Pumping system quality control system and method

Abstract

The present invention discloses a pumping system quality control system and method, the pumping system quality control system comprises a data acquisition module, a main server and an assembly station server, the data acquisition module is used to collect production data and geometric accuracy data of each component in the pumping system; the main server is connected to the data acquisition module, based on the production data and geometric accuracy data of each component, the geometric accuracy data affecting the assembly coaxiality is identified and defined as key geometric accuracy data; the assembly station server is connected to the main server, including an analysis and processing module and an assembly module; the analysis and processing module calculates the torque required for the key connection part based on the key geometric accuracy data to form an optimal assembly plan; the assembly module assembles the pumping system based on the optimal assembly plan. The present invention is conducive to the coordinated control of the pumping system assembly process and improves the assembly quality and efficiency of the pumping system.

Description

Technical Field

[0001] The invention belongs to the field of quality control, and in particular relates to a pumping system quality control system and method. Background Art

[0002] The concrete pumping system is the core component of the concrete pump truck. During the operation of the pumping system, the hydraulic oil drives the piston rod of the main oil cylinder to drive the two pistons to produce alternating reciprocating motion, and continuously delivers concrete to the delivery pipe on the placing boom. The concrete pumping system is mainly composed of a hopper, a delivery cylinder, a water tank, a main oil cylinder, and a piston. The hopper is connected to the delivery cylinder, the delivery cylinder is connected to the water tank, and the water tank is connected to the main oil cylinder. They are all clearance fits and are locked by screws and bolts. When the key geometric accuracy of each component is out of tolerance, and the assembly parameters do not match the dynamic force of the key connection parts, the coaxiality of the pumping system is out of tolerance, causing serious wear on one side of the piston, and even causing concrete to enter the water tank along the gap, causing the pumping system to shake severely during operation, seriously affecting the performance and life of the concrete pump truck. Summary of the invention

[0003] In view of the above problems, the present invention proposes a pumping system quality control system and method, which is conducive to the coordinated control of the pumping system assembly process and improves the assembly quality and efficiency of the pumping system.

[0004] In order to achieve the above technical objectives and the above technical effects, the present invention is implemented through the following technical solutions:

[0005] In a first aspect, the present invention provides a pumping system quality control system, comprising:

[0006] Data acquisition module, used to collect production data and geometric accuracy data of each component in the pumping system;

[0007] The main server is connected to the data acquisition module, and identifies the geometric accuracy data that affects the assembly coaxiality based on the production data and geometric accuracy data of each component, and defines it as key geometric accuracy data;

[0008] The assembly station server is connected to the main server and includes an analysis and processing module and an assembly module; the analysis and processing module calculates the torque required for the key connection parts based on the key geometric accuracy data to form an optimal assembly plan; the assembly module assembles the pumping system based on the optimal assembly plan.

[0009] Optionally, the data acquisition module includes a hopper geometry accuracy detection module, a delivery cylinder geometry accuracy detection module, a water tank geometry accuracy detection module, a main oil cylinder geometry accuracy detection module and / or a piston geometry accuracy detection module.

[0010] Optionally, the assembly station server further includes a typical manufacturing database, a prediction optimization module and an assembly coaxiality detection module;

[0011] The typical manufacturing database is used to store key geometric accuracy data;

[0012] The prediction optimization module is connected to the typical manufacturing database, and based on the key geometric accuracy data, uses the Markov prediction model to predict the coaxiality, which is recorded as the predicted coaxiality;

[0013] The assembly coaxiality detection module is connected to the prediction optimization module, compares the obtained coaxiality detection result with the predicted coaxiality, and feeds the comparison result back to the prediction optimization module to optimize the Markov prediction model.

[0014] Optionally, the expression of the Markov prediction model is:

[0015] π(n)=π(0)P n

[0016] Where π(n) is the probability vector of the working condition to which the assembly coaxiality belongs at time n, π(0) is the probability vector of the working condition to which the known assembly coaxiality belongs, and P n It is the probability matrix of the working condition transfer of the assembly coaxiality at time n.

[0017] Optionally, the analysis and processing module further includes a typical failure database, which is used to connect to the production system and store market maintenance information of the pumping system.

