Turning, drilling and milling composite machine tool for machining flange

Abstract

The invention discloses a turning, drilling and milling composite machine tool for machining flanges, and belongs to the technical field of machining, the machine tool comprises a rack, a bearing plate A / B / C, a turning mechanism, driving assemblies, a milling and drilling mechanism and a clamping and limiting assembly, linear motion of the bearing plates is achieved through the three driving assemblies, multi-procedure integrated machining is completed, and the machining efficiency is improved. A milling penetration depth optimization system is innovatively introduced, flange basic information, machining parameters and state data are collected through a data acquisition module, and target clamping force, a chatter mark suppression coefficient and collaborative parameters are dynamically adjusted through a clamping force optimization module, a machining state analysis module and a rotating speed-feeding collaborative model; and finally, the optimal cutting depth is output through the cutting depth optimization model. The method solves the problems that traditional machining efficiency is low, parameter adjustment depends on experience, vibration mark control is insufficient and the like, machining precision, stability and safety are remarkably improved, and the method is suitable for efficient and high-quality machining of complex flanges.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of machining, and particularly relates to a turning-drilling-milling combined machine tool for machining flanges. BACKGROUND

[0002] In the traditional flange machining process, a lathe, a drilling machine and a milling machine are usually used in sequence to complete the turning, drilling and milling processes respectively, resulting in multiple clamping of the workpiece, frequent switching of equipment, low machining efficiency and difficulty in ensuring accuracy.

[0003] In the prior art, although the combined machine tool can integrate some functions, the clamping stability is insufficient, the machining parameters (such as clamping force, rotating speed and feeding speed) lack dynamic optimization, vibration marks are easily generated due to temperature changes, material property fluctuations or vibration, and the surface quality is affected. In addition, the key parameters such as the cutting depth are adjusted depending on the experience of workers, which easily causes power overrun or tool wear, and there is a machining safety risk.

[0004] Therefore, there is an urgent need for a combined machine tool which can realize multi-process integration, optimize machining parameters in real time and improve stability. SUMMARY

[0005] In view of the deficiencies of the prior art, the application provides a turning-drilling-milling combined machine tool for machining flanges, which solves the above problems.

[0006] To achieve the above purpose, the application is implemented by the following technical scheme: a turning-drilling-milling combined machine tool for machining flanges, comprising a machine frame, a bearing plate A, a bearing plate B, a bearing plate C and a turning mechanism, the bearing plate A and the bearing plate B are in sliding cooperation with a sliding rail A installed on the machine frame, the bearing plate C is in sliding cooperation with a sliding rail B installed on the bearing plate A, and the turning mechanism is installed on the bearing plate B and used for milling and drilling the flange.

[0007] A clamping and limiting assembly is detachably installed on the bearing plate C and used for clamping and limiting the flange.

[0008] A driving assembly is provided with three groups of identical structures and is installed on the bearing plate A and the machine frame in the horizontal and vertical directions, and is used for driving the bearing plate A, the bearing plate B and the bearing plate C to move linearly.

[0009] A milling and drilling mechanism is installed on the bearing plate B and used for milling and drilling the flange.

[0010] A milling machining cutting depth optimization system is used for optimizing and adjusting the cutting depth of the flange subjected to milling machining, and comprises:

[0011] A data acquisition module acquires flange basic information, milling machining basic information and flange state information.

[0012] The clamping force optimization module outputs a clamping force evaluation factor by constructing a clamping force evaluation model based on the flange basic information and the flange temperature information, and obtains a target clamping force based on the clamping force evaluation factor and the current clamping force.

[0013] The processing state analysis module outputs a vibration mark evaluation coefficient by constructing a vibration mark evaluation model based on the flange state information, compares the vibration mark evaluation coefficient with a vibration mark coefficient threshold value, and then judges whether the processing is qualified.

[0014] The rotation speed-feeding speed analysis module constructs a rotation speed-feeding speed coordination model based on the target clamping force and the vibration mark evaluation coefficient under the rotation speed and the feeding speed, and outputs a rotation speed-feeding speed coordination coefficient.

[0015] The cutting depth analysis module constructs a cutting depth optimization model based on the current cutting depth and the rotation speed-feeding speed coordination coefficient, outputs a target cutting depth, and adjusts the current cutting depth to the target cutting depth.

