Emergency diesel engine state performance evaluation method and device, controller and medium

Abstract

The invention discloses an emergency diesel engine state performance evaluation method and device, a controller and a medium, and the method comprises the steps: obtaining the field actual measurement data of an emergency diesel engine, carrying out the modeling according to the information of all parts in the emergency diesel engine, and obtaining an emergency diesel engine mechanism model; the emergency diesel engine mechanism model comprises a complete machine performance prediction mechanism model, a lubrication system mechanism model and a connecting rod assembly dynamics analysis mechanism model, field actual measurement data are input into the emergency diesel engine mechanism model for data calculation, and state parameters of a connecting rod assembly in an emergency diesel engine are obtained. And performing state performance evaluation on the emergency diesel engine according to the state parameters of the connecting rod assembly in the emergency diesel engine and the field actual measurement data. It can be seen that by establishing the emergency diesel engine mechanism model, the state performance of the emergency diesel engine can be rapidly and accurately evaluated in real time according to the field actual measurement data, timely and accurate health condition feedback is provided for maintenance personnel, and the operation reliability of the emergency diesel engine is improved.

Description

Technical Field

[0001] The invention relates to the technical field of nuclear power emergency diesel engines, and in particular to an emergency diesel engine state performance evaluation method, device, controller and medium. Background Art

[0002] In the operation of nuclear power plants, the reliability and continuous stable operation of emergency diesel engines are crucial. As one of the key controllers, the emergency diesel engine bears the key responsibility of power supply in various emergency situations, so the real-time monitoring and health assessment of its working status are particularly important. In the operation of the emergency diesel generator, the connecting rod is a key component connecting the piston and the crankshaft, and its working status directly affects the reliability of the entire unit.

[0003] At present, emergency diesel engines in nuclear power plants mainly use regular tests to verify the operating reliability of diesel engines, and monitor the state parameters of diesel engines to assist in judging the operating reliability of diesel engines. However, due to the lack of mechanism models of key systems and components, it is impossible to conduct real-time evaluation and prediction of the performance parameters of key systems and components of emergency diesel engines under rapid start-up conditions. Therefore, how to quickly and accurately evaluate the state performance of emergency diesel engines in real time is an urgent problem to be solved by technicians in this field. Summary of the invention

[0004] Based on this, it is necessary to address the above technical problems. The embodiments of the present invention provide an emergency diesel engine status performance evaluation method, device, controller and medium, which can quickly and accurately evaluate the status performance of the emergency diesel engine in real time, and provide maintenance personnel with timely and accurate health status feedback, so as to timely discover potential problems and take preventive maintenance measures.

[0005] A first aspect of an embodiment of the present application provides an emergency diesel engine state performance evaluation method, the emergency diesel engine state performance evaluation method comprising: Obtaining on-site measured data of the emergency diesel engine, wherein the on-site measured data includes the pressure before the lubricating oil filter, the pressure after the lubricating oil filter, the pre-lubricating oil pressure, the lubricating oil temperature, the lubricating oil pressure, the emergency diesel engine speed, and the generator active power; Modeling is performed according to the information of each component in the emergency diesel engine to obtain an emergency diesel engine mechanism model, wherein the emergency diesel engine mechanism model includes a first target model, a second target model and a third target model, the first target model is a whole machine performance prediction mechanism model, the second target model is a lubrication system mechanism model, and the third target model is a connecting rod assembly dynamics analysis mechanism model; Inputting the field measured data into the emergency diesel engine mechanism model for data calculation to obtain the state parameters of the connecting rod assembly in the emergency diesel engine; The state performance of the emergency diesel engine is evaluated according to the state parameters of the connecting rod assembly in the emergency diesel engine and the field measured data.

[0006] A second aspect of an embodiment of the present application provides an emergency diesel engine state performance evaluation device, the emergency diesel engine state performance evaluation device comprising: An acquisition module is used to acquire the on-site measured data of the emergency diesel engine, wherein the on-site measured data includes the pressure before the lubricating oil filter, the pressure after the lubricating oil filter, the pre-lubricating oil pressure, the lubricating oil temperature, the lubricating oil pressure, the emergency diesel engine speed and the generator active power; A modeling module, used for modeling according to the information of each component in the emergency diesel engine to obtain an emergency diesel engine mechanism model, wherein the emergency diesel engine mechanism model includes a first target model, a second target model and a third target model, the first target model is a whole machine performance prediction mechanism model, the second target model is a lubrication system mechanism model, and the third target model is a connecting rod assembly dynamics analysis mechanism model; A calculation module, used for inputting the field measured data into the emergency diesel engine mechanism model to perform data calculation and obtain the state parameters of the connecting rod assembly in the emergency diesel engine; An evaluation module is used to evaluate the state performance of the emergency diesel engine according to the state parameters of the connecting rod assembly in the emergency diesel engine and the field measured data.

[0007] In a third aspect, a controller is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the emergency diesel engine status performance evaluation method as described in the first aspect when executing the computer program.

[0008] In a fourth aspect, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the emergency diesel engine status performance evaluation method as described in the first aspect is implemented.

[0009] In summary, the present invention provides a method, device, controller and medium for evaluating the state performance of an emergency diesel engine, which obtains field measured data of the emergency diesel engine, wherein the field measured data includes the pressure before the lubricating oil filter, the pressure after the lubricating oil filter, the pre-lubricating oil pressure, the lubricating oil temperature, the lubricating oil pressure, the emergency diesel engine speed and the generator active power. Modeling is performed according to the information of each component in the emergency diesel engine to obtain the emergency diesel engine mechanism model, wherein the emergency diesel engine mechanism model includes a first target model, a second target model and a third target model, the first target model is a whole machine performance prediction mechanism model, the second target model is a lubrication system mechanism model, and the third target model is a connecting rod assembly dynamics analysis mechanism model. The field measured data is input into the emergency diesel engine mechanism model for data calculation to obtain the state parameters of the connecting rod assembly in the emergency diesel engine, and the state performance of the emergency diesel engine is evaluated according to the state parameters of the connecting rod assembly in the emergency diesel engine and the field measured data. It can be seen that by establishing an emergency diesel engine mechanism model, this application can realize real-time evaluation of the emergency diesel engine status performance based on on-site measured data, and provide maintenance personnel with timely and accurate health status feedback, so as to timely discover potential problems and take preventive maintenance measures, thereby improving the operating reliability of the emergency diesel engine. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0011] Figure 1 It is a flow chart of a method for evaluating the state performance of an emergency diesel engine provided by one embodiment of the present invention; Figure 2-3 It is a schematic diagram of studying the lubrication performance of a connecting rod assembly under 100% rated load in a third initial model in an emergency diesel engine state performance evaluation method provided by an embodiment of the present invention; Figure 4 It is a polar coordinate diagram of the connecting rod big end bearing load in an emergency diesel engine state performance evaluation method provided by an embodiment of the present invention; Figure 5-6 It is a schematic diagram of studying the lubrication performance of a connecting rod assembly at 75% of the rated load in a third initial model in an emergency diesel engine state performance evaluation method provided by an embodiment of the present invention; Figure 7-8 It is a schematic diagram of studying the lubrication performance of a connecting rod assembly at 50% of the rated load in a third initial model in an emergency diesel engine state performance evaluation method provided by an embodiment of the present invention; Fig. 9 It is a structural schematic diagram of an emergency diesel engine state performance evaluation device provided by one embodiment of the present invention; Fig.10 It is a structural diagram of a controller provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0012] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technical personnel in this field without creative work are within the scope of protection of the present invention.

