Method for Detecting a Fault, in Particular an Impeller Blockage, in a Centrifugal Pump, and Centrifugal Pump

Abstract

A method for identifying a fault in an impeller blockage in a centrifugal pump includes a determining step and a calculating step. The determining step includes determining the fault frequency f.sub.r,pump of at least one fault-indicating harmonic of a motor current on the basis of a fault model, wherein the centrifugal pump has a three-phase drive motor. The calculating step includes calculating a harmonic amplitude ?.sub.f of the motor current for the at least one determined fault frequency f.sub.r,pump by transforming the three-phase motor current into a dq current coordinate system that contains currents i.sub.d and i.sub.q and rotates at the fault frequency f.sub.r,pump. A geometric sum of direct components of the currents i.sub.d and i.sub.q in the dq current coordinate system corresponds to the harmonic amplitude ?.sub.f.

Claims

1.-16. (canceled)

17. A method for identifying a fault in an impeller blockage in a centrifugal pump, comprising: determining the fault frequency f.sub.r,pump of at least one fault-indicating harmonic of a motor current on the basis of a fault model, wherein the centrifugal pump has a three-phase drive motor; calculating a harmonic amplitude ?.sub.f of the motor current for the at least one determined fault frequency f.sub.r,pump by transforming the three-phase motor current into a dq current coordinate system that contains currents i.sub.d and i.sub.q and rotates at the fault frequency f.sub.r,pump, wherein a geometric sum of direct components of the currents i.sub.d and i.sub.q in the dq current coordinate system corresponds to the harmonic amplitude ?.sub.f.

18. The method as claimed in claim 17, wherein the at least one fault frequency f.sub.r,pump is calculated based on a stator frequency of the drive motor and a number of pole pairs of the stator, in particular according to $f_{r,\mathrm{pump}}=\left(1?\frac{1}{p}\left(1-s\right)\right).Math.f_s,$ where p is the number of pole pairs of the stator, s is the motor slip and f.sub.s is the stator frequency.

19. The method as claimed in claim 18, wherein direct components of transformed currents i.sub.d and i.sub.q are ascertained using a low-pass filter, or a first-order low-pass filter, or a first-order Butterworth filter.

20. The method as claimed in claim 19, wherein the transformation into the dq current coordinate system is performed via Park transformation in accordance with: ${\underset{\_}{\stackrel{.fwdarw.}{l}}}_{\mathrm{dq}}={\underset{\_}{\stackrel{.fwdarw.}{l}}}_{\mathrm{??}}.Math.e^{-i\left({?}_{F}t\right)},$ where {right arrow over (i)}.sub.?? is a space-vector representation of the three-phase motor current in a stator coordinate system and the angular velocity ?.sub.F is calculated from the fault frequency f.sub.r,pump according to ?.sub.F=2?f.sub.r,pump.

21. The method as claimed in claim 20, wherein the transformation of the three-phase motor current into a space-vector representation in a stator coordinate system is performed by a Clarke transformation, wherein the space vector {right arrow over (i)}.sub.?? is determined by an existing control element of the pump controller, which control element carries out field-oriented control.

22. The method as claimed in claim 21, wherein a load-independent severity factor SF is ascertained based on the harmonic amplitude ?.sub.f, by forming the relationship between the harmonic amplitude ?.sub.f and the amplitude of the torque-generating component of the motor current, or the amplitude ?.sub.T of the current i.sub.q.

23. The method as claimed in claim 21, characterized in that the centrifugal pump monitors the calculated harmonic amplitude ?.sub.f and/or the severity factor SF during the running time and upon finding an anomaly in the calculated value outputs a fault message and/or triggers an intervention in the pump controller.

24. The method as claimed in claim 23, wherein the method is carried out on an integral microprocessor unit of the pump, a running time of the pump.

25. The method as claimed in claim 24, further comprising: an external central evaluation unit, and wherein two or more centrifugal pumps transmit their calculated values for the harmonic amplitude ?.sub.f and/or the severity factor SF to the evaluation unit to identify a fault.

26. The method as claimed in claim 25, wherein the central evaluation unit compares two or more of the received values with one another in order to identify anomalies and to detect a fault.

27. The method as claimed claim 24, wherein in addition to the values for the harmonic amplitude ?.sub.f and/or the severity factor SF, further operating parameters of the pump including the speed n and/or the operating point of the pump and/or a temperature value and/or the service life or running time of the pump are transmitted.

28. The method as claimed in claim 27, wherein for the comparison of the received values, the evaluation unit uses only such pumps the operating parameters of which are identical or are in a predefined range.