[0016] On the basis of the above technical solutions, the application further provides the following optional technical solutions.

[0017] A further technical solution is that the cutting depth optimization model is expressed as:

[0018]

[0019] Wherein, a tar represents the target cutting depth, a cur represents the current cutting depth, K W represents the rotation speed-feeding speed coordination coefficient, P max represents the maximum power of milling processing, P cur represents the current cutting power of milling processing, τ represents a safety margin ratio, K v represents the vibration mark evaluation coefficient.

[0020] A further technical solution is that the working steps of the rotation speed-feeding speed analysis module are:

[0021] The absolute value of the difference between the target clamping force and the current clamping force is processed by ratio to obtain a clamping force adaptation factor;

[0022] The vibration mark evaluation coefficient is processed by ratio to the average of the upper limit value and the lower limit value of the vibration mark evaluation coefficient threshold value to obtain a vibration mark suppression factor;

[0023] The clamping force adaptation factor, the current spindle rotation speed, the current feeding speed, and the vibration mark suppression factor are introduced into the constructed rotation speed-feeding speed coordination model to output the rotation speed-feeding speed coordination coefficient;

[0024] The rotation speed-feeding speed coordination model is expressed as:

[0025]

[0026] wherein K W represents the speed-feed synergy coefficient, F opt represents the theoretical optimal speed, N opt represents the theoretical optimal feed speed, N cur represents the current spindle speed, F cur represents the current feed speed, K ind represents the vibration suppression factor, F ind represents the clamping force adaptation factor.

[0027] Further technical solutions: the flange basic information includes material yield strength at current temperature, flange material thermal expansion coefficient and current flange temperature, the flange state information includes machining surface roughness and vibration frequency during machining, and the milling machining basic information includes spindle speed, feed speed and current depth of cut.

[0028] Further technical solutions: the working steps of the clamping force optimization module are:

[0029] material yield strength at current temperature, flange material thermal expansion coefficient and current flange temperature are introduced into the constructed clamping force evaluation model to output a clamping force evaluation factor, and the clamping force evaluation factor and the current clamping force are introduced into the constructed clamping force optimization model to output a target clamping force;

[0030] The clamping force evaluation model is represented as:

[0031]

[0032] wherein K F represents the clamping force evaluation factor, σ y (T) represents the material yield strength at current temperature, σ y (T0) represents the material yield strength at reference temperature, α represents the thermal expansion coefficient of the flange material, and ΔT represents the temperature change amount and ΔT=T-T0;

[0033] The clamping force optimization model is represented as:

[0034]

[0035] wherein F tar represents the target clamping force, K F represents the clamping force evaluation factor, F cur represents the current clamping force, β represents the roughness compensation coefficient, R a represents the clamping surface roughness, R a0 represents the reference roughness.

[0036] Further technical solutions: the working steps of the processing state analysis module are:

[0037] The roughness index is obtained by ratio processing of the machining surface roughness and the critical roughness, and the vibration frequency index is obtained by ratio processing of the vibration frequency during machining and the inherent frequency of the process system.

[0038] The roughness index and the vibration frequency index are introduced into the vibration mark evaluation model to output the vibration mark evaluation coefficient.

[0039] The obtained vibration mark evaluation coefficient is compared with the preset vibration mark evaluation coefficient threshold value, and if the vibration mark evaluation coefficient is not within the vibration mark evaluation coefficient threshold value, it indicates that this processing is unqualified.

[0040] The vibration mark evaluation model is represented as:

[0041] K v =R ind exp(μf ind )

[0042] Wherein, K v represents the vibration mark evaluation coefficient, R ind represents the roughness index, μ represents the frequency sensitivity coefficient, and f ind represents the vibration frequency index.

[0043] Further technical solutions: the clamping limiting assembly includes linear motion parts and a pressing block, three said linear motion parts are uniformly installed in the form of a ring on the mounting seat, the mounting seat is detachably installed on the bearing plate C, the output shaft of the linear motion part is fixedly connected with the pressure sensor embedded in the pressing block, and the pressing block is in sliding fit with the limiting sliding groove opened on the bearing plate C.

