Profiling efficient spraying method for magnesium casting deep-cavity special-shaped mold

Abstract

The invention relates to the technical field of material surface treatment, in particular to an efficient profiling spraying method for a magnesium casting deep-cavity special-shaped mold. An efficient profiling spraying method for a magnesium casting deep-cavity special-shaped mold comprises the steps that firstly, the actual size of the mold is obtained through a laser measuring instrument, the deviation rate is calculated through an ICP algorithm, a correction model is built through radial basis function interpolation, and the size is finished and rechecked; discretizing the mold surface to calculate the area, estimating the temperature by combining a finite element method and a heat conduction equation, and determining the total amount of a release agent; secondly, planning a nozzle track by using a spline curve, and optimizing spraying parameters by using a particle swarm optimization algorithm; during spraying, operation is performed according to an optimization result, release agent parameters are adjusted according to temperature deviation by using a self-adaptive fuzzy PID control algorithm, meanwhile, particle size distribution is inversed based on the maximum entropy principle by means of high-speed camera shooting, and accordingly, the pressure and flow of atomized gas are adjusted to cool and start equipment as required.

Description

Technical Field

[0001] The invention relates to the technical field of material surface treatment, in particular to a high-efficiency profiling spraying method for a deep-cavity special-shaped magnesium casting mold. Background Art

[0002] In modern manufacturing, magnesium casting technology is widely used in many fields such as aerospace, automobile manufacturing, and electronic equipment due to its good casting performance, high strength-to-weight ratio, and excellent corrosion resistance. With the increasing complexity of product structures and the continuous improvement of performance requirements, the use of deep-cavity special-shaped molds for magnesium casting is becoming more and more frequent. The surface quality of deep-cavity special-shaped molds for magnesium casting plays a decisive role in the molding quality, demolding effect, and service life of the casting. Spraying release agents is a key process to ensure the normal use of molds, and its quality directly affects the stability of the entire magnesium casting production process and the reliability of product quality. However, traditional spraying methods have many difficulties when dealing with deep-cavity special-shaped molds for magnesium casting.

[0003] On the one hand, due to the complex shape of deep-cavity special-shaped molds for magnesium casting, and the presence of special structures such as deep cavities and special-shaped curved surfaces, it is difficult to ensure the dimensional accuracy of each part of the mold. Traditional measurement methods are difficult to accurately obtain its actual size, resulting in a lack of accurate data basis in subsequent processing, finishing, and spraying processes, making it difficult to achieve efficient and accurate spraying operations. On the other hand, the complex mold surface makes it difficult to accurately control the amount of release agent used during the spraying process. Excessive use of release agent not only causes waste, but may also affect the quality of the casting; insufficient use will lead to demolding difficulties and damage the mold and casting. At the same time, traditional spraying methods often rely solely on experience when planning the nozzle trajectory and determining the spraying parameters. They lack scientific and effective optimization algorithms and are difficult to take into account multiple indicators such as spraying efficiency and coating uniformity. This results in unstable coating quality and is unable to meet the needs of high-quality magnesium casting production. In addition, during the spraying process, changes in mold temperature and the atomization effect of the release agent also have a significant impact on the coating quality. Traditional methods are difficult to effectively regulate based on real-time changes. Summary of the Invention

[0004] In order to completely solve the problems in the existing technology of spraying deep-cavity special-shaped magnesium casting molds, such as the difficulty in accurately measuring mold dimensions, poor control of release agent dosage, and the lack of scientific algorithms for nozzle trajectory and parameter settings, which makes it difficult to take multiple indicators into account, the present invention proposes the following technical solutions:

[0005] The high-efficiency spraying method for the contoured deep-cavity special-shaped mold of cast magnesium is as follows:

[0006] S1: Use a laser measuring instrument to obtain the actual size of the mold, and calculate the comprehensive deviation rate between the actual and designed sizes using the ICP algorithm;

[0007] S2: Based on the measurement deviation, radial basis function interpolation is used to build a correction model. After the mold is CNC trimmed, the dimensions are checked according to the S1 method.

[0008] S3: Discretize the complex mold surface and calculate the area. Use the finite element method combined with the heat conduction equation to estimate the temperature change during spraying and determine the total amount of release agent required for the spraying equipment.