[0018] Optionally, the analysis and processing module performs the following steps to obtain the optimal assembly solution:

[0019] Based on the key geometric accuracy data and the mathematical model of the assembly dimension chain of the pumping system, the influence value of the key geometric accuracy data on the assembly coaxiality is calculated;

[0020] Based on the key geometric accuracy data and the dynamic force analysis model of the pumping system, the force magnitude of the key connection parts is calculated, and according to the preload-torque model, the torque magnitude required for the key connection parts is calculated;

[0021] According to the relationship between the influence value and the maximum threshold value of the coaxiality, it is determined whether to adjust the assembly parameters according to the calculated torque to form an optimal assembly plan.

[0022] Optionally, the calculation formula of the impact value is:

[0023] y=y1+y2+y3+y4+y5

[0024]

[0025]

[0026]

[0027]

[0028]

[0029]

[0030] y5=x5

[0031] Among them, y is the influence value of key geometric accuracy data on assembly coaxiality, y1, y2, y3, y4, y5 are the influence values ​​of hopper verticality, conveying cylinder verticality, water tank coaxiality, main oil cylinder coaxiality and piston assembly coaxiality on assembly coaxiality, x1, x2, x3, x4, x5 are the verticality of hopper, conveying cylinder verticality, water tank coaxiality, main oil cylinder coaxiality and piston assembly coaxiality, l1 is the outer circle size of the water tank side of the conveying cylinder, l2 is the effective stroke of the pumping system piston in the conveying cylinder, l3 is the width of the water tank, l4 and l5 are the thickness of the connecting hole between the water tank and the two conveying cylinders, and l6 is the length of the inner shaft of the main oil cylinder inserted into the water tank hole.

[0032] Optionally, the calculation formula for the torque required at the connection between the master cylinder and the water tank is:

[0033]

[0034] F5=(F d -F z ) / 6=[P1*S1-μ*(G l3 +n*V*ρ)-G l3 ] / 6

[0035] Among them, T1 is the tightening torque of the connection between the main oil cylinder and the water tank, F5 is the bolt force of the connection between the main oil cylinder and the water tank, and F d is the piston motion power, F z is the piston movement resistance, P is the bolt pitch, d is the bolt nominal diameter, μ1 is the thread friction coefficient, μ2 is the end face friction coefficient, d2 is the bolt median diameter, and D w is the diameter of the bolt flange surface, P1 is the working pressure of the main oil cylinder, S1 is the area of ​​the main oil cylinder, μ is the friction coefficient of concrete in the conveying pipe, ρ is the density of concrete, n is the number of bends in the conveying pipe, V is the volume of the conveying pipe, G l3 It is the sum of the concrete gravity at the conveying pipe and the gravity of the elbow.

[0036] Optionally, the calculation formula for the torque required at the connection between the hopper and the water tank is:

[0037]

[0038] F6=[G1+G l1 +G l3 +G c +G2+(F d -F z )*sinα-F1] / sinα

[0039] Among them, T2 is the tightening torque at the connection between the hopper and the water tank, F6 is the bolt force at the connection between the hopper and the water tank, μ1 is the thread friction coefficient, μ2 is the end surface friction coefficient, and D w is the bolt flange diameter, P is the bolt pitch, d is the bolt nominal diameter, d2 is the bolt mid-diameter, G1 is the hopper gravity, G2 is the conveying cylinder gravity, G l1 is the concrete gravity in the hopper, G l3 G is the sum of the concrete gravity at the conveying pipe and the bend gravity. c is the impact force during feeding, F1 is the support force of the hinge point, F d is the piston motion power, F z is the resistance to piston movement, and α is the installation inclination angle of the pumping system.

[0040] In a second aspect, the present invention provides a method for controlling the quality of a concrete pumping system, comprising:

[0041] Use the data acquisition module to collect production data and geometric accuracy data of each component in the pumping system;

[0042] Using a main server connected to the data acquisition module, based on the production data and geometric accuracy data of each component, the geometric accuracy data affecting the assembly coaxiality is identified and defined as key geometric accuracy data;

[0043] By using the assembly station server connected to the main server, the torque required for the key connection parts is calculated based on the key geometric accuracy data to form an optimal assembly plan, and the pumping system is assembled based on the optimal assembly plan.