[0044] Further technical solutions: the driving assembly includes a lead screw and a motor B, the lead screw is rotatably installed on the rack, the lead screw is fixedly connected with the output shaft of the driving A which is detachably installed on the rack, and the lead screw is threadedly connected with the bearing plate B.

[0045] Further technical solutions: the milling and drilling mechanism includes a main shaft, a main shaft seat and a motor A, the main shaft is rotatably installed on the main shaft seat, the main shaft seat is detachably installed with the support frame which is detachably installed on the bearing plate B, and the motor A is detachably installed on the support frame and its output shaft is drivingly connected with the main shaft through a belt wheel pair.

[0046] Further technical solutions: the turning mechanism includes a motor C installed on the rack, a three-jaw chuck and a tailstock, the motor C is detachably installed on the rack and its output shaft is fixedly connected with the three-jaw chuck, the tailstock is in sliding fit with the sliding rail A installed on the rack and can be limited on the rack through the bolt assembly.

[0047] The application provides a turning-drilling-milling combined machine tool for machining a flange, and has the following beneficial effects compared with the prior art:

[0048] 1. The application can reduce the clamping frequency of workpieces and the floor area occupied by equipment by integrating the functions of turning, drilling and milling, thereby significantly improving the machining efficiency.

[0049] 2. The application can construct a dynamic model based on data such as temperature, material yield strength and vibration frequency, and can optimize the clamping force, rotating speed and feeding speed in real time to ensure the machining stability, and can automatically determine the machining eligibility by comparing the vibration evaluation model with the threshold value, thereby reducing the surface roughness and improving the finished product accuracy, and the cutting depth optimization model is introduced to dynamically adjust the cutting parameters in combination with the power limit and vibration coefficient, thereby avoiding equipment overload and prolonging the tool life. BRIEF DESCRIPTION OF DRAWINGS

[0050] Fig. 1 It is a three-dimensional structural schematic diagram of the application.

[0051] Fig. 2 It is a structural schematic diagram of the milling and drilling mechanism in the application.

[0052] Fig. 3 It is a structural schematic diagram of the clamping and limiting assembly 8 in the application.

[0053] Fig. 4 It is a flowchart of the milling machining cutting depth optimization system in the application.

[0054] Legend of the drawing: 1, machine frame; 2, bearing plate A; 3, bearing plate B; 4, bearing plate C; 5, turning mechanism; 6, driving assembly; 601, lead screw; 7, milling and drilling mechanism; 701, main shaft; 702, main shaft seat; 703, motor A; 704, support frame; 8, clamping and limiting assembly; 801, linear motion part; 802, pressing block. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical scheme and advantages of the application more clear, the application is further described in detail below in combination with the drawings and examples. It should be understood that the specific examples described herein are only used to explain the application and do not limit the application.

[0056] The specific implementation of the application is described in detail below in combination with specific examples.

[0057] Please refer to Figs. 1 to 4For an embodiment of the present application, a flange machining turning-milling compound machine tool comprises a rack 1, a bearing plate A 2, a bearing plate B 3, a bearing plate C 4 and a turning mechanism 5, the bearing plate A 2 and the bearing plate B 3 are in sliding fit with a sliding rail A (not shown in the figure) installed on the rack 1, the bearing plate C 4 is in sliding fit with a sliding rail B (not shown in the figure) installed on the bearing plate A 2, and further comprising:

[0058] A clamping limiting assembly 8 is detachably installed on the bearing plate C 4 and used for clamping and limiting the flange;

[0059] A driving assembly 6 is provided with three groups of identical structures and is installed on the bearing plate A 2 and the rack 1 in horizontal and vertical directions, and is used for driving the bearing plate A 2, the bearing plate B 3 and the bearing plate C 4 to move linearly;

[0060] A milling-drilling mechanism 7 is installed on the bearing plate B 3 and used for milling and drilling the flange;

[0061] A milling machining cutting depth optimization system is used for optimizing and adjusting the cutting depth of the flange subjected to milling and comprises:

[0062] A data acquisition module acquires flange basic information, milling machining basic information and flange state information;

[0063] A clamping force optimization module constructs a clamping force evaluation model by the flange basic information and the flange temperature information to output a clamping force evaluation factor, and acquires a target clamping force according to the clamping force evaluation factor and a current clamping force;