[0013] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0014] It should also be understood that the term "and / or" used in the present description and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0015] As used in the present specification and the appended claims, the term “if” may be interpreted as “when” or “uponce” or “in response to determining”, depending on the context. Similarly, the phrases “if it is determined” or “if matched to [described condition or event]” may be interpreted as meaning “upon determination” or “in response to determination” or “uponce matched to [described condition or event]” or “in response to matching to [described condition or event]”, depending on the context.

[0016] In addition, in the description of the present specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0017] References to "one embodiment" or "some embodiments" etc. described in the present specification mean that one or more embodiments of the present invention include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0018] It should be understood that the order of execution of the steps in the following embodiments does not imply a precedence of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0019] In order to illustrate the technical solution of the present invention, specific embodiments are provided below for illustration.

[0020] See also Figure 1 , is a flow chart of a method for evaluating the state performance of an emergency diesel engine provided by an embodiment of the present invention, such as Figure 1 As shown, the emergency diesel engine state performance evaluation method can be implemented through the following steps.

[0021] S101: Acquire on-site measured data of the emergency diesel engine, wherein the on-site measured data includes pressure before the lubricating oil filter, pressure after the lubricating oil filter, pre-lubricating oil pressure, lubricating oil temperature, lubricating oil pressure, emergency diesel engine speed, and generator active power.

[0022] In step S101, the pressure before the lubricating oil filter refers to the pressure of the lubricating oil before entering the filter, reflecting the fuel supply status of the emergency diesel engine; the pressure after the lubricating oil filter refers to the pressure measured after the lubricating oil passes through the filter, which is usually lower than the pressure before, indicating the resistance of the filter to the oil flow; the pre-lubricating oil pressure refers to the lubricating oil pressure provided by the pre-lubricating system before the engine starts, ensuring that the engine parts are lubricated in time when starting; the lubricating oil temperature refers to the temperature of the lubricating oil in the emergency diesel engine, which affects its viscosity and lubrication effect, and should usually be kept within an appropriate range; the lubricating oil pressure refers to the pressure of the lubricating oil when it flows in the emergency diesel engine, ensuring that the lubricating oil can be effectively delivered to various components; the speed of the emergency diesel engine refers to the speed of the diesel engine in an emergency state, which is usually required to be maintained within a certain range to ensure the normal operation of the generator; the active power of the generator refers to the actual output power of the generator, usually in kilowatts (kW), reflecting its power supply capacity. These parameters are important indicators to ensure the normal operation of the emergency diesel engine. The present application installs pressure sensors before and after the lubricating oil filter to obtain the pressure before the lubricating oil filter, the pressure after the lubricating oil filter, the pre-lubricating oil pressure and the lubricating oil pressure, installs a temperature sensor in the lubricating oil pipeline to obtain the lubricating oil temperature, installs a speed sensor on the emergency diesel engine to obtain the speed of the emergency diesel engine, installs a power sensor or a power meter at the output port of the generator to obtain the active power of the generator, connects all sensors to a data recorder or a controller, so that the data recorder or the controller can obtain the field measured data of the emergency diesel engine fed back by all sensors, thereby Accurately reflect the actual working status of the emergency diesel engine.

[0023] In this embodiment, by acquiring the on-site measured data of the emergency diesel engine, the operating status of the emergency diesel engine can be fully understood, so that once a failure or abnormal situation occurs later, it can be quickly and accurately located and measures can be taken to improve the emergency response capability.

[0024] S102: Modeling is performed according to the information of each component in the emergency diesel engine to obtain an emergency diesel engine mechanism model, wherein the emergency diesel engine mechanism model includes a first target model, a second target model and a third target model, the first target model is a whole machine performance prediction mechanism model, the second target model is a lubrication system mechanism model, and the third target model is a connecting rod assembly dynamics analysis mechanism model.

[0025] In step S102, the information of each component in the emergency diesel engine is obtained, such as the cylinder, crankshaft, connecting rod, turbocharger, lubrication system, etc. After determining the information of each component in the emergency diesel engine, according to the basic parameters of the diesel engine (such as power, speed), and the working principle, characteristics and operating conditions (such as load, ambient temperature, etc.) of each component information, software tools (such as MATLAB / Simulink, ANSYS, etc.) can be used for simulation modeling, and then the mathematical models of each component are integrated together to form a complete emergency diesel engine mechanism model to ensure that the model can accurately reflect the actual operating status of the diesel engine. The emergency diesel engine mechanism model includes a first target model, a second target model and a third target model. The first target model is a whole machine performance prediction mechanism model, the second target model is a lubrication system mechanism model, and the third target model is a connecting rod assembly dynamics analysis mechanism model.

[0026] In one embodiment of the invention, modeling is performed based on information of each component in the emergency diesel engine to obtain an emergency diesel engine mechanism model, including: The component information of the emergency diesel engine of the nuclear power plant is divided according to a preset division method to obtain first divided component information, second divided component information and third divided component information, wherein the first divided component information includes the intake and exhaust pipes, the engine body, the intercooler and the turbocharger, the second divided component information includes the main lubricating oil pump, the pre-lubricating oil pump, the heat exchanger, the lubricating oil filter and the pipelines including the lubricating oil pipelines of each subsystem entering the emergency diesel engine, and the third divided component information includes the connecting rod body, the connecting rod large and small end bearings, the crankshaft and the piston pin; Models are constructed for the first divided component information, the second divided component information and the third divided component information in a simulation platform to obtain a first target model, a second target model and a third target model.

