Shield / TBM cutter ring surface laser shock peening method

Abstract

The invention discloses a shield / TBM cutter ring surface laser shock peening method, and belongs to the technical field of shield / TBM cutter ring machining, and the shield / TBM cutter ring surface laser shock peening method comprises the following steps: S1, obtaining historical data; s2, data preprocessing; s3, constructing a shield / TBM cutter ring surface laser shock peening knowledge graph; s4, shield / TBM cutter ring detection and finish machining; s5, positioning is carried out; s6, predicting laser shock peening parameters of the surface of the shield / TBM cutter ring; s7, the shield / TBM cutter ring is machined based on the predicted surface laser shock peening parameters; according to the knowledge graph, the surface laser shock peening parameters of the shield / TBM cutter ring can be optimal, namely, the surface laser shock peening effect of the shield / TBM cutter ring can be optimal.

Description

Technical Field

[0001] This invention belongs to the field of shield / TBM cutter ring processing technology, specifically relating to a laser shock strengthening method for the surface of shield / TBM cutter rings. Background Technology

[0002] The shield tunneling machine (TBM) cutterhead ring is a ring-shaped component with a certain width and thickness that is installed on the disc cutterhead of the TBM. Its inner diameter is matched with the cutterhead body. Its main function is to cut the rock at the tunnel face and ensure that the TBM can break through the rock smoothly during the tunneling process.

[0003] Strength is one of the important properties of the cutterhead ring of a tunnel boring machine (TBM). Currently, the method to improve the strength of the cutterhead ring is surface laser shock peening, which uses a high-energy laser beam to rapidly heat and melt alloy powder or ceramic powder to form a coating with super wear resistance and impact resistance on the surface of the cutterhead ring, thereby significantly improving the strength of the cutterhead ring.

[0004] Chinese Patent Application No. 201811377150.9 discloses a method for strengthening the surface of a tunnel boring machine cutter ring, comprising: vacuum drying alloy powder; clamping the cutter ring to be processed and strengthened on a positioner with a chuck; grinding the surface of the cutter ring's cutting edge; simultaneously cladding the cutter ring surface with gravity powder feeding and laser; and heat-insulating and cooling the processed cutter ring.

[0005] The above-mentioned technology has the following problems: the surface strengthening parameters of the above-mentioned shield machine cutterhead surface strengthening method are selected arbitrarily without systematic theoretical support, making it difficult to guarantee that the surface strengthening effect of the cutterhead will reach the optimal level.

[0006] In view of this, a laser shock peening method for the surface of the cutterhead ring of a shield tunneling machine (TBM) is designed to solve the above problems. Summary of the Invention

[0007] To address the problems mentioned in the background section, this invention provides a method for laser shock peening of the cutterhead surface of a tunnel boring machine (TBM), which optimizes the laser shock peening parameters and achieves the best laser shock peening effect.

[0008] To achieve the above objectives, the present invention provides the following technical solution: a method for laser shock peening of the surface of a shield / TBM cutterhead ring, comprising the following steps:

[0009] S1: Obtain historical laser shock blasting data on the surface of shield / TBM cutter rings, including surface laser shock blasting data with one or more of the following as independent variables: shield / TBM cutter ring material, shield / TBM cutter ring width, shield / TBM cutter ring thickness, alloy powder type, and laser parameters;

[0010] S2: Preprocess the acquired historical laser shock blasting data on the surface of the shield / TBM cutter ring;

[0011] S3: Construct a knowledge graph of laser shock blasting on the surface of shield / TBM cutter rings based on preprocessed historical shield / TBM cutter ring surface laser shock blasting data;

[0012] S4: Inspection and precision machining of shield / TBM cutter rings whose surfaces require laser shock peening;

[0013] S5: Positioning the shield / TBM cutter ring whose surface has been finely machined and is to be laser-strengthened;

[0014] S6: Input the parameters of the finished shield / TBM cutter ring, including the material, width and thickness of the shield / TBM cutter ring. Based on the constructed knowledge graph of laser shock strengthening of the shield / TBM cutter ring surface, predict the surface laser shock strengthening parameters of the shield / TBM cutter ring to be laser-strengthened, including the alloy powder type and laser parameters.