[0064] A machining state analysis module constructs a vibration mark evaluation model by the flange state information to output a vibration mark evaluation coefficient and compare it with a vibration mark coefficient threshold value, and then judges whether the machining is qualified;

[0065] A rotation speed-feeding speed analysis module constructs a rotation speed-feeding speed coordination model based on the target clamping force and the rotation speed and the feeding speed under the vibration mark evaluation coefficient to output a rotation speed-feeding speed coordination coefficient;

[0066] A cutting depth analysis module constructs a cutting depth optimization model by the current cutting depth and the rotation speed-feeding speed coordination coefficient to output a target cutting depth and adjust the current cutting depth to the target cutting depth.

[0067] Specifically, when starting the machining process, the clamping limiting assembly 8 automatically adjusts the clamping position according to the flange size, and the pressure sensor monitors the clamping force distribution in real time. The driving assembly 6 controls the movement trajectory of the three bearing plates respectively, so that the tool approaches the workpiece according to the predetermined path, and the milling and drilling mechanism 7 selects the tool according to the process requirement and performs milling or drilling operation. The data acquisition module continuously collects the flange temperature, flange clamping surface roughness, and machining surface roughness, vibration frequency, cutting power and other parameters, and transmits them to the optimization system. The clamping force optimization module compares the difference between the material yield strength at the current temperature and the reference value, and dynamically adjusts the clamping force set value to prevent clamping failure caused by thermal deformation. The machining state analysis module generates a vibration pattern evaluation coefficient according to the machining surface roughness and vibration frequency characteristics. The rotational speed-feeding speed analysis module integrates the target clamping force and the vibration pattern evaluation coefficient to obtain the rotational speed-feeding speed synergy coefficient, and the cutting depth analysis module automatically adjusts the cutting depth based on the current power consumption and the rotational speed-feeding speed synergy coefficient to balance the machining efficiency and tool life.

[0068] Compared with the prior art, the clamping device of the traditional composite machine tool cannot adapt to the change of material properties caused by temperature change, while the present scheme establishes a dynamic clamping force compensation mechanism by real-time monitoring of temperature and material parameters. The existing equipment adopts a fixed relationship formula in matching the cutting parameters, while the present scheme constructs a clamping force-rotational speed-feeding speed multivariate synergy model to realize closed-loop optimization of cutting parameters. In the traditional process, the cutting depth is only set according to experience, and in the present scheme, the cutting power, vibration state and process stability are included in the optimization objective function to form an adaptive adjustment strategy.

[0069] Through the above technical scheme, the present application realizes real-time collaborative optimization of multi-process integrated machining and process parameters, the dynamic compensation function of the clamping device effectively suppresses the positioning error caused by thermal deformation, the three-degree-of-freedom driving system improves the machining capability of complex surfaces, the closed-loop optimization algorithm significantly reduces the probability of vibration pattern generation, the automatic matching of process parameters avoids the risk of power overrun, the intelligent adjustment of cutting depth prolongs the service life of the tool, and finally the machining precision is guaranteed while the production efficiency is improved.

[0070] Preferably, the flange basic information includes the material yield strength at the current temperature, the thermal expansion coefficient of the flange material, and the current flange temperature, the flange state information includes the machining surface roughness and the vibration frequency during machining, and the milling machining basic information includes the spindle speed, the feeding speed and the current cutting depth.

[0071] The material yield strength at the current temperature refers to the plastic deformation resistance of the flange material at the processing environment temperature, which can be obtained in real time through the temperature sensor and the material performance database, and is used to evaluate whether the clamping force will cause the flange to yield due to the compression effect; the thermal expansion coefficient of the flange material refers to the ratio of the size change of the flange caused by temperature change, which is used to correct the clamping position offset caused by temperature fluctuation; the current flange temperature refers to the real-time temperature of the flange body during processing, which can be collected by an infrared temperature measuring device in a non-contact manner, and is used to compensate for the thermal expansion effect; the machining surface roughness refers to the microscopic unevenness of the machined area, which can be detected online by a contact profilometer, and is used to reflect the deterioration of the machining quality caused by tool wear or vibration; the vibration frequency refers to the mechanical vibration frequency of the process system during milling, which can be obtained by using an acceleration sensor, and is used to identify the risk of system resonance; the spindle speed, the feed speed and the current depth of cut refer to the rotating speed, the linear moving speed and the cutting depth of the tool during milling.

