Fault detection method and device, electronic equipment and storage medium

Abstract

The invention discloses a fault detection method and device, electronic equipment and a storage medium, and relates to the technical field of fault detection. The method comprises the steps that the theoretical water delivery pressure of the feed pump is calculated according to the real-time total flow of the feed pump; calculating the theoretical main pipeline flow of the feed pump based on the theoretical water delivery pressure; calculating the theoretical input power of the feed pump based on the theoretical main pipeline flow and the theoretical water delivery pressure; performing cavitation verification on the feed pump according to the theoretical main pipeline flow to obtain a cavitation verification result; and under the condition that the cavitation verification result is passed, determining a fault detection result of the water feed pump according to the theoretical water delivery pressure, the theoretical main pipeline flow, the theoretical input power and respective corresponding actual values. According to the technical scheme, the accuracy of the fault detection result of the water feeding pump is improved.

Description

TECHNICAL FIELD

[0001] Embodiments of the present application relate to the technical field of fault detection, and in particular to a fault detection method and device, electronic equipment and storage medium. BACKGROUND

[0002] As the core power equipment in industrial systems such as coal-fired units and chemical plants, the running state of the feed water pump directly affects the stability, safety and operating efficiency of the entire system. Therefore, accurate and reliable fault detection of the feed water pump is the key to ensuring the continuous and stable operation of the industrial system, and has important practical significance.

[0003] However, the existing fault detection methods for feed water pumps mostly only use the threshold of a single parameter (such as flow or pressure) to make fault judgments. Although this method is simple to implement, the abnormality of a single parameter may be caused by non-fault factors such as working condition fluctuations and pipeline interference, which is easy to produce misjudgment and thus reduces the accuracy of detection.

[0004] Therefore, there is an urgent need to propose a new method to solve the above problems. SUMMARY

[0005] The present application provides a fault detection method, device, electronic equipment and storage medium to improve the accuracy of the fault detection results of the feed water pump.

[0006] In a first aspect, the embodiments of the present application provide a fault detection method, which comprises:

[0007] calculating the theoretical water delivery pressure of the feed water pump according to the real-time total flow of the feed water pump;

[0008] calculating the theoretical main pipeline flow of the feed water pump based on the theoretical water delivery pressure;

[0009] calculating the theoretical input power of the feed water pump based on the theoretical main pipeline flow and the theoretical water delivery pressure;

[0010] performing cavitation verification on the feed water pump according to the theoretical main pipeline flow to obtain a cavitation verification result;

[0011] if the cavitation verification result is passed, determining the fault detection result of the feed water pump according to the theoretical water delivery pressure, the theoretical main pipeline flow, the theoretical input power and their respective actual values.

[0012] The technical scheme of the embodiment of the present application first calculates the theoretical water delivery pressure of the feed water pump according to the real-time total flow of the feed water pump, thereby providing a data basis for subsequent calculation of the theoretical main pipeline flow. Then, the theoretical main pipeline flow of the feed water pump is calculated based on the theoretical water delivery pressure, thereby providing a data basis for subsequent calculation of the theoretical input power of the feed water pump. Subsequently, the theoretical input power of the feed water pump is calculated based on the theoretical main pipeline flow and the theoretical water delivery pressure, thereby providing a data basis for subsequent fault detection. Then, cavitation verification is performed on the feed water pump according to the theoretical main pipeline flow, and a cavitation verification result is obtained, which can avoid problems such as pump impeller cavitation, vibration intensification, and abnormal noise caused by cavitation, effectively eliminate the interference factor of cavitation, and ensure the effectiveness of subsequent fault detection. At the same time, the boundary conditions of fault detection are determined, the range of fault source elimination is reduced, the detection conclusion is more accurate and reliable, and the service life of the equipment is prolonged. Finally, in the case that the cavitation verification result is passed, the fault detection result of the feed water pump is determined according to the theoretical water delivery pressure, the theoretical main pipeline flow, the theoretical input power, and the actual values corresponding thereto, multi-dimensional fault cross verification is realized, the misjudgment probability caused by single parameter judgment is effectively reduced, and the accuracy of the fault detection result is significantly improved. Therefore, the technical scheme of the present application solves the problem of low detection accuracy caused by fault judgment based on only a single parameter in the prior art.

[0013] In a second aspect, the embodiment of the present application further provides a fault detection device, which comprises:

[0014] a pressure calculation module configured to calculate the theoretical water delivery pressure of the feed water pump according to the real-time total flow of the feed water pump;

[0015] a flow calculation module configured to calculate the theoretical main pipeline flow of the feed water pump based on the theoretical water delivery pressure;

[0016] a power calculation module configured to calculate the theoretical input power of the feed water pump based on the theoretical main pipeline flow and the theoretical water delivery pressure;

[0017] a verification module configured to perform cavitation verification on the feed water pump according to the theoretical main pipeline flow, and obtain a cavitation verification result;

[0018] a fault detection module configured to, in the case that the cavitation verification result is passed, determine the fault detection result of the feed water pump according to the theoretical water delivery pressure, the theoretical main pipeline flow, the theoretical input power, and the actual values corresponding thereto.

[0019] In a third aspect, the embodiment of the present application further provides an electronic device, which comprises:

[0020] at least one processor; and a memory connected to the at least one processor in communication;

[0021] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to perform the fault detection method according to any one of the embodiments of the present application.

[0022] In a fourth aspect, the embodiments of the present application further provide a storage medium containing computer executable instructions, which, when executed by a computer processor, implement the fault detection method according to any one of the embodiments of the present application.

[0023] It should be noted that the above computer instructions can be stored on the computer readable storage medium in whole or in part. The computer readable storage medium can be packaged together with the processor of the fault detection device, or can be packaged separately from the processor of the fault detection device, and the present application does not limit this.

[0024] The description of the second aspect, the third aspect and the fourth aspect in the present application can refer to the detailed description of the first aspect; and the beneficial effects of the description of the second aspect, the third aspect and the fourth aspect can refer to the beneficial effect analysis of the first aspect, which will not be repeated here.

[0025] In the present application, the name of the above-mentioned fault detection device does not constitute a limitation on the device or functional module itself, and in actual implementation, these devices or functional modules can appear with other names. As long as the functions of each device or functional module are similar to those of the present application, they belong to the scope of the claims of the present application and their equivalents.

[0026] These aspects or other aspects of the present application will be more apparent in the following description. BRIEF DESCRIPTION OF DRAWINGS

[0027] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0028] Figure 1 A flowchart of a fault detection method provided by an embodiment of the present application;

[0029] Figure 2 A flowchart of another fault detection method provided by an embodiment of the present application;

[0030] Figure 3 A structural diagram of a fault detection device provided by an embodiment of the present application;

[0031] Figure 4 Fig. 1 is a structural schematic diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0032] The application will be further described below in conjunction with the drawings and embodiments. It should be understood that the specific embodiments described herein are intended to be illustrative only and not limiting of the application. Additionally, it should be understood that in the drawings and the specification, like reference numerals are used to represent like elements throughout the several views.

[0033] The term "and / or" in this application merely describes an association relationship of associated objects, and indicates that there can be three relationships, for example, A and / or B can represent three cases of A alone, A and B together, and B alone.