[0015] S7: Machining of shield / TBM cutter rings based on predicted surface laser shock peening parameters.

[0016] Furthermore, in step S2, the preprocessing includes deleting missing value data, deleting outlier data, deleting duplicate value data, data standardization, and data normalization.

[0017] Furthermore, the specific steps in step S3 include:

[0018] S301: Using one of the following as independent variables—shield / TBM cutter ring material, shield / TBM cutter ring width, shield / TBM cutter ring thickness, alloy powder type, and laser parameters—and the surface laser shock strengthening effect parameter as the dependent variable, extract the amount of data from the preset threshold in the surface laser strengthening shock data from high to low.

[0019] S302: Calculate the relative merits and demerits of each independent variable based on the average value of the data extracted under each independent variable, and then sort them.

[0020] S303: Using the material, width, thickness, alloy powder type, and laser parameters of the shield / TBM cutter ring as entities, establish the relationship between the material, width, thickness, alloy powder type, and laser parameters of the shield / TBM cutter ring, which is the knowledge graph of laser shock strengthening on the surface of the shield / TBM cutter ring.

[0021] Furthermore, the specific steps of step S4 include:

[0022] S401: The shield / TBM cutter rings to be laser-strengthened on the surface are sequentially passed through a 3D scanner to obtain 3D scanning data;

[0023] S402: Constructing a 3D model of the shield / TBM cutterhead based on 3D scanning data;

[0024] S403: Compare with the preset 3D model of the shield / TBM cutterhead to obtain the stagger data of the shield / TBM cutterhead;

[0025] S404: Precision machining of shield / TBM cutter rings based on the uneven data of the cutter rings;

[0026] S405: After finishing, repeat the above process of acquiring 3D scanning data, constructing 3D model, comparing 3D model and finishing the cutter ring until the 3D model of the cutter ring is the same as the preset 3D model data of the cutter ring, and then you will get the finished cutter ring.

[0027] Furthermore, in step S6, the specific steps for predicting the surface laser shock strengthening parameters of the shield / TBM cutter ring to be laser-strengthened using the knowledge graph of laser shock strengthening on the surface of the shield / TBM cutter ring include:

[0028] Based on the input of the shield / TBM cutter ring material, width, and thickness, and the entities and relationships between them in the knowledge graph of laser shock strengthening of the shield / TBM cutter ring surface, the surface laser shock strengthening parameters of the shield / TBM cutter ring to be laser-strengthened are derived step by step.

[0029] Furthermore, in step S3, the constructed knowledge graph of laser shock peening enhancement on the surface of the shield / TBM cutterhead also includes:

[0030] Solid-state LSTM model relating alloy powder type and laser parameters;

[0031] Historical alloy powder types and laser parameters are also input into the LSTM model for training;

[0032] During prediction, the surface laser shock strengthening parameters of the shield / TBM cutter ring to be laser-strengthened, derived from the entities and relationships between entities in the knowledge graph of laser shock strengthening of the shield / TBM cutter ring surface, are the first parameters. The surface laser shock strengthening parameters of the shield / TBM cutter ring to be laser-strengthened, predicted by the LSTM model, are the second parameters. If the first and second parameters are the same, this is the output result; otherwise, the prediction is repeated.

[0033] Compared with the prior art, the present invention has the following beneficial effects:

[0034] 1. This invention constructs a knowledge graph of laser shock blasting on the surface of shield / TBM cutter rings based on historical data of laser shock blasting on shield / TBM cutter rings. Based on the shield / TBM cutter ring parameters input into the knowledge graph, it predicts the surface laser shock blasting parameters of the shield / TBM cutter rings to be laser-blasted. Based on the surface laser shock blasting parameters of the shield / TBM cutter rings to be laser-blasted, it performs surface laser shock blasting on the shield / TBM cutter rings. Compared with the prior art, the knowledge graph can optimize the surface laser shock blasting parameters of the shield / TBM cutter rings, that is, it can optimize the surface laser shock blasting effect of the shield / TBM cutter rings.