[0027] Specifically, the component information of the emergency diesel engine of the nuclear power plant is divided according to a preset division method to obtain first divided component information, second divided component information and third divided component information, wherein the first divided component information includes intake and exhaust pipes, engine body, intercooler and turbocharger, the second divided component information includes main lubricating oil pump, pre-lubricating oil pump, heat exchanger, lubricating oil filter and pipelines including lubricating oil pipelines of various subsystems entering the emergency diesel engine, the third divided component information includes connecting rod body, connecting rod large and small end bearings, crankshaft, piston pin, and then the intake and exhaust pipes, engine body, intercooler and turbocharger in the first divided component information are divided into the third divided component information, and the third divided component information includes the third divided component information. The engine body, intercooler and turbocharger are modeled in the simulation platform to obtain the first target model, i.e. the whole machine performance prediction mechanism model. The second divided component information, including the main lubricating oil pump, pre-lubricating oil pump, heat exchanger, lubricating oil filter and the lubricating oil pipelines entering the subsystems of the emergency diesel engine, are modeled in the simulation platform to obtain the second target model, i.e. the lubrication system mechanism model. The third divided component information, including the connecting rod body, connecting rod large and small end bearings, crankshaft and piston pin, are modeled in the simulation platform to obtain the third target model, i.e. the connecting rod assembly dynamic analysis mechanism model. By modeling the various components of the emergency diesel engine in layers, not only can their performance, faults and optimization paths be analyzed independently, but also strong support can be provided for the integrated optimization of the entire emergency diesel engine, thereby improving the reliability and efficiency of the entire emergency diesel engine.

[0028] It should be noted that the preset division method can be set according to actual conditions, and this application does not impose any limitation on this.

[0029] In one embodiment of the invention, the first divided component information, the second divided component information, and the third divided component information are respectively modeled in a simulation platform to obtain the first target model, the second target model, and the third target model, including: Respectively building models for the first divided component information, the second divided component information, and the third divided component information in a simulation platform to obtain a first initial model, a second initial model, and a third initial model; The first initial model, the second initial model and the third initial model are simulated and calibrated respectively, and the calibrated first initial model, the second initial model and the third initial model are verified respectively to generate the first target model, the second target model and the third target model.

[0030] Specifically, the first divided component information, the second divided component information and the third divided component information are modeled in the simulation platform to obtain the first initial model, the second initial model and the third initial model. For the first initial model, according to the provided test data, the first initial model is calibrated, and the speed, power, explosion pressure, exhaust average temperature, intake pressure A column, intake pressure B column and fuel consumption rate are calculated at 100%, 75%, 50% and 25% load respectively, and then the calibrated first initial model is verified. When the verification and calibration results are successful, the first target model is generated, that is, the whole machine performance prediction mechanism model. The main test data and simulation results of each working condition are shown in Table 1 below: Table 1

[0031] For the second initial model, based on the test data of the lubrication system at three different speeds, the second initial model is calibrated, and the pre-lubricating oil pressure, lubricating oil pressure, turbocharger oil pressure 1, turbocharger oil pressure 2, valve gear lubricating oil pressure, piston cooling oil pressure, lubricating oil temperature (because the lubricating oil temperature needs to be calculated for a longer time to converge, the result will be confirmed after a longer calculation), lubricating oil filter front pressure, lubricating oil filter rear pressure and filter pressure difference are calculated at 1500rpm, 1000rpm and 500rpm respectively. Then, the calibrated second initial model is verified. When the verification and calibration results are successful, the second target model, i.e., the lubrication system mechanism model, is generated. The main test data and simulation results of each working condition are shown in Tables 2 and 3 below: Table 2

[0032] Table 3

[0033] For the third initial model, the third initial model is calibrated according to the provided test data, and the lubrication performance and wear calculation of the connecting rod assembly are carried out at 100%, 75% and 50% of the rated load respectively. Then, the calibrated third initial model is verified. When the verification and calibration results are successful, the third target model is generated, that is, the connecting rod assembly dynamics analysis mechanism model.

[0034] In the study of the lubrication performance of the connecting rod assembly under 100% rated load, the bearing lubrication performance related parameters are calculated and analyzed through model simulation. The parameters include the minimum oil film thickness, the maximum oil film pressure, etc. One of the main indicators for measuring the bearing lubrication performance is the minimum oil film thickness. The minimum oil film thickness of the connecting rod big end bearing changes with the crankshaft angle. Figure 2As shown in the figure, the minimum oil film thickness varies greatly at different crankshaft angles. The minimum oil film thickness decreases sharply from the combustion top dead center to 18°CA after the combustion top dead center, and decreases slowly from 18°CA to 81°CA after the combustion top dead center. The minimum oil film thickness appears at 81°CA after the combustion top dead center. The maximum oil film pressure of the connecting rod big end bearing changes with the crankshaft angle as shown in the figure. Figure 3 As shown, the maximum oil film pressure peak occurs at 13.5°CA after combustion top dead center. This is because 13.5°CA after combustion top dead center is located near the maximum explosion pressure, and the larger bearing load leads to a larger maximum oil film pressure. For example, when the minimum film thickness occurs at 81°CA after combustion top dead center, which corresponds to 0.129s in the model calculation, the bearing load applied during the calculation process still exists at 0.129s, which is about 1 / 6 of the peak load. That is, in the process from 13.5°CA after combustion top dead center to 81°CA after combustion top dead center, it has been forcefully applied to the bearing, the load gradually decreases, the peak oil film pressure gradually decreases, but the minimum film thickness gradually decreases. Among them, the bearing load is obtained by extracting the fluid load in the bearing lubrication domain, and after coordinate transformation, the bearing load under the polar coordinate diagram of the connecting rod big end bearing load can be obtained, as shown in the figure. Figure 4 shown.

[0035] In the study of the lubrication performance of the connecting rod assembly under 75% of the rated load, the minimum oil film thickness of the connecting rod big end bearing changes with the crankshaft angle as follows Figure 5 As shown in the figure, in one cycle, the minimum oil film thickness at different crankshaft angles varies greatly. The oil film thickness decreases sharply after the explosion pressure, and the minimum oil film thickness decreases sharply from the combustion top dead center to 18°CA after the combustion top dead center. The minimum film thickness decreases slowly from 18°CA to 81°CA after the combustion top dead center, and the minimum oil film thickness appears at 81°CA after the combustion top dead center. The maximum oil film pressure of the connecting rod big end bearing changes with the crankshaft angle as shown in the figure. Figure 6 As shown in the figure, unlike the rated working condition, the maximum oil film pressure does not appear near the explosion pressure, but appears at the moment when the inertia force is the largest. 18°CA after the combustion top dead center is near the maximum explosion pressure, and the large bearing load causes a peak in the maximum oil film pressure; in the study of the lubrication performance of the connecting rod assembly under 50% of the rated load, the minimum oil film thickness of the connecting rod big end bearing changes with the crankshaft angle as shown in the figure. Figure 7 As shown in Figure 2, in one cycle, the minimum oil film thickness at different crankshaft angles varies greatly. The maximum oil film pressure at the connecting rod big end bearing changes with the crankshaft angle as shown in Figure 2. Figure 8As shown. Due to the low load, the oil film pressure generated by the inertial force near the exhaust top dead center becomes the peak. Through the above steps, the model building, simulation calibration and verification of the information of each component in the emergency diesel engine can be realized, and finally an accurate and reliable target model can be generated. These target models can be used for performance evaluation, fault prediction, optimization design, etc., thereby providing strong support for the safe operation of the emergency diesel engine.

