Detection device, detection method, and detection system

Abstract

To provide a detection device, a detection method, and a detection system that improve detection accuracy of occurrence of cavitation.SOLUTION: A suction pressure acquisition unit 121 acquires pressure data indicating pressure of a pump 12. A variation coefficient calculation unit 123 calculates a variation coefficient indicating amplitude of magnitude of pressure of the pump on the basis of the pressure data acquired by the suction pressure acquisition unit 121. An adjustment unit 124 performs an adjustment for detection information to be used for detection of occurrence of cavitation, including the variation coefficient calculated by the variation coefficient calculation unit 123, by using a pressure transmission coefficient indicating transmissibility of pressure of the pump. A determination unit 125 detects occurrence of cavitation of the pump 12 on the basis of the detection information adjusted by the adjustment unit 124.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to a detection device, a detection method, and a detection system. [Background technology]

[0002] Pumps are used to transfer or pump liquids in various plants that produce petroleum, petrochemicals, chemicals, gas, etc. Centrifugal pumps using impellers have been widely used, but in recent years, positive displacement pumps have been increasingly used to achieve high pressure and improve the accuracy of discharge volume.

[0003] Pumps pressurize the liquid drawn into the suction port and expel it from the discharge port. Depending on the operating conditions, the liquid may vaporize and cause cavitation. Cavitation is a physical phenomenon in which pressure differences within a liquid cause bubbles or cavities to appear and disappear in a short period of time. Cavitation can lead to reduced pump efficiency, noise and vibration, and damage to the pump's interior. Furthermore, the energy released when the bubbles or cavities disappear can damage or destroy the pump, posing a significant safety risk. However, because it is difficult to completely prevent cavitation, a system capable of detecting its onset early is crucial.

[0004] To address this issue, the following cavitation detection device has been proposed. For example, the detection device acquires the pump suction pressure from a pressure sensor and calculates a coefficient of variation, such as a standard deviation or moving average value, from the suction pressure value. The detection device then determines that cavitation has occurred when the current coefficient of variation reaches several times the standard value that is used when the pump is operating normally. The detection device then displays the results on an administrator's terminal or the like (Patent Document 1).

[0005] This technology evaluates the amount of pressure fluctuation caused by cavitation using a coefficient of variation to detect cavitation. More specifically, when cavitation occurs in a pump, the pressure fluctuation increases compared to when the pump is operating normally. Therefore, the detection device evaluates the magnitude of the pressure fluctuation when cavitation occurs using a coefficient of variation to detect the occurrence of cavitation. Therefore, this technology requires that the pressure fluctuation be accurately transmitted to the pressure sensor. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] Japanese Patent Application Publication No. 2020-90945 Summary of the Invention [Problem to be solved by the invention]

[0007] However, conventional detection devices may be unstable in detecting cavitation occurrence when pressure fluctuations are not accurately transmitted to the sensor. For example, when pressure fluctuations are extremely low overall or locally within the pump, depending on the type of pump, bubbles or cavities generated by a pressure drop may not disappear, and the presence of cavities in the liquid may hinder the transmission of vibrations, making it difficult for pressure fluctuations to be accurately transmitted to the sensor.

[0008] The disclosed technology aims to provide a detection device, a detection method, and a detection system that improve the accuracy of detecting the occurrence of cavitation. [Means for solving the problem]

[0009] In one aspect of the detection device, detection method, and detection system disclosed herein, the pressure acquisition unit acquires pressure data indicating the pressure of the pump. The variation coefficient calculation unit calculates a variation coefficient indicating the amplitude of fluctuation in the magnitude of the pressure of the pump based on the pressure data acquired by the pressure acquisition unit. The adjustment unit During the detection period the coefficient of variation calculated by the coefficient of variation calculation unit; and The coefficient of variation is calculated by the coefficient of variation calculation unit in a state where the fluctuation of the pressure data after a certain period of time has elapsed since the start of operation of the pump is within a certain value. The present invention provides a method for detecting cavitation occurrence by calculating an adjusted coefficient of variation by multiplying a reference coefficient of variation, which is a threshold value used for detecting cavitation occurrence, by a pressure transmission coefficient that indicates the ease of pressure transmission in the pump and whose magnitude is inversely proportional to the pressure of the pump, and adjusting the detection information. The determination unit compares the adjusted coefficient of variation with the reference coefficient of variation to detect the occurrence of cavitation in the pump. [Effects of the Invention]

[0010] In one aspect, the present invention can improve the accuracy of detecting the occurrence of cavitation. [Brief explanation of the drawings]

[0011] [Figure 1] FIG. 1 is a diagram showing an example of the overall configuration of a plant in which a detection system is used. [Figure 2] FIG. 2 is a block diagram showing the details of the detection system. [Figure 3] FIG. 3 is a diagram showing an example of cavitation detection using the adjusted coefficient of variation. [Figure 4] FIG. 4 is a flowchart of a process for detecting the occurrence of cavitation by the detection system according to the first embodiment. [Figure 5] FIG. 5 is a diagram showing the calculation of the coefficient of variation by a conventional detection device. [Figure 6] FIG. 6 is a diagram illustrating calculation of the coefficient of variation by the detection device according to the first embodiment. [Figure 7] FIG. 7 is a block diagram showing details of the detection system according to the third embodiment. [Figure 8] FIG. 8 is a flowchart of a process for detecting the occurrence of cavitation by the detection system according to the third embodiment. [Figure 9] FIG. 9 is a hardware configuration diagram of the detection device. [Figure 10] FIG. 10 is a diagram for explaining process abnormality detection using the coefficient of variation. [Figure 11] FIG. 11 is a diagram showing an example of statistical information related to cavitation. DETAILED DESCRIPTION OF THE INVENTION

[0012] Hereinafter, embodiments of the detection device, detection method, and detection system disclosed in the present application will be described in detail with reference to the accompanying drawings. Note that the present invention is not limited to these embodiments. Furthermore, the same elements are given the same reference numerals, redundant explanations are omitted as appropriate, and the embodiments can be combined as appropriate within a range that does not cause inconsistency.

[0013] [Embodiment 1] [Overall configuration] Fig. 1 is a diagram showing an example of the overall configuration of a plant in which a detection system 100 is used. With reference to Fig. 1, the configuration of the plant 1 in which a detection system 100 is used will be briefly described. As shown in Fig. 1, the plant 1, a management terminal device 2, and the detection system 100 are arranged.

[0014] Plant 1 is an example of various plants that produce petroleum, petrochemicals, chemicals, gas, etc., and includes factories and the like equipped with various facilities for obtaining products. Examples of products are LNG (liquefied natural gas), resins (plastics, nylon, etc.), chemical products, etc. Examples of facilities are factory facilities, machinery facilities, production facilities, power generation facilities, storage facilities, wellhead facilities for extracting petroleum, natural gas, etc.

[0015] The control system in the plant 1 is constructed using a distributed control system (DCS) or the like. For example, although not shown, the control system in the plant 1 uses process data used in the plant 1 to execute various controls on control devices such as field devices installed in the equipment to be controlled and operation devices corresponding to the equipment to be controlled. The control system includes a computer such as a server. The detection system 100 and the management terminal device 2 may also be included in the control system.

[0016] The plant 1 has piping 11 and a pump 12 for transferring or pumping a fluid, equipment 14 to be controlled in the plant 1, and a liquid source 15. The plant 1 may also include a detection system 100 and a management terminal device 2.