[0034] The terms "first" and "second" and the like in the specification of the application and the drawings are used to distinguish different objects or different treatments of the same object, and are not used to describe the specific order of the objects.

[0035] In addition, the terms "include" and "have" and any variations thereof mentioned in the description of the present application are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device including a series of steps or units is not limited to the listed steps or units, but can optionally include other steps or units not listed or can optionally include other steps or units inherent to the process, method, product or device.

[0036] Before the example embodiments are discussed in more detail, it should be mentioned that some of the example embodiments are described as processes or methods depicted as flow diagrams. While the flow diagrams depict the operations (or steps) as sequential processes, many of the operations can be performed in parallel, concurrently or simultaneously. In addition, the order of the operations can be re-arranged. The processes can be terminated when their operations are completed, but can also have additional steps not included in the figure. The processes can correspond to methods, functions, routines, subroutines, subprograms, etc. In addition, the embodiments and features of the embodiments in the present application can be combined with each other, without conflict.

[0037] It should be noted that in the embodiments of the present application, the words "exemplary" or "for example" are used to mean serving as an example, instance, or illustration. Any embodiment or design described herein as "exemplary" or "for example" should not be construed as being preferred or advantageous over other embodiments or designs. Rather, the exemplary or example embodiments are presented as a means of explanation of the concepts being presented.

[0038] In the description of the present application, the meaning of "a plurality of" is two or more, unless otherwise specified.

[0039] Figure 1 A flowchart of a fault detection method provided for an embodiment of the present application, the embodiment can be applicable to the case where the feed water pump needs to be fault detected, the method can be executed by a fault detection device, the device can be realized in the form of software and / or hardware, for example, the device can be an electronic device. Referring to Figure 1 , the fault detection method of the embodiment specifically includes the following steps:

[0040] Step 110, calculating the theoretical water delivery pressure of the feed water pump according to the real-time total flow of the feed water pump.

[0041] Specifically, the feed water pump refers to a device used for delivering and pressurizing water (or other liquids) to a boiler, a reaction device or a high-rise user in a boiler system, an industrial process or a water supply system. The real-time total flow refers to the total amount of water actually delivered by the feed water pump per unit of time at the current running moment. The theoretical water delivery pressure refers to the ideal pressure parameter calculated according to the real-time total flow of the feed water pump, which is essentially the energy that the pump should provide to unit weight of liquid under no-loss working condition. This energy can be intuitively represented by the height of the liquid lifted, and can also be equivalent to the pressure that the liquid needs to overcome, which is the same physical quantity as the theoretical lift but in different forms of representation.

[0042] In specific implementation, the real-time total flow, real-time speed and attribute information (such as impeller diameter) of the feed water pump can be input into a pre-trained water delivery pressure calculation model to obtain the theoretical water delivery pressure of the feed water pump. The water delivery pressure calculation model refers to a model obtained by training a deep learning model according to normal historical running data of the feed water pump (including historical total flow, historical speed and historical attribute information).

[0043] In the embodiment, the above steps provide a data basis for subsequent calculation of the theoretical main pipeline flow.

[0044] Step 120, calculating the theoretical main pipeline flow of the feed water pump based on the theoretical water delivery pressure.

[0045] Specifically, the theoretical main pipeline flow refers to the amount of water that should be delivered per unit of time in the main pipeline, which is the ideal flow of the main pipeline under the theoretical working condition, and the unit is consistent with the real-time total flow.

[0046] In a specific implementation, the obtained theoretical water delivery pressure can be input into a preset main pipeline flow calculation formula to obtain the theoretical main pipeline flow of the water supply pump. The main pipeline flow calculation formula refers to a quantitative mapping formula between the historical theoretical water delivery pressure and the corresponding historical main pipeline flow data, which is established based on historical normal working condition data of the water supply pump, and through statistical analysis and curve fitting (such as linear fitting, polynomial fitting, or nonlinear fitting) of the historical theoretical water delivery pressure and the corresponding historical main pipeline flow data.

[0047] In this embodiment, the above steps provide a data basis for subsequent calculation of the theoretical input power of the water supply pump.

[0048] Step 130, based on the theoretical main pipeline flow and the theoretical water delivery pressure, the theoretical input power of the water supply pump is calculated.

[0049] Specifically, the theoretical input power refers to an ideal power value required to drive the water supply pump to reach an ideal operating state, which is calculated according to the theoretical water delivery pressure and the theoretical main pipeline flow.

[0050] In a specific implementation, the product of the theoretical main pipeline flow, the theoretical water delivery pressure, the density of the conveying medium, and the gravitational acceleration can be calculated to obtain the fluid ideal effective power of the water supply pump. Then, the ratio of the fluid ideal effective power to the water pump energy conversion efficiency (obtained by fitting the water supply pump design parameters, rated performance curve, or normal working condition historical operation data) is calculated to obtain the theoretical input power.

[0051] In this embodiment, the above steps provide a data basis for subsequent fault detection.

[0052] Step 140, cavitation verification is performed on the water supply pump according to the theoretical main pipeline flow to obtain a cavitation verification result.

[0053] Specifically, cavitation verification refers to a verification process to verify whether cavitation occurs when the water supply pump is running. The cavitation verification result refers to a conclusion obtained after cavitation verification, which is divided into two categories: “pass” and “fail”.

[0054] In a specific implementation, the theoretical cavitation allowance can be obtained by querying the main pipeline flow and cavitation allowance correspondence table based on the theoretical main pipeline flow; at the same time, the effective cavitation allowance of the water supply pump is calculated, and the formula is: effective cavitation allowance = (actual pressure at the inlet of the water supply pump - saturated steam pressure of the conveying medium) / (density of the conveying medium x gravitational acceleration) - inlet pipeline resistance loss / (density of the conveying medium x gravitational acceleration). The main pipeline flow and cavitation allowance correspondence table refers to a mapping table of theoretical main pipeline flow and critical cavitation allowance, which is pre-established based on the design parameters, performance test data, or historical normal working condition operation data of the water supply pump, and is used to quickly query the minimum cavitation allowance required for the water supply pump not to cavitate under different flows.

[0055] Then, the effective cavitation margin is compared with the theoretical cavitation margin. If the effective cavitation margin ≥ the theoretical cavitation margin + a safety margin, it is determined that the cavitation check result is passed, indicating that there is no cavitation under the current operating condition of the feed pump; if the effective cavitation margin < the theoretical cavitation margin + a safety margin, it is determined that the cavitation check result is failed, indicating that there is a risk of cavitation, at which time the staff needs to be warned (such as suggesting timely adjustment of the operating condition or troubleshooting system problems, etc.). The safety margin refers to an additional margin set in advance according to actual conditions or needs to ensure system safety and avoid misjudgment of cavitation risk.

[0056] In this embodiment, through the above steps, the problems of pump impeller cavitation, vibration aggravation, abnormal noise, etc. caused by cavitation can be avoided, the interference factor of cavitation can be effectively eliminated, and the effectiveness of subsequent fault detection can be ensured; at the same time, the boundary conditions of fault detection are clear, the troubleshooting range of fault source is narrowed, the subsequent detection conclusion is more accurate and reliable, and the service life of the equipment is prolonged.

[0057] Step 150, in the case that the cavitation check result is passed, the fault detection result of the feed pump is determined according to the theoretical water delivery pressure, the theoretical main pipeline flow rate, the theoretical input power and the actual values corresponding thereto.

