A slurry pump anti-wear performance detection system

Abstract

The present invention discloses a system for detecting the anti-wear performance of a slurry pump, which relates to the technical field of equipment performance detection. The system comprises a model building unit, a particle calculation unit, and a performance analysis unit. According to the compressive strength in the equipment information and the shape of the equipment components in the slurry pump, a contour model of the components is constructed. At the same time, according to the particle size and size of the ore in the environmental information, a mathematical model is used to calculate the sphericity of the ore, and based on the sphericity of the ore, the random effect of the particles is calculated. The wear value of the components in the slurry pump is calculated by combining the contour model with the sphericity and random effect of the particles, and the wear value is compared with a threshold value. An early warning signal is obtained according to the comparison result, so that there is a clear detection position in the process of performance detection of the slurry pump, thereby reducing the process of detecting all equipment components and improving data detection efficiency.

Description

Technical Field

[0001] The invention belongs to the technical field of equipment performance detection, and in particular is a system for detecting the anti-wear performance of a slurry pump. Background Art

[0002] Centrifugal slurry pumps serve as the power part of deep-sea mineral resource mining. The conveying system consists of centrifugal slurry pumps and their supporting pipelines. The conveying medium contains particles such as sand, gravel, and ore. There is often mutual friction and collision between the particles and the pipe wall and the flow-through components in the pump, which causes the pipe wall, impeller, and pump casing material to fall off, causing the pipe wall, impeller, and pump casing to become thinner and worn through, and the components cannot reach their expected service life, affecting the continuity of transportation and even creating safety hazards.

[0003] The invention with patent application publication number CN112302965A discloses a slurry pump performance detection method and device, which includes a slurry box that is connected to the slurry pump and is equipped with experimental slurries of solids with different concentrations and particle sizes, a sound sensor and a vibration sensor for extracting noise and vibration when the slurry pump is working, and a detection box; a control module and a detection module are arranged in the detection box, the control module controls the experimental slurries of solids with different concentrations and particle sizes to pass through the slurry pump, the detection module is connected to the sound sensor and the vibration sensor and performs data analysis and processing; the slurry pump performance detection device of the technical solution of the present invention analyzes the performance of the slurry pump when transporting slurries of solids with various concentrations and particle sizes by extracting the noise and vibration generated by the slurry pump when transporting slurries of solids with different concentrations and particle sizes, and judges the extreme values ​​of slurry concentration and particle size of solids transported by the slurry pump through the detection module. The detection is convenient and fast, and online detection is realized.

[0004] However, when the above scheme is used to test the performance of the slurry pump, the wear value of each area in the slurry pump is different, and the sphericity of the particles also affects the degree of wear in the slurry pump. When testing the wear performance of the slurry pump, if all positions of the slurry pump are tested, the complexity of the test data will increase. Summary of the Invention

[0005] The present invention aims to solve at least one of the technical problems existing in the prior art; to this end, the present invention proposes an anti-wear performance detection system for a slurry pump, which is used to solve the above-mentioned technical problem.

[0006] To achieve the above object, the present invention proposes the following solution: a slurry pump anti-wear performance detection system, comprising:

[0007] A model building unit builds a contour model of the component based on the compressive strength in the equipment information and the shape of the equipment component in the slurry pump;

[0008] A particle calculation unit calculates the sphericity of the ore using a mathematical model based on the particle size and size of the ore in the environmental information, and calculates the random effect of the particles based on the sphericity of the ore;

[0009] The performance analysis unit calculates the wear value of the components in the slurry pump based on the contour model, the sphericity of the particles and the random effect, and obtains an early warning signal based on the wear value and the threshold value A1.

[0010] As a further solution of the present invention, the device information and the environment information are acquired by the information acquisition unit and transmitted to the model building unit and the particle calculation unit respectively.

[0011] As a further solution of the present invention, the equipment components in the equipment information refer to components of the slurry pump that come into direct contact with the particulate matter, including the inlet extension section, impeller, volute and outlet extension section of the slurry pump.

[0012] As a further solution of the present invention, the method for constructing the contour model is:

[0013] First draw the outline model based on the shape of the device;

[0014] Select any equipment component as the target component, extract the compressive strength of the target component, and mark the compressive strength on the contour model of the target equipment;

[0015] The contour model of the target component is divided into structured grids to form multiple sub-regions, and the sub-regions are marked in the contour model to obtain the final contour model.