[0017] The liquid source 15 stores the liquid to be supplied to the equipment 14. The liquid source 15 may be a tank or the like that stores, preserves, and maintains the pressure of a liquid. The liquid source 15 may also be a well or an oil well provided in an area where resources such as groundwater and an oil field are accumulated or buried. The liquid source 15 may also be a river, a pond, a lake, a dam, or the like. The liquid source 15 may also be a tank that stores a liquid to be supplied by another pump.

[0018] The piping 11 is a pipe for circulating a liquid that connects the liquid source 15 and the equipment 14. A valve or the like may be arranged in the piping 11. The piping 11 sends the liquid stored in the liquid source 15 to the equipment 14. For example, the piping 11 branches near the inlet to the pump 12, and a pressure meter 13 is arranged at the end of the branch. The branch pipe of the piping 11 that is connected to the pressure meter 13 is called a pressure guiding pipe.

[0019] The pump 12 transfers or pumps the liquid stored in the liquid source 15 through the piping 11 to supply it to the equipment 14. The pump 12 is, for example, a positive displacement pump. The pump 12 may also be a centrifugal pump, a diffuser pump, a cascade pump, an axial flow pump, a mixed flow pump, a cross flow pump, or the like. A plurality of pumps 12 may be arranged in the plant 1.

[0020] The pressure meter 13 is provided between the liquid source 15 and the pump 12, and measures the suction pressure of the pump 12. Specifically, the pressure meter 13 is provided at the end of a pressure pipe branching off from the pipe 11 connecting the liquid source 15 and the pump 12. The pressure meter 13 is, for example, an existing facility that is provided when the pump 12 is installed. The pressure meter 13 functions as a sensor that detects the operation of the pump 12. If there are multiple pumps 12, a pressure meter 13 may be provided for each pump 12. FIG. 1 illustrates an example in which one liquid source 15, one pressure meter 13, and one pump 12 are provided in the plant 1. The measured value by the pressure meter 13 may be used to control the plant 1.

[0021] The device 14 may be a field device installed at the site of the plant 1. The device 14 may be at least a part of factory equipment, machinery, production equipment, power generation equipment, storage equipment, etc. The device 14 may include a device that receives a supply of liquid such as water, oil, fuel, refrigerant, or chemical and performs a processing operation using the liquid. The device 14 may include multiple devices.

[0022] The management terminal device 2 is a computer used by the manager of the plant 1. The management terminal device 2 notifies the manager of the occurrence of cavitation by, for example, displaying information about the occurrence of cavitation detected by the detection device 102.

[0023] [Detection System] The detection system 100 detects cavitation based on the coefficient of variation of suction pressure data, which indicates the raw, unfiltered value of the suction pressure of the pump 12. The detection system 100 is configured to be applicable to an existing plant 1, etc., and can detect cavitation by acquiring suction pressure data and calculating the coefficient of variation. The detection system 100 may be included in the control system of the plant 1. The detection system 100 may also be included in a measuring instrument, such as a sensor, provided within the plant 1.

[0024] Fig. 2 is a block diagram showing the details of the detection system. Next, the details of the detection system 100 will be described with reference to Fig. 2. The detection system 100 has a suction pressure measuring device 101 and a detection device 102 shown in Fig. 2. In Fig. 2, an example of the movement direction of the liquid inside the pipe 11 is shown by an arrow pointing from the liquid source 15 to the equipment 14.

[0025] The suction pressure measuring device 101 is, for example, a differential pressure transmitter. The suction pressure measuring device 101 is disposed, for example, at the end of a T-joint, which is a branching pipe provided midway through a pressure guiding pipe. The suction pressure measuring device 101 is connected to the detection device 102 so that data can be transmitted and received via analog or digital transmission.

[0026] The suction pressure measuring device 101 measures the suction pressure of the pump 12. The suction pressure measuring device 101 then converts the measurement into suction pressure data representing the raw, unfiltered value of the suction pressure. The suction pressure measuring device 101 then transmits the suction pressure data to the detection device 102 via high-speed digital communication.

[0027] Here, the detection device 102 according to this embodiment detects the occurrence of cavitation using the suction pressure of the pump 12, as an example, but it is also possible to use other pressures related to the pump 12. For example, the detection device 102 may detect the occurrence of cavitation using the pressure around the pump 12. As the pressure around the pump 12, for example, the priming pressure, the drain pressure, or the discharge pressure can be used.

[0028] [Detection device] The detection device 102 is a controller of an instrumentation system that detects the occurrence of cavitation using the raw, unfiltered pressure value measured by the suction pressure measuring device 101. The detection device 102 is connected to the management terminal device 2 via a network. The detection device 102 has a suction pressure acquisition unit 121, a memory unit 122, a coefficient of variation calculation unit 123, an adjustment unit 124, a determination unit 125, and a notification unit 126.

[0029] The suction pressure acquisition unit 121 receives suction pressure data indicating the suction pressure of the pump 12 from the suction pressure measuring device 101. If the suction pressure data is stored in a database or the like (not shown), the suction pressure acquisition unit 121 may access the database or the like to acquire the suction pressure data. Alternatively, the suction pressure acquisition unit 121 may acquire the suction pressure data from the control system of the plant 1. The suction pressure acquisition unit 121 stores the acquired suction pressure data in the memory unit 122. This suction pressure acquisition unit 121 is one example of a "pressure acquisition unit."

[0030] Storage unit 122 stores the suction pressure data acquired from suction pressure acquisition unit 121. Storage unit 122 may also store other data processed by detection device 102. For example, storage unit 122 may store intermediate data, calculation results, parameters, and the like that are calculated and used by detection device 102 in the process of generating detection results. Storage unit 122 may also supply the stored data to a request source in response to a request from each unit within detection device 102. For example, storage unit 122 outputs the stored suction pressure data to variation coefficient calculation unit 123 in response to a request from variation coefficient calculation unit 123.

[0031] The variation coefficient calculation unit 123 calculates the variation coefficient of the suction pressure data for the detection period. The variation coefficient is a value indicating the amplitude of fluctuation in the magnitude of the suction pressure, and is one of the detection information used to detect the occurrence of cavitation. That is, the variation coefficient calculation unit 123 calculates the variation coefficient indicating the amplitude of fluctuation in the magnitude of the suction pressure based on the suction pressure data acquired by the suction pressure acquisition unit 121.

[0032] The coefficient of variation calculation unit 123 calculates the coefficient of variation based on, for example, the average value and standard deviation of the suction pressure data for the detection period. Specifically, the coefficient of variation calculation unit 123 calculates the average value and standard deviation of the suction pressure data for the detection period and calculates the coefficient of variation by dividing the standard deviation by the average value. The coefficient of variation is an index that indicates the amplitude of pressure oscillations that indicate fluctuations in suction pressure. A large coefficient of variation indicates large fluctuations in suction pressure, and it is estimated that large fluctuations in suction pressure are due to the occurrence of cavitation. Therefore, the coefficient of variation is a value that increases with the occurrence of cavitation. In other words, if pressure is properly transmitted to the detection device 102, a high coefficient of variation indicates that cavitation is occurring.

[0033] The variation coefficient calculation unit 123 may calculate the moving average value of the suction pressure data during the detection period as the average value, and may calculate the moving standard deviation of the suction pressure data as the standard deviation. This allows the variation coefficient calculation unit 123 to sequentially calculate the variation coefficient of the suction pressure data while shifting the detection period, thereby enabling early detection of the occurrence of cavitation in the pump 12. The variation coefficient calculation unit 123 outputs the calculated variation coefficient to the adjustment unit 124.

