Condition monitoring method for a pump assembly and power converter system

Abstract

A condition monitoring method for a pump assembly and a power converter system are provided. The condition monitoring method for a pump assembly includes estimating a plurality of system curves of the pump assembly over a long period of time in order to detect changes in operating conditions of the pump assembly for assessing whether the pump assembly requires maintenance. The method includes a curve fitting process in which the estimated system curves are fitted on operating point data of the pump assembly. The curve fitting process includes providing the estimated system curves for a plurality of fitting time windows, wherein each fitting time window of the plurality of fitting time windows includes a plurality of operating points of the pump assembly.

Description

Technical Field

[0001] The present invention relates to a method for monitoring the condition of a pump assembly, and a power converter system for a pump assembly utilizing the method. Background Technology

[0002] Pumps are significant energy consumers in industrial sectors. Furthermore, in many cases, they are crucial components of larger processes, and their failure can lead to costly downtime. Therefore, ensuring pump efficiency and reliability through monitoring and maintenance is a critical objective for many industrial systems.

[0003] The system to which a pump supplies flow, including components such as pipes, heat exchangers, valves, tanks, and others, can be mathematically described by a velocity profile (hereinafter referred to as the system profile) using the total head. This defines the total head loss of the system surrounding the pump at different flow velocities. The system profile contains information about the static pressure difference between the pump's suction and discharge sides, which is directly related to the surface level in the reservoirs and tanks connected to the pump. As another parameter, it includes a measurement of the system's flow resistance. Furthermore, when the characteristic performance profiles of the pump supplying flow to the system are also known, these profiles together can be used to predict the pump's operating point and its energy consumption at different velocities. These characteristics make knowledge of the system profile extremely useful from an energy efficiency and condition monitoring perspective.

[0004] The flow resistance of a system, represented by a system curve, can be monitored to detect and measure scaling and clogging in the affected system. Continuous monitoring of system flow resistance can estimate the energy lost due to the additional flow resistance caused by scaling. It is also possible to detect impending clogging before the problem develops to the point of causing unplanned and costly downtime. Leaks can also be detected as an unexpected decrease in the observed flow resistance coefficient.

[0005] Furthermore, knowledge of system curves is useful when considering energy-saving measures in pump systems. Since system curves can be used to predict pump performance at different speeds, more energy-efficient variable speed control schemes for pump alternatives can be evaluated. With the help of system curves, the performance of alternative pumps or impeller overhauls can also be estimated.

[0006] Monitoring the flow resistance of heat exchangers that accumulate contaminants over time traditionally requires measuring instruments to generate relevant information. Such instruments incur additional costs and may not be readily available in all locations where observing system curves can help detect and measure phenomena affecting the energy efficiency and reliability of pumped processes.

[0007] Several sensorless methods exist for estimating system curves for pump assemblies. These known sensorless methods require identifying an operating sequence during which the pump operating point is estimated and recorded, and deriving the system curve from the recorded data. Identifying the operating sequence includes specific control sequences that control the pump assembly.

[0008] One of the problems associated with known sensorless methods used for estimating system curves is that most practical pump assemblies cannot be expected to allow for the execution of identification operating sequences, which alters the control logic of the process. Using identification operating sequences to estimate the system curves of a pump assembly, in conjunction with condition monitoring, is particularly problematic because multiple estimated system curves are needed over time to detect changes in the pump assembly's operating state. Summary of the Invention

[0009] The purpose of this invention is to provide a condition monitoring method and a power converter system for implementing the method, in order to solve the aforementioned problems. This objective is achieved through the condition monitoring method and power converter system described below.

[0010] This invention is based on the concept of detecting changes in the operating state of a pump assembly by determining operating point data during normal operation and fitting estimated system curves onto the operating point data, wherein the curve fitting is performed over multiple fitting time windows over a long period. In other words, a large number of system curves for the pump assembly are estimated over a long period to detect changes in the operating state of the pump assembly for assessing whether the pump assembly requires maintenance.