[0036] In addition, when establishing the dynamic analysis mechanism model of the connecting rod assembly, component wear will occur. By calculating the corresponding component wear, the dynamic analysis mechanism model of the connecting rod assembly can be optimized, so that the model can output more accurate state parameters. For example, for the wear of the connecting rod big end bearing, the wear calculation can be based on the Archard model. The Archard model believes that the wear amount between the contact surfaces is proportional to the normal contact pressure and the relative sliding distance, and inversely proportional to the hardness of the material. The calculation formula is shown as follows: ; Where V is the total wear volume, S is the relative slip distance, is the dimensionless wear coefficient, is the normal load on the contact surface, H is the material hardness, divide both sides of the above formula by the contact area A, and express it in differential form: ; Among them, k is the dimensioned fit wear coefficient, h is the wear depth, and p is the bearing-journal mixed lubrication contact pressure. Based on the calculated bearing-journal mixed lubrication contact pressure, the wear amount of the inner surface of the bearing in one working cycle can be calculated using the following formula: ; in: is the total wear amount of the i-th bearing inner surface node in one working cycle, is the time of one working cycle, is the mixed lubrication contact pressure of the bearing-journal at the node i at time t, is the relative speed of the bearing shell and journal at node i at time t. For example, according to the Archard model, the maximum wear amount on the inner surface of the bearing shell in one working cycle is According to the wear limit standard of sliding bearings, the bearing clearance increment is limited to 50% of the original clearance and the remaining thickness of the alloy layer is greater than 20% of the original thickness. The wear cycle number of the bearing bush is calculated to be , that is, the wear life is hours .

[0037] In this embodiment, an emergency diesel engine mechanism model is established so that the performance of the emergency diesel engine under different operating conditions can be accurately predicted and optimized, thereby improving the overall performance and operating efficiency of the emergency diesel engine, thereby providing better support for the operation and maintenance of the emergency diesel engine.

[0038] S103: Inputting the field measured data into the emergency diesel engine mechanism model to perform data calculation to obtain state parameters of the connecting rod assembly in the emergency diesel engine.

[0039] In step S103, the field measured data is cleaned and sorted to ensure the accuracy and completeness of the data, and the field measured data is converted into a format recognizable by the model, such as CSV, Excel or the data input format of a specific software, and then the processed field measured data is input into the emergency diesel engine mechanism model to ensure that the input data corresponds to the parameters and variables in the model so as to perform accurate calculations, thereby obtaining the state parameters of the connecting rod assembly in the emergency diesel engine, such as the stress, deformation, lubrication performance, wear condition, etc. of the connecting rod assembly.

[0040] In one embodiment of the invention, the field measured data is input into the emergency diesel engine mechanism model for data calculation to obtain the state parameters of the connecting rod assembly in the emergency diesel engine, including: Inputting the emergency diesel engine speed and the generator active power into the first target model to calculate the cylinder pressure curve of the emergency diesel engine in real time; Inputting the lubricating oil filter front pressure, the lubricating oil filter rear pressure, the pre-lubricating oil pressure, the lubricating oil temperature, the lubricating oil pressure and the emergency diesel engine speed into the second target model, and calculating the bearing lubricating oil pressure and the bearing lubricating oil temperature of the connecting rod assembly in real time; The cylinder pressure curve of the emergency diesel engine, the bearing lubricating oil pressure and the bearing lubricating oil temperature of each connecting rod assembly are input into the third target model, and the stress-strain parameters, bearing lubrication performance parameters and fatigue life parameters of the connecting rod assembly are calculated in real time.

[0041] Specifically, the emergency diesel engine speed and the generator active power are input into the first target model (machine performance prediction mechanism model), and the cylinder pressure curve of the emergency diesel engine is calculated in real time. Then, the pressure before the lubricating oil filter, the pressure after the lubricating oil filter, the pre-lubricating oil pressure, the lubricating oil temperature, the lubricating oil pressure and the emergency diesel engine speed are input into the second target model (lubrication system mechanism model), and the bearing lubricating oil pressure and bearing lubricating oil temperature of the connecting rod assembly are calculated in real time. Finally, the obtained cylinder pressure curve of the emergency diesel engine, the bearing lubricating oil pressure and the bearing lubricating oil temperature of each connecting rod assembly are input into the third target model (connecting rod assembly dynamic analysis mechanism model), and the stress-strain parameters, bearing lubrication performance parameters and fatigue life parameters of the connecting rod assembly are calculated in real time. Among them, the stress in the stress-strain parameters refers to the complex stress state that the connecting rod assembly will be subjected to during operation, including alternating tensile and compressive stresses and bending stresses. The magnitude and direction of these stresses will change continuously with the movement of the connecting rod, and the strain is the change in shape and size of the connecting rod after being subjected to stress; the bearing lubrication performance parameters may include the viscosity of the lubricating oil, the thickness of the lubricating film, the friction coefficient, etc. The selection and optimization of these parameters need to be comprehensively considered based on the working conditions, materials, and lubrication methods of the bearings. Fatigue life parameters are usually determined through fatigue tests, that is, measuring the number of cycles required for fatigue failure of the connecting rod assembly under a certain stress level, and are affected by many factors, including the material, structure, manufacturing process, and working environment of the connecting rod. By calculating the stress-strain parameters, bearing lubrication performance parameters, and fatigue life parameters of the connecting rod assembly in real time, it is helpful to timely discover the lubricating oil film state, connecting rod stress state, and wear and fatigue damage of the connecting rod assembly, reminding the operator to take corresponding measures to avoid the occurrence or expansion of faults, thereby improving the operating efficiency and safety of emergency diesel engines.