[0034] The coefficient of variation calculation unit 123 calculates the coefficient of variation C of the suction pressure data during the detection period using, for example, the following formula (1): v where P adv is the average value of the suction pressure data during the detection period. p is the standard deviation of the suction pressure data during the detection period.

[0035]

number

[0036] Furthermore, the coefficient of variation calculation unit 123 calculates the standard deviation S of the suction pressure data during the detection period using the following formula (2): pHere, n is the number of suction pressure data during the detection period. i is the static pressure at the suction port of the pump 12 (suction pressure data).

[0037]

number

[0038] The adjustment unit 124 receives an input of the coefficient of variation of the suction pressure data from the coefficient of variation calculation unit 123. The adjustment unit 124 previously stores a pressure transmission coefficient, which is a coefficient that adjusts the coefficient of variation by taking into account the ease of transmission of pressure vibrations. The new coefficient that takes into account the ease of transmission of pressure vibrations is a parameter for appropriately detecting the occurrence of cavitation in a state where internal cavities caused by cavitation hinder the transmission of vibrations. The pressure transmission coefficient is indirectly estimated from the suction pressure using the measured value of the suction pressure and the observed state of the pump 12. The pressure transmission coefficient can be approximately one-half to one-third of the suction pressure based on statistical information. For example, the adjustment unit 124 can use one-third of the pressure transmission coefficient.

[0039] Adjustment unit 124 multiplies the coefficient of variation of the suction pressure data by the pressure transmission coefficient to calculate an adjusted coefficient of variation. Adjustment unit 124 then outputs the calculated adjusted coefficient of variation to determination unit 125. That is, adjustment unit 124 adjusts the detection information used to detect the occurrence of cavitation, including the coefficient of variation calculated by coefficient of variation calculation unit 123, using the pressure transmission coefficient, which indicates the ease with which the suction pressure is transmitted.

[0040] For example, if the pressure transmission coefficient is set to one-half or one-third of the suction pressure, the coefficient of variation is multiplied by a large value when the pressure is low, and by a small value when the pressure is high. In other words, when the pressure is low, the coefficient of variation can be increased by multiplication.

[0041] In this regard, when cavitation occurs severely at low pressures, cavities caused by cavitation may impede the transmission of vibrations, resulting in a coefficient of variation that is smaller than the actual value. Therefore, the adjustment unit 124 adjusts the coefficient of variation to an appropriate value by multiplying the coefficient of variation for low pressures, thereby enabling cavitation detection over a wide pressure range. Thus, in order to convert the transmission ease of pressure vibrations, which is expressed as a temporal change (e.g., moment-to-moment changes such as in a differential equation), into a coefficient of variation, which is the amount of fluctuation over a certain period of time, the detection device 102 multiplies the coefficient of variation by approximately one-half to one-third the pressure to calculate a new coefficient, the adjusted coefficient of variation, that takes into account the transmission ease of pressure vibrations. Furthermore, by using this adjusted coefficient of variation, the detection device 102 can apply the same index to any pressure range.

[0042] Determination unit 125 receives the adjusted coefficient of variation as input from coefficient of variation calculation unit 123. Determination unit 125 determines that cavitation has occurred in pump 12 when the acquired adjusted coefficient of variation exceeds a predetermined reference coefficient of variation. The reference coefficient of variation is a threshold value used to detect the occurrence of cavitation. Here, determination unit 125 can use, as the reference coefficient of variation, the coefficient of variation of suction pressure data acquired by suction pressure acquisition unit 121 prior to the above-mentioned detection period, or a coefficient obtained by performing a predetermined calculation on this coefficient of variation (for example, multiplying by a predetermined constant).

[0043] For example, the determination unit 125 may use, as the reference coefficient of variation, a coefficient obtained by multiplying the coefficient of variation of the suction pressure data obtained when a certain time, such as several tens of seconds to several minutes, has elapsed since the start of operation of the pump 12 and the operation is stable by a certain number. Here, the "state of stable operation" refers to, for example, a state in which the fluctuations in the suction pressure data of the pump 12 are within a certain value. Note that the determination unit 125 may repeatedly set the reference coefficient of variation at predetermined timings according to, for example, the operating state of the pump 12 or the device 14.

[0044] The determination unit 125 notifies the notification unit 126 of the detection of the occurrence of cavitation. The determination unit 125 may also notify the notification unit 126 of the fact that cavitation has not been detected.

[0045] The notification unit 126 receives notification of the detection of cavitation from the determination unit 125. Then, the notification unit 126 transmits information about the detection of cavitation to the management terminal device 2 to notify the manager of the occurrence of cavitation. The notification unit 126 may also notify the control system of the plant 1 of the occurrence of cavitation.

[0046] FIG. 3 is a diagram showing an example of cavitation detection using an adjusted coefficient of variation. In FIG. 3, the horizontal axis represents suction pressure, and the vertical axis represents the coefficient of variation. The region above the reference coefficient of variation is cavitation occurrence region 201. Curve 202 represents the coefficient of variation calculated by coefficient of variation calculation unit 123 when a centrifugal pump is used. Curve 203 represents the coefficient of variation calculated by coefficient of variation calculation unit 123 when a positive displacement pump is used. As shown by curve 202, the coefficient of variation for the centrifugal pump is included in cavitation occurrence region 201 in region 205, so cavitation is detected.

[0047] In contrast, in the case of a positive displacement pump, as shown by curve 203, the coefficient of variation calculated when the pressure is low does not fall within cavitation occurrence region 201. This is because when the pressure is low, saturated steam due to cavitation does not disappear, so the pressure is not accurately transmitted to detection device 102, and variation coefficient calculation unit 123 calculates a low coefficient of variation. Therefore, adjustment unit 124 multiplies the coefficient of variation calculated by variation coefficient calculation unit 123 by the pressure transmission coefficient to calculate an adjusted coefficient of variation shown by curve 204. Since curve 204 representing the adjusted coefficient of variation falls within cavitation occurrence region 201 even when the pressure is low and the pressure is not accurately transmitted, determination unit 125 can detect cavitation even when the pressure is low.

[0048] [Detection process flow] 4 is a flowchart of the process of detecting the occurrence of cavitation by the detection system according to Embodiment 1. Next, the flow of the process of detecting the occurrence of cavitation by the detection system 100 according to Embodiment 1 will be described with reference to FIG.

[0049] The suction pressure measuring device 101 measures the suction pressure of the pump 12 (step S1). After that, the suction pressure measuring device 101 transmits the measurement result to the detection device 102 as suction pressure data.

[0050] The suction pressure acquisition unit 121 acquires the suction pressure data transmitted from the suction pressure measuring device 101 (step S2). Thereafter, the suction pressure acquisition unit 121 stores the suction pressure data in the storage unit 122.

[0051] The variation coefficient calculation unit 123 acquires the suction pressure data for the detection period from the storage unit 122. Next, the variation coefficient calculation unit 123 calculates the average value of the suction pressure data (step S3).

[0052] Next, the coefficient of variation calculation unit 123 calculates the standard deviation of the suction pressure data (step S4).

[0053] Next, the variation coefficient calculation unit 123 calculates the variation coefficient using the average value and the standard deviation (step S5), and then outputs the calculated variation coefficient to the adjustment unit .