[0009] S4: Plan the nozzle trajectory with a spline curve, and optimize the spraying parameters by comprehensively considering multiple indicators using the particle swarm optimization algorithm;

[0010] S5: Based on the nozzle trajectory and spraying parameters of S4, the spraying equipment is started to spray the deep-cavity special-shaped magnesium casting mold. At the same time, the adaptive fuzzy PID control algorithm is used to adjust the release agent related parameters according to the temperature deviation and change rate;

[0011] S6: After the spraying operation starts in S5, the particle size distribution is inverted based on the maximum entropy principle with the help of high-speed camera, and the atomizing gas pressure and flow are adjusted accordingly to achieve cooling and start the spraying equipment.

[0012] Preferably, in step S1, the ICP algorithm has the following expression:

[0013]

[0014] Where p i Represents the actual point cloud set P = {p1,p2,...,p n}, q i Denotes the design point cloud set Q = {q1,q2,...,q n}, where:

[0015]

[0016] Where T represents the homogeneous transformation matrix containing the rotation matrix R and the translation vector t.

[0017] Preferably, in step S2, when constructing the correction model by radial basis function interpolation, the relevant expression is as follows:

[0018]

[0019] Where, represents the radial basis function, x i Indicates the position of the known measurement deviation point, p(x) represents the set constant polynomial, c i represents the coefficients obtained by solving the set linear equations, and N represents the polynomial coefficients obtained by solving the set linear equations.

[0020] Preferably, the set linear equations are expressed as follows:

[0021]

[0022] Where x i (i=1,…,N) represents the independent variable vector, usually related to the data point, represents the set function, where Represents the vector x i with x j The transformation of the distance between k (x i )(k=1,…,m) represents the relationship between the independent variable x i The polynomial function of the equations, y i (i=1,…,N) represents the independent variable x i The corresponding dependent variable observation, c i (i=1,…,N) and d k (k=1,…,m) represents the unknown coefficients to be solved,

[0023] Preferably, in step S3, when discretizing the complex mold surface to calculate the area, the mold surface is discretized into M triangular facets, and the three vertex coordinates of the kth triangular facet are v k1 =(x k1 ,y k1 ,z k1 ), v k2 =(x k2 ,y k2 ,z k2 ), v k3 =(x k3 ,y k3 ,z k3 ), then the area of ​​the triangle is A k Computed by vector cross product:

[0024]

[0025] a=v k2 -v k1 ;

[0026] b=v k3 -v k1 ;

[0027] Among them, the relevant expression of the total mold surface area is as follows:

[0028]

[0029] Preferably, in step S4, when planning the nozzle trajectory, it is necessary to determine the coefficient ai 、b i 、b i 、b i The specific value of can be obtained by solving the relevant condition equation. The relevant condition equation is expressed as follows:

[0030] S i (x) = a i +b i (xx i )+b i (xx i ) 2 +b i (xx i ) 3 ,x∈[x i ,x i+1 ];

[0031] Where S i (x) means that in the interval [x i ,x i+1 ], x represents the position coordinate of the nozzle in space, x i and x i+1 Represents a trajectory node.

[0032] Preferably, in step S4, the spraying parameters are optimized, and the relevant expressions are as follows:

[0033] v ij (t+1)=ωv ij (t)+c1r 1j (t)(p ij -x ij (t))+c2r 2j (t)(g j -x ij (t));

[0034] x ij (t+1)=x ij (t)+v ij (t+1);

[0035] Where, v ij (t) represents, ω represents, c1 represents the learning factor of the step length of the particle to fly to its own historical best position, c2 represents the learning factor of the step length of the particle to fly to the global best position, r 1j (t), r 2j (t) represents a random number between 0 and 1, p ij represents the historical best position of the i-th particle in the j-th dimension space, x ij (t) represents the position of the i-th particle in the j-dimensional space at time t.

[0036] Preferably, in said S5, when adjusting the release agent related parameters, the related expressions are as follows:

[0037]

[0038] Preferably, in said S6, when inverting the particle size distribution based on the maximum entropy principle, a likelihood function is first constructed:

[0039]

[0040] At the same time, combined with the maximum entropy principle, the formula is:

[0041]

[0042] Finally, the atomizing gas pressure and flow rate are adjusted according to the inversion results, and the formula is:

[0043]

[0044] Where f(d) represents the particle size distribution function, which is used to describe the distribution of particles of different particle sizes d in the population, d represents the particle size, and y j represents the measurement data, N represents the total number of measurement data, Represents the variance of the jth measurement value, which is used to measure the discreteness of the measurement value, μ j (f) represents the theoretical value corresponding to the jth measured value calculated based on the particle size distribution function f(d), d min Indicates the minimum value of particle size, d max Indicates the maximum particle size.