[0016] As a further embodiment of the present invention, the random effect of particles is calculated as follows:

[0017] Extract the particle size and dimensions from the environmental information and use them as input data to calculate the particle sphericity based on the EDEM particle packing model;

[0018] In the equipment components of the slurry pump, the inlet position of each equipment component is used as the initial position, and the flow velocity at the initial position is obtained. Based on the initial position and flow velocity, the Loth lift, pressure gradient, and virtual mass force are calculated respectively;

[0019] Update the position and velocity of the ore particles in real time according to the Loth lift, pressure gradient, and virtual mass force, and repeat the above steps until the preset time or number of iterations is reached;

[0020] The Loth lift, pressure gradient and virtual mass force were programmed into C++ language, and a discrete random walk model was also programmed to simulate the random effect of pulsating velocity on ore particles.

[0021] As a further solution of the present invention, the calculation method of the wear value of the component is:

[0022] Based on the slurry pump's transport flow rate, the size of the ore particles is obtained, and the mass fraction of the ore particles is obtained according to the different sizes. The mass fraction is then multiplied by the density of the ore to obtain the volume fraction. At the same time, the volume fractions of ores of different sizes are accumulated to obtain the particle volume fraction.

[0023] According to the contour model of the target component, the contour model is first connected in sequence according to the connection position in the slurry pump to obtain the virtual operation model of the slurry pump;

[0024] According to the actual operating parameters of the slurry pump, the operating parameters under different conditions are set for the virtual operation model. The random effect of particles is used as an influencing parameter to simulate and obtain the main collision area of ​​ore particles on the target component. The specific operating parameters include flow rate, head and speed.

[0025] based on The wear value MSi of the main collision area is obtained, where i represents different target components, Vk is the particle volume fraction, Ls is the head, Yc is the rotation speed, t is the running time of the slurry pump, Pki is the compressive strength of the target component i, Qx is the particle sphericity, a1 and a2 are weight coefficients, and Ci is the historical wear value of the target component i.

[0026] As a further solution of the present invention, the mass proportion is obtained by a mass accumulation curve, which is the proportion of the mass of the ore particles to the total mass within different size ranges.

[0027] As a further solution of the present invention, a method for obtaining the early warning signal is:

[0028] The wear value is compared with the threshold A1. When the wear value is less than or equal to the threshold A1, it indicates that the target component is in normal operation. Conversely, when the wear value is greater than the threshold A1, an early warning signal is generated.

[0029] As a further solution of the present invention, in the performance analysis unit, a simulation model of the slurry pump operation is established and the E / CRC wear model is used for calculation.

[0030] As a further solution of the present invention, it also includes a wear warning unit for detecting warning signals and generating reminder information, which is transmitted to staff.

[0031] Compared with the prior art, the present invention has the following beneficial effects:

[0032] The present invention constructs a contour model for the equipment components of the slurry pump and divides the contour model into grids to form multiple sub-areas. Based on the operating parameters of the slurry pump under different conditions, the main collision areas of the equipment components under random action are obtained, and the performance parameters of the main collision areas are tested. Therefore, when performing performance testing on the slurry pump, there is a clear testing location, thereby reducing the process of testing all equipment components and improving data detection efficiency.

[0033] The present invention uses C++ language to incorporate Loth lift, pressure gradient and virtual mass force, and incorporates a discrete random walk model to simulate the random effect of pulsating velocity on ore particles, thereby improving the accuracy of data processing and making the data output more accurate.

[0034] The present invention is based on the secondary development of EDEM and implants the E / CRC wear model. Different particle sphericity is obtained by stacking spherical particles, and the spherical particle size is used as the input data for equipment component wear, which is conducive to the accurate calculation of equipment component wear values ​​and provides a basis for equipment maintenance. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 This is a schematic diagram of the system framework of the present invention;

[0036] Figure 2 These are the spherical and non-spherical particle models of the present invention. DETAILED DESCRIPTION

[0037] The technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0038] Example 1:

[0039] See also Figure 1 , the present application provides a slurry pump anti-wear performance detection system, including a basic information acquisition unit, a model building unit, a particle calculation unit, a performance analysis unit and a wear warning unit;

[0040] The information collection unit collects equipment information and environmental information based on the established deep-sea mining system. Environmental information refers to information about the application scenario of the equipment. Specifically, environmental information refers to the particle size and size of ore in the deep sea. Equipment information includes the compressive strength of equipment components and the flow rate during equipment transportation. Equipment components refer to components of the slurry pump that come into direct contact with the transported particulate matter. In this embodiment, the equipment components specifically include the inlet extension section, impeller, volute, and outlet extension section of the slurry pump. In this embodiment, the slurry pump is a 100SHL4147 centrifugal slurry pump. The information collection unit then transmits the environmental information and equipment information to the particle calculation unit and the model construction unit respectively.

[0041] It should be further explained that the particle size of deep-sea ore is obtained by calculating the particle size of the ore in the samples collected by the staff during the early stage of deep-sea ore sampling.