[0011] The advantage of the condition monitoring method according to the invention is that it does not require separate measuring instruments to estimate the operating state of the pump assembly. Only two instantaneous performance variables of the pump and two characteristic performance curves of the pump are needed. In many embodiments, the former can be obtained from signals suitable for actuating the pump, while the latter can usually be readily obtained from the pump manufacturer. Attached Figure Description

[0012] The invention will now be described in more detail with reference to the accompanying drawings and preferred embodiments, in which:

[0013] Figure 1 A simplified schematic diagram of a pump assembly according to an embodiment of the present invention is shown;

[0014] Figure 2A and Figure 2B The diagram illustrates how pump operating point data can be estimated based on the pump's characteristic performance curves and instantaneous performance variables.

[0015] Figure 3 This illustrates how the pump's operating point lies at the intersection of the pump's characteristic performance curves and the system curves of the pump components; and

[0016] Figure 4 This is a flowchart illustrating the curve fitting process used in an embodiment of the present invention. Detailed Implementation

[0017] Figure 1 A simplified schematic diagram of a pump assembly is shown, comprising a first reservoir 11, a second reservoir 12, a pump 2, a variable speed drive 4 adapted to actuate the pump 2, a control system 8 adapted to control the variable speed drive 4, and a flow system 6 fluidly connected to the pump 2. The pump 2 is adapted to move fluid from the first reservoir 11 to the second reservoir 12 via the flow system 6. The variable speed drive 4 includes an electric motor 41 connected to the pump 2 and a frequency converter 42 adapted to supply power to the electric motor. The flow system 6 includes a filter device 62 adapted to separate solid matter from the fluid.

[0018] A method for estimating Figure 1 The method for system curves of the pump assembly shown includes: determining at least two characteristic performance curves of pump 2; estimating at least two instantaneous performance variables of pump 2 for multiple operating points of the pump assembly; and determining operating point data of the pump assembly based on the at least two characteristic performance curves of pump 2 and the estimated instantaneous performance variables of pump 2, the operating point data including estimated flow rates Q at multiple operating points of the pump assembly. est And estimated head H est ; and the method includes estimating the system curve of the pump assembly based on operating point data, wherein the operating point data is determined during normal operation of the pump assembly, and the method includes a curve fitting process in which the estimated system curve is fitted onto the operating point data.

[0019] In one implementation, at least two characteristic performance curves of the pump are determined by obtaining them from the pump manufacturer. Typically, the characteristic performance curves obtained from the pump manufacturer are the QP and QH curves, examples of which are shown below. Figure 2A and Figure 2B Alternatively, at least two characteristic performance curves of the pump may be determined by some other method that does not require measurement using flow sensors and / or pressure sensors. Also in this alternative embodiment, the at least two characteristic performance curves of the pump typically include the pump's QP and QH curves.

[0020] The characteristic performance curves of a pump are typically available at its nominal speed. To estimate the pump's operating point at speeds other than its nominal speed, the characteristic performance curves at the nominal speed must be converted to those at the instantaneous speed using the following pump similarity law:

[0021]

[0022]

[0023]

[0024] In the above equation, n0 is the nominal speed of the pump, n is the instantaneous speed of the pump, Q0 is the flow rate at the nominal speed of the pump, H0 is the head at the nominal speed of the pump, and P0 is the nominal shaft power at the nominal speed of the pump.

[0025] Figure 2A and Figure 2B This paper illustrates the estimation of pump operating point data based on the pump's characteristic performance curves and instantaneous performance variables. The instantaneous performance variables include the estimated pump speed n. est And the estimated shaft power P of the pump est The control system is suitable for determining the estimated pump speed n based on data related to the operation of the frequency converter. est And the estimated shaft power P of the pump est Data related to the operation of the frequency converter includes the converter's current and voltage in vector form.

[0026] In an alternative implementation, the instantaneous performance variables of the pump include the estimated pump speed and the estimated pump shaft torque.

[0027] In one implementation, the instantaneous performance variables of the pump are defined based on signals from a variable speed drive suitable for actuating the pump. In another implementation, where the signals from the variable speed drive associated with the instantaneous performance variables of the pump include noise, the instantaneous performance variables of the pump are defined based on a low-pass filtered signal from the variable speed drive.