[0072] Specifically, when the material yield strength decreases due to temperature change during flange processing, the yield strength and the thermal expansion coefficient at the current temperature are obtained in real time to dynamically adjust the clamping force to avoid clamping failure or deformation caused by material softening; when the vibration frequency approaches the natural frequency of the process system, the machining surface roughness data increases synchronously, and the two are combined to judge the risk of vibration marks and trigger the adjustment of the machining parameters.

[0073] Compared with the prior art, the change in material performance caused by temperature is not considered in the clamping force calculation in traditional flange processing, and the adjustment of the machining parameters depends on offline detection results. The present scheme integrates temperature, vibration and surface quality multi-dimensional data to realize online collaborative optimization of the clamping force and the cutting parameters. The prior art usually handles the setting of the clamping force and the adjustment of the machining parameters separately, and the present scheme analyzes the material thermal characteristics, the dynamic vibration state and the power consumption in association to form a closed-loop control logic.

[0074] Preferably, the working steps of the clamping force optimization module are as follows:

[0075] The material yield strength at the current temperature, the thermal expansion coefficient of the flange material and the current flange temperature are introduced into the constructed clamping force evaluation model to output a clamping force evaluation factor, and the clamping force evaluation factor and the current clamping force are introduced into the constructed clamping force optimization model to output a target clamping force;

[0076] The clamping force evaluation model is represented as:

[0077]

[0078] wherein K F represents the clamping force evaluation factor, σ y (T) represents the material yield strength at the current temperature, σy (T0) represents the yield strength of the material at the reference temperature, and a represents the thermal expansion coefficient of the flange material, and ΔT represents the temperature change amount and ΔT = T - T0;

[0079] The clamping force optimization model is represented as:

[0080]

[0081] Wherein, F tar represents the target clamping force, K F represents the clamping force evaluation factor, F cur represents the current clamping force, β represents the roughness compensation coefficient, R a represents the clamping surface roughness, R a0 represents the reference roughness.

[0082] Wherein, the yield strength of the material at the current temperature σ y (T) refers to the real-time material strength of the flange in the processing environment, which can be realized by combining a temperature sensor with a material yield strength-temperature table, and is used to reflect the characteristics of the decrease in material rigidity caused by temperature rise. The yield strength σ y (T0) refers to the reference value of the material strength under standard test conditions, which can be obtained by consulting a material manual, and is used as a reference parameter for compensation calculation. The thermal expansion coefficient a refers to the physical characteristic parameter of the material thermal expansion, which can be measured by a thermal expansion tester, and is used to quantify the influence of temperature change on the deformation of the clamping structure. The clamping surface roughness R a refers to the microscopic appearance parameter of the contact surface between the workpiece and the clamping assembly, which can be detected online by a contact type roughness meter, and is used to characterize the friction state of the contact surface. The reference roughness R a0 refers to the surface roughness set value under ideal clamping state, which is set to 0.8 μm for example, and is used as a reference benchmark for roughness compensation. The roughness compensation coefficient β refers to the influence weight of surface roughness on clamping force, which can be obtained by experimental calibration or empirical calibration, and is used to adjust the clamping force correction amplitude when the roughness deviates from the reference value.

[0083] Specifically, under temperature fluctuation conditions, the clamping force evaluation factor is calculated by the product of the yield strength ratio and the thermal expansion compensation term, wherein the yield strength ratio reflects the change trend of material strength with temperature, and the thermal expansion compensation term offsets the deformation error of the clamping structure caused by temperature difference. For example, when the temperature rises, σ y(T) decreases, the factor is automatically increased to increase the clamping force to compensate for the decrease in material rigidity; at the same time, the product of the thermal expansion coefficient and the temperature difference reversely corrects the clamping force to avoid over-restraint caused by the expansion of the clamping structure, and then the target clamping force calculation introduces a roughness compensation term, which dynamically adjusts the clamping force output by multiplying the deviation of the actual roughness from the reference value by a compensation coefficient. For example, when it is detected that the clamping surface roughness is lower than the reference, the compensation term automatically increases the clamping force to enhance the friction of the contact surface to prevent the workpiece from sliding; otherwise, the clamping force is reduced to avoid surface indentation.