29. The method as claimed in claim 25, wherein the evaluation unit is a cloud-based solution.

30. The method as claimed claim 29, wherein the evaluation unit automatically generates a service task for the relevant pump when a fault is detected.

31. A circulation pump, having a three-phase a permanent magnet synchronous motor, and a microprocessor unit which is configured to carry out the method as claimed in 17.

32. A system comprising at least two centrifugal pumps and at least one central evaluation unit having a processor which is configured to carry out the method as claimed in claim 25.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0026] FIGS. 1a, 1b, 1c show different current spectrum diagrams for visualizing the fault-indicating harmonic frequencies;

[0027] FIG. 2 shows a comparison of the steady-state stator coordinate system and of the rotating dq coordinate system;

[0028] FIG. 3 shows an illustration of the dq coordinate system rotating at the fault frequency for the fault analysis;

[0029] FIG. 4 shows a block diagram for illustrating the individual method steps for fault monitoring; and

[0030] FIG. 5 shows a system diagram of the system.

DETAILED DESCRIPTION

[0031] The disclosure is concerned with a method for current-based fault monitoring of a centrifugal pump, in particular of a circulating pump, which method is optimized with regard to the memory requirement and the number of operation steps that are to be carried out. The idea of the disclosure is initially based on the assumption that mechanical faults in the pump or in the drive motor affect certain frequencies of the current spectrum.

[0032] FIGS. 1a, 1b and 1c show, by way of example, the respective current spectrum of the same motor phase at the speeds 1600 rpm, 2200 rpm and 2800 rpm of a heat circulating pump having an impeller with seven channels. In the respective diagram illustration, the current spectrum both for the fault-free case (curve with the solid line) and for the fault case (curve with the dashed line) is included, wherein the latter was caused by an artificially caused blockage of one channel of the impeller. The respective spectra are illustrated in dB, wherein the fundamental oscillation of the illustrated motor phase is normalized to 0 dB. The amplitudes of the sidebands f.sub.r,pump+, referred to as the upper sideband below, and f.sub.r,pump?, referred to as the lower sideband below, are designated in the figures.

[0033] At a speed of 1600 rpm (FIG. 1a), the fault impeller blockage causes an increase in the amplitude of the lower sideband from ?103.5 dB in the healthy state to ?90.1 dB in the faulty state. The amplitude of the upper sideband remains about the same. At a speed of 2200 rpm (FIG. 1b), the difference between the current spectra becomes clearer. The lower sideband amplitude increases from ?104.8 dB to ?75.5 dB and the upper sideband amplitude increases from ?131.0 dB to ?98.8 dB. The spectrum at 2800 rpm looks similar to the spectrum of 2200 rpm, but the amplitudes at the sidebands are even more pronounced. The amplitude of the lower sideband increases from ?114.8 dB to ?76.0 dB and that of the upper sideband increases from ?127.1 dB to ?90.9 dB. The results of the upper spectrum analysis show that information about the state of the pump is contained in the current signal, wherein the differences between healthy and faulty become more apparent at higher speed.

[0034] For the fault monitoring, specific frequencies of the current spectrum therefore need to be evaluated, wherein the most promising approach in regard to minimizing the memory requirement and the number of operations for the application in circulating pumps is based on the multiple reference frame theory. Similar to field-oriented control (FOC), the idea is to let a coordinate system rotate. Whereas in FOC the coordinate system rotates in the frequency of the rotor, it rotates, in the sense of fault identification, with the frequency of a fault.

[0035] As was already shown with reference to FIGS. 1a, 1b, 1c, imbalance and alignment errors of the mechanics in the hydraulic part and drive part of the pump affect the amplitudes of the sidebands of the current spectrum. Said imbalance and alignment errors can be caused by a blocked impeller, a bearing fault or else dry running of the pump. The procedure of the method according to the disclosure is shown in simplified fashion in the block diagram of FIG. 4. The above-mentioned, relevant fault frequency f.sub.r,pump can be calculated by reverting to a fault model 10 which calculates the fault frequency according to formula (1) on the basis of the stator frequency (rotor speed n), the motor slip s and the number p of pole pairs of the drive motor:

[00004]$\begin{array}{cc}{f}_{r,\mathrm{pump}}=\left(1?\frac{1}{p}\left(1-s\right)\right).Math.f_s.& \left(1\right)\end{array}$

[0036] In the case of a three-phase motor, the motor currents can be combined in a space vector. For this, it is assumed that the sum of the phase currents is zero. The real part of the space vector is denoted by ? current and the imaginary part by ? current. The ?-? coordinate system (see FIG. 2) is referred to as stator-fixed coordinate system (stator coordinate system). The transformation of the three-phase stator currents into the two-phase ?-? current is referred to as Clarke transformation.