[0058] Specifically, the actual value refers to the actual operating parameter of the feed pump corresponding to the theoretical value (theoretical water delivery pressure, theoretical main pipeline flow rate or theoretical input power) in one-to-one correspondence, which is collected in real time by a sensor, an instrument or the like, and is a data reflecting the real operating state of the pump, such as actual water delivery pressure, actual input power and actual main pipeline flow rate. The fault detection result refers to a conclusion (such as normal or abnormal) that whether the feed pump has a fault, which is obtained by comparing the deviation of the theoretical water delivery pressure, the theoretical main pipeline flow rate, the theoretical input power and the actual values thereof, and combining a preset fault judgment threshold or logic.

[0059] In a specific implementation, when the cavitation check result is passed, the deviation degree of the actual water delivery pressure, the actual main pipeline flow rate, and the actual input power from the respective corresponding theoretical values can be calculated first to obtain the respective deviation degrees, such as: | actual water delivery pressure - theoretical water delivery pressure | / theoretical water delivery pressure = pressure deviation degree, | actual input power - theoretical input power | / theoretical input power = power deviation degree, and | actual main pipeline flow rate - theoretical main pipeline flow rate | / theoretical main pipeline flow rate = flow rate deviation degree. Then, the fault detection result is determined according to the deviation comparison result: if the deviation degrees of the pressure, the flow rate, and the power are all not greater than the respective corresponding deviation threshold values, it is determined that the fault detection result is normal; if the deviation degrees of the three are all greater than the respective corresponding deviation threshold values, it is determined that the fault detection result is a serious anomaly, at which time the staff can be prompted that the equipment may have a major fault (such as serious wear of the impeller, serious blockage of the pipeline, etc.), which needs to be urgently investigated; if the deviation degree of 1-2 parameters is greater than the corresponding threshold value and the remaining parameters are normal, it is determined that the fault detection result is a local anomaly, which indicates that the equipment has a targeted fault hidden danger (such as only pressure deviation exceeding the standard may indicate pipeline leakage, and only power deviation exceeding the standard may indicate motor efficiency decline), at which time the abnormal parameters can be sent to the terminal of the staff to help the staff to perform directional investigation according to the abnormal parameter dimension. The deviation threshold values corresponding to the respective parameters can be determined in advance according to the design rated range of the water supply pump, the actual operation condition requirement, and historical normal data statistics, and can support differentiated setting (such as the pressure threshold value is set to 10%, the flow rate threshold value is set to 8%, and the power threshold value is set to 12%, or can be uniformly set to 10%, etc.).

[0060] In the embodiment, through the above steps, multi-dimensional fault cross-validation is realized, the probability of misjudgment caused by single parameter judgment is effectively reduced, and the accuracy of the fault detection result is significantly improved.

[0061] The fault detection method provided by the embodiment of the present application first calculates the theoretical water delivery pressure of the feed pump according to the real-time total flow of the feed pump, thereby providing a data basis for subsequent calculation of the theoretical main pipeline flow. Then, the theoretical main pipeline flow of the feed pump is calculated based on the theoretical water delivery pressure, thereby providing a data basis for subsequent calculation of the theoretical input power of the feed pump. Subsequently, the theoretical input power of the feed pump is calculated based on the theoretical main pipeline flow and the theoretical water delivery pressure, thereby providing a data basis for subsequent fault detection. Then, the feed pump is subjected to cavitation verification according to the theoretical main pipeline flow, and a cavitation verification result is obtained, which can avoid problems such as pump impeller cavitation, vibration intensification and abnormal noise caused by cavitation, effectively eliminate the interference factor of cavitation, and ensure the effectiveness of subsequent fault detection. At the same time, the boundary conditions of fault detection are determined, the range of fault source elimination is narrowed, the subsequent detection conclusion is more accurate and reliable, and the service life of the equipment is prolonged. Finally, when the cavitation verification result is passed, the fault detection result of the feed pump is determined according to the theoretical water delivery pressure, the theoretical main pipeline flow, the theoretical input power and the respective corresponding actual values, multi-dimensional fault cross verification is realized, the misjudgment probability caused by single parameter judgment is effectively reduced, and the accuracy of the fault detection result is significantly improved. Therefore, the technical scheme of the present application solves the problem of low detection accuracy caused by fault judgment based on only a single parameter in the prior art.

[0062] Figure 2 The flowchart of another fault detection method provided by the embodiment of the present application is based on the embodiment described above. In this embodiment, the method can further include the following steps.

[0063] Step 210: calculating the theoretical water delivery pressure of the feed pump according to the real-time total flow of the feed pump.

[0064] Further, step 210 can specifically include: calculating the product of the real-time total flow and the rotational speed first-order coefficient to obtain a first intermediate parameter; calculating the product of the square of the real-time total flow and the rotational speed second-order coefficient to obtain a second intermediate parameter; and calculating the sum of the first intermediate parameter, the second intermediate parameter and the rotational speed constant term to obtain the theoretical water delivery pressure.

[0065] Specifically, the rotational speed first-order coefficient is a proportional coefficient fitted based on historical operation data of the feed water pump, and is used to quantify the linear influence of the flow on the theoretical water delivery pressure. The first intermediate parameter is an intermediate transition parameter calculated by the real-time total flow and the rotational speed first-order coefficient, and is used to preliminarily quantify the linear contribution of the flow to the pressure. The rotational speed second-order coefficient is a proportional coefficient fitted based on historical operation data of the feed water pump, and is used to quantify the nonlinear influence of the flow on the theoretical water delivery pressure. The second intermediate parameter is an intermediate transition parameter calculated by the square of the real-time total flow and the rotational speed second-order coefficient, and is used to supplement the quantification of the nonlinear correlation between the flow and the pressure. The rotational speed constant term is a constant fitted based on historical operation data of the feed water pump, and does not change with the real-time flow.

[0066] In a specific implementation, the real-time rotational speed of the feed water pump can be first queried in the rotational speed and coefficient array correspondence table to obtain the coefficient array (including the rotational speed first-order coefficient, the rotational speed second-order coefficient, and the rotational speed constant term) matched with the real-time rotational speed. The rotational speed and coefficient array correspondence table is calibrated or fitted in advance according to historical operation data of the feed water pump, and the rotational speed second-order coefficient is forcedly constrained to be less than zero during the calibration or fitting process, so as to ensure that the subsequent calculated theoretical water delivery pressure conforms to the physical law.

[0067] Then, the product of the real-time total flow (Q) and the rotational speed first-order coefficient (a1) is calculated to obtain the first intermediate parameter (A1), that is, A1=a1×Q; the product of the square of the real-time total flow and the rotational speed second-order coefficient (a2) is calculated to obtain the second intermediate parameter (A2), that is, A2=a2×Q 2 ; and the sum of the first intermediate parameter, the second intermediate parameter, and the rotational speed constant term (a0) is calculated to obtain the theoretical water delivery pressure (H), that is, H=A1+A2+a0. In summary, the calculation process of the theoretical water delivery pressure can be represented by the following formula: H=a0+a1×Q+a2×Q 2 .

[0068] In this embodiment, the accuracy of the obtained theoretical water delivery pressure is improved through the above steps.

[0069] Step 211: calculating the theoretical main pipeline flow of the feed water pump based on the theoretical water delivery pressure.