[0044] Compared with the prior art, the present invention has the following beneficial effects:

[0045] The data acquisition module in the present invention has the ability to simultaneously detect the production data and geometric accuracy data of each component, and upload all data to the main server, breaking the situation in which the key parameters of each component in the traditional pumping system assembly are isolated from each other, which is beneficial to the coordinated control of the pumping system assembly process and improves the assembly quality and efficiency of the pumping system.

[0046] The assembly station server in the present invention provides the optimal assembly plan for the assembly process of each pumping system based on a multi-information fusion analysis method, and feeds back to the assembly station in a visual state, which can better guide the assembly personnel's work and reduce the unqualified rate of the pumping system.

[0047] The typical failure database constructed according to the market maintenance information of the pumping system in the present invention provides data support for the after-sales service of the pumping system and realizes the quality traceability of the whole process of the pumping system. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to make the content of the present invention more clearly understood, the present invention is further described in detail below according to specific embodiments and in conjunction with the accompanying drawings, wherein:

[0049] Figure 1 It is a structural schematic diagram of a quality control system of a concrete pumping system according to an embodiment of the present invention;

[0050] Figure 2 A schematic diagram of a quality control process of a concrete pumping system according to an embodiment of the present invention;

[0051] Figure 3 This is a force analysis diagram of a concrete pumping system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the scope of protection of the present invention.

[0053] The application principle of the present invention is described in detail below in conjunction with the accompanying drawings.

[0054] Example 1

[0055] The embodiment of the present invention provides a pumping system quality control system, the pumping system includes a hopper, a delivery cylinder, a water tank, a main oil cylinder and a piston, the two ends of the delivery cylinder are connected to the hopper and the water tank respectively, the hopper and the water tank are fixed by a screw, the main oil cylinder and the water tank are connected by bolts, and the piston is installed on the main oil cylinder. For details, please refer to Figure 3 The pumping system quality control system specifically includes: a data acquisition module, a main server and an assembly station server, see Figure 1 .

[0056] The data acquisition module is used to collect production data and geometric accuracy data of various components in the pumping system; in the specific implementation process, the data acquisition module includes a hopper geometric accuracy detection module, a delivery cylinder geometric accuracy detection module, a water tank geometric accuracy detection module, a main oil cylinder geometric accuracy detection module and a piston geometric accuracy detection module, each detection module detects the geometric accuracy of the corresponding components (hopper, delivery cylinder, water tank, main oil cylinder and piston), and collects the production data of the corresponding components, the production data includes the name of the raw material supplier, the raw material specification model, the key processing parameters, the component model, etc., and the production data and the detected geometric accuracy data are uploaded to the main server; in the embodiment of the present invention, the role of the production data is to facilitate information flow tracking;

[0057] The main server is connected to the data acquisition module, and based on the production data and geometric accuracy data of each component, the principal component analysis method is used to identify the geometric accuracy data that affects the assembly coaxiality (that is, to identify which information of each component has a greater impact on the assembly coaxiality), and define it as key geometric accuracy data; in the specific implementation process, the main server will classify and store the key geometric accuracy data to facilitate subsequent data capture and viewing; the classification process is generally divided into two types, the first is to classify and store according to different components, and the second is to classify and store according to all data and key data in the process;

[0058] The assembly station server is connected to the main server, captures the required information from the main server, and uploads the assembly station data information to the main server. The assembly station data information mainly refers to the assembly parameter information of the key connection parts in the assembly process, such as the tightening torque, tightening sequence and assembly coaxiality data. The data comes from the process parameters of the actual assembly site and the detected assembly coaxiality. The main server can analyze the assembly coaxiality and the geometric accuracy of each key component, and reversely guide the optimization of the processing technology of the key components. The assembly station server includes an analysis and processing module, an assembly module, a typical manufacturing database, a typical failure database, a prediction and optimization module, an assembly coaxiality detection module and a visualization module.

[0059] The analysis and processing module calculates the torque required by the key connection parts in the pumping system based on the key geometric accuracy data to form an optimal assembly solution;

[0060] The assembly module assembles the pumping system based on the optimal assembly solution.