[0054] The adjustment unit 124 multiplies the coefficient of variation by a pressure transfer coefficient stored in advance to calculate an adjusted coefficient of variation (step S6). The pressure transfer function can be, for example, a value approximately equal to one-half to one-third of the suction pressure data. The adjustment unit 124 then outputs the calculated adjusted coefficient of variation to the determination unit 125.

[0055] The determination unit 125 determines whether the adjusted coefficient of variation acquired from the adjustment unit 124 exceeds a predetermined standard coefficient of variation (step S7). If the adjusted coefficient of variation is equal to or less than the standard coefficient of variation (step S7: No), the determination unit 125 determines that cavitation is not occurring. Then, the detection process returns to step S1.

[0056] On the other hand, if the adjusted coefficient of variation exceeds the reference coefficient of variation (step S7: Yes), the determination unit 125 determines that cavitation has occurred (step S8). Thereafter, the determination unit 125 notifies the notification unit 126 that cavitation has been detected.

[0057] Next, upon receiving the notification of the detection of cavitation, the notification unit 126 transmits information about the occurrence of cavitation to the management terminal device 2, thereby notifying the manager of the occurrence of cavitation (step S9).

[0058] [effect] As described above, the detection device 102 according to this embodiment calculates the coefficient of variation of the pump 12's follow-up pressure using the raw value of the suction pressure, and then calculates an adjusted coefficient of variation by adjusting the coefficient of variation using the pressure transmission coefficient to take into account the ease with which pressure vibrations are transmitted. The detection device 102 then compares the calculated adjusted coefficient of variation with the reference coefficient of variation to detect cavitation.

[0059] Because positive displacement pumps have a high suction force, their pump suction pressure is generally lower than that of centrifugal pumps when the inflow rate to the pump is low. Incidentally, in the case of centrifugal pumps, even if the pump tries to suck in fluid under the same conditions, it is unable to do so successfully, and the pump suction pressure generally does not decrease. When the pump suction pressure decreases, as in the case of the positive displacement pump described above, the cavities caused by cavitation within the pump are less likely to return to their original state, but are more likely to return to their original state at the outlet. In other words, the cavity area expands within the pump. This expanded cavity acts as a cushion, absorbing and reflecting pressure, making it difficult for pressure fluctuations to be accurately transmitted to the sensor, and the detection device will calculate a low pressure fluctuation coefficient.

[0060] As described above, when the pressure inside the pump is extremely low, either locally or globally, the coefficient of variation used to determine whether cavitation has occurred can be small, even though the cavitation causes the liquid to become turbulent and the pressure fluctuations to be large. This makes it difficult for conventional detection devices to accurately detect the occurrence of cavitation.

[0061] In contrast, the detection device 102 according to this embodiment can detect the occurrence of cavitation even when the pressure inside the pump 12 is extremely low overall or locally. This makes it possible to improve the accuracy of detecting the occurrence of cavitation. In particular, when a positive displacement pump is used as the pump 12, it is possible to improve the accuracy of detecting the occurrence of cavitation.

[0062] FIG. 5 is a diagram showing the calculation of the coefficient of variation using a conventional detection device. FIG. 6 is a diagram showing the calculation of the coefficient of variation using the detection device according to the first embodiment. Here, with reference to FIGS. 5 and 6, an improvement in the accuracy of cavitation detection using the detection device 102 according to the present embodiment will be described. Graph 211 in FIG. 5 represents the passage of time on the horizontal axis and the coefficient of variation on the vertical axis. Graph 221 in FIG. 6 represents the passage of time on the horizontal axis and the adjusted coefficient of variation on the vertical axis. Graph 212 in FIG. 5 and graph 222 in FIG. 6 represent the passage of time on the horizontal axis and the amount of bubbles observed in pump 12 on the vertical axis. FIGS. 5 and 6 show the results of observing bubbles over time under similar conditions.

[0063] In the case of a conventional detection device used to detect cavitation without adjusting the coefficient of variation, the coefficient of variation is small in section 213 of graph 211 in Figure 5, but a moderate amount of bubbles are observed in the corresponding section 215 of graph 212. Similarly, the coefficient of variation is small in section 214 of graph 211, but a large amount of bubbles are observed in the corresponding section 216 of graph 212. In other words, even though cavitation is actually occurring as shown in sections 215 and 216, the conventional detection device cannot detect cavitation in sections 213 and 214 because the coefficient of variation is small. This is because the suction pressure is not transmitted due to the large number of bubbles when the suction pressure is extremely low.

[0064] In contrast, in the case of detection device 102 according to this embodiment, a moderate amount of bubbles occurs in section 225 of graph 222 in FIG. 6, similar to section 215 of graph 211 in FIG. 5, but the adjusted coefficient of variation in the corresponding section 223 of graph 221 is large. Similarly, a large amount of bubbles occurs in section 226 of graph 222 in FIG. 6, similar to section 216 of graph 211 in FIG. 5, but the adjusted coefficient of variation in the corresponding section 224 of graph 221 is large. In other words, even if many bubbles occur when the suction pressure is extremely low, detection device 102 according to this embodiment can detect cavitation by calculating a large adjusted coefficient of variation, as shown in sections 223 and 224. In this way, detection device 102 according to this embodiment can detect the occurrence of cavitation even when the suction pressure is extremely low, thereby improving the accuracy of detecting the occurrence of cavitation.

[0065] [Embodiment 2] Next, a second embodiment will be described. Detection device 102 according to this embodiment detects the occurrence of cavitation when the suction pressure is extremely low by lowering the reference coefficient of variation in response to low suction pressure and expanding the cavitation occurrence region. Detection device 102 according to this embodiment is also represented by the block diagram in Figure 2. In the following explanation, explanations of the operation of each part that is the same as in the first embodiment will be omitted.

[0066] Adjustment unit 124 receives an input of the coefficient of variation of the suction pressure data from coefficient of variation calculation unit 123. Adjustment unit 124 according to this embodiment stores in advance a pressure transmission coefficient for adjusting the cavitation region, which is a coefficient for adjusting the reference coefficient of variation in consideration of the ease with which pressure vibrations are transmitted. This pressure transmission coefficient for adjusting the cavitation region is indirectly estimated from the measured value of the suction pressure and the observed results of the state of pump 12. The pressure transmission coefficient for adjusting the cavitation region can be expressed as a function that approaches 1 as the suction pressure increases and approaches 0 as the suction pressure decreases, depending on the suction pressure.

[0067] In this embodiment, adjustment unit 124 has a predetermined reference coefficient of variation. Adjustment unit 124 then calculates an adjusted reference coefficient of variation by multiplying the reference coefficient of variation by a pressure transmission coefficient for adjusting the cavitation region according to the suction pressure. As a result, adjustment unit 124 changes cavitation occurrence region 201 so that it widens downward as the suction pressure decreases. Adjustment unit 124 then outputs the calculated adjusted reference coefficient of variation together with the coefficient of variation to determination unit 125.

[0068] That is, the reference coefficient of variation is one of the detection information used to detect the occurrence of cavitation. Then, the adjustment unit 124 adjusts the reference coefficient of variation, which is a predetermined threshold value used to detect the occurrence of cavitation, included in the detection information, to calculate the adjusted reference coefficient of variation.