[0070] Further, step 211 can specifically include: calculating the difference between the theoretical water delivery pressure and the potential energy difference to obtain an effective action water head; and calculating the ratio of the effective action water head to the equivalent resistance coefficient to obtain the theoretical main pipeline flow.

[0071] Specifically, the potential energy difference refers to the static pressure difference or the elevation difference of the water supply pump inlet and outlet or different positions of the system, which is the potential energy difference of the fluid due to the change of pressure or position height. The specific form can be determined according to the actual situation or requirements. The static pressure difference can be obtained by measuring the pressure difference between the inlet and outlet of the water supply pump in real time through a differential pressure sensor (such as a differential pressure transmitter); the elevation difference is obtained by determining the position height difference of the inlet and outlet of the water supply pump or the key nodes of the system through pre-mapping methods such as leveling and elevation measurement. The effective action head refers to an intermediate parameter calculated according to the theoretical water delivery pressure and the potential energy difference. The equivalent resistance coefficient refers to a parameter for quantifying the hindering effect of the pipeline on the medium flow, which can be obtained through hydraulic calculation or experimental calibration according to the pipeline design parameters and medium characteristics (such as viscosity and density).

[0072] In a specific implementation, the difference between the theoretical water delivery pressure (H) and the potential energy difference (c0) can be calculated first to obtain the effective action head (B1), that is, B1=H-c0; then the ratio of the effective action head and the equivalent resistance coefficient (c1) is calculated to obtain the theoretical main pipeline flow (Q m ), that is, Q m =B1 / c1. In summary, the calculation process of the theoretical main pipeline flow can be represented by the following formula: Q m = (H-c0) / c1.

[0073] In this embodiment, the accuracy of the obtained theoretical main pipeline flow is improved through the above steps.

[0074] Step 212, based on the theoretical main pipeline flow and the theoretical water delivery pressure, the theoretical input power of the water supply pump is calculated.

[0075] Further, step 212 can specifically include: determining the shaft power of the water supply pump according to the theoretical main pipeline flow, the theoretical water delivery pressure and the real-time rotating speed of the water supply pump; calculating the ratio of the shaft power and the motor efficiency of the water supply pump to obtain the motor shaft side power; calculating the sum of the motor shaft side power and the auxiliary power consumption basic value to obtain the theoretical input power.

[0076] Specifically, the real-time rotating speed of the water supply pump refers to the real-time rotating speed of the motor driving the pump shaft during the operation of the water supply pump, which can be collected in real time through a rotating speed sensor. The shaft power refers to the mechanical power output at the shaft end of the water supply pump. The motor efficiency of the water supply pump refers to the ratio of the output power and the input power of the motor, which reflects the efficiency level of the motor converting electrical energy into mechanical energy. This parameter can be obtained through motor nameplate marking, experimental testing or historical operation data calibration. The motor shaft side power refers to the mechanical power transmitted by the motor to the water supply pump shaft. The auxiliary power consumption basic value refers to the basic power consumption required for the operation of auxiliary equipment (such as cooling fan, lubricating oil pump, control circuit, etc.) in the water supply pump system, which is pre-set (or calibrated through historical data) according to the actual situation or requirements.

[0077] In a specific implementation, the shaft power of the water supply pump can be determined according to the theoretical main pipeline flow, the theoretical water delivery pressure, and the real-time rotating speed of the water supply pump. The specific calculation formula is: P s = ρ × g × Q m × H / η1+ P m (n), where P s is the shaft power; ρ is the density of the medium (such as water); g is the acceleration of gravity; η1 is the hydraulic efficiency, which reflects the efficiency of the water pump in converting mechanical energy into fluid hydraulic energy, and is obtained by querying a water pump hydraulic efficiency table (which is based on the design parameters, operating characteristics, and historical measured data of the water pump); P m (n) is the mechanical / liquid coupling loss power, which is a quadratic function of the real-time rotating speed of the water pump, and represents the energy loss in the mechanical transmission and liquid coupling process. The expression is P m (n) = b0 + b1 × n + b2 × n 2 , where b0, b1, and b2 are parameters to be determined, which need to be fitted and calibrated through historical operating data of the water supply pump; and n is the real-time rotating speed of the water supply pump.

[0078] Then, the ratio of the shaft power to the motor efficiency (η2) of the water supply pump is calculated to obtain the motor shaft-side power (P1), that is, P1 = P s / η2. Finally, the sum of the motor shaft-side power and the auxiliary power basic value (P a ) is calculated to obtain the theoretical input power (P), that is, P = P1 + P a .

[0079] In this embodiment, the accuracy of the obtained theoretical input power is improved through the above steps.

[0080] Step 213, calculate the theoretical circulation backflow flow according to the real-time discharge pressure and the recirculation valve position of the water supply pump.

[0081] Specifically, the real-time discharge pressure refers to the real-time medium pressure at the discharge end (outlet side) of the water supply pump, which represents the pressure capacity of the pump body output medium, and can be measured in real time by a pressure sensor. The recirculation valve position refers to the opening degree of the recirculation valve of the water supply pump, which is used to adjust the medium flow back to the suction end, and can be measured by a valve position sensor (such as a potentiometric sensor or a Hall sensor). The theoretical circulation backflow flow refers to the theoretical medium flow from the discharge end of the pump body back to the suction end, which is calculated according to the real-time suction pressure, the real-time discharge pressure, and the recirculation valve position.

[0082] In a specific implementation, the theoretical circulation backflow flow is calculated according to the real-time discharge pressure and the recirculation valve position of the water supply pump. The specific calculation formula is: ; where is the theoretical circulation backflow flow; The to-be-calibrated parameters are obtained by fitting the historical operation data of the feed water pump in this embodiment ; The real-time discharge pressure is The recirculation back junction pressure is The recirculation valve position is .

[0083] In this embodiment, the above steps provide a data basis for subsequently obtaining the theoretical total flow.

[0084] Step 214, the sum of the theoretical circulation back flow and the theoretical main pipeline flow is calculated to obtain the theoretical total flow.

[0085] Specifically, the theoretical total flow refers to the sum of the theoretical circulation back flow and the theoretical main pipeline flow, reflecting the total scale of the medium participating in energy conversion when the feed water pump is running.

[0086] In a specific implementation, the sum of the theoretical circulation back flow ( ) and the theoretical main pipeline flow ( ) is calculated to obtain the theoretical total flow ( ), and the specific expression is: = + .

[0087] In this embodiment, the above steps provide a data basis for subsequently obtaining the available net positive suction head.

[0088] Step 215, according to the suction pipe resistance loss, suction lift, real-time suction pressure and theoretical total flow of the feed water pump, the available net positive suction head of the feed water pump is calculated.

[0089] Specifically, the suction pipe resistance loss refers to the pressure loss caused by the resistance of the medium flowing in the suction pipeline of the feed water pump due to the friction along the pipeline and local pipe fittings (such as elbows, filters, valves), which can be obtained by measuring the pressure difference of the fixed section of the suction pipeline. The suction lift refers to the elevation difference between the suction end of the feed water pump and the medium liquid level, reflecting the potential energy difference of the medium due to the change in position height, which can be obtained by measuring the elevation difference between the suction end and the medium liquid level through leveling, laser ranging and other methods. The real-time suction pressure refers to the real-time medium pressure at the suction end (inlet side) of the feed water pump, reflecting the pressure state of the medium before entering the pump body, which can be measured in real time by a pressure sensor. The available net positive suction head refers to the actual anti-cavitation capability provided by the suction end of the feed water pump.