[0061] The typical manufacturing database is used to store key geometric accuracy data, assembly parameters and equipment parameters, etc., and gradually improve the typical working condition information of the pumping system assembly by collecting information in real time;

[0062] The typical failure database is used to interact with the production system through an open interface to store the market maintenance information of the pumping system; specifically, the process of building the typical failure database is as follows: the production system feeds back the market maintenance information of the pumping system to the assembly station server, and the assembly station server builds a typical failure database based on the market maintenance information of the pumping system to support the after-sales service of the pumping system; in actual use, since the typical failure database includes production data, geometric accuracy detection data, assembly parameters and market maintenance information of key components, when a pumping system fails, the information in the database can be queried to retrieve the corresponding solution to support the after-sales service of the pumping system.

[0063] The prediction optimization module is connected to the typical manufacturing database, based on the key geometric accuracy data, according to the corresponding relationship between the geometric accuracy data and the assembly coaxiality in the typical working condition database, the state transition probability matrix of this assembly is obtained, and the coaxiality is predicted by using the Markov prediction model, which is recorded as the predicted coaxiality to guide the assembly process of the pumping system; in the specific implementation process, the predicted coaxiality includes several working conditions of 2-3mm, 3-4mm, 4-5mm, 5-6mm, 6-7mm, 7-8mm, 8-9mm and greater than 9mm;

[0064] The assembly coaxiality detection module is connected to the prediction optimization module. After assembly is completed, the obtained coaxiality detection result is compared with the predicted coaxiality, and the comparison result is fed back to the prediction optimization module. At the same time, the obtained coaxiality detection result is added to the typical working condition database. The prediction optimization module updates the state transition probability matrix according to the supplemented typical working condition database and optimizes the Markov prediction model. In a specific embodiment of the present invention, the expression of the Markov prediction model is:

[0065] π(n)=π(0)P n

[0066] Where π(n) is the probability vector of the working condition to which the assembly coaxiality belongs at time n, π(0) is the probability vector of the working condition to which the known assembly coaxiality belongs, and P n is the working condition transition probability matrix of the assembly coaxiality at time n; the Markov prediction model in the embodiment of the present invention is established and obtained by the following steps:

[0067] (1) Select the time period to be studied based on the key geometric accuracy data and assembly coaxiality data collected at the production site;

[0068] (2) The assembly coaxiality data is split into corresponding working conditions, and the assembly coaxiality in the same working condition is regarded as one state;

[0069] (3) The state transition of assembly coaxiality is statistically analyzed during the study period, and the probability matrix P of the assembly coaxiality state transition in each period is obtained. n .

[0070] The visualization module is used to display the relevant data in the data acquisition module, the main server and the assembly station server through the display, including the collected information of each component, prediction information, data analysis and processing results and the optimal assembly plan of the pumping system.

[0071] In a specific implementation of the embodiment of the present invention, the analysis and processing module performs the following steps to obtain the optimal assembly solution:

[0072] Based on the key geometric accuracy data and the mathematical model of the assembly dimension chain of the pumping system, the influence value of the key geometric accuracy data on the assembly coaxiality is calculated;

[0073] Based on the key geometric accuracy data and the dynamic force analysis model of the pumping system, the force magnitude of the key connection parts is calculated, and according to the preload-torque model, the torque magnitude required for the key connection parts is calculated;

[0074] According to the relationship between the impact value and the maximum coaxiality threshold, determine whether to adjust the assembly parameters according to the calculated torque size to form the optimal assembly plan. In the specific implementation process, when the calculated impact value is greater than 9mm, it is required to adjust the assembly parameters according to the calculated torque size. When the calculated impact value is less than 9mm, it can be assembled according to the existing assembly parameters on site.

[0075] The mathematical model of the assembly dimension chain of the pumping system is as follows:

[0076] in,

[0077] Hopper verticality (x1):

[0078] Conveying cylinder verticality (x2):

[0079] Sink coaxiality (x3):

[0080] When panning:

[0081] When the tilt angle is opposite:

[0082] When the tilt angle is the same:

[0083] Main cylinder coaxiality (x4):

[0084] Piston assembly coaxiality (x5): y5 = x5

[0085] Among them, y1, y2, y3, y4, and y5 are the influence values ​​of the hopper verticality, conveying cylinder verticality, water tank coaxiality, main oil cylinder coaxiality, and piston assembly coaxiality on assembly coaxiality, l1 is the outer circle size of the conveying cylinder water tank side, l2 is the effective stroke of the pumping system piston in the conveying cylinder, l3 is the water tank width, l4 and l5 are the thickness of the connecting hole between the water tank and the two conveying cylinders, and l6 is the length of the main oil cylinder inserted into the water tank hole.