[0028] Figure 2A The QP curve is shown. Figure 2B The QH curve is shown. Figure 2A and Figure 2B Both curves are shown. The continuous curve represents the characteristic performance curve of the pump at the nominal speed n0, while the dashed curve represents the characteristic performance curve of the pump at the estimated speed n0. est The estimated characteristic performance curve is shown below.

[0029] Figure 3 This illustrates how the pump's operating point lies at the intersection of the pump's characteristic QH curve and the system curve of the pump assembly. The shape of the system's QH curve is defined by the flow resistance of the system and the static pressure difference between the pump's suction and discharge sides. The system curve of the pump assembly can be represented as a polynomial curve:

[0030] H = kQ 2 +H st ,

[0031] Where k is the flow resistance factor of the flow system, representing the sum of all flow resistance components during the flow process, H st The static head of the flow system.

[0032] As the pump speed changes, its QH operating point shifts along the system curve. Assuming the flow system of the pump assembly remains constant during this speed change, the flow resistance k and static head Hst can be estimated by fitting the system curve defined above onto the operating point data using the least squares method.

[0033] The curve fitting process includes providing estimated system curves for multiple fitting time windows. Each fitting time window includes multiple operating points of the pump assembly. In one implementation, the multiple fitting time windows include overlapping fitting time windows. In an alternative implementation, the fitting time windows do not overlap.

[0034] Curve fitting is a known process and will not be described in detail here.

[0035] The optimal length of the fitting time window depends on the pump assembly. In one implementation, the length of each fitting time window ranges from 30 seconds to 48 hours. In another implementation, the length of each fitting time window ranges from 1 minute to 24 hours.

[0036] In the implementation method, the length of the fitting time window is given by equation l. w =15 minutes · 2 N Determine that N is the index of the fitting time window, starting from zero. If four fitting time windows are used in this embodiment, N has values ​​of 0, 1, 2, and 3, and the lengths of the fitting time windows are 15 minutes, 30 minutes, 1 hour, and 2 hours, respectively.

[0037] In the curve fitting process, a specific fitting time window is used to fit the system curve on the working point data at a specific time interval T. Figure 4 This is a flowchart illustrating the curve fitting process of an embodiment of the present invention.

[0038] In use Figure 4 In the implementation of the flowchart, the time interval T is one minute, and there are three fitting time windows represented by w1, w2, and w3. The lengths of the fitting time windows are w1 = 10 minutes, w2 = 20 minutes, and w3 = 30 minutes. The process starts from t = 0. The longest fitting time window is w3, with a length of 30 minutes. When the pump running time exceeds 30 minutes, operating point data is saved for the fitting time windows w1, w2, and w3, such that the operating point data for w1 is saved from the 20-30 minute period, the operating point data for w2 is saved from the 10-30 minute period, and the operating point data for w3 is saved from the 0-30 minute period. The estimated system curve is fitted onto the operating point data of each fitting time window in the fitting time windows w1, w2, and w3. For each fitting time window, a corresponding estimated system curve is created through a curve fitting process.

[0039] Figure 4 The method shown continues by saving operating point data for fitting time windows at time intervals defined by T. Therefore, when the pump run time exceeds 31 minutes, operating point data is saved for fitting time windows w1, w2, and w3, such that w1 saves operating point data from time interval 21 to 31 minutes, w2 saves from time interval 11 to 31 minutes, and w3 saves operating point data from time interval 1 to 31 minutes. An estimated system curve is created for each fitting time window at time intervals defined by T, which is one minute in this example.

[0040] The time interval is shorter than the shortest fitting time window. In this implementation, the length of the time interval is in the range of 30 seconds to 5 minutes.

[0041] In one implementation, the method includes determining at least one estimated parameter for each fitting time window, and a filtering process for removing unsuitable estimated system curves. The filtering process is adapted to identify unsuitable estimated system curves based on at least one acceptance criterion, which includes conditions for at least one estimated parameter.

[0042] At least one estimated parameter includes at least one of the following: the estimated flow resistance factor k of the system. w The system's estimated static head H st,w Coefficient of determination R 2 w and speed difference D s,w The speed difference is the difference between the maximum and minimum speeds of pump 2 within the fitted time window.