[0090] In a specific implementation, according to the suction pipe resistance loss, suction lift, real-time suction pressure and theoretical total flow of the feed water pump, the available net positive suction head of the feed water pump is calculated, and the specific calculation formula is: ; wherein, is the available net positive suction head; is the real-time suction pressure; is the saturated vapor pressure of the medium at the current temperature T; z is the suction stroke; is the suction pipe resistance loss.

[0091] In this embodiment, the accuracy of the obtained available net positive suction head is improved through the above steps.

[0092] Step 216, determining whether the available net positive suction head is not less than the critical net positive suction head.

[0093] If not less than, step 218 is performed; if less than, step 217 is performed.

[0094] Specifically, the critical net positive suction head refers to the minimum anti-cavitation ability threshold at which the water pump does not cavitate, and is an inherent characteristic parameter of the water pump, determined by the pump body design, impeller structure and manufacturing process, and can be obtained through the water pump performance curve or manufacturer's technical data.

[0095] In a specific implementation, after obtaining the available net positive suction head, it can be determined whether the available net positive suction head is not less than the critical net positive suction head. If less than, it indicates that the anti-cavitation ability of the suction end of the feed water pump is insufficient, and the pump body has a cavitation risk. At this time, it can be determined that the cavitation verification result is failed. If not less than, it indicates that the anti-cavitation ability of the suction end of the feed water pump meets the safe operation requirement, and the pump body is not prone to cavitation, and the running state is stable and reliable. At this time, it can be determined that the cavitation verification result is passed.

[0096] Step 217, determining that the cavitation verification result is failed.

[0097] In a specific implementation, when it is determined that the cavitation verification result is failed, a warning information can be sent in real time, and the cavitation risk area state of the feed water pump is marked and updated synchronously (such as from "safe" to "high risk"), to help the operation and maintenance personnel to respond quickly and reduce the risk of fault expansion.

[0098] Step 218, determining that the cavitation verification result is passed.

[0099] In a specific implementation, when it is determined that the cavitation verification result is passed, it indicates that the anti-cavitation ability of the feed water pump meets the safe operation requirement and has no cavitation related risk. The subsequent fault detection process can be continued, avoiding the invalid subsequent detection caused by the unremoved cavitation risk, and focusing the detection on other potential fault dimensions, so that the fault detection process is more targeted and coherent, while ensuring that the water pump is always in a safe operation condition during the detection process, and improving the efficiency and reliability of the overall detection work.

[0100] Step 219, respectively calculating the difference between the theoretical water delivery pressure, the theoretical main pipe flow, the theoretical input power and the actual values corresponding thereto, to obtain the current pressure difference, the current flow difference and the current power difference.

[0101] Specifically, the actual value (actual water delivery pressure / actual main pipeline flow / actual input power) is a real-time measurement obtained by a sensor, a meter, or the like, and is a real parameter value during the operation of the water pump, directly reflecting the current actual operation state of the water pump. The current pressure difference is the difference between the actual water delivery pressure and the theoretical water delivery pressure. The current flow difference is the difference between the actual main pipeline flow and the theoretical main pipeline flow. The current power difference is the difference between the actual input power and the theoretical input power.

[0102] In a specific implementation, the current pressure difference = actual water delivery pressure - theoretical water delivery pressure; the current flow difference = actual main pipeline flow - theoretical main pipeline flow; and the current power difference = actual input power - theoretical input power.

[0103] In this embodiment, the above steps provide a data basis for subsequent calculation of the fault score of the water pump.

[0104] Step 220, calculating the fault score of the water pump according to the current pressure difference, the current flow difference, and the current power difference.

[0105] Specifically, the fault score refers to a quantitative value calculated based on the current pressure difference, the current flow difference, and the current power difference, which is used to comprehensively evaluate the degree of deviation of the operation state of the water pump from the ideal working condition, directly reflects the fault severity level, and provides a quantitative basis for fault determination.

[0106] In a specific implementation, the current pressure difference, the current flow difference, and the current power difference can be standardized first, and then mapped to the same numerical interval (such as 0-10), so as to eliminate the dimensional differences of different parameters and avoid interference with the final score results. After standardization, the three standardized data are weighted and summed based on the preset weights, and the fault score is obtained, and the specific calculation formula is: fault score = standardized current pressure difference x pressure difference weight + standardized current flow difference x flow difference weight + standardized current power difference x power difference weight. The weights corresponding to each difference value can be set in advance according to the actual application scene or requirements (such as pressure difference weight 0.4, flow difference weight 0.35, and power difference weight 0.25), and the total weight should satisfy 1 (i.e. 100%).

[0107] In this embodiment, the above steps achieve comprehensive coverage of multi-dimensional risks, avoid one-sidedness of single parameter evaluation, and convert the fault state into a quantitative index, unifying the evaluation standard. This not only simplifies the fault decision and disposal process, improves the fault response efficiency, but also improves the determination accuracy of the fault score, and further improves the accuracy of the subsequent fault detection result.

[0108] Further, step 220 may specifically include: constructing residual components for the current pressure difference, current flow difference, and current power difference respectively, to obtain each residual component; obtaining historical residual data corresponding to each residual component within a preset historical window; calculating the drift sensitivity index corresponding to each residual component based on the historical residual data within the preset historical window and each residual component; and determining the fault score based on each drift sensitivity index and the corresponding confidence weight.

[0109] Specifically, residual components refer to quantitative indicators constructed for the current pressure difference, current flow difference, and current power difference, reflecting the deviation of the corresponding difference from its normal fluctuation range. The preset historical window refers to a time range set in advance according to actual conditions or needs, specifically defined as a continuous time period from the preset time to the previous time (e.g., "10 seconds before the previous time to the previous time", "5 seconds before the previous time to the previous time"). Historical residual data refers to past residual records corresponding to the current residual component within the preset historical window. The drift sensitivity index is an indicator calculated based on the historical residual data within the preset historical window and the current residual component, used to quantify the degree of deviation of the current residual from the historical normal level. The credibility weight refers to a preset weight value based on actual conditions or needs, used to reflect the importance of different residual components in fault determination; the total weight is 1.

[0110] In the specific implementation, residual components can first be constructed for the current pressure difference, current flow difference, and current power difference, respectively, to obtain each residual component. That is, the residual component of the current pressure difference equals the current pressure difference, the residual component of the current flow difference equals the current flow difference, and the residual component of the current power difference equals the current power difference. Then, based on a preset historical window, the historical residual data corresponding to each residual component within the preset historical window is obtained from the database storing water pump-related data. Next, based on the historical residual data within the preset historical window and each residual component, the drift sensitivity index corresponding to each residual component is calculated. The specific calculation formula is as follows:

[0111] ;

[0112] in, For the i-th type of residual component ( The drift sensitivity index at the current time t; t is the current time. Let i be the type i residual component at time j; Let t be the online estimate of the variance of the i-th type of residual component at time t, which can be obtained by combining the sliding window method with existing techniques such as the unbiased variance estimation formula and the exponentially weighted moving average algorithm; k is the preset historical window start time.