[0042] And for the dynamic analysis mechanism model of the connecting rod assembly, a single group of connecting rod dynamic components can be used for modeling and calculation. In order to improve the calculation efficiency and reduce the difficulty of model convergence, only the flexible deformation of the object of interest is considered in the model, and the other components are set as rigid bodies. The crankshaft and the small end pin are set as rigid domains, and the other components are set as flexible domains, saving a lot of calculation time. In order to realize the online deployment and calculation of the model, the proxy model is constructed by deep neural network (DNN). The DNN model consists of an input layer, a series of hidden layers and an output layer, and each layer consists of several nodes or neurons. And for the fatigue life parameters of the connecting rod, this model uses the Basquin high-cycle fatigue criterion to predict the fatigue life, assuming that the fatigue life and elastic stress conform to the power relationship. Since the connecting rod is in a compressed state, it is mainly controlled by the third principal stress, and the other two principal stresses are very small. Therefore, we can regard the stress state in the dangerous point area of ​​the rod as uniaxial stress, and the third principal stress can be used as the amplitude stress in the Basquin relationship.

[0043] ; in, is the stress amplitude, and b are material constants, is the number of failure cycles.

[0044] For the fatigue life parameters of the connecting rod big end bearing, the Basquin formula based on shear stress is used to predict the fatigue life according to its multi-axis high-cycle fatigue cycle characteristics.

[0045] ; in, is the shear stress amplitude, and b are material constants, is the number of failure cycles.

[0046] In this embodiment, through the emergency diesel engine mechanism model, the state parameters of the connecting rod assembly in the emergency diesel engine can be calculated quickly and accurately, thereby achieving accurate prediction and optimization of the performance of the emergency diesel engine under different operating conditions, so as to subsequently quickly and accurately evaluate the state performance of the emergency diesel engine and avoid the impact of different environmental conditions on the performance.

[0047] S104: Evaluate the state performance of the emergency diesel engine according to the state parameters of the connecting rod assembly in the emergency diesel engine and the field measured data.

[0048] In step S104, after the state parameters of the connecting rod assembly in the emergency diesel engine are calculated by the emergency diesel engine mechanism model, the state performance of the emergency diesel engine is evaluated according to the state parameters of the connecting rod assembly in the emergency diesel engine and the field measured data to obtain an evaluation result.

[0049] In one embodiment of the invention, the state performance evaluation of the emergency diesel engine is performed according to the state parameters of the connecting rod assembly in the emergency diesel engine and the field measured data, including: Performing deviation analysis based on the state parameters of the connecting rod assembly in the emergency diesel engine and the field measured data to obtain the expected state deviation vector of the emergency diesel engine; Conducting data tracing for the emergency diesel engine and building a performance evaluation space for the emergency diesel engine; Calculating a performance evaluation index of the emergency diesel engine based on the state expectation deviation vector and the performance evaluation space; Determining whether the performance evaluation index of the emergency diesel engine is less than a preset performance evaluation index; If the performance evaluation index of the emergency diesel engine is less than the preset performance evaluation index, a performance warning signal is generated and an equipment maintenance plan is formulated, wherein the equipment maintenance plan is used to instruct staff to perform equipment maintenance on the emergency diesel engine.

[0050] Specifically, the state parameters of the connecting rod assembly in the emergency diesel engine and the field measured data are vectorized respectively to generate a real-time state vector and an expected state vector. According to the expected state vector, the real-time state vector is identified for deviation to generate the state expected deviation vector of the emergency diesel engine, that is, the state parameters of the connecting rod assembly in the emergency diesel engine and the field measured data are compared to find the difference between the two and obtain the state expected deviation vector of the emergency diesel engine. Vectorization is a method of converting data into vector form for mathematical calculation and analysis. The process of deviation identification can be realized through vector operation, which is specifically expressed as: state expected deviation vector = real-time state vector - expected state vector. Deviation identification refers to comparing the real-time state vector with the expected state vector, finding the difference between the two, and revealing the performance deviation of the emergency diesel engine. By calculating the deviation of each parameter, it is determined in which aspects of the operating state of the emergency diesel engine is different from the expected state, which helps to accurately evaluate the performance of the emergency diesel engine, timely discover performance deviations, and take corresponding maintenance or optimization measures. The data of the emergency diesel engine is traced, and the performance evaluation space of the emergency diesel engine is built to realize all-round monitoring, performance optimization and anomaly detection of the operating status of the emergency diesel engine. The state expectation deviation vector is input into the performance evaluation space, and the performance evaluation index of the emergency diesel engine is calculated. It is helpful to understand the overall performance of the emergency diesel engine, discover performance deviations in time, and take corresponding maintenance or optimization measures. By presetting a performance evaluation index, it represents the minimum acceptable standard of the performance of the emergency diesel engine. If the performance evaluation index is lower than this preset value, it indicates that the emergency diesel engine may be in an abnormal state or insufficient performance, and there may be potential risks or failures. The performance evaluation index is a comprehensive indicator of the current performance calculated, reflecting the operating status and health of the emergency diesel engine. Determine whether the performance evaluation index is less than the preset performance evaluation index. If the performance evaluation index is lower than the threshold, it means that the performance of the emergency diesel engine has declined, and the operating status may be unstable or abnormal, and then it is necessary to formulate an equipment maintenance plan. The equipment maintenance plan is used to instruct the staff to perform equipment maintenance on the emergency diesel engine. At this time, a performance warning signal needs to be generated to inform the system or operator that the performance of the emergency diesel engine has dropped to an unsafe state and requires attention or intervention. After the warning signal is generated, the operator is reminded of possible problems through an alarm or notification, requiring inspection of the status of the emergency diesel engine or maintenance measures. By monitoring the performance evaluation index of the emergency diesel engine and generating a warning signal, effective measures can be taken in time when the performance of the emergency diesel engine deteriorates to reduce the risk of failure.

[0051] It should be noted that the preset performance evaluation index can be set according to actual conditions, and this application does not impose any limitation on this.

[0052] In one embodiment of the invention, data tracing is performed on the emergency diesel engine to build a performance evaluation space for the emergency diesel engine, including: Performing a global expected deviation search on the emergency diesel engine to obtain a state expected deviation vector record set; Performing confidence evaluation processing on the state expected deviation vector record set to obtain a performance evaluation record set; The state expected deviation vector record set and the performance evaluation record set are input into the preset performance evaluation coordinate system to construct the performance evaluation space of the emergency diesel engine, wherein the preset performance evaluation coordinate system is constructed with the sample state expected deviation vector as the horizontal axis and the sample performance evaluation index as the vertical axis.