[0086] The calculation formula of the impact value is:

[0087] y=y1+y2+y3+y4+y5.

[0088] like Figure 3 As shown, the force analysis model of the pumping system is as follows:

[0089] The force model of the bolts at the assembly of the main oil cylinder and the water tank is:

[0090] F5=(F d -F z ) / 6=[P1*S1-μ*(G l3 +n*V*ρ)-G l3 ] / 6

[0091] The bolt force model at the assembly of the hopper and the water tank is:

[0092] F6=[G1+G l1 +G l3 +G c +G2+(F d -F z )*sinα-F1] / sinα

[0093] Among them, F d is the piston motion power, F z is the piston movement resistance, P1 is the main cylinder working pressure, S1 is the main cylinder area, G l3 is the sum of the concrete gravity and the elbow gravity at the conveying pipe, μ is the friction coefficient of concrete in the conveying pipe, ρ is the density of concrete, n is the number of elbows in the conveying pipe, V is the volume of the conveying pipe, G l3 is the sum of the concrete gravity at the conveying pipe and the elbow gravity, G1 is the hopper gravity, G2 is the conveying cylinder gravity, G l1 is the concrete gravity in the hopper, G c is the impact force during material replenishment, F1 is the support force of the hinge point, and α is the installation inclination angle of the pumping system.

[0094] The calculation formula for the torque required at the key connection point is:

[0095]

[0096]

[0097] Among them, T1 is the tightening torque of the connection between the main oil cylinder and the water tank, F5 is the bolt force at the connection between the main oil cylinder and the water tank, T2 is the tightening torque of the connection between the hopper and the water tank, P is the bolt pitch, d is the nominal diameter of the bolt, μ1 is the thread friction coefficient, μ2 is the end face friction coefficient, d2 is the bolt diameter, D w is the diameter of the bolt flange surface, and F6 is the force on the bolts at the connection between the hopper and the water tank.

[0098] Example 2

[0099] An embodiment of the present invention provides a method for controlling the quality of a concrete pumping system, comprising the following steps:

[0100] Step (1) using a data acquisition module to collect production data and geometric accuracy data of each component in the pumping system;

[0101] Step (2) using a main server connected to the data acquisition module, based on the production data and geometric accuracy data of each component, identifying the geometric accuracy data that affects the assembly coaxiality and defining it as key geometric accuracy data;

[0102] Step (3) uses an assembly station server connected to the main server to calculate the torque required for key connection parts based on the key geometric accuracy data, form an optimal assembly plan, and assemble the pumping system based on the optimal assembly plan.

[0103] In a specific implementation of an embodiment of the present invention, the data acquisition module includes a hopper geometric accuracy detection module, a conveying cylinder geometric accuracy detection module, a water tank geometric accuracy detection module, a main oil cylinder geometric accuracy detection module and / or a piston geometric accuracy detection module, which detects the geometric accuracy of corresponding components and collects production data of corresponding components, wherein the production data includes the name of the raw material supplier, raw material specification model, key processing parameters, component model, etc., and the production data and the detected geometric accuracy data are uploaded to the main server; in an embodiment of the present invention, the role of the production data is to facilitate information flow tracking.

[0104] In a specific implementation of the embodiment of the present invention, the assembly station server further includes a typical manufacturing database, a typical failure database, a prediction optimization module, an assembly coaxiality detection module and a visualization module;

[0105] The typical manufacturing database is used to store key geometric accuracy data, assembly parameters and equipment parameters, etc., and gradually improve the typical working condition information of the pumping system assembly by collecting information in real time;

[0106] The typical failure database is used to connect with the production system to store the market maintenance information of the pumping system; specifically, the construction process of the typical failure database is as follows: the production system feeds back the market maintenance information of the pumping system to the assembly station server, and the assembly station server builds a typical failure database based on the market maintenance information of the pumping system to support the after-sales service of the pumping system; in actual use, since the typical failure database includes the production data, geometric accuracy detection data, assembly parameters and market maintenance information of key components, when a pumping system fails, the corresponding solution can be retrieved by querying the information in the database to support the after-sales service of the pumping system.