[0045] The beneficial effects of the present invention are:

[0046] 1. The present invention obtains the actual size of the mold through a laser measuring instrument, calculates the deviation rate using the ICP algorithm, and then uses radial basis function interpolation to construct a correction model to perform CNC trimming on the mold. It can accurately measure and correct the mold size and improve the mold size accuracy.

[0047] 2. The present invention discretizes the complex mold surface and calculates the area, combines the finite element method and the heat conduction equation to estimate the temperature change during spraying, determines the total amount of release agent, and realizes precise control of the release agent dosage, avoiding the adverse effects caused by excessive or insufficient dosage.

[0048] 3. The present invention plans the nozzle trajectory with a spline curve, and uses the particle swarm optimization algorithm to comprehensively consider multiple indicators to optimize the spraying parameters, so that the nozzle trajectory is more reasonable and the spraying parameters are more optimized, which can better take into account the requirements of multiple indicators and improve the spraying quality.

[0049] 4、The application uses self-adaptive fuzzy PID control algorithm to adjust the release agent related parameters according to temperature deviation and rate of change, and adjusts the atomizing gas pressure and flow rate by means of high-speed photography and maximum entropy principle inversion particle size distribution, realizes real-time adjustment and control in the spraying process, and further improves the spraying effect and quality. BRIEF DESCRIPTION OF DRAWINGS

[0050] Figure 1 The application discloses a casting magnesium deep-cavity special-shaped mold profiling efficient spraying method. DETAILED DESCRIPTION

[0051] The casting magnesium deep-cavity special-shaped mold profiling efficient spraying method has the following steps:

[0052] S1: actual size of the mold is obtained by using a laser measuring instrument, and an integrated deviation rate of actual and designed sizes is calculated by an ICP algorithm;

[0053] S2: based on the measurement deviation, a radial basis function interpolation is adopted to construct a correction model, after numerical control finishing of the mold, the size is rechecked by the method of S1;

[0054] S3: a complex mold surface is discretized and area is calculated, and a finite element method is combined with a heat conduction equation to estimate temperature change during spraying, so that the total amount of release agent required by the spraying equipment is determined;

[0055] S4: a spline curve is used to plan a nozzle trajectory, a particle swarm optimization algorithm is used, and spraying parameters are optimized in combination with multiple indexes;

[0056] S5: according to the nozzle trajectory and the spraying parameters of S4, the spraying equipment is started, and the casting magnesium deep-cavity special-shaped mold is sprayed, meanwhile, a self-adaptive fuzzy PID control algorithm is used to adjust the release agent related parameters according to temperature deviation and rate of change;

[0057] S6: after the spraying operation of S5 is started, high-speed photography is used, a maximum entropy principle is used to invert the particle size distribution, and the atomizing gas pressure and flow rate are adjusted according to the particle size distribution, so that cooling is realized and the spraying equipment is started.

[0058] In step S1, the ICP algorithm has the following related expressions:

[0059]

[0060] In the formula, p i represents an element in an actual point cloud set P={p1, p2,..., p n} and q i represents an element in a designed point cloud set Q={q1, q2,..., q n}, wherein:

[0061]

[0062] Where T represents the homogeneous transformation matrix containing the rotation matrix R and the translation vector t.

[0063] Preferably, in step S2, when the correction model is constructed by radial basis function interpolation, the relevant expression is as follows:

[0064]

[0065] Where, represents the radial basis function, x i Indicates the position of the known measurement deviation point, p(x) represents the set constant polynomial, c i represents the coefficients obtained by solving the set linear equations, and N represents the polynomial coefficients obtained by solving the set linear equations.