[0037] In order to drive an AC motor, a pump controller transforms the stator-fixed ?-? current into the rotor-fixed dq current, which is referred to as Park transformation. From a mathematical point of view, a coordinate system is made to rotate in line with the speed n of the rotor. As a result, the dq current is a DC value which can be used for controlling the motor. The interesting aspect is that the vector sum of d and q current corresponds exactly to the amplitude of the fundamental oscillation of the motor current. The method according to the disclosure for automated fault identification makes use of this principle from the prior art.

[0038] Looking at a real motor, the phase current and therefore the current space vector is thus superimposed with oscillations, the extent of which increases during faulty operation of the pump or of the drive motor. For the method according to the disclosure, it is now assumed that the motor current is the sum of the torque-forming current having the amplitude ?.sub.T and the speed ?.sub.S and of a harmonic having the amplitude ?.sub.F and the speed ?.sub.F. The motor currents of the three phases can be calculated according to following equations (2):

[00005]$\begin{array}{cc}{i}_a\left(t\right)={\hat{i}}_T\cos \left({?}_{S}t\right)+{\hat{i}}_F\cos \left({?}_{F}t+?\right)i_b\left(t\right)={\hat{i}}_T\cos \left({?}_{S}t-\frac{2?}{3}\right)+{\hat{i}}_F\cos \left({?}_{F}t+?-\frac{2?}{3}\right)i_c\left(t\right)={\hat{i}}_T\cos \left({?}_{S}t-\frac{4?}{3}\right)+{\hat{i}}_F\cos \left({?}_{F}t+?-\frac{4?}{3}\right)& \left(2\right)\end{array}$

[0039] In this case, ?.sub.F contains information about the state of the pump and about the severity of the fault. As an example, ?.sub.F can be calculated on the basis of equation (1).

[0040] As illustrated in FIG. 2, the current space vector {right arrow over (i)}.sub.?? in the stator coordinate system is equal to the sum of the torque-forming component {right arrow over (i)}.sub.T|??, which rotates at the speed ?.sub.S, and the fault component {right arrow over (i)}.sub.F|??, which rotates at the speed ?.sub.F. The current space vector {right arrow over (i)}.sub.?? of the three-phase motor current is calculated according to following equation (3):

[00006]$\begin{array}{cc}{\underset{\_}{\stackrel{.fwdarw.}{l}}}_{\mathrm{??}}={\hat{i}}_T.Math.e^{i\left({?}_{S}t\right)}+{\hat{i}}_F.Math.e^{i\left({?}_{F}t+?\right)}& \left(3\right)\end{array}$

[0041] In the block diagram shown in FIG. 4, this step is already carried out by the existing field-oriented controller 20 of the pump controller which provides the two currents i.sub.? and i.sub.? as output variables.

[0042] In the sense of the method according to the disclosure, the length of {right arrow over (i)}.sub.F|?? is of interest. The dq coordinate system is now rotated at the speed of the harmonic frequency (?.sub.K=?.sub.F). In order to calculate the current vector in dq coordinates, the standard equation for the Park transformation is used, which is designated by the step 30 in the block diagram. The Park transformation can be implemented mathematically according to the following equation:

[00007]$\begin{array}{cc}{\underset{\_}{\stackrel{.fwdarw.}{l}}}_{\mathrm{dq}}={\underset{\_}{\stackrel{.fwdarw.}{l}}}_{\mathrm{??}}.Math.e^{-i\left({?}_{F}t\right)}& \left(4\right)\end{array}$

[0043] If formula (3) is inserted into formula (4), formula (5) arises for the present vector {right arrow over (i)}.sub.dq in the dq coordinate system:

[00008]$\begin{array}{cc}{\underset{\_}{\stackrel{.fwdarw.}{l}}}_{\mathrm{dq}}={\hat{i}}_F.Math.e^{i?}+{\hat{i}}_T.Math.e^{i\left[\left({?}_S-{?}_F\right)t\right]}& \left(5\right)\end{array}$

[0044] The three-phase current vector {right arrow over (i)}.sub.dq is equal to the sum of the vectors {right arrow over (i)}.sub.T|dq, which rotate at the speed (?.sub.S??.sub.F), and the steady-state vector {right arrow over (i)}.sub.F|dq, see FIG. 3. If ?.sub.F is greater than ?.sub.S, both {right arrow over (i)}.sub.dq and {right arrow over (i)}.sub.T|dq rotate in the other direction.