[0042] The model building unit builds a contour model based on the device information. The specific contour model building method is as follows:

[0043] S1: Extract the equipment components from the equipment information and draw the outline model of the components according to their shapes;

[0044] S2: Select any equipment component as the target component, extract the compressive strength of the target component, and then mark it on the contour model of the target component based on the compressive strength value;

[0045] S3: Then, the contour model of the target component is divided into a structured grid to form a plurality of sub-regions, and each sub-region is marked in the contour model. The specific structured grid division of the contour model is an existing technology and will not be described in detail here.

[0046] The model building unit then transmits the contour model to the performance analysis unit;

[0047] The particle calculation unit calculates the sphericity of the particles in the mud based on the environmental information. The specific sphericity calculation method is as follows:

[0048] ST1: Extract the particle size and dimension from the environmental information and use them as input data to calculate the particle sphericity through a mathematical model. The mathematical model uses the EDEM particle stacking model to calculate the particle sphericity, such as Figure 2 As shown, in this embodiment, the spherical particles include triangular pyramids, cuboids and spheres, and their corresponding spherical particle sizes are 0.67, 0.81 and 1, respectively. The specific EDEM particle accumulation model calculation is a prior art and will not be described in detail here.

[0049] ST2: Loth lift, pressure gradient, and virtual mass force are incorporated into the C++ language, and a discrete random walk model is incorporated to simulate the random effect of pulsating velocity on ore particles. The specific method for obtaining the random effect is as follows:

[0050] In the equipment components of the slurry pump, the inlet position of each equipment component is used as the initial position, and the flow velocity at the initial position is obtained. Based on the initial position and the flow velocity, the Loth lift, pressure gradient, and virtual mass force are calculated respectively. The specific calculation method is prior art and will not be described in detail here. It should be further explained that the Loth lift, pressure gradient, and virtual mass force are programmed in C++ language and automatically calculated.

[0051] The position and velocity of the ore particles are updated in real time according to the Loth lift, pressure gradient, and virtual mass force, and the above steps are repeated until a preset time or number of iterations is reached. The specific preset time or number of iterations is set by those skilled in the art;

[0052] The particle calculation unit then transmits the particle sphericity and the random effects of the particles to the performance analysis unit;

[0053] The performance analysis unit calculates the wear value of the slurry pump at this time based on the wear model and the sphericity of the particles, and obtains an early warning signal based on the wear value. The specific method for obtaining the wear value and early warning signal is as follows:

[0054] F1: First, calculate the particle volume fraction based on the slurry pump's transport flow rate. The specific particle volume fraction calculation formula is as follows: obtain the size of the ore particles and obtain the mass proportion of the ore particles based on different sizes. Then, multiply the mass proportion by the density of the ore to obtain the volume proportion. At the same time, the volume proportions of ores of different sizes are accumulated to obtain the particle volume fraction. The mass proportion is obtained from the mass accumulation curve, which is the ratio of the mass of the ore particles in different size ranges to the total mass.

[0055] F2: Based on the contour model of the target component, the contour model is first connected in sequence according to the connection position in the slurry pump to obtain the virtual operation model of the slurry pump;

[0056] F3: Then, based on the actual operating parameters of the slurry pump, the operating parameters under different conditions are set for the virtual operating model. The random effect of the particles is used as the influencing parameter to simulate and obtain the main contact sub-areas of the ore particles on the target component. These sub-areas are marked as the main collision areas. The specific operating parameters include flow rate, head, speed, etc.

[0057] F4: Formula-based Obtain the wear value MSi of the main collision area, where i represents different target components, Vk is the particle volume fraction, Ls is the head, Yc represents the rotational speed, t represents the current running time of the slurry pump, Pki represents the compressive strength of the target component i, Qx is the particle sphericity, a1 and a2 are weight coefficients, Ci is the historical wear value of the target component i, that is, the wear value calculated at the end of the last operation of the slurry pump, and then compare the wear value with the threshold A1. When the wear value is less than or equal to the threshold A1, it indicates that the target component is in a normal operating state. Conversely, when the wear value is greater than the threshold A1, an early warning signal is generated, indicating that the corresponding target component has abnormal wear. The performance analysis unit transmits the early warning signal to the wear early warning unit. The threshold A1 is set by those skilled in the art.

[0058] The wear warning unit is used to detect warning signals. When a warning signal is detected, a corresponding reminder message will be generated and transmitted to relevant staff, so that the relevant staff can maintain the equipment in a timely manner, thereby improving the operating efficiency of the equipment.