[0069] Determination unit 125 receives input of the coefficient of variation and the adjusted reference coefficient of variation from coefficient of variation calculation unit 123. Then, determination unit 125 compares the acquired coefficient of variation with the adjusted reference coefficient of variation. Determination unit 125 determines that cavitation has occurred in pump 12 when the coefficient of variation exceeds the calculated adjusted reference coefficient of variation. Because cavitation occurrence region 201 is adjusted so that the adjusted reference coefficient of variation is low when the pressure is low, determination unit 125 can detect cavitation even when the calculated coefficient of variation is low due to low suction pressure and difficulty in properly transmitting pressure.

[0070] As described above, the detection device 102 according to this embodiment adjusts the basic coefficient of variation using the pressure transmission coefficient for adjusting the cavitation region. In this way, even if the basic coefficient of variation is adjusted to expand the cavitation occurrence region when pressure is low, it is possible to detect the occurrence of cavitation when the pressure inside the pump 12 is extremely low overall or locally. Therefore, even if a method of expanding the cavitation occurrence region is used as in the detection device 102 according to this embodiment, it is possible to improve the accuracy of detecting the occurrence of cavitation.

[0071] [Embodiment 3] Next, a third embodiment will be described. In each of the above embodiments, the adjustment unit 124 previously stored a pressure transfer coefficient estimated indirectly from the suction pressure using the relationship between the suction pressure and the amount of foam generated. In this embodiment, the detection device 102 calculates the pressure transfer coefficient. FIG. 7 is a block diagram showing details of a detection system according to the third embodiment. The detection device 102 included in the detection system 100 according to this embodiment has a pressure transfer coefficient calculation unit 127 in addition to the units shown in FIG. 2. In the following description, descriptions of functions similar to those of the units in the first embodiment will be omitted.

[0072] The database 3 holds past statistical information regarding the pump 12. For example, the database 3 stores observation results of conditions such as the suction pressure of the pump 12 and the amount of foam in the pump 12 in association with each other as information for each time.

[0073] The pressure transmission coefficient calculation unit 127 acquires statistical information about the pump 12 from the database 3. Then, the pressure transmission coefficient calculation unit 127 uses the acquired statistical information about the pump 12 to calculate a pressure transmission coefficient that takes into account the ease with which pressure is transmitted.

[0074] For example, the pressure transmission coefficient calculation unit 127 performs machine learning using AI (Artificial Intelligence) using the measurement value of the suction pressure and the observation results of the amount of foam in the pump 12 as learning data, and generates a machine learning model that takes the suction pressure as input and outputs a pressure transmission coefficient. Then, the pressure transmission coefficient calculation unit 127 acquires the suction pressure from the storage unit 122, inputs the acquired suction pressure into the machine learning model, and acquires the pressure transmission coefficient. Thereafter, the pressure transmission coefficient calculation unit 127 outputs the acquired pressure transmission coefficient to the adjustment unit 124.

[0075] Alternatively, the pressure transmission coefficient calculation unit 127 can calculate the pressure transmission coefficient in the following manner.

[0076] For example, the pressure transfer coefficient calculation unit 127 may indirectly calculate the pressure transfer coefficient from the flow rate using the relationship between the dynamic pressure calculated from the flow rate and the static pressure calculated from the suction pressure. The principle of calculating this pressure transfer function is explained below. The energy of a liquid is composed of dynamic pressure and static pressure. Dynamic pressure can be measured as the flow rate, and static pressure can be measured as the side pressure. Here, Bernoulli's theorem is a theorem that states that energy is conserved along a streamline in the steady flow of an ideal fluid. Therefore, the pressure transfer coefficient calculation unit 127 can estimate the pressure trend from the flow rate using Bernoulli's theorem and calculate a new coefficient that takes into account the pressure fluctuation coefficient and the ease of transmission of pressure vibrations. Specifically, the pressure transfer coefficient calculation unit 127 can calculate the pressure transfer function based on the fact that the relationship between dynamic pressure and static pressure is disrupted by a decrease in density in the fluid due to the generation of cavities caused by cavitation. The fluctuation coefficient calculation unit 123 can also calculate the fluctuation coefficient from the flow rate using the relationship between the dynamic pressure calculated from the flow rate and the static pressure calculated from the suction pressure.

[0077] Alternatively, the pressure transmission coefficient calculation unit 127 may calculate the pressure transmission coefficient from the relationship between the time from when the pump 12 starts operating until when it stops operating and the suction pressure. The principle of calculating this pressure transmission function will be explained below. Ideally, pressure changes in accordance with the timing at which the pump 12 starts operating. However, in reality, a discrepancy in the pressure change occurs due to the pressure propagation of the liquid, in addition to the distance from the pump 12 to the suction pressure measuring device 101. For example, when cavitation occurs, numerous cavities are generated by bubbles, which reduces the viscosity of the liquid and slows the pressure transmission speed. Therefore, the pressure transmission coefficient calculation unit 127 uses this discrepancy in the pressure change to determine the ease of transmission of pressure vibrations, and calculates the pressure transmission coefficient based on the determined ease of transmission of pressure vibrations.

[0078] The pressure transmission coefficient calculation unit 127 may also calculate the pressure transmission coefficient from basic information about the fluid, such as its temperature, viscosity, and density. The pressure transmission coefficient calculation unit 127 can calculate the pressure transmission coefficient using one or a combination of the basic information. The principle behind calculating this pressure transmission function is explained below. The likelihood of cavities occurring in a liquid under low pressure varies depending on the liquid's temperature, viscosity, and density. For example, a liquid with a low boiling point is less likely to develop severe cavities due to cavitation, which impedes pressure transmission, while a liquid with a high temperature is more likely to develop severe cavities due to cavitation, which impedes pressure transmission. In this way, the pressure transmission coefficient calculation unit 127 can infer the ease with which pressure vibrations propagate from the liquid's basic information, enabling it to calculate the pressure transmission coefficient.

[0079] Alternatively, the pressure transfer coefficient calculation unit 127 may calculate the pressure transfer coefficient based on information from a pressure gauge located farther from the pump 12 than the suction pressure measuring device 101. The principle of calculating this pressure transfer function will be described below. Ideally, pressure changes propagate from an earlier stage to a later stage in the process. By utilizing this pressure propagation and comparing changes in the values ​​of pressure gauges located farther from the suction pressure measuring device 101, the pressure transfer coefficient calculation unit 127 can determine the ease of transmission of pressure vibrations and calculate the pressure transfer coefficient. For example, when cavitation occurs due to a bend in the pipe 11, the density of the fluid changes. Therefore, the pressure transfer coefficient calculation unit 127 can estimate the change in liquid density from differences in the timing of the pressure changes, determine the ease of transmission of pressure vibrations, and calculate the pressure transfer coefficient.

[0080] Here, the pressure transmission coefficient calculation unit 127 may calculate the pressure transmission coefficient in advance, or may calculate the pressure transmission coefficient each time the variation coefficient is calculated by the variation coefficient calculation unit 123. Alternatively, the pressure transmission coefficient calculation unit 127 may repeatedly calculate the pressure transmission coefficient periodically or when a predetermined condition is satisfied.

[0081] [Detection process flow] Fig. 8 is a flowchart of the process of detecting the occurrence of cavitation by the detection system according to Embodiment 3. Next, the flow of the process of detecting the occurrence of cavitation by the detection system 100 according to Embodiment 3 will be described with reference to Fig. 8.

[0082] The suction pressure measuring device 101 measures the suction pressure of the pump 12 (step S11). After that, the suction pressure measuring device 101 transmits the measurement result to the detection device 102 as suction pressure data.