[0035] 2. Before laser shock strengthening of the shield / TBM cutter ring surface, the present invention first obtains three-dimensional scanning data by scanning with a three-dimensional scanner, then constructs a three-dimensional model based on the three-dimensional scanning data, then obtains the difference data by comparing with the preset three-dimensional model, and then performs fine processing based on the difference data. This can ensure that the shield / TBM cutter ring parameters reach the optimal during surface laser shock strengthening treatment, so as to achieve the optimal surface laser shock strengthening effect of the shield / TBM cutter ring.

[0036] 3. The knowledge graph prediction of this invention is based on dual prediction of entities and entity relationships, as well as LSTM model prediction, which can optimize the surface laser shock strengthening parameters of the shield / TBM cutter ring, that is, optimize the surface laser shock strengthening effect of the shield / TBM cutter ring. Attached Figure Description

[0037] Figure 1 Flow chart of the method of the present invention. Detailed Implementation

[0038] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only 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 technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0039] Example 1

[0040] This invention provides the following technical solution: a method for laser shock peening of the surface of a shield / TBM cutterhead ring, comprising the following steps:

[0041] S1: Obtain historical laser shock blasting data on the surface of shield / TBM cutter rings, including surface laser shock blasting data with one or more of the following as independent variables: shield / TBM cutter ring material, shield / TBM cutter ring width, shield / TBM cutter ring thickness, alloy powder type, and laser parameters;

[0042] S2: Preprocess the acquired historical laser shock blasting data on the surface of the shield / TBM cutter ring;

[0043] S3: Construct a knowledge graph of laser shock blasting on the surface of shield / TBM cutter rings based on preprocessed historical shield / TBM cutter ring surface laser shock blasting data;

[0044] S4: Inspection and precision machining of shield / TBM cutter rings whose surfaces require laser shock peening;

[0045] S5: Positioning the shield / TBM cutter ring whose surface has been finely machined and is to be laser-strengthened;

[0046] S6: Input the parameters of the finished shield / TBM cutter ring, including the material, width and thickness of the shield / TBM cutter ring. Based on the constructed knowledge graph of laser shock strengthening of the shield / TBM cutter ring surface, predict the surface laser shock strengthening parameters of the shield / TBM cutter ring to be laser-strengthened, including the alloy powder type and laser parameters.

[0047] S7: Machining of shield / TBM cutter rings based on predicted surface laser shock peening parameters.

[0048] Specifically, in step S2, preprocessing includes deleting missing values, deleting outlier values, deleting duplicate values, data standardization, and data normalization.

[0049] Specifically, the specific steps in step S3 include:

[0050] S301: Using one of the following as independent variables—shield / TBM cutter ring material, shield / TBM cutter ring width, shield / TBM cutter ring thickness, alloy powder type, and laser parameters—and the surface laser shock strengthening effect parameter as the dependent variable, extract the amount of data from the preset threshold in the surface laser strengthening shock data from high to low.

[0051] S302: Calculate the relative merits and demerits of each independent variable based on the average value of the data extracted under each independent variable, and then sort them.

[0052] S303: Using the material, width, thickness, alloy powder type, and laser parameters of the shield / TBM cutter ring as entities, establish the relationship between the material, width, thickness, alloy powder type, and laser parameters of the shield / TBM cutter ring, which is the knowledge graph of laser shock strengthening on the surface of the shield / TBM cutter ring.

[0053] Assume the preset data extraction volume is five;

[0054] The surface laser-enhanced impact effect data extracted from shield / TBM cutter ring material A from high to low are (x1, x2, x3, x4, x5);

[0055] The surface laser-enhanced impact effect data extracted from the shield / TBM cutter ring material B from high to low are (y1, y2, y3, y4, y5);

[0056] The surface laser-strengthened impact effect of shield / TBM cutterhead material A is as follows:

[0057]

[0058] The surface laser-strengthened impact effect of shield / TBM cutterhead material B is as follows:

[0059]

[0060] Then compare shield / TBM cutter rings A and B. If A > B, then shield / TBM cutter ring material A is better, and vice versa. This entity in the knowledge graph is to provide predictive results for producers when they are hesitant about which material to choose for shield / TBM cutter rings.