[0107] The prediction optimization module is connected to the typical manufacturing database, and based on the key geometric accuracy data, the Markov prediction model is used to predict the coaxiality, which is recorded as the predicted coaxiality, to guide the assembly process of the pumping system; in the specific implementation process, the predicted coaxiality includes several working conditions of 2-3mm, 3-4mm, 4-5mm, 5-6mm, 6-7mm, 7-8mm, 8-9mm and greater than 9mm;

[0108] The visualization module is used to display the relevant data in the data acquisition module, the main server and the assembly station server through the display, including the collected information of each component, the prediction information, the data analysis and processing results and the optimal assembly plan of the pumping system;

[0109] The assembly coaxiality detection module is connected to the prediction optimization module, compares the obtained coaxiality detection result with the predicted coaxiality, and feeds the comparison result back to the prediction optimization module to optimize the Markov prediction model.

[0110] Among them, the expression of the Markov prediction model is:

[0111] π(n)=π(0)P n

[0112] Where π(n) is the probability vector of the working condition to which the assembly coaxiality belongs at time n, π(0) is the probability vector of the working condition to which the known assembly coaxiality belongs, and P n It is the probability matrix of the working condition transfer of the assembly coaxiality at time n.

[0113] That is, the method in the embodiment of the present invention further comprises the following steps after the pumping system assembly step is performed based on the optimal assembly solution:

[0114] After step (4) is assembled, the pumping system assembly coaxiality detection system is used to perform pumping system assembly coaxiality detection, and the coaxiality detection results are compared and analyzed with the quality prediction results to optimize the assembly quality prediction model.

[0115] After step (5) is completed, all data are stored in the typical working condition database, and the typical working condition information of the pumping system assembly is gradually improved.

[0116] In a specific implementation of the embodiment of the present invention, the analysis and processing module performs the following steps to obtain the optimal assembly solution:

[0117] Based on the key geometric accuracy data and the mathematical model of the assembly dimension chain of the pumping system, the influence value of the key geometric accuracy data on the assembly coaxiality is calculated;

[0118] Based on the key geometric accuracy data and the dynamic force analysis model of the pumping system, the force magnitude of the key connection parts is calculated, and according to the preload-torque model, the torque magnitude required for the key connection parts is calculated;

[0119] According to the relationship between the influence value and the maximum threshold value of the coaxiality, it is determined whether to adjust the assembly parameters according to the calculated torque to form an optimal assembly plan.

[0120] The mathematical model of the assembly dimension chain of the pumping system is as follows:

[0121] in,

[0122] Hopper verticality (x1):

[0123] Conveying cylinder verticality (x2):

[0124] Sink coaxiality (x3):

[0125] When panning:

[0126] When the tilt angle is opposite:

[0127] When the tilt angle is the same:

[0128] Main cylinder coaxiality (x4):

[0129] Piston assembly coaxiality (x5): y5 = x5

[0130] Among them, y1, y2, y3, y4, and y5 are the influence values ​​of the hopper verticality, conveying cylinder verticality, water tank coaxiality, main oil cylinder coaxiality, and piston assembly coaxiality on assembly coaxiality, l1 is the outer circle size of the conveying cylinder water tank side, l2 is the effective stroke of the pumping system piston in the conveying cylinder, l3 is the water tank width, l4 and l5 are the thickness of the connecting hole between the water tank and the two conveying cylinders, and l6 is the length of the main oil cylinder inserted into the water tank hole.

[0131] The calculation formula of the impact value is:

[0132] y=y1+y2+y3+y4+y5.