[0059] Example 2:

[0060] This embodiment is based on the first embodiment, and differs from the first embodiment in that the simulation model for the slurry pump operation in the performance analysis unit in this embodiment is calculated using the E / CRC wear model. Specifically, the E / CRC wear model is implanted based on the secondary development of EDEM to calculate the wear value of the target component under various working conditions of the ore particles. The specific calculation process is the existing technology and will not be described in detail here:

[0061] Example 3:

[0062] This embodiment is based on the first and second embodiments, and is used to integrate the first and second embodiments and implement them.

[0063] Some of the data in the above formula are calculated by removing the dimensions and taking their numerical values. The formula is a formula that is closest to the actual situation obtained by software simulation of a large amount of collected data; the preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained through simulation of a large amount of data.

[0064] The above embodiments are only used to illustrate the technical method of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A slurry pump anti-wear performance detection system, characterized in that: include: A model building unit builds a contour model of the component based on the compressive strength in the equipment information and the shape of the equipment component in the slurry pump; A particle calculation unit calculates the sphericity of the ore using a mathematical model based on the particle size and size of the ore in the environmental information, and calculates the random effect of the particles based on the sphericity of the ore; The performance analysis unit calculates the wear value of the components in the slurry pump based on the contour model, the sphericity of the particles, and the random effect, and obtains an early warning signal based on the wear value and the threshold A1; The random action of particles is calculated as: Extract the particle size and dimensions from the environmental information and use them as input data to calculate the particle sphericity based on the EDEM particle packing model; In the equipment components of the slurry pump, the inlet position of each equipment component is used as the initial position, and the flow velocity at the initial position is obtained. Based on the initial position and flow velocity, the Loth lift, pressure gradient, and virtual mass force are calculated respectively; Update the position and velocity of the ore particles in real time according to the Loth lift, pressure gradient, and virtual mass force, and repeat the above steps until the preset time or number of iterations is reached; The Loth lift, pressure gradient and virtual mass force were programmed into C++ language, and a discrete random walk model was also programmed to simulate the random effect of pulsating velocity on ore particles.

2. The anti-wear performance detection system of a slurry pump according to claim 1, characterized in that: The device information and environmental information are acquired by the information acquisition unit and transmitted to the model building unit and the particle calculation unit respectively.

3. The anti-wear performance detection system of a slurry pump according to claim 1, characterized in that: The equipment components in the equipment information refer to the components of the slurry pump that come into direct contact with particulate matter, including the inlet extension section, impeller, volute and outlet extension section of the slurry pump.

4. The anti-wear performance detection system of a slurry pump according to claim 1, characterized in that: The method of constructing the contour model is: First draw the outline model based on the shape of the device; Select any equipment component as the target component, extract the compressive strength of the target component, and mark the compressive strength on the contour model of the target equipment; The contour model of the target component is divided into structured grids to form multiple sub-regions, and the sub-regions are marked in the contour model to obtain the final contour model.

5. The anti-wear performance detection system of a slurry pump according to claim 1, characterized in that: The calculation method of the wear value of the component is: Based on the slurry pump's transport flow rate, the size of the ore particles is obtained, and the mass fraction of the ore particles is obtained according to the different sizes. The mass fraction is then multiplied by the density of the ore to obtain the volume fraction. At the same time, the volume fractions of ores of different sizes are accumulated to obtain the particle volume fraction. According to the contour model of the target component, the contour model is first connected in sequence according to the connection position in the slurry pump to obtain a virtual operation model of the slurry pump; According to the actual operating parameters of the slurry pump, the operating parameters under different conditions are set for the virtual operation model. The random effect of particles is used as an influencing parameter to simulate and obtain the main collision area of ​​ore particles on the target component. The specific operating parameters include flow rate, head and speed. based on The wear value MSi of the main collision area is obtained, where i represents different target components, Vk is the particle volume fraction, Ls is the head, Yc is the rotation speed, t is the running time of the slurry pump, Pki is the compressive strength of the target component i, Qx is the particle sphericity, a1 and a2 are weight coefficients, and Ci is the historical wear value of the target component i.

6. The anti-wear performance detection system of a slurry pump according to claim 5, characterized in that: The mass proportion is obtained from the mass accumulation curve, which is the proportion of the mass of the ore particles to the total mass within different size ranges.

7. The anti-wear performance detection system of a slurry pump according to claim 1, characterized in that: The method for obtaining early warning signals is: The wear value is compared with the threshold A1. When the wear value is less than or equal to the threshold A1, it indicates that the target component is in normal operation. Conversely, when the wear value is greater than the threshold A1, an early warning signal is generated.

8. The anti-wear performance detection system of a slurry pump according to claim 1, characterized in that: In the performance analysis unit, the simulation model of the slurry pump operation is established and the E / CRC wear model is used for calculation.

9. The anti-wear performance detection system of a slurry pump according to claim 1, characterized in that: It also includes a wear warning unit for detecting warning signals and generating reminder information for transmission to staff.

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