[0043] In an implementation, at least one estimation parameter includes the system's estimated flow resistance factor k. w And at least one acceptance criterion includes the system's estimated flow resistance factor k. w The condition must be greater than zero. In another embodiment, at least one estimation parameter includes a coefficient of determination R. 2 w And at least one acceptance criterion includes a coefficient of determination R. 2 w The condition is that the value must be greater than the limit value of the coefficient of determination, wherein the limit value of the coefficient of determination is greater than or equal to 0.5. In another embodiment, wherein the pump is a rotary pump, at least one estimated parameter includes the speed difference D. s,w And at least one acceptance criterion includes the speed difference D. s,w The condition is greater than or equal to 20 rpm.

[0044] The method according to the invention requires determining the operating point data of the pump assembly during normal operation of the pump assembly, which includes multiple pump speeds.

[0045] For the fitting time window of the estimated system curve through the filtering process, the estimated flow resistance factor k of the system is recorded. w and / or the estimated static head H of the system st,w In the implementation, the start time and length of each fitting time window are also recorded.

[0046] In the condition monitoring method according to the present invention, the curve fitting process includes providing an estimated system curve for multiple fitting time windows, wherein each fitting time window includes multiple operating points of the pump assembly. The multiple fitting time windows are set over a long period of time to detect changes in the operating state of the pump assembly for assessing whether the pump assembly requires maintenance.

[0047] In this implementation, the change in the operating state of the pump assembly includes the system's estimated flow resistance factor k. w The value of changes. In this embodiment, when the system's estimated flow resistance factor k w When the value reaches a predetermined limit, the pump assembly is interpreted as requiring maintenance. The predetermined limit is greater than or equal to 1.5 × k. w0 , where k w0 This is a reference value for the estimated flow resistance factor obtained when the pump assembly is new or recently cleaned. In an alternative embodiment, the predetermined limit value is greater than or equal to 1.25 × k w0 .

[0048] In one implementation, the long period for providing multiple fitting time windows is at least one week. In another implementation, the long period is at least one month. Furthermore, estimated system curves can be provided continuously during the operation of the pump assembly, in which case the maximum value over the long period will be the operating life of the pump assembly.

[0049] When the pump assembly's filter is replaced and / or the pump assembly's flow system is cleaned, the system's flow resistance factor decreases. In an implementation of the condition monitoring method, a baseline flow resistance coefficient k0 is determined after replacing the pump assembly's filter and / or cleaning the pump assembly's flow system. After determining the new baseline flow resistance coefficient, the system's estimated flow resistance coefficient is compared with the new baseline flow resistance coefficient to detect changes in the pump assembly's operating condition.

[0050] The flow resistance factor k is estimated through the monitoring system. wThe value of this value can determine the cost-effectiveness of pump component maintenance. Furthermore, in systems where a gradual increase in system flow resistance is abnormal, but the accumulation of solid matter during flow remains a threat, the proposed method can detect the upward trend of the estimated flow resistance factor, thus providing an early warning before complete blockage and clogging of the flow.

[0051] In one implementation, the condition monitoring method includes notifying the pump assembly operator when maintenance is required. Based on the notification provided by the condition monitoring method, the operator can perform maintenance on the pump assembly at cost-effective intervals.

[0052] The condition monitoring method according to the present invention can also be used to detect a decrease in the flow resistance factor of a system, which can be an indication of leakage.

[0053] In a typical implementation, the condition monitoring method according to the present invention is a computer-implemented method.

[0054] exist Figure 1 In the pump assembly, the variable speed drive 4 includes a frequency converter 42. In an alternative embodiment, the variable speed drive includes another type of power converter, such as a DC-DC converter.

[0055] The control system 8 is adapted to estimate at least two instantaneous performance variables of pump 2 at multiple operating points of the pump assembly based on data related to the operation of frequency converter 42. The data related to the operation of frequency converter 42 includes the power supplied to motor 41 and the rotational speed of motor 41. The rotational speed of pump 2 can be determined based on the rotational speed of motor 41.

[0056] The control system 8 is part of the frequency converter 42. In an alternative embodiment, the control system is not part of the power converter of the variable speed drive.

[0057] It will be apparent to those skilled in the art that the concept of the present invention can be implemented in various ways. The present invention and its embodiments are not limited to the examples described above, but can be varied within the scope of the claims.