[0084] Compared with the prior art, the traditional clamping force adjustment method usually only makes static compensation based on a single temperature or roughness parameter, without considering the coupling effect of material strength and thermal expansion, and without establishing a real-time roughness feedback mechanism. While the present scheme solves the problem of material strength attenuation and structure deformation caused by temperature change through a double dynamic compensation mechanism, and realizes real-time matching of clamping force and contact surface friction state through online roughness detection, overcoming the limitations of single parameter compensation.

[0085] Preferably, the working steps of the processing state analysis module are:

[0086] The roughness index is obtained by ratio processing of the processing surface roughness and the critical roughness, and the vibration frequency index is obtained by ratio processing of the vibration frequency during processing and the inherent frequency of the process system;

[0087] The roughness index and the vibration frequency index are introduced into the vibration mark evaluation model to output a vibration mark evaluation coefficient;

[0088] The obtained vibration mark evaluation coefficient is compared with a preset vibration mark evaluation coefficient threshold value, and if the vibration mark evaluation coefficient is not within the vibration mark evaluation coefficient threshold value, it indicates that the current processing is unqualified;

[0089] The vibration mark evaluation model is represented as:

[0090] K v = R ind exp(μf ind )

[0091] Wherein, K v represents the vibration mark evaluation coefficient, R ind represents the roughness index, μ represents the frequency sensitivity coefficient, and f ind represents the vibration frequency index.

[0092] The critical roughness refers to the maximum surface roughness threshold allowed by the process, which can be pre-set according to material properties or processing accuracy requirements, for example, set to 0.8 microns according to the type of flange material, to define the qualified boundary of surface quality;

[0093] The natural frequency refers to the vibration frequency of the machine tool process system under no external excitation, which can be obtained through modal experiment or finite element simulation, for example, the peak frequency of the frequency spectrum in the idling state is measured by an acceleration sensor, which is used to evaluate the degree of influence of vibration on machining stability;

[0094] The frequency sensitivity coefficient refers to the contribution weight of vibration frequency to the formation of vibration marks, which can be fitted through historical data or calibrated through process test, for example, the coefficient is obtained by regression according to the vibration mark depth data under different vibration frequencies, which is used to adjust the non-linear effect of the vibration frequency index in the evaluation model.

[0095] Specifically, the machining state analysis module first obtains the machining surface roughness and vibration frequency data in real time, normalizes the surface roughness with the preset critical value to obtain the roughness index, which is used to represent the deviation degree of surface quality. At the same time, the ratio of the actual vibration frequency to the system natural frequency is taken as the vibration frequency index, which reflects the correlation between vibration energy and system resonance risk. Subsequently, the two indexes are input into the vibration mark evaluation model, and the non-linear coupling relationship between roughness and vibration frequency is quantified as a vibration mark evaluation coefficient in the form of an exponential function. The frequency sensitivity coefficient adjusts the contribution weight of vibration to the vibration mark in this process, for example, when the coefficient increases, a slight change in vibration frequency will cause the evaluation coefficient to rise significantly. Finally, the evaluation coefficient is compared with the preset threshold range, and if it exceeds the threshold, the machining is judged to be unqualified, triggering an alarm or stop command.

[0096] Compared with the prior art, the traditional method usually only monitors a single parameter or relies on artificial experience to judge the vibration mark risk, for example, only detects whether the surface roughness meets the requirements, while ignoring the closeness of the vibration frequency to the system natural frequency. The present application can simultaneously capture the combined influence of surface quality degradation and vibration instability by introducing a double-index cooperative evaluation mechanism, for example, when the surface roughness does not exceed the limit but the vibration is close to the system natural frequency, the vibration mark risk can still be identified in time through model calculation, avoiding the misjudgment of single parameter monitoring.

[0097] Through the above technical solution, the present application can identify the vibration mark problem caused by abnormal surface roughness or vibration frequency close to the system natural frequency in real time, for example, in the process of milling the flange end face, when the vibration frequency reaches 80% of the natural frequency, even if the surface roughness still meets the requirements, the system can still give an early warning through the evaluation coefficient exceeding the limit, so as to avoid the batch rejection caused by the expansion of vibration marks and improve the machining quality stability.