[0083] The suction pressure acquisition unit 121 acquires the suction pressure data transmitted from the suction pressure measuring device 101 (step S12). Thereafter, the suction pressure acquisition unit 121 stores the suction pressure data in the storage unit 122.

[0084] The variation coefficient calculation unit 123 acquires the suction pressure data for the detection period from the storage unit 122. Next, the variation coefficient calculation unit 123 calculates the average value of the suction pressure data (step S13).

[0085] Next, the coefficient of variation calculation unit 123 calculates the standard deviation of the suction pressure data (step S14).

[0086] Next, the variation coefficient calculation unit 123 calculates the variation coefficient using the average value and the standard deviation (step S15), and then outputs the calculated variation coefficient to the adjustment unit .

[0087] The pressure transmission coefficient calculation unit 127 acquires past statistical information about the pump 12 from the database 3 and calculates the pressure transmission coefficient based on the suction pressure data (step S16). For example, the adjustment unit 124 performs machine learning on the past statistical information to generate a machine learning model, inputs the suction pressure data into the generated machine learning model, and calculates the pressure transmission coefficient. The pressure transmission coefficient calculation unit 127 then outputs the calculated pressure transmission coefficient to the adjustment unit 124.

[0088] Next, adjustment unit 124 calculates an adjusted coefficient of variation by multiplying the coefficient of variation acquired from coefficient of variation calculation unit 123 by the pressure transmission coefficient acquired from pressure transmission coefficient calculation unit 127 (step S17). Thereafter, adjustment unit 124 outputs the calculated adjusted coefficient of variation to determination unit 125.

[0089] The determination unit 125 determines whether the adjusted coefficient of variation acquired from the adjustment unit 124 exceeds a predetermined standard coefficient of variation (step S18). If the adjusted coefficient of variation is equal to or less than the standard coefficient of variation (step S18: No), the determination unit 125 determines that cavitation is not occurring. Then, the detection process returns to step S11.

[0090] On the other hand, if the adjusted coefficient of variation exceeds the reference coefficient of variation (step S18: Yes), the determination unit 125 determines that cavitation has occurred (step S19). Thereafter, the determination unit 125 notifies the notification unit 126 of the detection of cavitation.

[0091] Next, upon receiving the notification of the detection of cavitation, the notification unit 126 transmits information about the occurrence of cavitation to the management terminal device 2, thereby notifying the manager of the occurrence of cavitation (step S20).

[0092] As described above, the detection device 102 according to this embodiment calculates the pressure transmission coefficient and adjusts the coefficient of variation using the calculated pressure transmission coefficient. This makes it easy to calculate the pressure transmission coefficient according to the state of the pump 12, and also makes it possible to detect cavitation using the pressure transmission coefficient according to the state of the pump 12, thereby enabling more accurate detection of the occurrence of cavitation.

[0093] [system] The information including the processing procedures, control procedures, specific names, various data and parameters shown in the above documents and drawings can be changed arbitrarily unless otherwise specified.

[0094] Furthermore, the components of each device shown in the figure are functional concepts and do not necessarily have to be physically configured as shown. In other words, the specific form of distribution and integration of each device is not limited to that shown. In other words, all or part of them can be functionally or physically distributed and integrated in any unit depending on various loads, usage conditions, etc.

[0095] For example, all or part of the functions of the suction pressure measuring device 101 may be incorporated into the detection device 102. Furthermore, the detection device 102 may be included in the management terminal device 2.

[0096] Furthermore, each processing function performed by each device can be realized, in whole or in part, by a CPU (Central Processing Unit) and a program analyzed and executed by the CPU, or can be realized as hardware using wired logic.

[0097] [Hardware] Next, an example of the hardware configuration of the detection device 102 will be described. Fig. 9 is a hardware configuration diagram of the detection device. As shown in Fig. 9, the detection device 102 has a processor 91, a memory 92, a communication device 93, and an HDD (Hard Disk Drive) 94. The processor 91 is connected to the memory 92, the communication device 93, and the HDD 94 via a bus.

[0098] The communication device 93 is a network interface card or the like, and is used for communication with other information processing devices. For example, the communication device 93 relays communication between the processor 91 and the suction pressure measuring device 101 and the management terminal device 2.

[0099] The HDD 94 is an auxiliary storage device. The HDD 94 realizes the function of the storage unit 122 illustrated in Fig. 2. The HDD 94 also stores various programs including programs that realize the functions of the suction pressure acquisition unit 121, the variation coefficient calculation unit 123, the adjustment unit 124, the determination unit 125, and the notification unit 126 illustrated in Fig. 2. The HDD 94 may also store various programs including programs that realize the functions of the suction pressure acquisition unit 121, the variation coefficient calculation unit 123, the adjustment unit 124, the determination unit 125, the notification unit 126, and the pressure transmission coefficient calculation unit 127 illustrated in Fig. 7.

[0100] Processor 91 reads out various programs stored in HDD 94, loads them into memory 92, and executes them. As a result, processor 91 realizes the functions of suction pressure acquisition unit 121, variation coefficient calculation unit 123, adjustment unit 124, determination unit 125, and notification unit 126, which are exemplified in Fig. 2. Processor 91 also realizes the functions of suction pressure acquisition unit 121, variation coefficient calculation unit 123, adjustment unit 124, determination unit 125, notification unit 126, and pressure transmission coefficient calculation unit 127, which are exemplified in Fig. 7.

[0101] In this way, the detection device 102 operates as an information processing device that executes various processing methods by reading and executing a program. The detection device 102 can also realize functions similar to those of the above-described embodiments by reading the program from a recording medium using a media reader and executing the read program. Note that the program referred to here is not limited to being executed by the detection device 102. For example, the present invention can also be applied in a similar manner to cases where another computer or server executes a program, or where these execute a program in cooperation with each other.

[0102] This program can be distributed via a network such as the Internet. In addition, this program can be recorded on a computer-readable recording medium such as a hard disk, a flexible disk (FD), a CD-ROM, a magneto-optical disk (MO), or a digital versatile disk (DVD), and can be executed by being read from the recording medium by a computer.

[0103] (application) Furthermore, the pressure transmission coefficient can also be used in the following processes. For example, it can also be applied to frequency analysis. If pressure vibrations are not transmitted due to cavities or the like, the peak of the natural vibration related to an abnormality will also decrease, and it may be difficult to detect the abnormality because it does not exceed the threshold value generally set for anomaly detection. In such cases, too, by adjusting the natural vibration using the pressure transmission coefficient, the peak of the natural vibration can be increased, making it possible to detect an abnormality.

[0104] For example, the detection device 102 may be provided with an anomaly detection unit that acquires the vibration of the pump 12 and detects the peak of the natural vibration by FFT (Fast Fourier Transform) to detect an anomaly when foreign matter adheres to the impeller of the pump 12. However, even in this case, the peak of the natural vibration may be difficult to see when the suction pressure is low. Therefore, the anomaly detection unit can adjust the calculation result using FFT using a pressure transmission coefficient, making it possible to find the peak of the natural vibration even at low pressures.

[0105] Furthermore, the detection device 102 can be provided with an analysis unit that analyzes the vibration of the pipe 11. Here, it is assumed that the vibration of the pipe 11 will decrease when the suction pressure is significantly low. Therefore, the analysis unit can improve the accuracy of detecting the vibration of the pipe 11 by adjusting the vibration of the pipe 11 using the pressure transmission coefficient.