[0066] Preferably, the linear equations are set as follows:

[0067]

[0068] Where x i (i=1,…,N) represents the independent variable vector, usually related to the data point, represents the set function, where Represents the vector x i with x j The transformation of the distance between k (x i )(k=1,…,m) represents the relationship between the independent variable x i The polynomial function of the equations, y i (i=1,…,N) represents the independent variable x i The corresponding dependent variable observation, c i (i=1,…,N) and d k (k=1,…,m) represents the unknown coefficients to be solved,

[0069] In step S3, when discretizing the complex mold surface to calculate the area, the mold surface is discretized into M triangular patches, and the three vertex coordinates of the kth triangular patch are v k1 =(x k1 ,y k1 ,z k1 ), v k2 =(x k2 ,y k2 ,z k2 ), v k3 =(x k3 ,y k3 ,z k3 ), then the area of ​​the triangle is Ak Computed by vector cross product:

[0070]

[0071] a=v k2 -v k1 ;

[0072] b=v k3 -v k1 ;

[0073] Among them, the relevant expression of the total mold surface area is as follows:

[0074]

[0075] In step S4, when planning the nozzle trajectory, it is necessary to determine the coefficient a i 、b i 、b i 、b i The specific value of can be obtained by solving the relevant condition equation. The relevant condition equation is expressed as follows:

[0076] S i (x) = a i +b i (xx i )+b i (xx i ) 2 +b i (xx i ) 3 ,x∈[x i ,x i+1 ];

[0077] Where S i (x) means that in the interval [x i ,x i+1 ], x represents the position coordinate of the nozzle in space, x i and x i+1 Represents a trajectory node.

[0078] Preferably, in step S4, the spraying parameters are optimized, and the relevant expressions are as follows:

[0079] v ij (t+1)=ωv ij (t)+c1r 1j (t)(p ij -x ij (t))+c2r 2j (t)(g j -x ij (t));

[0080] x ij (t+1)=x ij (t)+v ij (t+1);

[0081] Where, v ij (t) represents, ω represents, c1 represents the learning factor of the step length of the particle to fly to its own historical best position, c2 represents the learning factor of the step length of the particle to fly to the global best position, r 1j (t), r 2j (t) represents a random number between 0 and 1, p ij represents the historical best position of the i-th particle in the j-th dimension space, x ij (t) represents the position of the i-th particle in the j-dimensional space at time t.

[0082] In S5, when adjusting the release agent related parameters, the relevant expressions are as follows:

[0083]

[0084] In S6, when inverting the particle size distribution based on the maximum entropy principle, the likelihood function is first constructed:

[0085]

[0086] At the same time, combined with the maximum entropy principle, the formula is:

[0087]

[0088] Finally, the atomizing gas pressure and flow rate are adjusted according to the inversion results, and the formula is:

[0089]

[0090] Where f(d) represents the particle size distribution function, which is used to describe the distribution of particles of different particle sizes d in the population, d represents the particle size, and y j represents the measurement data, N represents the total number of measurement data, Represents the variance of the jth measurement value, which is used to measure the discreteness of the measurement value, μ j (f) represents the theoretical value corresponding to the jth measured value calculated based on the particle size distribution function f(d), d min Indicates the minimum value of particle size, d max Indicates the maximum particle size.

Claims

1. A high-efficiency spraying method for the contour-coating of deep-cavity special-shaped magnesium casting molds, characterized in that: The following steps are involved: S1: Use a laser measuring instrument to obtain the actual size of the mold, and calculate the comprehensive deviation rate between the actual and designed sizes using the ICP algorithm; S2: Based on the measurement deviation, radial basis function interpolation is used to build a correction model. After the mold is CNC trimmed, the dimensions are checked according to the S1 method. S3: Discretize the complex mold surface and calculate the area. Use the finite element method combined with the heat conduction equation to estimate the temperature change during spraying and determine the total amount of release agent required for the spraying equipment. S4: Plan the nozzle trajectory with a spline curve, and optimize the spraying parameters by comprehensively considering multiple indicators using the particle swarm optimization algorithm; S5: Based on the nozzle trajectory and spraying parameters of S4, the spraying equipment is started to spray the deep-cavity special-shaped magnesium casting mold. At the same time, the adaptive fuzzy PID control algorithm is used to adjust the release agent related parameters according to the temperature deviation and change rate; S6: After the spraying operation starts in S5, the particle size distribution is inverted based on the maximum entropy principle with the help of high-speed camera, and the atomizing gas pressure and flow are adjusted accordingly to achieve cooling and start the spraying equipment.

2. The high-efficiency spraying method for profiling a deep-cavity special-shaped magnesium casting mold according to claim 1 is characterized in that: In step S1, the ICP algorithm has the following expressions: Where p i Represents the actual point cloud set P = {p1,p2,...,p n }, q i Denotes the design point cloud set Q = {q1,q2,...,q n }, where: Where T represents the homogeneous transformation matrix containing the rotation matrix R and the translation vector t.