[0053] Specifically, by accessing a global state record database or a historical data set, a global expected deviation retrieval and analysis is performed on the operating history data of the emergency diesel engine to obtain a state expected deviation vector record set, which includes multiple sample state expected deviation vectors. By performing confidence assessment processing on the state expected deviation vector record set, a performance evaluation record set is obtained, wherein the confidence assessment is to ensure that the data used for performance evaluation is high-quality and reliable by evaluating the accuracy and reliability of each record. Then, with the sample state expected deviation vector as the horizontal axis and the sample performance evaluation index as the vertical axis, the deviation vector and the performance index are mapped to a two-dimensional coordinate system, and a coordinate system for visualizing and analyzing the performance of the emergency diesel engine is established. The state expected deviation vector record set and the performance evaluation record set are input into a preset performance evaluation coordinate system, and a three-dimensional evaluation space is generated according to the performance evaluation index corresponding to different deviation vectors, which reflects the performance of the emergency diesel engine under various working conditions. By conducting data tracing and multi-dimensional analysis of emergency diesel engines and building a performance evaluation space for emergency diesel engines, we can intuitively see the relationship between performance and deviation, achieve all-round monitoring of the operating status of emergency diesel engines, performance optimization and anomaly detection, and thus optimize maintenance plans and strategies.

[0054] In one embodiment of the invention, the performance evaluation index of the emergency diesel engine is calculated based on the state expected deviation vector and the performance evaluation space, including: Inputting the state expected deviation vector into the performance evaluation space, calculating the distance between the state expected deviation vector and each sample state expected deviation vector in the performance evaluation space, and obtaining a plurality of vector target distances; Determining whether the multiple vector target distances are less than a vector target distance threshold; If any one of the plurality of vector target distances is less than the vector target distance threshold, generating an identification vector target distance; Cluster calculation is performed based on the sample performance evaluation index corresponding to the identification vector target distance to generate the performance evaluation index of the emergency diesel engine.

[0055] Specifically, the state expected deviation vector is input into the performance evaluation space, and the distance between the state expected deviation vector and each sample state expected deviation vector in the performance evaluation space is calculated to obtain multiple vector target distances. Common distance calculation methods include Euclidean distance, cosine similarity, etc. The purpose of calculating the distance is to find the historical states that are most similar to the current state, so as to obtain the corresponding performance evaluation index. Multiple vector target distances reflect the degree of difference between the input vector and each sample vector in the space, representing the similarity between the current state and the historical sample state. The smaller the distance, the closer the current state is to the state of a historical sample. The state expected deviation vector is a multidimensional vector that describes the difference between the current operating state and the expected state of the emergency diesel engine. The performance evaluation space is a multidimensional space established previously, which contains a large number of sample state expected deviation vectors and corresponding performance evaluation indices. A critical value, namely the vector target distance threshold, is pre-set to measure whether the current state is close enough to the historical sample state. It is determined whether each vector target distance is less than the threshold to determine whether the current state matches the state of certain samples. If any of the vector target distances among the multiple vector target distances is less than the vector target distance threshold, it is considered that the input state expected deviation vector is similar to the corresponding sample state expected deviation vector, that is, the positions of the two in the performance evaluation space are close. In this case, a representation is generated to indicate that the input state expected deviation vector is similar to a sample vector in the performance evaluation space. It can be a simple logical value (such as True or False) or a more complex data structure for recording specific similarity information. By identifying the vectors that meet the conditions, the most valuable historical sample states are screened out to avoid using irrelevant data to affect the evaluation results. Once the historical sample vector closest to the current state is found, clustering calculations are performed based on the performance evaluation index of the sample. Common clustering calculations include K-means clustering, hierarchical clustering, etc., and then the performance evaluation index of the emergency diesel engine is obtained to identify the overall performance of the current emergency diesel engine under the running state. By inputting the state expected deviation vector into the performance evaluation space and calculating the distance between similar vectors, a performance evaluation index based on historical data is generated to reflect the current performance status of the emergency diesel engine, which helps to understand the overall status of the emergency diesel engine performance, reduces the error of the evaluation results, and avoids the interference of irrelevant data.

[0056] It should be noted that the vector target distance threshold can be set according to actual conditions, and this application does not impose any limitation on this.

[0057] In this embodiment, the state performance of the emergency diesel engine is evaluated based on the state parameters of the connecting rod assembly in the emergency diesel engine and the actual measured data on site, so as to perform real-time monitoring and early warning, thereby improving the accuracy of the state performance evaluation of the emergency diesel engine. Then, based on the evaluation results, a reasonable maintenance plan and management strategy are formulated to extend the service life of the emergency diesel engine and reduce maintenance costs, thereby improving the operating efficiency and overall performance of the emergency diesel engine.

[0058] In summary, the present invention provides a method, device, controller and medium for evaluating the state performance of an emergency diesel engine, which obtains field measured data of the emergency diesel engine, wherein the field measured data includes the pressure before the lubricating oil filter, the pressure after the lubricating oil filter, the pre-lubricating oil pressure, the lubricating oil temperature, the lubricating oil pressure, the emergency diesel engine speed and the generator active power. Modeling is performed according to the information of each component in the emergency diesel engine to obtain the emergency diesel engine mechanism model, wherein the emergency diesel engine mechanism model includes a first target model, a second target model and a third target model, the first target model is a whole machine performance prediction mechanism model, the second target model is a lubrication system mechanism model, and the third target model is a connecting rod assembly dynamics analysis mechanism model. The field measured data is input into the emergency diesel engine mechanism model for data calculation to obtain the state parameters of the connecting rod assembly in the emergency diesel engine, and the state performance of the emergency diesel engine is evaluated according to the state parameters of the connecting rod assembly in the emergency diesel engine and the field measured data. It can be seen that by establishing an emergency diesel engine mechanism model, this application can realize real-time evaluation of the emergency diesel engine status performance based on on-site measured data, and provide maintenance personnel with timely and accurate health status feedback, so as to timely discover potential problems and take preventive maintenance measures, thereby improving the operating reliability of the emergency diesel engine.

[0059] See also Fig. 9 , Fig. 9 Schematic diagram of the structure of the emergency diesel engine state performance evaluation device provided by the embodiment of the present invention. The emergency diesel engine state performance evaluation device corresponds to the emergency diesel engine state performance evaluation method in the above embodiment. Fig. 9 as well as Fig. 9 For the convenience of explanation, only the parts related to this embodiment are shown. Fig. 9 The emergency diesel engine state performance evaluation device 90 includes: an acquisition module 91, a modeling module 92, a calculation module 93, and an evaluation module 94.