[0133] like Figure 3 As shown, the force analysis model of the pumping system is as follows:

[0134] The force model of the bolts at the assembly of the main oil cylinder and the water tank is:

[0135] F5=(F d -F z ) / 6=[P1*S1-μ*(G l3 +n*V*ρ)-G l3 ] / 6

[0136] The bolt force model at the assembly of the hopper and the water tank is:

[0137] F6=[G1+G l1 +G l3 +G c +G2+(F d -F z )*sinα-F1] / sinα

[0138] Among them, F d is the piston motion power, F z is the piston movement resistance, P1 is the main cylinder working pressure, S1 is the main cylinder area, G l3 is the sum of the concrete gravity and the elbow gravity at the conveying pipe, μ is the friction coefficient of concrete in the conveying pipe, ρ is the density of concrete, n is the number of elbows in the conveying pipe, V is the volume of the conveying pipe, G l3 is the sum of the concrete gravity at the conveying pipe and the elbow gravity, G1 is the hopper gravity, G2 is the conveying cylinder gravity, G l1 is the concrete gravity in the hopper, G c is the impact force during material replenishment, F1 is the support force of the hinge point, and α is the installation inclination angle of the pumping system.

[0139] The calculation formula for the torque required at the key connection point is:

[0140]

[0141]

[0142] Among them, T1 is the tightening torque of the connection between the main oil cylinder and the water tank, F5 is the bolt force at the connection between the main oil cylinder and the water tank, T2 is the tightening torque of the connection between the hopper and the water tank, P is the bolt pitch, d is the nominal diameter of the bolt, μ1 is the thread friction coefficient, μ2 is the end face friction coefficient, d2 is the bolt diameter, D wis the diameter of the bolt flange surface, and F6 is the force on the bolts at the connection between the hopper and the water tank.

[0143] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A pumping system quality control system, characterized in that: include: The pumping system includes a hopper, a delivery cylinder, a water tank, a main oil cylinder and a piston; Data acquisition module, used to collect production data and geometric accuracy data of each component in the pumping system; The main server is connected to the data acquisition module, and identifies the geometric accuracy data that affects the assembly coaxiality based on the production data and geometric accuracy data of each component, and defines it as key geometric accuracy data; The assembly station server is connected to the main server and includes an analysis and processing module and an assembly module; the analysis and processing module calculates the influence value of the key geometric accuracy data on the assembly coaxiality based on the key geometric accuracy data, and calculates the torque required for the key connection parts in the pumping system, and determines whether to adjust the assembly parameters according to the calculated torque according to the relationship between the influence value and the maximum coaxiality threshold value to form an optimal assembly plan; The assembly module assembles the pumping system based on the optimal assembly solution; The calculation formula of the impact value is: y=y1+y2+y3+y4+y5 y5=x5 Among them, y is the influence value of key geometric accuracy data on assembly coaxiality, y1, y2, y3, y4, y5 are the influence values ​​of hopper verticality, conveying cylinder verticality, water tank coaxiality, main oil cylinder coaxiality and piston assembly coaxiality on assembly coaxiality, x1, x2, x3, x4, x5 are the verticality of hopper, conveying cylinder verticality, water tank coaxiality, main oil cylinder coaxiality and piston assembly coaxiality, l1 is the outer circle size of the water tank side of the conveying cylinder, l2 is the effective stroke of the piston in the conveying cylinder, l3 is the width of the water tank, l4 and l5 are the thickness of the connecting hole between the water tank and the two conveying cylinders, and l6 is the length of the inner shaft of the main oil cylinder inserted into the water tank hole.

2. A pumping system quality control system according to claim 1, characterized in that: The two ends of the delivery cylinder are respectively connected to the hopper and the water tank, the hopper and the water tank are fixed by a screw, the main oil cylinder is connected to the water tank by bolts, and the piston is installed on the main oil cylinder; The data acquisition module includes a hopper geometric accuracy detection module, a delivery cylinder geometric accuracy detection module, a water tank geometric accuracy detection module, a main oil cylinder geometric accuracy detection module and a piston geometric accuracy detection module.

3. A pumping system quality control system according to claim 1, characterized in that: The assembly station server also includes a typical manufacturing database, a prediction optimization module and an assembly coaxiality detection module; The typical manufacturing database is used to store the key geometric accuracy data; The prediction optimization module is connected to the typical manufacturing database, and based on the key geometric accuracy data, uses the Markov prediction model to predict the coaxiality, which is recorded as the predicted coaxiality; The assembly coaxiality detection module is connected to the prediction optimization module, compares the actual coaxiality detection result obtained with the predicted coaxiality, and feeds the comparison result back to the prediction optimization module to optimize the Markov prediction model.