[0106] Furthermore, the detection device 102 may use the unadjusted coefficient of variation to detect signs of failure of the pump 12 or the like or to detect process abnormalities. FIG. 10 is a diagram illustrating process abnormality detection using the coefficient of variation. For example, a process using the pump 12 is normally monitored in region 301 of FIG. 10. When the monitoring status of the process changes to region 302, the coefficient of variation decreases, indicating that the amount of pressure fluctuation is smaller than in the normal monitoring state. When the coefficient of variation is small, the impeller of the pump 12 is worn, i.e., the edge of the impeller that scoops out the fluid is worn, causing pressure fluctuations to be smaller than normal, making it difficult for the pump 12 to deliver the fluid.

[0107] Therefore, the detection device 102 may have a pump abnormality detection unit that detects an abnormality in the process that uses the pump 12 based on the coefficient of variation. The pump abnormality detection unit acquires the coefficient of variation from the coefficient of variation calculation unit 123. Then, when the coefficient of variation is smaller than a predetermined threshold, the pump abnormality detection unit determines that the time to replace the impeller of the pump 12 is approaching. Alternatively, the pump abnormality detection unit may determine that the time to replace the impeller of the pump 12 is approaching when the difference in the coefficient of variation from the normal monitoring state is larger than a predetermined threshold.

[0108] Furthermore, by recording the relationship between the coefficient of variation and each component of the pump 12 at the timing of replacement and maintenance, the relationship between pressure and coefficient of variation can be evaluated more precisely, and future replacement timing can be more accurately estimated without disassembling and inspecting the equipment. This eliminates the need for disassembly and inspection, which would require several million yen per pump 12, for example. These are application examples of mid- to long-term (several years) deterioration diagnosis of equipment.

[0109] Another example of a short-term application is process anomaly detection. Specifically, if the coefficient of variation fluctuates over a short period of time under the same pressure, it is possible that the viscosity associated with the suction pressure fluctuation has changed. It is therefore possible to infer a process anomaly from the viscosity estimation. That is, the detection device 102 may have a process anomaly detection unit that detects a sudden change in the coefficient of variation under the same suction pressure, infers the occurrence of a viscosity change, and determines that a process anomaly has occurred. For example, the process anomaly detection unit can determine that a sudden change in the coefficient of variation has occurred if the value obtained by dividing the difference in the coefficient of variation under the same suction pressure by the time interval exceeds an upper threshold or falls below a lower threshold.

[0110] Furthermore, the detection device 102 may store information related to the pump 12, such as trend information on the cumulative time of cavitation occurrence, obtained by cavitation detection. By referring to the trend information on the cumulative time of cavitation occurrence stored in the detection device 102, the administrator can understand the cavitation occurrence trend, identify pumps 12 that require overhaul and inspection, and plan maintenance schedules.

[0111] FIG. 11 is a diagram showing an example of cavitation-related statistical information. Here, an example will be described in which pumps A to D are present. Graph 311 shows the pump operation time for one month. In graph 311, the vertical axis represents the pump type and the horizontal axis represents the operation time. Graph 312 shows the cavitation occurrence rate for one month. In graph 312, the vertical axis represents the pump type and the horizontal axis represents the cavitation occurrence rate. Graph 313 shows the trend of cavitation occurrence for pump C. In graph 313, the horizontal axis represents each month and the cavitation occurrence rate. For example, the detection device 102 may store graphs 311 to 313.

[0112] By referring to the graph 311 stored in the detection device 102, the administrator can see that the operating times of pumps A, B, C, and D are long in this order. Maintenance is generally performed according to the cumulative operating time of the pump 12, and the administrator can determine that the maintenance priority is highest, starting with pump A.

[0113] Furthermore, the administrator can check the cavitation occurrence rate by referring to the graph 312 of the detection device 102, and can confirm that the cavitation occurrence rate of pump C is higher than that of the other pumps A, B, and D.

[0114] Furthermore, by focusing on Pump C, the manager can see by referring to graph 313 that the cavitation occurrence rate of Pump C is on the rise. From this trend, the manager can predict that the cavitation occurrence rate of Pump C will also increase in the following months. Furthermore, since large cavitations have occurred in the most recent month, the manager can conclude that the damage to Pump C has progressed further. By adding the cavitation occurrence rate to the normal maintenance guideline obtained from the cumulative pump operating time, the manager can more accurately estimate the timing and prioritize pump maintenance.

[0115] Some examples of combinations of the disclosed technical features are set out below. (1) a pressure acquisition unit that acquires pressure data indicating the pressure of the pump; a variation coefficient calculation unit that calculates a variation coefficient indicating a fluctuation range of the magnitude of the pressure of the pump based on the pressure data acquired by the pressure acquisition unit; an adjustment unit that adjusts detection information used to detect the occurrence of cavitation, including the coefficient of variation calculated by the coefficient of variation calculation unit, using a pressure transmission coefficient that indicates ease of pressure transmission in the pump; and a determination unit that detects occurrence of cavitation in the pump based on the detection information after adjustment by the adjustment unit; and A detection device comprising: (2) The detection device according to (1), wherein the pressure acquisition unit acquires any one of the suction pressure, priming pressure, drain pressure, or discharge pressure of the pump as the pressure of the pump. (3) The detection device according to (1) or (2), wherein the adjustment unit adjusts the coefficient of variation using the pressure transmission coefficient to calculate an adjusted coefficient of variation. (4) The detection device described in (3) is characterized in that the judgment unit judges that cavitation has occurred in the pump when the adjusted coefficient of variation exceeds a predetermined standard coefficient of variation included in the detection information. (5) the adjustment unit adjusts a reference coefficient of variation, which is a predetermined threshold value used for detecting the occurrence of cavitation, included in the detection information, to calculate an adjusted reference coefficient of variation; The detection device according to any one of (1) to (4), wherein the determination unit determines that cavitation has occurred in the pump when the coefficient of variation exceeds the reference coefficient of variation. (6) The detection device according to any one of (1) to (5), further comprising a pressure transfer coefficient calculation unit that calculates the pressure transfer coefficient. (7) The detection device according to (6), wherein the pressure transmission coefficient calculation unit calculates the pressure transmission coefficient based on the pressure of the pump and the occurrence state of the cavitation. (8) The detection device described in (6) is characterized in that the pressure transmission coefficient calculation unit calculates the pressure transmission coefficient based on the flow rate using the relationship between the dynamic pressure obtained from the flow rate of the pump and the static pressure obtained from the pressure of the pump. (9) The detection device described in (8) is characterized in that the variation coefficient calculation unit calculates the variation coefficient based on the flow rate using the relationship between the dynamic pressure obtained from the flow rate of the pump and the static pressure obtained from the pressure of the pump. (10) The detection device described in (6) is characterized in that the pressure transmission coefficient calculation unit calculates the pressure transmission coefficient based on the relationship between the time from when the pump starts to when it stops and the pressure of the pump. (11) The detection device according to (6), wherein the pressure transmission coefficient calculation unit calculates the pressure transmission coefficient based on basic information about the fluid sent by the pump. (12) The detection device described in (6) is characterized in that the pressure transmission coefficient calculation unit calculates the pressure transmission coefficient based on information on the measured pressure measured by a second pressure gauge that is positioned farther from the pump than the first pressure gauge that measured the pressure of the pump. (13) Detection device Acquire pressure data indicating the pressure of the pump, Calculating a coefficient of variation indicating a fluctuation range of the magnitude of the pressure of the pump based on the acquired pressure data; adjusting the detection information used to detect the occurrence of cavitation, including the calculated coefficient of variation, using a pressure transmission coefficient that indicates the ease with which pressure in the pump is transmitted; Based on the adjusted detection information, occurrence of cavitation in the pump is detected. A detection method characterized by: (14) A detection system having a pressure measuring device and a detection device, the pressure measuring device measures the pressure of the pump and generates pressure data indicative of the measurement result; The detection device is a pressure acquisition unit that acquires the pressure data from the pressure measuring device; a variation coefficient calculation unit that calculates a variation coefficient indicating a fluctuation range of the magnitude of the pressure of the pump based on the pressure data acquired by the pressure acquisition unit; an adjustment unit that adjusts detection information used to detect the occurrence of cavitation, including the coefficient of variation calculated by the coefficient of variation calculation unit, using a pressure transmission coefficient that indicates ease of pressure transmission in the pump; and a determination unit that detects occurrence of cavitation in the pump based on the detection information after adjustment by the adjustment unit. A detection system comprising: [Explanation of symbols]