[0061] Similarly, the cutterhead width of a tunnel boring machine (TBM) is intended to provide a predictive result for manufacturers when they are hesitant about choosing the width of a cutterhead made of a certain material.

[0062] The thickness of the cutterhead ring of a tunnel boring machine (TBM) is intended to provide a predictive result for manufacturers when they are hesitant about choosing the thickness of a cutterhead ring made of a certain material;

[0063] The alloy powder type is intended to provide predictive results for manufacturers when they are hesitant about choosing the alloy powder type for a particular material shield / TBM cutterhead.

[0064] Laser parameters are provided to help manufacturers make predictions when they are hesitant about choosing laser parameters for a particular material of shield / TBM cutterhead.

[0065] Specifically, step S4 includes the following steps:

[0066] S401: The shield / TBM cutter rings to be laser-strengthened on the surface are sequentially passed through a 3D scanner to obtain 3D scanning data;

[0067] S402: Constructing a 3D model of the shield / TBM cutterhead based on 3D scanning data;

[0068] S403: Compare with the preset 3D model of the shield / TBM cutterhead to obtain the stagger data of the shield / TBM cutterhead;

[0069] S404: Precision machining of shield / TBM cutter rings based on the uneven data of the cutter rings;

[0070] S405: After finishing, repeat the above process of acquiring 3D scanning data, constructing 3D model, comparing 3D model and finishing the cutter ring until the 3D model of the cutter ring is the same as the preset 3D model data of the cutter ring, and then you will get the finished cutter ring.

[0071] Specifically, in step S6, the specific steps for predicting the surface laser shock strengthening parameters of the shield / TBM cutter ring to be laser-strengthened using the knowledge graph of laser shock strengthening on the surface of the shield / TBM cutter ring include:

[0072] Based on the input of the shield / TBM cutter ring material, width, and thickness, and the entities and relationships between them in the knowledge graph of laser shock strengthening of the shield / TBM cutter ring surface, the surface laser shock strengthening parameters of the shield / TBM cutter ring to be laser-strengthened are derived step by step.

[0073] Example 2

[0074] The difference between this embodiment and Embodiment 1 is that:

[0075] Specifically, in step S3, the knowledge graph of laser shock peening enhancement on the surface of the shield / TBM cutterhead also includes:

[0076] Solid-state LSTM model relating alloy powder type and laser parameters;

[0077] Historical alloy powder types and laser parameters are also input into the LSTM model for training;

[0078] During prediction, the surface laser shock strengthening parameters of the shield / TBM cutter ring to be laser-strengthened, derived from the entities and relationships between entities in the knowledge graph of laser shock strengthening of the shield / TBM cutter ring surface, are the first parameters. The surface laser shock strengthening parameters of the shield / TBM cutter ring to be laser-strengthened, predicted by the LSTM model, are the second parameters. If the first and second parameters are the same, this is the output result; otherwise, the prediction is repeated.

[0079] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A method for laser shock peening of the cutterhead surface of a tunnel boring machine (TBM), characterized in that, The following steps are involved: S1: Obtain historical laser shock blasting data on the surface of shield / TBM cutter rings, including surface laser shock blasting data with one or more of the following as independent variables: shield / TBM cutter ring material, shield / TBM cutter ring width, shield / TBM cutter ring thickness, alloy powder type, and laser parameters; S2: Preprocess the acquired historical laser shock blasting data on the surface of the shield / TBM cutter ring; S3: Construct a knowledge graph of laser shock blasting on the surface of shield / TBM cutter rings based on preprocessed historical shield / TBM cutter ring surface laser shock blasting data; S4: Inspection and precision machining of shield / TBM cutter rings whose surfaces require laser shock peening; S5: Positioning the shield / TBM cutter ring whose surface is to be laser-strengthened after precision machining; S6: Input the parameters of the finished shield / TBM cutter ring, including the material, width and thickness of the shield / TBM cutter ring. Based on the constructed knowledge graph of laser shock strengthening of the shield / TBM cutter ring surface, predict the surface laser shock strengthening parameters of the shield / TBM cutter ring to be laser-strengthened, including the alloy powder type and laser parameters. S7: Machining of shield / TBM cutter rings based on predicted surface laser shock peening parameters.