[0113] Finally, based on each drift sensitivity index and the corresponding confidence weight, a fault score is determined. Specifically, the maximum value of each drift sensitivity index after weighting is taken as the target drift sensitivity index, and the specific calculation formula is: wherein, is the current effective component index set, = ); is the target drift sensitivity index at the current time; is the confidence weight of the i-th type of component.

[0114] Then, based on the target drift sensitivity index, the fault score is calculated, and the specific calculation formula is: ; wherein, is a control threshold, , is a predetermined safety margin, is a set of historical target drift sensitivity indices in a normal state, is an empirical quantile of the target drift sensitivity index, is a target false positive rate, usually 0.1%-1%; is a small value greater than 0, used to avoid division by zero.

[0115] It should be noted that, in order to improve the accuracy of fault detection, if continuous sampling steps trigger a fault warning; when > , the fault detection result is directly determined as a fault, and if the subsequent continuous L sampling steps are lower than (h is a predetermined rollback margin, h>0), the fault detection result is determined based on Score(t) in combination with a predetermined score and fault result corresponding table. The predetermined score and fault result corresponding table refers to a pre-set quantitative score and fault detection result (such as normal, warning, fault, etc.) corresponding rule table according to the value range of the fault score in advance, for example: if Score(t)∈[0,3), it corresponds to normal; if Score(t)∈[3,5), it corresponds to warning; if Score(t)∈[5,10], it corresponds to fault.

[0116] In this embodiment, through the above steps, the accuracy and precision of the fault score can be effectively improved.

[0117] Step 221, determining a fault detection result according to the fault score.

[0118] In a specific implementation, after obtaining the fault score, the fault detection result can be determined according to a pre-set grading scoring standard. For example, when the fault score is in the range of 0-10, the specific corresponding rules are as follows: 0-3 (including 3): the fault detection result is normal level, the equipment running state is stable, no additional intervention is needed, and continuous monitoring can be maintained; 3-6 (including 6): the fault detection result is a pre-warning level, there is a slight running deviation, potential problems such as pipeline leakage, valve jamming, filter screen blockage, etc. need to be checked in time to avoid the deviation from expanding; 6-8 (including 8): the fault detection result is a fault level, obvious abnormalities have occurred, and core component problems such as impeller wear, motor running abnormalities, and seal damage need to be checked during shutdown; and 8-10: the fault detection result is an emergency fault level, the equipment is in a high-risk running state, and immediate shutdown for repair is needed to prevent the fault from further expanding to cause equipment damage or system shutdown.

[0119] In the embodiment, through the above steps, the fault determination is standardized and the disposal is accurate, and the efficiency and reliability of the feed water pump fault management are greatly improved.

[0120] Optionally, to further improve the accuracy of the parameters obtained by fitting the historical running data of the feed water pump under multiple working conditions in the embodiment, the historical running data can be selected as the running data corresponding to typical working conditions such as the start-stop section, the deep peak-regulation section, the small-flow recirculation opening section, and the steady-state section, thereby providing sufficient and representative data sources for parameter fitting. The determination of each working condition can be realized by the change rate of key parameters (such as speed, recirculation valve position, total flow, suction pressure, and discharge pressure) in a pre-set period, in combination with a pre-set change rate-working condition correspondence table. The change rate-working condition correspondence table is a rule table pre-established according to the change rate characteristics and actual situation of the key running parameters of the feed water pump, and is used to map different change rate intervals to corresponding running working conditions.

[0121] Optionally, to further improve the accuracy of the parameters obtained by fitting the historical data, a constrained regular least squares problem can be constructed in the fitting process, specifically as follows: an optimization problem is constructed under the premise of ensuring physical consistency:

[0122] ;

[0123] In the summation formula, the first term is the fitting error, is a training data set, is an actual observation value, is a theoretical prediction value, the second term in the summation formula is an L2 regularization, which is used to alleviate the multicollinearity problem of multiple parameters; and the third term in the summation formula is a similarity law soft constraint term, which suppresses the extrapolation error across the speed interval.

[0124] Iterative optimization of parameters is achieved using a constrained trust region algorithm or a sequential quadratic programming solver. The initial values ​​of the parameters can be obtained by fitting the data from the equipment nameplate points to an empirical curve; the regularization coefficient With soft constraint weights The optimal parameters were determined using a grid search method, with the optimization criterion being "minimum verification error and acceptable parameter condition number." Then, the mechanism residuals are constructed using the training set. and with Train a small linear regression corrector for input The optimization objective is:

[0125] ;

[0126] Among them, the corrector is selected in the form of linear regression. , The parameter set is defined by the regularization coefficient α and the model size, which are determined by early stopping and K-fold cross-validation to ensure that the residual variance converges significantly on the validation set.

[0127] The fault detection method provided by the embodiment of the present application first calculates the theoretical water delivery pressure of the feed pump according to the real-time total flow of the feed pump, thereby providing a data basis for subsequent calculation of the theoretical main pipeline flow. Then, the theoretical main pipeline flow of the feed pump is calculated based on the theoretical water delivery pressure, thereby providing a data basis for subsequent calculation of the theoretical input power of the feed pump. Subsequently, the theoretical input power of the feed pump is calculated based on the theoretical main pipeline flow and the theoretical water delivery pressure, thereby providing a data basis for subsequent fault detection. Then, the theoretical circulation backflow flow is calculated according to the real-time discharge pressure and the recirculation valve position of the feed pump. The sum of the theoretical circulation backflow flow and the theoretical main pipeline flow is calculated to obtain the theoretical total flow. The available net positive suction head of the feed pump is calculated according to the suction pipe resistance loss, the suction stroke, the real-time suction pressure and the theoretical total flow of the feed pump. It is determined whether the available net positive suction head is not less than the critical net positive suction head. If it is less than, it is determined that the cavitation check result is failed. If it is not less than, it is determined that the cavitation check result is passed. Then, the difference between the theoretical water delivery pressure, the theoretical main pipeline flow and the theoretical input power and the respective actual values is calculated, and the current pressure difference, the current flow difference and the current power difference are obtained. The fault score of the feed pump is calculated according to the current pressure difference, the current flow difference and the current power difference, thereby achieving comprehensive coverage of multi-dimensional risks, avoiding one-sidedness of single parameter evaluation, and converting the fault state into a quantitative index, thereby unifying the evaluation standard. This not only simplifies the fault decision and disposal process, improves the fault response efficiency, but also improves the determination accuracy of the fault score, and further improves the accuracy of the subsequent fault detection result. Finally, the fault detection result is determined according to the fault score, thereby realizing fault determination standardization and disposal precision, and greatly improving the efficiency and reliability of the feed pump fault management. Therefore, the technical scheme of the present application solves the problem of low detection accuracy caused by fault judgment only according to a single parameter in the prior art.

[0128] Figure 3 The structure diagram of the fault detection device provided by the embodiment of the present application, the device and the fault detection method of each embodiment described above belong to the same inventive concept, and the details not described in detail in the embodiment of the fault detection device can be referred to the embodiment of the fault detection method described above.

[0129] As shown in the Figure 3 , the device comprises:

[0130] The pressure calculation module 310 is configured to calculate the theoretical water delivery pressure of the feed pump according to the real-time total flow of the feed pump.