[0116] 1. Plant 2. Management terminal 11 Piping 12 Pump 13 Pressure meter 14 Equipment 15 Liquid source 100 Detection System 101 Suction pressure measuring device 102 Detection device 121 Suction pressure acquisition unit 122 Storage section 123 Coefficient of variation calculation section 124 Adjustment section 125 Judgment section 126 Information Department 127 Pressure transmission coefficient calculation section

Claims

1. a pressure acquisition unit that acquires pressure data indicating the pressure of the pump; a variation coefficient calculation unit that calculates a variation coefficient indicating a fluctuation range of the magnitude of the pressure of the pump based on the pressure data acquired by the pressure acquisition unit; an adjustment unit that calculates an adjusted coefficient of variation by multiplying the coefficient of variation calculated by the coefficient of variation calculation unit during the detection period and the reference coefficient of variation, which is a threshold value used to detect the occurrence of cavitation, calculated by the coefficient of variation calculation unit in a state where the fluctuation of the pressure data after a certain period has elapsed since the start of operation of the pump, by a pressure transmission coefficient whose magnitude is inversely proportional to the pressure of the pump and which represents the ease with which the pressure of the pump is transmitted, and adjusts the detection information; a determination unit that compares the adjusted coefficient of variation with the reference coefficient of variation to detect occurrence of cavitation in the pump; A detection device comprising:

2. a pressure acquisition unit that acquires pressure data indicating the pressure of the pump; a variation coefficient calculation unit that calculates a variation coefficient indicating a fluctuation range of the magnitude of the pressure of the pump based on the pressure data acquired by the pressure acquisition unit; an adjustment unit that calculates an adjusted reference coefficient of variation by multiplying the reference coefficient of variation, which is a threshold value used to detect the occurrence of cavitation and which is calculated by the coefficient of variation calculation unit in a state where the fluctuation of the pressure data after a certain period of time has elapsed since the start of operation of the pump, by a pressure transmission coefficient that is proportional to the pressure of the pump within a range of greater than 0 and less than or equal to 1 and represents the ease with which pressure of the pump is transmitted, to the detection information used to detect the occurrence of cavitation, and which includes the coefficient of variation calculated by the coefficient of variation calculation unit during a detection target period and a reference coefficient of variation that is a threshold value used to detect the occurrence of cavitation and which is calculated by the coefficient of variation calculation unit in a state where the fluctuation of the pressure data after a certain period of time has elapsed since the start of operation of the pump is within a certain value, thereby adjusting the detection information; a determination unit that compares the coefficient of variation with the adjusted reference coefficient of variation to detect occurrence of cavitation in the pump; A detection device comprising:

3. 3. The detection device according to claim 1, wherein the pressure acquisition unit acquires any one of a suction pressure, a priming pressure, a drain pressure, and a discharge pressure of the pump as the pressure of the pump.

4. 2. The detection device according to claim 1, wherein the determination unit determines that cavitation has occurred in the pump when the adjusted coefficient of variation exceeds a predetermined reference coefficient of variation included in the detection information.

5. 3. The detection device according to claim 2, wherein the determination unit determines that cavitation has occurred in the pump when the coefficient of variation exceeds the reference coefficient of variation.

6. 3. The detection device according to claim 1, further comprising a pressure transfer coefficient calculation unit that calculates the pressure transfer coefficient.

7. 7. The detection device according to claim 6, wherein the pressure transfer coefficient calculation unit calculates the pressure transfer coefficient based on the pressure of the pump and the occurrence state of the cavitation.

8. The detection device according to claim 6, wherein the pressure transmission coefficient calculation unit calculates the pressure transmission coefficient based on the flow rate using a relationship between a dynamic pressure calculated from the flow rate of the pump and a static pressure calculated from the pressure of the pump.

9. The detection device according to claim 8, wherein the coefficient of variation calculation unit calculates the coefficient of variation based on the flow rate using a relationship between a dynamic pressure calculated from the flow rate of the pump and a static pressure calculated from the pressure of the pump.

10. 7. The detection device according to claim 6, wherein the pressure transmission coefficient calculation unit calculates the pressure transmission coefficient based on a relationship between the time from when the pump starts to when the pump stops and the pressure of the pump.

11. 7. The detection device according to claim 6, wherein the pressure transmission coefficient calculation unit calculates the pressure transmission coefficient based on basic information about the fluid sent by the pump.

12. The detection device according to claim 6, characterized in that the pressure transmission coefficient calculation unit calculates the pressure transmission coefficient based on information about a measured pressure measured by a second pressure gauge that is positioned farther from the pump than a first pressure gauge that measures the pressure of the pump.

13. Detection device Acquire pressure data indicating the pressure of the pump, Calculating a coefficient of variation indicating a fluctuation range of the magnitude of the pressure of the pump based on the acquired pressure data; the detection information used to detect the occurrence of cavitation includes the coefficient of variation calculated during the detection period and a reference coefficient of variation, which is a threshold value used to detect the occurrence of cavitation and is calculated when the fluctuation of the pressure data after a certain period has elapsed since the start of operation of the pump is within a certain value; and the detection information is adjusted by multiplying the coefficient of variation by a pressure transmission coefficient, the magnitude of which is inversely proportional to the pressure of the pump and which indicates the ease with which the pressure of the pump is transmitted; The adjusted coefficient of variation is compared with the reference coefficient of variation to detect occurrence of cavitation in the pump. A detection method characterized by:

14. A detection system having a pressure measuring device and a detection device, the pressure measuring device measures the pressure of the pump and generates pressure data indicative of the measurement result; The detection device is a pressure acquisition unit that acquires the pressure data from the pressure measuring device; a variation coefficient calculation unit that calculates a variation coefficient indicating a fluctuation range of the magnitude of the pressure of the pump based on the pressure data acquired by the pressure acquisition unit; an adjustment unit that calculates an adjusted coefficient of variation by multiplying the coefficient of variation calculated by the coefficient of variation calculation unit during the detection period and the reference coefficient of variation, which is a threshold value used to detect the occurrence of cavitation, calculated by the coefficient of variation calculation unit in a state where the fluctuation of the pressure data after a certain period has elapsed since the start of operation of the pump, by a pressure transmission coefficient whose magnitude is inversely proportional to the pressure of the pump and which represents the ease with which the pressure of the pump is transmitted, and adjusts the detection information; a determination unit that compares the adjusted coefficient of variation calculated by the adjustment unit with the reference coefficient of variation to detect occurrence of cavitation in the pump. A detection system comprising:

Images