[0060] An acquisition module 91 is used to acquire the field measured data of the emergency diesel engine, wherein the field measured data includes the pressure before the lubricating oil filter, the pressure after the lubricating oil filter, the pre-lubricating oil pressure, the lubricating oil temperature, the lubricating oil pressure, the emergency diesel engine speed and the generator active power; A modeling module 92 is used to perform modeling according to the information of each component in the emergency diesel engine to obtain an emergency diesel engine mechanism model, wherein the emergency diesel engine mechanism model includes a first target model, a second target model and a third target model, wherein the first target model is a whole machine performance prediction mechanism model, the second target model is a lubrication system mechanism model, and the third target model is a connecting rod assembly dynamics analysis mechanism model; A calculation module 93 is used to input the field measured data into the emergency diesel engine mechanism model to perform data calculation and obtain the state parameters of the connecting rod assembly in the emergency diesel engine; The evaluation module 94 is used to evaluate the state performance of the emergency diesel engine according to the state parameters of the connecting rod assembly in the emergency diesel engine and the field measured data.

[0061] Optionally, the modeling module 92 is specifically used for: The component information of the emergency diesel engine of the nuclear power plant is divided according to a preset division method to obtain first divided component information, second divided component information and third divided component information, wherein the first divided component information includes the intake and exhaust pipes, the engine body, the intercooler and the turbocharger, the second divided component information includes the main lubricating oil pump, the pre-lubricating oil pump, the heat exchanger, the lubricating oil filter and the pipelines including the lubricating oil pipelines of each subsystem entering the emergency diesel engine, and the third divided component information includes the connecting rod body, the connecting rod large and small end bearings, the crankshaft and the piston pin; Models are constructed for the first divided component information, the second divided component information, and the third divided component information in a simulation platform to obtain the first target model, the second target model, and the third target model.

[0062] Optionally, the modeling module 92 is further used for: Respectively building models for the first divided component information, the second divided component information, and the third divided component information in a simulation platform to obtain a first initial model, a second initial model, and a third initial model; The first initial model, the second initial model and the third initial model are simulated and calibrated respectively, and the calibrated first initial model, the second initial model and the third initial model are verified respectively to generate the first target model, the second target model and the third target model.

[0063] Optionally, the calculation module 93 is specifically used for: Inputting the emergency diesel engine speed and the generator active power into the first target model to calculate the cylinder pressure curve of the emergency diesel engine in real time; Inputting the lubricating oil filter front pressure, the lubricating oil filter rear pressure, the pre-lubricating oil pressure, the lubricating oil temperature, the lubricating oil pressure and the emergency diesel engine speed into the second target model, and calculating the bearing lubricating oil pressure and the bearing lubricating oil temperature of the connecting rod assembly in real time; The cylinder pressure curve of the emergency diesel engine, the bearing lubricating oil pressure and the bearing lubricating oil temperature of each connecting rod assembly are input into the third target model, and the stress-strain parameters, bearing lubrication performance parameters and fatigue life parameters of the connecting rod assembly are calculated in real time.

[0064] Optionally, the evaluation module 94 is specifically used for: Perform deviation analysis based on the state parameters of the connecting rod assembly in the emergency diesel engine and the field measured data to obtain the state expected deviation vector of the emergency diesel engine; Conducting data tracing for the emergency diesel engine and building a performance evaluation space for the emergency diesel engine; Calculating a performance evaluation index of the emergency diesel engine based on the state expectation deviation vector and the performance evaluation space; Determining whether the performance evaluation index of the emergency diesel engine is less than a preset performance evaluation index; If the performance evaluation index of the emergency diesel engine is less than the preset performance evaluation index, a performance warning signal is generated and a controller maintenance plan is formulated, wherein the controller maintenance plan is used to instruct staff to perform controller maintenance on the emergency diesel engine.

[0065] Optionally, the evaluation module 94 is further used for: Performing a global expected deviation search on the emergency diesel engine to obtain a state expected deviation vector record set; Performing confidence evaluation processing on the state expected deviation vector record set to obtain a performance evaluation record set; The state expected deviation vector record set and the performance evaluation record set are input into a preset performance evaluation coordinate system to construct a performance evaluation space of the emergency diesel engine, wherein the preset performance evaluation coordinate system is constructed with the sample state expected deviation vector as the horizontal axis and the sample performance evaluation index as the vertical axis.

[0066] Optionally, the evaluation module 94 is further used for: Inputting the state expected deviation vector into the performance evaluation space, calculating the distance between the state expected deviation vector and each sample state expected deviation vector in the performance evaluation space, and obtaining a plurality of vector target distances; Determining whether the multiple vector target distances are less than a vector target distance threshold; If any one of the plurality of vector target distances is less than the vector target distance threshold, generating an identification vector target distance; Cluster calculation is performed based on the sample performance evaluation index corresponding to the identification vector target distance to generate the performance evaluation index of the emergency diesel engine.

[0067] It should be noted that the information interaction, execution process and other contents between the above-mentioned units are based on the same concept as the embodiment of the method of the present invention. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0068] Fig.10 Schematic diagram of a controller provided by an embodiment of the present invention. Fig.10 As shown, the controller of this embodiment includes: at least one processor ( Fig.10 Only one is shown), a memory, and a computer program stored in the memory and executable on at least one processor, wherein when the processor executes the computer program, the steps in any of the above-mentioned emergency diesel engine status performance evaluation method embodiments are implemented.

[0069] The controller may include, but is not limited to, a processor and a memory. It can be understood by those skilled in the art that Fig.10 This is merely an example of a controller and does not constitute a limitation of the controller. The controller may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, it may also include a network interface, a display screen, and an input system.

[0070] In one embodiment, a computer-readable storage medium is provided. When the instructions in the computer-readable storage medium are executed by a processor in a controller, the controller can execute the steps of any embodiment of an emergency diesel engine state performance evaluation method disclosed in the present invention, which will not be repeated here. The computer-readable storage medium can be non-volatile or volatile.

[0071] The processor may be a CPU, or other general-purpose processors, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0072] The memory includes a readable storage medium, an internal memory, etc., wherein the internal memory may be the memory of the controller, and the internal memory provides an environment for the operation of the operating system and computer-readable instructions in the readable storage medium. The readable storage medium may be the hard disk of the controller, and in other embodiments, it may also be an external storage controller of the controller, for example, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the controller. Further, the memory may also include both an internal storage unit of the controller and an external storage controller. The memory is used to store an operating system, a cooperative application, a boot loader (BootLoader), data, and other programs, such as the program code of a computer program, etc. The memory may also be used to temporarily store data that has been output or is to be output.

[0073] It can be understood by those skilled in the art that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0074] The technical business in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the system is divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here. If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium.