[0098] Preferably, the working steps of the rotation speed-feed speed analysis module are:

[0099] The absolute value of the difference between the target clamping force and the current clamping force is processed by ratio with the target clamping force to obtain a clamping force adaptation factor;

[0100] The chattering suppression factor is obtained by ratio processing of the chattering evaluation coefficient and the average of the upper limit value and the lower limit value of the chattering evaluation coefficient threshold value;

[0101] The clamping force adaptation factor, the current spindle speed, the current feed speed and the chattering suppression factor are introduced into the constructed spindle speed-feed speed coordination model to output a spindle speed-feed speed coordination coefficient;

[0102] The spindle speed-feed speed coordination model is expressed as:

[0103]

[0104] wherein K W represents the spindle speed-feed speed coordination coefficient, F opt represents the theoretical optimal spindle speed, N opt represents the theoretical optimal feed speed, N cur represents the current spindle speed, F cur represents the current feed speed, K ind represents the chattering suppression factor, F ind represents the clamping force adaptation factor.

[0105] The clamping force adaptation factor is a quantitative index of the deviation degree of the target clamping force from the current clamping force, and can be calculated by dividing the absolute value of the difference between the target clamping force and the current clamping force by the target clamping force. The chattering suppression factor is a quantitative parameter of the vibration pattern control requirement in the machining process, and can be obtained by ratio processing of the chattering evaluation coefficient and the average of the upper limit value and the lower limit value of the pre-set threshold value. The factor is used to represent the deviation amplitude of the current vibration suppression requirement relative to the reference state. The theoretical optimal spindle speed is a theoretical value of the spindle rotation speed calculated according to the material properties and process requirements under ideal machining conditions, and can be obtained by calculating the material cutting speed formula combined with the tool diameter parameter. The theoretical optimal feed speed is a theoretical value of the tool feed speed calculated based on the cutting parameter matching relationship under ideal machining conditions, and can be determined by the product of the feed per tooth, the number of tool teeth and the spindle speed.

[0106] Specifically, when the clamping force deviates from the target value during processing, the system first quantifies the adaptive deviation of the current clamping system through the clamping force adaptation factor calculation module. At the same time, the vibration suppression factor calculation module continuously monitors the vibration state, compares and analyzes the real-time vibration suppression evaluation coefficient with the process standard threshold. After the two dynamic factors and the current processing parameters are input into the collaborative model, the model constructs the adjustment benchmark through the ratio relationship between the theoretical optimal parameters and the real-time parameters, and then forms the final collaborative coefficient by combining the double-factor product constraint. For example, when the clamping force adaptation factor increases, it indicates that the clamping system deviates from the ideal state, and at this time the model output will correspondingly reduce the collaborative coefficient to adjust the processing parameters; when the vibration suppression factor exceeds the set range, the model limits the feed speed increase amplitude through an exponential decay mechanism. This double constraint mechanism makes the adjustment of the rotational speed and the feed speed not only maintain the trend of approaching the theoretical optimal value, but also effectively suppress the stability risk caused by parameter mutation.

[0107] Compared with the prior art, the traditional method usually uses fixed threshold judgment or single-factor compensation mechanism for parameter adjustment, which is difficult to balance the dual requirements of dynamic changes of the clamping system and vibration suppression. The segmented control strategy commonly used in the prior art is prone to cause parameter step changes, while the present scheme constructs a smooth adjustment mechanism through the continuous quantization of the adaptation factor and the suppression factor. The parameter adjustment in the prior art is mostly based on empirical formulas or static models, and the present scheme dynamically correlates the theoretical optimal parameters with the actual parameters, achieving adaptive optimization of the processing process.

[0108] Through the above technical scheme, the present application can dynamically balance the clamping force stability and vibration suppression demand according to the real-time processing state, and realize precise collaborative control of the rotational speed and the feed speed. When the material characteristics of the flange fluctuate or the environmental temperature changes, causing the clamping force demand to change, the system can automatically adjust the processing parameters to avoid vibration marks. When the vibration intensifies suddenly during processing, the collaborative model reduces the feed speed in time through the suppression factor to prevent the surface quality from deteriorating. The present scheme effectively solves the problem of insufficient collaborative precision of the processing parameters of the compound machine tool under complex working conditions, and improves the stability and product qualification rate of the flange processing process.