[0045] Looking at time-dependent variables, i.sub.d and i.sub.q consist of a DC component and an AC component, as can be seen in equations (6) and (7).

[00009]$\begin{array}{cc}{i}_d=i_{F.Math.d}+i_{T.Math.d}.Math.\cos \left(\left({?}_S-{?}_F\right)t\right)& \left(6\right)\end{array}$$\begin{array}{cc}{i}_q=i_{F.Math.q}+i_{T.Math.q}.Math.\sin \left(\left({?}_S-{?}_F\right)t\right)& \left(7\right)\end{array}$

[0046] The initial amplitude ?.sub.f can be calculated from the geometric sum of i.sub.F|d i.sub.F|q, see following equation (8).

[00010]$\begin{array}{cc}{\hat{i}}_f=\sqrt{i_{F.Math.d}^2+i_{F.Math.q}^2}& \left(8\right)\end{array}$

[0047] In the block diagram of FIG. 4, this method step is designated by the reference sign 50. If the DC components of i.sub.d and i.sub.q are ascertained, the amplitude ?.sub.f can be calculated therefrom. The amplitude of a harmonic can thus be calculated by using simple transformations. A simple and memory-friendly method for calculating the DC components of i.sub.d and i.sub.q is a first-order filter which is designated by the reference sign 40 in the block diagram of FIG. 4.

[0048] For example, a first-order Butterworth filter can be chosen, the transfer function of which can be determined as follows according to equation (9)

[00011]$\begin{array}{cc}H\left(z\right)=\frac{1-e^{{?}_{c}T}}{z-e^{{?}_{c}T}},& \left(9\right)\end{array}$ [0049] wherein T is equal to the sampling time of the microprocessor unit. The filter allows simple implementation. However, the cutoff frequency ?.sub.c must be chosen to be relatively small in order to remove the oscillation as much as possible. As a result, the time constant of the filter is relatively high, which makes the system slow and can constitute a problem in dynamic systems. This is not critical in the case of use in a pump, however, since no fast load changes are to be expected.

[0050] Circulating pumps are usually operated in a pressure-controlled manner. This means that the load and the speed of the pump can change during operation, which means a change in the current consumption of the pump at the same time. In order to take this into account, a severity factor (SF) for a fault, which relates to the current consumption, is calculated. This is illustrated by the reference sign 60 in the block diagram of FIG. 4. Modern circulating pumps have an FOC 10 from which the information about the current consumption can be obtained. In order to ensure the load independence, the severity factor is formed from the relationship of the fault indicator ?.sub.f and of the amplitude ?.sub.T of the torque-forming component which is equal to the q current in the used FOC, wherein the d current is regulated to zero:

[00012]$\mathrm{SF}=\frac{{\hat{i}}_f}{{\hat{i}}_T}.Math.100\%.$

[0051] On the basis of the severity factor SF, a decision can then be made about whether or not a fault is present in the pump. The decision can be made locally by the pump controller, see block 70 of FIG. 4. Alternatively, however, it is also possible to set up an external evaluation unit which receives the severity factor SF from a multiplicity of pumps. Such a system is shown by way of example in FIG. 5. The pump 1, here a heat circulating pump, uses the previously presented method to calculate the severity factor SF and transmits it via a gateway 2 to an external evaluation unit 3 which is implemented in a cloud-based manner in the present case. The transmitted data, in particular the severity factor and further operating parameters (e.g. operating point, speed, temperatures, service life) of the pump, are combined in the cloud 3 with corresponding data of further pumps from the same fleet.

[0052] Due to the large amount of data available from a complete pump fleet, a comparison of the severity factors under similar boundary conditions (operating point, speed, temperatures, service life) can then be carried out. This is used to filter out faulty pumps and to identify the imminent failure of pumps. A large deviation in the severity factor of one pump from the respective values of the other pumps or from an average value of the other pumps can be interpreted as a degeneration or blockage of the impeller. In this case, the pump owner or pump operator can be informed immediately and, where appropriate, a service technician can be sent over: the information of the pump owner or pump operator and/or the service task can preferably be generated and carried out automatically by the system 4.

[0053] The foregoing disclosure has been set forth merely to illustrate the disclosure and is not intended to be limiting. Since modifications of the disclosed embodiments incorporating the spirit and substance of the disclosure may occur to persons skilled in the art, the disclosure should be construed to include everything within the scope of the appended claims and equivalents thereof.