Claims

1. A method for monitoring the condition of a pump assembly, the pump assembly comprising a pump (2), a variable speed drive (4) adapted to actuate the pump (2), and a flow system (6) fluidly connected to the pump (2), wherein, The method includes: Determine at least two characteristic performance curves of the pump (2); Estimate at least two instantaneous performance variables of the pump (2) for multiple operating points of the pump assembly; The operating point data of the pump assembly is determined based on the at least two characteristic performance curves of the pump (2) and the estimated instantaneous performance variables of the pump (2), the operating point data including the estimated flow rate (Q) at the plurality of operating points of the pump assembly. est ) and estimated head (H est );as well as The system curve of the pump assembly is estimated based on the operating point data. The characteristic feature is that the operating point data is determined during normal operation of the pump assembly, and the method includes a curve fitting process in which an estimated system curve is fitted onto the operating point data. The curve fitting process includes providing estimated system curves for multiple fitting time windows, wherein each fitting time window includes multiple operating points of the pump assembly. The multiple fitting time windows are set over a long period of time to detect changes in the operating state of the pump assembly and to assess whether the pump assembly needs maintenance.

2. The condition monitoring method according to claim 1, wherein, The method includes: determining at least one estimated parameter for each fitting time window; and a filtering process for removing unsuitable estimated system curves, wherein the filtering process is adapted to identify the unsuitable estimated system curves based on at least one acceptance criterion, the at least one acceptance criterion including conditions for the at least one estimated parameter.

3. The condition monitoring method according to claim 2, wherein, The at least one estimated parameter includes at least one of the following: the estimated flow resistance factor (k) of the flow system (6). w The estimated static head (H) of the flow system (6) st,w ), coefficient of determination (R) 2 w ) and speed difference (D) s,w The speed difference is the difference between the maximum speed and the minimum speed of the pump (2) in the fitting time window.

4. The condition monitoring method according to claim 3, wherein, The at least one estimated parameter includes the estimated flow resistance factor (k) of the flow system (6). w ), and the at least one acceptance criterion includes the estimated flow resistance factor (k) of the flow system (6). w The condition that it must be greater than zero.

5. The condition monitoring method according to claim 3, wherein, The at least one estimated parameter includes the coefficient of determination (R0). 2 w ), and the at least one acceptance criterion includes the coefficient of determination (R). 2 w The condition that the coefficient must be greater than the limit value of the definite coefficient.

6. The condition monitoring method according to claim 5, wherein, The limit value of the determination coefficient is greater than or equal to 0.

5.

7. The condition monitoring method according to claim 1, wherein, The long period of time is at least one week.

8. The condition monitoring method according to claim 3, wherein, The method includes: recording the estimated flow resistance factor (k) of the flow system (6) for the fitting time window of the estimated system curve through the filtering process. w ) and / or the estimated static head (H) of the flow system (6). st,w ).

9. The condition monitoring method according to claim 1, wherein, The multiple fitting time windows include overlapping fitting time windows.

10. The condition monitoring method according to claim 1, wherein, The length of each fitting time window in the fitting time window ranges from 30 seconds to 48 hours.

11. The condition monitoring method according to claim 1, wherein, The method includes: notifying the operator of the pump assembly when the pump assembly requires maintenance.

12. The condition monitoring method according to claim 1, wherein, The changes in the operating state of the pump assembly include the estimated flow resistance factor (k) of the flow system (6). w The value of ) changes, wherein when the estimated flow resistance factor (k) of the flow system (6) changes. w When the value of ) reaches a predetermined limit, the pump assembly is interpreted as requiring maintenance.

13. A power converter system for a pump assembly, comprising: A power converter adapted to supply power to an electric motor (41), the electric motor (41) being adapted to be connected to a pump (2). as well as A control system (8) adapted to control the power converter; The control system (8) is characterized in that it is adapted to perform the condition monitoring method according to claim 1.

14. The power converter system according to claim 13, wherein, The power converter is a frequency converter (42).

15. The power converter system according to claim 14, wherein, The control system (8) is adapted to estimate the at least two instantaneous performance variables of the pump (2) for the plurality of operating points of the pump assembly based on data related to the operation of the frequency converter (42).

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