[0075] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, it should be understood by those skilled in the art that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A method for evaluating the state performance of an emergency diesel engine, characterized in that: include: Obtaining on-site measured data of the emergency diesel engine, wherein the on-site measured data includes the pressure before the lubricating oil filter, the pressure after the lubricating oil filter, the pre-lubricating oil pressure, the lubricating oil temperature, the lubricating oil pressure, the emergency diesel engine speed, and the generator active power; Modeling is performed according to the information of each component in the emergency diesel engine to obtain an emergency diesel engine mechanism model, wherein the emergency diesel engine mechanism model includes a first target model, a second target model and a third target model, the first target model is a whole machine performance prediction mechanism model, the second target model is a lubrication system mechanism model, and the third target model is a connecting rod assembly dynamics analysis mechanism model; Inputting the field measured data into the emergency diesel engine mechanism model for data calculation to obtain the state parameters of the connecting rod assembly in the emergency diesel engine; The state performance of the emergency diesel engine is evaluated according to the state parameters of the connecting rod assembly in the emergency diesel engine and the field measured data.

2. The emergency diesel engine state performance evaluation method according to claim 1, characterized in that: The step of modeling according to the information of each component in the emergency diesel engine to obtain the mechanism model of the emergency diesel engine includes: The component information of the emergency diesel engine of the nuclear power plant is divided according to a preset division method to obtain first divided component information, second divided component information and third divided component information, wherein the first divided component information includes the intake and exhaust pipes, the engine body, the intercooler and the turbocharger, the second divided component information includes the main lubricating oil pump, the pre-lubricating oil pump, the heat exchanger, the lubricating oil filter and the pipelines including the lubricating oil pipelines of each subsystem entering the emergency diesel engine, and the third divided component information includes the connecting rod body, the connecting rod large and small end bearings, the crankshaft and the piston pin; Models are constructed for the first divided component information, the second divided component information, and the third divided component information in a simulation platform to obtain the first target model, the second target model, and the third target model.

3. The emergency diesel engine state performance evaluation method according to claim 2, characterized in that: The first divided component information, the second divided component information and the third divided component information are respectively modeled in a simulation platform to obtain the first target model, the second target model and the third target model, including: Respectively building models for the first divided component information, the second divided component information, and the third divided component information in a simulation platform to obtain a first initial model, a second initial model, and a third initial model; The first initial model, the second initial model and the third initial model are simulated and calibrated respectively, and the calibrated first initial model, the second initial model and the third initial model are verified respectively to generate the first target model, the second target model and the third target model.

4. The emergency diesel engine state performance evaluation method according to claim 1, characterized in that: The step of inputting the field measured data into the emergency diesel engine mechanism model to perform data calculation to obtain the state parameters of the connecting rod assembly in the emergency diesel engine includes: Inputting the emergency diesel engine speed and the generator active power into the first target model to calculate the cylinder pressure curve of the emergency diesel engine in real time; Inputting the lubricating oil filter front pressure, the lubricating oil filter rear pressure, the pre-lubricating oil pressure, the lubricating oil temperature, the lubricating oil pressure and the emergency diesel engine speed into the second target model, and calculating the bearing lubricating oil pressure and the bearing lubricating oil temperature of the connecting rod assembly in real time; The cylinder pressure curve of the emergency diesel engine, the bearing lubricating oil pressure and the bearing lubricating oil temperature of each connecting rod assembly are input into the third target model, and the stress-strain parameters, bearing lubrication performance parameters and fatigue life parameters of the connecting rod assembly are calculated in real time.

5. The emergency diesel engine state performance evaluation method according to claim 1, characterized in that: The state performance evaluation of the emergency diesel engine according to the state parameters of the connecting rod assembly in the emergency diesel engine and the field measured data includes: Perform deviation analysis based on the state parameters of the connecting rod assembly in the emergency diesel engine and the field measured data to obtain the state expected deviation vector of the emergency diesel engine; Conducting data tracing for the emergency diesel engine and building a performance evaluation space for the emergency diesel engine; Calculating a performance evaluation index of the emergency diesel engine based on the state expectation deviation vector and the performance evaluation space; Determining whether the performance evaluation index of the emergency diesel engine is less than a preset performance evaluation index; If the performance evaluation index of the emergency diesel engine is less than the preset performance evaluation index, a performance warning signal is generated and a controller maintenance plan is formulated, wherein the controller maintenance plan is used to instruct staff to perform controller maintenance on the emergency diesel engine.

6. The emergency diesel engine state performance evaluation method according to claim 5, characterized in that: The data tracing of the emergency diesel engine and building a performance evaluation space for the emergency diesel engine include: Performing a global expected deviation search on the emergency diesel engine to obtain a state expected deviation vector record set; Performing confidence evaluation processing on the state expected deviation vector record set to obtain a performance evaluation record set; The state expected deviation vector record set and the performance evaluation record set are input into a preset performance evaluation coordinate system to construct a performance evaluation space of the emergency diesel engine, wherein the preset performance evaluation coordinate system is constructed with the sample state expected deviation vector as the horizontal axis and the sample performance evaluation index as the vertical axis.

7. The emergency diesel engine state performance evaluation method according to claim 5, characterized in that: The step of calculating the performance evaluation index of the emergency diesel engine based on the state expected deviation vector and the performance evaluation space includes: Inputting the state expected deviation vector into the performance evaluation space, calculating the distance between the state expected deviation vector and each sample state expected deviation vector in the performance evaluation space, and obtaining a plurality of vector target distances; Determining whether the multiple vector target distances are less than a vector target distance threshold; If any one of the plurality of vector target distances is less than the vector target distance threshold, generating an identification vector target distance; Cluster calculation is performed based on the sample performance evaluation index corresponding to the identification vector target distance to generate the performance evaluation index of the emergency diesel engine.

8. An emergency diesel engine status performance evaluation device, characterized in that: include: An acquisition module is used to acquire the on-site measured data of the emergency diesel engine, wherein the on-site measured data includes the pressure before the lubricating oil filter, the pressure after the lubricating oil filter, the pre-lubricating oil pressure, the lubricating oil temperature, the lubricating oil pressure, the emergency diesel engine speed and the generator active power; A modeling module, used for modeling according to the information of each component in the emergency diesel engine to obtain an emergency diesel engine mechanism model, wherein the emergency diesel engine mechanism model includes a first target model, a second target model and a third target model, the first target model is a whole machine performance prediction mechanism model, the second target model is a lubrication system mechanism model, and the third target model is a connecting rod assembly dynamics analysis mechanism model; A calculation module, used for inputting the field measured data into the emergency diesel engine mechanism model to perform data calculation and obtain the state parameters of the connecting rod assembly in the emergency diesel engine; An evaluation module is used to evaluate the state performance of the emergency diesel engine according to the state parameters of the connecting rod assembly in the emergency diesel engine and the field measured data.

9. A controller comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the emergency diesel engine status performance evaluation method as described in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the emergency diesel engine status performance evaluation method according to any one of claims 1 to 7 is implemented.

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