[0131] The flow calculation module 320 is configured to calculate the theoretical main pipeline flow of the feed pump based on the theoretical water delivery pressure.

[0132] The power calculation module 330 is configured to calculate the theoretical input power of the feed pump based on the theoretical main pipeline flow and the theoretical water delivery pressure.

[0133] The verification module 340 is configured to perform cavitation verification on the water supply pump according to the theoretical main pipeline flow, and obtain a cavitation verification result.

[0134] The fault detection module 350 is configured to, when the cavitation verification result is passed, determine a fault detection result of the water supply pump according to the theoretical water delivery pressure, the theoretical main pipeline flow, the theoretical input power and respective actual values.

[0135] On the basis of the above embodiment, the verification module 340 is specifically configured to:

[0136] calculate a theoretical circulation backflow flow according to the real-time discharge pressure and the recirculation valve position of the water supply pump, calculate a sum of the theoretical circulation backflow flow and the theoretical main pipeline flow to obtain a theoretical total flow, calculate an available net positive suction head of the water supply pump according to a suction pipe resistance loss, a suction lift, a real-time suction pressure and the theoretical total flow, determine whether the available net positive suction head is not less than a critical net positive suction head, and determine that the cavitation verification result is passed when the available net positive suction head is not less than the critical net positive suction head, or determine that the cavitation verification result is not passed when the available net positive suction head is less than the critical net positive suction head.

[0137] On the basis of the above embodiment, the power calculation module 330 is specifically configured to:

[0138] determine a shaft power of the water supply pump according to the theoretical main pipeline flow, the theoretical water delivery pressure and a real-time rotating speed of the water supply pump, calculate a ratio of the shaft power to a motor efficiency of the water supply pump to obtain a motor shaft-side power, and calculate a sum of the motor shaft-side power and an auxiliary power consumption basic value to obtain the theoretical input power.

[0139] On the basis of the above embodiment, the pressure calculation module 310 is specifically configured to:

[0140] calculate a product of the real-time total flow and a rotating speed first-order coefficient to obtain a first intermediate parameter, calculate a product of a square of the real-time total flow and a rotating speed second-order coefficient to obtain a second intermediate parameter, and calculate a sum of the first intermediate parameter, the second intermediate parameter and a rotating speed constant term to obtain the theoretical water delivery pressure.

[0141] On the basis of the above embodiment, the flow calculation module 320 is specifically configured to:

[0142] calculate a difference between the theoretical water delivery pressure and a potential energy difference to obtain an effective action water head, and calculate a ratio of the effective action water head to an equivalent resistance coefficient to obtain the theoretical main pipeline flow.

[0143] On the basis of the above embodiment, the fault detection module 350 is specifically configured to:

[0144] The differences between the theoretical water delivery pressure, the theoretical main pipeline flow rate, and the theoretical input power and their corresponding actual values ​​are calculated respectively to obtain the current pressure difference, current flow rate difference, and current power difference; based on the current pressure difference, current flow rate difference, and current power difference, the fault score of the water pump is calculated; and the fault detection result is determined based on the fault score.

[0145] Based on the above embodiments, the fault detection module 350 calculates a fault score for the water pump according to the current pressure difference, the current flow difference, and the current power difference, including:

[0146] Residual components are constructed for the current pressure difference, the current flow difference, and the current power difference, respectively, to obtain each residual component; historical residual data corresponding to each residual component within a preset historical window is obtained; based on the historical residual data within the preset historical window and each residual component, the drift sensitivity index corresponding to each residual component is calculated; based on each drift sensitivity index and the corresponding confidence weight, the fault score is determined.

[0147] The fault detection device provided in the embodiments of the present invention can execute the fault detection method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of executing the method.

[0148] It is worth noting that in the embodiments of the above-mentioned fault detection device, the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy differentiation and are not used to limit the scope of protection of the present invention.

[0149] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Figure 4 A block diagram of an exemplary electronic device 4 suitable for implementing embodiments of the present invention is shown. Figure 4 The electronic device 4 shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0150] like Figure 4 As shown, electronic device 4 is represented in the form of a general-purpose computing electronic device. The components of electronic device 4 may include, but are not limited to: one or more processors or processing units 16, system memory 28, and bus 18 connecting different system components (including system memory 28 and processing unit 16).

[0151] Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration bus, a processor or local bus using any of a variety of bus architectures. By way of example, these architectures include Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.

[0152] Electronic device 4 typically includes a variety of computer system readable media. These media can be any available media that is accessible by electronic device 4 and includes both volatile and non-volatile media, removable and non-removable media.

[0153] System memory 28 can include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. Electronic device 4 can further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, storage system 34 can be provided for reading from and writing to a non-removable, non-volatile magnetic media (e.g., a "hard drive"). Figure 4 not shown, is typically provided as residual storage across electronic device 4, and can be used for storing data that is both received as well as data that is generated by the processor 20. Although Figure 4 not shown, is typically provided as residual storage across electronic device 4, and can be used for storing data that is both received as well as data that is generated by the processor 20. Although

[0154] Program / utility 40 having a set (at least one) of program modules 42 can be stored in, for example, system memory 28 by way of example, such program modules 42 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data, each or some combination thereof, which can include implementation of the network environment. Program modules 42 generally carry out the functions and / or methodologies of embodiments of the present application as described herein.

[0155] The electronic device 4 can also communicate with one or more external devices 14 such as a keyboard, a pointing device, a display 24, etc.; other devices that enable a user to interact with the electronic device 4; and / or any devices (e.g., a network card, a modem, etc.) that enable the electronic device 4 to communicate with one or more other computing devices. Such communication can occur via the input / output (I / O) interface 22. Still yet, the electronic device 4 can communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or the Internet) through a network adapter 20. As Figure 4 illustrated, the network adapter 20 communicates with the other components of the electronic device 4 via the bus 18. It should be appreciated that the bus 18 can be one of any Figure 4 schematically shown in FIG. 1, other hardware and / or software modules that are not shown can be used in conjunction with the electronic device 4. These include, but are not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data archival storage systems, etc.

[0156] The processing unit 16 executes various functional applications and page displays by running programs stored in the system memory 28, such as implementing the fault detection method provided by embodiments of the present application, which includes:

[0157] calculating a theoretical main pipeline flow of the feed water pump based on the theoretical water delivery pressure; calculating a theoretical input power of the feed water pump based on the theoretical main pipeline flow and the theoretical water delivery pressure; performing cavitation verification on the feed water pump according to the theoretical main pipeline flow to obtain a cavitation verification result; and determining a fault detection result of the feed water pump according to the theoretical water delivery pressure, the theoretical main pipeline flow, the theoretical input power and respective actual values, in a case where the cavitation verification result is passed.

[0158] Of course, those skilled in the art can understand that the processor can also implement the technical solutions of the fault detection method provided by any embodiments of the present application.

[0159] The embodiments of the present application provide a computer readable storage medium, which has a computer program stored thereon, the program being executed by a processor to implement, for example, the fault detection method provided by embodiments of the present application, which includes:

[0160] The theoretical water delivery pressure of the feed water pump is calculated according to the real-time total flow of the feed water pump; the theoretical main pipeline flow of the feed water pump is calculated based on the theoretical water delivery pressure; the theoretical input power of the feed water pump is calculated based on the theoretical main pipeline flow and the theoretical water delivery pressure; the cavitation check of the feed water pump is performed according to the theoretical main pipeline flow, and a cavitation check result is obtained; in the case that the cavitation check result is passed, the fault detection result of the feed water pump is determined according to the theoretical water delivery pressure, the theoretical main pipeline flow, the theoretical input power and respective actual values.