3. The high-efficiency spraying method for profiling a deep-cavity special-shaped magnesium casting mold according to claim 1 is characterized in that: In step S2, when the correction model is constructed by radial basis function interpolation, the relevant expression is as follows: Where, represents the radial basis function, x i Indicates the position of the known measurement deviation point, p(x) represents the set constant polynomial, c i represents the coefficients obtained by solving the set linear equations, and N represents the polynomial coefficients obtained by solving the set linear equations.

4. The high-efficiency spraying method for profiling a deep-cavity special-shaped magnesium casting mold according to claim 4 is characterized in that: The related expressions of the set linear equations are as follows: Where x i (i=1,…,N) represents the independent variable vector, usually related to the data point, represents the set function, where Represents the vector x i with x j The transformation of the distance between k (x i )(k=1,…,m) represents the relationship between the independent variable x i The polynomial function of the equations, y i (i=1,…,N) represents the independent variable x i The corresponding dependent variable observation, c i (i=1,…,N) and d k (k=1,…,m) represents the unknown coefficients to be solved.

5. The high-efficiency spraying method for profiling a deep-cavity special-shaped magnesium casting mold according to claim 1 is characterized in that: In the step S3, when the complex mold surface is discretized to obtain the area, the mold surface is discretized into M triangular facets, and the three vertex coordinates of the kth triangular facet are v k1 =(x k1 ,y k1 ,z k1 ), v k2 =(x k2 ,y k2 ,z k2 ), v k3 =(x k3 ,y k3 ,z k3 ), then the area of ​​the triangle is A k Computed by vector cross product: a=v k2 -v k1 ; b=v k3 -v k1 ; Among them, the relevant expression of the total mold surface area is as follows:

6. The high-efficiency spraying method for profiling a deep-cavity special-shaped magnesium casting mold according to claim 1 is characterized in that: In step S4, when planning the nozzle trajectory, it is necessary to determine the coefficient a i 、b i 、b i 、b i The specific value of can be obtained by solving the relevant condition equation. The relevant condition equation is expressed as follows: S i (x)=a i +b i (x-x i )+b i (x-x i ) 2 +b i (x-x i ) 3 ,x∈[x i ,x i+1 ]; Where S i (x) means that in the interval [x i ,x i+1 ], x represents the position coordinate of the nozzle in space, x i and x i+1 Represents a trajectory node.

7. The high-efficiency spraying method for profiling a deep-cavity special-shaped magnesium casting mold according to claim 1 is characterized in that: In step S4, the spraying parameters are optimized, and the relevant expressions are as follows: v ij (t+1)=ωv ij (t)+c1r 1j (t)(p ij -x ij (t))+c2r 2j (t)(g j -x ij (t)); x ij (t+1)=x ij (t)+v ij (t+1); Where, v ij (t) represents, ω represents, c1 represents the learning factor of the step length of the particle to fly to its own historical best position, c2 represents the learning factor of the step length of the particle to fly to the global best position, r 1j (t), r 2j (t) represents a random number between 0 and 1, p ij represents the historical best position of the i-th particle in the j-th dimension space, x ij (t) represents the position of the i-th particle in the j-dimensional space at time t.

8. The high-efficiency spraying method for profiling a deep-cavity special-shaped magnesium casting mold according to claim 1 is characterized in that: In the above-mentioned S5, when adjusting the release agent related parameters, the relevant expressions are as follows:

9. The high-efficiency spraying method for profiling a deep-cavity special-shaped magnesium casting mold according to claim 1, characterized in that: In S6, when inverting the particle size distribution based on the maximum entropy principle, the likelihood function is first constructed: At the same time, combined with the maximum entropy principle, the formula is: Finally, the atomizing gas pressure and flow rate are adjusted according to the inversion results, and the formula is: Where f(d) represents the particle size distribution function, which is used to describe the distribution of particles of different particle sizes d in the population, d represents the particle size, and y j represents the measurement data, N represents the total number of measurement data, Represents the variance of the jth measurement value, which is used to measure the discreteness of the measurement value, μ j (f) represents the theoretical value corresponding to the jth measured value calculated based on the particle size distribution function f(d), d min Indicates the minimum value of particle size, d max Indicates the maximum particle size.

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