure set points. The Root Mean Square (RMS) voltage and current, power drawn, voltage THD, current THD, rotational speed, pressure developed, and flow rate for normal and faulty cases have been recorded. The power signatures for cavitation condition at input side of the drive (Element 1, Element 2, and Element 3) and input of the pump–motor set (Element 4, Element 5, and Element 6) are shown in
Figure 9. Similarly, the power signature for water hammering condition is shown in
Figure 10. The classification/grouping of test data can be performed among the classes that have various attributes and a target function.
The outline of all the measured power quality readings (minimum, average, and maximum values) for the different pressure set points are provided in
Table 6. The seven significant power quality parameters considered for the analysis includes voltage, current, kW, kVar, power factor, voltage, and current THD. The voltage range across the PCC varies from 406 V to 410 V, where voltage deviation from the nominal value is less for higher pressure set points. The voltage drops gradually when the pressure set point is significantly less compared to the rated capacity of the cascade pumping setup. When loading of the pumping setup increases (from 0.1 bar to 0.5 bar), the power drawn by the system increases gradually. Whereas, the power factor of the system is better for the lesser loading conditions (i.e., 0.1 bar) when compared with the rated capacity of the setup.
5. Conclusions
The article discusses the real-time simulation of harmful pump operations (i.e., cavitation and water hammering) of centrifugal pumping systems and compares them with the normal operating conditions. Furthermore, the classification of faults and prediction of preferable pump operating points in a pumping system was performed from the experimental power quality measurements. An industrial parallel pumping system was considered for experimental validation, and the unique power quality signatures obtained for water hammering and cavitation enabled the classification of faults from the normal operating condition. The classification of faults based on the power quality pattern can be applied to the centrifugal pump-based pumping systems. The vibration parameters (such as acceleration, velocity, and displacement) show a significant difference to classify normal pump operation from the faulty conditions.
The extensive experimental study on cascade pumping system reveals that the preferable operating region enhances reliability as well as reducing the occurrence of faults. Further, this article serves as a reference for insight power quality issues in VFD pumping systems and paves the way for sensorless control. Also, the unique power quality signatures obtained from the experimental study could be used for machine-based fault classifications in future works.