2. The method for laser shock peening of the cutterhead surface of a shield tunneling machine (TBM) according to claim 1, characterized in that: In step S2, the preprocessing includes deleting missing value data, deleting outlier value data, deleting duplicate value data, data standardization, and data normalization.

3. The method for laser shock peening of the cutterhead surface of a shield tunneling machine (TBM) according to claim 1, characterized in that: The specific steps in step S3 include: S301: Using one of the following as independent variables—shield / TBM cutter ring material, shield / TBM cutter ring width, shield / TBM cutter ring thickness, alloy powder type, and laser parameters—and the surface laser shock strengthening effect parameter as the dependent variable, extract the amount of data from the preset threshold in the surface laser strengthening shock data from high to low. S302: Calculate the relative merits and demerits of each independent variable based on the average value of the data extracted under each independent variable, and then rank them. S303: Using the material, width, thickness, alloy powder type, and laser parameters of the shield / TBM cutter ring as entities, establish the relationship between the material, width, thickness, alloy powder type, and laser parameters of the shield / TBM cutter ring, which is the knowledge graph of laser shock strengthening on the surface of the shield / TBM cutter ring.

4. The method for laser shock peening of the cutterhead surface of a shield tunneling machine (TBM) according to claim 1, characterized in that: The specific steps of step S4 include: S401: The shield / TBM cutter rings to be laser-strengthened on the surface are sequentially passed through a 3D scanner to obtain 3D scanning data; S402: Constructing a 3D model of the shield / TBM cutterhead based on 3D scanning data; S403: Compare with the preset 3D model of the shield / TBM cutterhead to obtain the stagger data of the shield / TBM cutterhead; S404: Precision machining of shield / TBM cutter rings based on the uneven data of the cutter rings; S405: After finishing, repeat the above process of acquiring 3D scanning data, constructing 3D model, comparing 3D model and finishing the cutter ring until the 3D model of the cutter ring is the same as the preset 3D model data of the cutter ring, and then you will get the finished cutter ring.

5. The method for laser shock peening of the cutterhead surface of a shield tunneling machine (TBM) according to claim 1, characterized in that: In step S6, the specific steps for predicting the surface laser shock strengthening parameters of the shield / TBM cutter ring to be laser-shock strengthened using the knowledge graph of laser shock strengthening on the surface of the shield / TBM cutter ring include: Based on the input of the shield / TBM cutter ring material, width, and thickness, and the entities and relationships between them in the knowledge graph of laser shock strengthening of the shield / TBM cutter ring surface, the surface laser shock strengthening parameters of the shield / TBM cutter ring to be laser-strengthened are derived step by step.

6. The method for laser shock peening of the cutterhead surface of a shield tunneling machine (TBM) according to claim 3, characterized in that: In step S3, the constructed knowledge graph of laser shock peening enhancement on the surface of the shield / TBM cutterhead also includes: Solid-state LSTM model relating alloy powder type and laser parameters; Historical alloy powder types and laser parameters are also input into the LSTM model for training; During prediction, the surface laser shock strengthening parameters of the shield / TBM cutter ring to be laser-strengthened, derived from the entities and relationships between entities in the knowledge graph of laser shock strengthening of the shield / TBM cutter ring surface, are the first parameters. The surface laser shock strengthening parameters of the shield / TBM cutter ring to be laser-strengthened, predicted by the LSTM model, are the second parameters. If the first and second parameters are the same, this is the output result; otherwise, the prediction is repeated.

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