[0161] The computer storage medium of the embodiment of the application can adopt any combination of one or more computer readable media. The computer readable medium can be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium may, for example, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or component, or any combination thereof. More specific examples (non-exhaustive list) of the computer readable storage medium include an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, the computer readable storage medium can be any tangible medium that contains or stores a program that can be used by or in connection with an instruction execution system, device or component.

[0162] The computer readable signal medium can include a data signal propagated in a baseband or as a part of a carrier wave, in which a computer readable program code is borne. Such a propagated data signal can take multiple forms, including but not limited to an electromagnetic signal, an optical signal or any suitable combination thereof. The computer readable signal medium can also be any computer readable medium other than the computer readable storage medium, which can send, propagate or transmit a program for use by or in connection with an instruction execution system, device or component.

[0163] The program code contained on the computer readable medium can be transmitted by any suitable medium, including but not limited to wireless, wire, optical cable, RF, etc., or any suitable combination thereof.

[0164] Computer program code for carrying out operations of the present application can be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0165] Those skilled in the art will appreciate that the modules or steps of the present application described above can be implemented using general computing devices, which can be centralized on a single computing device or distributed on a network of multiple computing devices. Alternatively, they can be implemented using computer-executable program code, which can be stored in a storage device and executed by a computing device, or they can be implemented as individual integrated circuit modules, or a plurality of modules or steps can be implemented as a single integrated circuit module. Thus, the present application is not limited to any particular combination of hardware and software.

[0166] In addition, the acquisition, storage, use, processing, etc. of data in the technical solutions of the present application comply with relevant provisions of laws and regulations.

[0167] Note that the above are only preferred embodiments of the present application and the technical principles applied. Those skilled in the art will understand that the present application is not limited to the specific embodiments herein, and that various obvious changes, re-adjustments and substitutions can be made by those skilled in the art without departing from the scope of the present application. Therefore, although the present application has been described in detail through the above embodiments, the present application is not limited to the above embodiments, and can include more other equivalent embodiments without departing from the concept of the present application, and the scope of the present application is determined by the scope of the appended claims.

Claims

1. A fault detection method characterized by, The method comprises: calculating a theoretical water delivery pressure of the feed water pump according to a real-time total flow of the feed water pump; calculating a theoretical main pipeline flow of the feed water pump based on the theoretical water delivery pressure; calculating a theoretical input power of the feed water pump based on the theoretical main pipeline flow and the theoretical water delivery pressure; performing cavitation verification on the feed water pump according to the theoretical main pipeline flow to obtain a cavitation verification result; in a case where the cavitation verification result is passed, determining a fault detection result of the feed water pump according to the theoretical water delivery pressure, the theoretical main pipeline flow, the theoretical input power and respective corresponding actual values.

2. The fault detection method according to claim 1, characterized in that, The cavitation verification on the feed water pump according to the theoretical main pipeline flow to obtain a cavitation verification result comprises: calculating a theoretical circulation backflow flow according to a real-time discharge pressure and a recirculation valve position of the feed water pump; calculating a sum of the theoretical circulation backflow flow and the theoretical main pipeline flow to obtain a theoretical total flow; calculating an available net positive suction head of the feed water pump according to a suction pipe resistance loss, a suction lift, a real-time suction pressure and the theoretical total flow of the feed water pump; determining whether the available net positive suction head is not less than a critical net positive suction head; if yes, determining that the cavitation verification result is passed; if no, determining that the cavitation verification result is not passed.

3. The fault detection method of claim 1, wherein, The calculation of the theoretical input power of the feed water pump based on the theoretical main pipeline flow and the theoretical water delivery pressure comprises: determining a shaft power of the feed water pump according to the theoretical main pipeline flow, the theoretical water delivery pressure and a real-time rotating speed of the feed water pump; calculating a ratio of the shaft power to a motor efficiency of the feed water pump to obtain a motor shaft side power; calculating a sum of the motor shaft side power and an auxiliary power consumption basic value to obtain the theoretical input power.

4. The fault detection method of claim 1, wherein, The calculation of the theoretical water delivery pressure of the feed water pump according to a real-time total flow of the feed water pump comprises: calculating a product of the real-time total flow and a rotating speed first-order coefficient to obtain a first intermediate parameter; calculating a product of a square of the real-time total flow and a rotating speed second-order coefficient to obtain a second intermediate parameter; calculating a sum of the first intermediate parameter, the second intermediate parameter and a rotating speed constant term to obtain the theoretical water delivery pressure.

5. The fault detection method of claim 1, wherein, The calculation of the theoretical main pipeline flow of the feed water pump based on the theoretical water delivery pressure comprises: calculating a difference between the theoretical water delivery pressure and a potential energy difference to obtain an effective action water head; calculating a ratio of the effective action water head to an equivalent resistance coefficient to obtain the theoretical main pipeline flow.

6. The fault detection method of claim 1, wherein, The determination of a fault detection result of the feed water pump according to the theoretical water delivery pressure, the theoretical main pipeline flow, the theoretical input power and respective corresponding actual values comprises: respectively calculating difference values of the theoretical water delivery pressure, the theoretical main pipeline flow, the theoretical input power and respective corresponding actual values to correspondingly obtain a current pressure difference, a current flow difference and a current power difference; calculating a fault score of the feed water pump according to the current pressure difference, the current flow difference and the current power difference; determining the fault detection result according to the fault score.

7. The fault detection method of claim 6, wherein, The calculation of the fault score of the feed water pump according to the current pressure difference, the current flow difference and the current power difference comprises: Residual components are constructed based on the current pressure difference, the current flow difference and the current power difference respectively, to obtain each residual component; History residual data corresponding to each residual component within a preset history window is obtained; Based on the history residual data within the preset history window and each residual component, a drift sensitivity index corresponding to each residual component is calculated; Based on each drift sensitivity index and a corresponding credibility weight, the fault score is determined.

8. A fault detection apparatus characterized by comprising: The device comprises: a pressure calculation module configured to calculate a theoretical water delivery pressure of the feed water pump according to a real-time total flow of the feed water pump; a flow calculation module configured to calculate a theoretical main pipeline flow of the feed water pump based on the theoretical water delivery pressure; a power calculation module configured to calculate a theoretical input power of the feed water pump based on the theoretical main pipeline flow and the theoretical water delivery pressure; a verification module configured to perform cavitation verification on the feed water pump according to the theoretical main pipeline flow, to obtain a cavitation verification result; a fault detection module configured to, in a case where the cavitation verification result is passed, determine a fault detection result of the feed water pump according to the theoretical water delivery pressure, the theoretical main pipeline flow, the theoretical input power and respective corresponding actual values.

9. An electronic device, comprising: The electronic device comprises: at least one processor; and a memory connected to the at least one processor in communication; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the fault detection method of any one of claims 1-7.

10. A storage medium containing computer-executable instructions, wherein: The computer executable instructions, when executed by a computer processor, are used to execute the fault detection method of any one of claims 1-7.

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