4. A pumping system quality control system according to claim 3, characterized in that: The expression of the Markov prediction model is: π(n)=π(0)P n Where π(n) is the probability vector of the working condition to which the assembly coaxiality belongs at time n, π(0) is the probability vector of the working condition to which the known assembly coaxiality belongs, and P n It is the probability matrix of the working condition transfer of the assembly coaxiality at time n.

5. A pumping system quality control system according to claim 3, characterized in that: The analysis and processing module also includes a typical failure database, which is used to connect to the production system and store market maintenance information of the pumping system.

6. A pumping system quality control system according to claim 1, characterized in that: The calculation formula for the torque required at the connection between the main oil cylinder and the water tank is: F5=(F d -F z ) / 6=[P1*S1-μ*(G l3 +n*V*ρ)-G l3 ] / 6 Among them, T1 is the tightening torque of the connection between the main oil cylinder and the water tank, F5 is the bolt force of the connection between the main oil cylinder and the water tank, and F d is the piston motion power, F z is the piston movement resistance, P is the bolt pitch, d is the bolt nominal diameter, μ1 is the thread friction coefficient, μ2 is the end face friction coefficient, d2 is the bolt median diameter, and D w is the diameter of the bolt flange surface, P1 is the working pressure of the main oil cylinder, S1 is the area of ​​the main oil cylinder, μ is the friction coefficient of concrete in the conveying pipe, ρ is the density of concrete, n is the number of bends in the conveying pipe, V is the volume of the conveying pipe, G l3 It is the sum of the concrete gravity at the conveying pipe and the gravity of the elbow.

7. A pumping system quality control system according to claim 1, characterized in that: The calculation formula for the torque required at the connection between the hopper and the water tank is: F6=[G1+G l1 +G l3 +G c +G2+(F d -F z )*sinα-F1] / sinα Among them, T2 is the tightening torque at the connection between the hopper and the water tank, F6 is the bolt force at the connection between the hopper and the water tank, μ1 is the thread friction coefficient, μ2 is the end surface friction coefficient, and D w is the bolt flange diameter, P is the bolt pitch, d is the bolt nominal diameter, d2 is the bolt mid-diameter, G1 is the hopper gravity, G2 is the conveying cylinder gravity, G l1 is the concrete gravity in the hopper, G l3 G is the sum of the concrete gravity at the conveying pipe and the bend gravity. c is the impact force during feeding, F1 is the support force of the hinge point, and F d is the piston motion power, F z is the resistance to piston movement, and α is the installation inclination angle of the pumping system.

8. A method for quality control of a concrete pumping system, characterized in that: include: The pumping system includes a hopper, a delivery cylinder, a water tank, a main oil cylinder and a piston; Use the data acquisition module to collect production data and geometric accuracy data of each component in the pumping system; Using a main server connected to the data acquisition module, based on the production data and geometric accuracy data of each component, the geometric accuracy data affecting the assembly coaxiality is identified and defined as key geometric accuracy data; Using an assembly station server connected to the main server, based on the key geometric accuracy data, calculate the influence value of the key geometric accuracy data on the assembly coaxiality, and calculate the torque required for the key connection parts, and determine whether to adjust the assembly parameters according to the calculated torque according to the relationship between the influence value and the maximum threshold of the coaxiality, so as to form an optimal assembly plan, and assemble the pumping system based on the optimal assembly plan; The calculation formula of the impact value is: y=y1+y2+y3+y4+y5 y5=x5 Among them, y is the influence value of key geometric accuracy data on assembly coaxiality, y1, y2, y3, y4, y5 are the influence values ​​of hopper verticality, conveying cylinder verticality, water tank coaxiality, main oil cylinder coaxiality and piston assembly coaxiality on assembly coaxiality, x1, x2, x3, x4, x5 are the verticality of hopper, conveying cylinder verticality, water tank coaxiality, main oil cylinder coaxiality and piston assembly coaxiality, l1 is the outer circle size of the water tank side of the conveying cylinder, l2 is the effective stroke of the piston in the conveying cylinder, l3 is the width of the water tank, l4 and l5 are the thickness of the connecting hole between the water tank and the two conveying cylinders, and l6 is the length of the inner shaft of the main oil cylinder inserted into the water tank hole.

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