[0109] Preferably, the depth of cut optimization model is represented as:

[0110]

[0111] wherein a tar represents the target depth of cut, a cur represents the current depth of cut, K W represents the rotational speed-feed collaborative coefficient, P max represents the maximum milling power, P cur represents the current cutting power, τ represents the safety margin ratio (generally taken as 0.2), K vrepresents a chatter evaluation coefficient.

[0112] wherein, the target depth of cut refers to the optimal cutting depth that the milling cutter needs to be adjusted to in one cutting stroke, which can be realized by motor-driven feed shaft displacement sensor feedback closed-loop control, for real-time correction of cutting parameters during machining, the current depth of cut refers to the current actual cutting depth of the milling cutter, which can be collected by displacement sensor or laser ranging device as the initial reference value for model operation, the speed-feed coordination coefficient refers to the matching degree quantization parameter of spindle speed and tool feed speed, which can be dynamically matched by the output power of spindle motor and feed motor through coordination control algorithm, for balancing the machining efficiency and cutting stability. The maximum power of milling refers to the upper limit of instantaneous power allowed by the spindle drive system of the machine tool, which can be set by motor rated power parameter or overload protection threshold, for preventing equipment failure caused by cutting overload. The current cutting power refers to the real-time monitored spindle load power, which can be collected by current sensor or torque sensor as the input parameter for power constraint condition calculation. The safety margin ratio refers to the depth of cut adjustment margin coefficient reserved to prevent chatter, which can be set as a fixed percentage or dynamically adjusted according to material characteristics, for reducing cutting intensity when the risk of chatter increases. The chatter evaluation coefficient refers to the quantization index representing the severity of vibration lines on the machined surface, which can be obtained by vibration spectrum analysis or surface roughness detection data calculation, for triggering the inhibitory adjustment of the depth of cut.

[0113] Specifically, the model takes the current depth of cut as the reference value, and ensures that the target depth of cut is always within the power carrying range of the machine tool by taking the smaller value between the speed-feed coordination coefficient and the power limit ratio. When the actual cutting power approaches the maximum allowable power, the model automatically reduces the depth of cut by reducing the coordination coefficient ratio, avoiding power overload shutdown. At the same time, the product of the chatter evaluation coefficient and the safety margin ratio is introduced into the model: when the chatter evaluation coefficient exceeds the threshold, the sign function outputs a positive value, triggering the reduction of the depth of cut by the safety margin coefficient; when the chatter is within the controllable range, the sign function outputs a negative value or zero, retaining the depth of cut value after coordination optimization. This double constraint mechanism realizes dynamic balance between cutting efficiency and machining safety by real-time collection of power and vibration data.

[0114] Compared with the prior art, the traditional flange machining relies on manual adjustment of the depth of cut by the operator based on experience, which cannot respond to cutting power fluctuations and sudden chatter problems in real time, and is prone to cause abnormal tool wear or surface quality defects of the workpiece. The present scheme converts power monitoring data and vibration feedback signals into control parameters by establishing a mathematical model, realizes automatic closed-loop adjustment of the depth of cut, actively intervenes in adjustment when the cutting load mutates or the machining stability decreases, and eliminates the machining risks caused by human judgment errors.

[0115] Through the technical scheme, the application effectively solves the problems of power over-limit and insufficient chatter control caused by manual experience adjustment. The cutting depth is dynamically optimized according to real-time power load and vibration data, avoiding equipment downtime or tool damage caused by cutting overload, and the generation of machining surface quality defects is inhibited through the chatter feedback mechanism. The machining continuity and stability are ensured, and the waste rate and maintenance cost are reduced.

[0116] Preferably, the clamping and limiting assembly 8 comprises linear motion members 801 and pressing blocks 802, three linear motion members 801 are uniformly installed in a ring shape on a mounting seat (not marked in the figure), the mounting seat is detachably mounted on the carrier plate C4, the output shaft of the linear motion member 801 is fixedly connected with a pressure sensor embedded in the pressing block 802, and the pressing block 802 is in sliding fit with a limiting sliding groove (not marked in the figure) opened on the carrier plate C4. The purpose of this arrangement is to push the pressing block 802 to move linearly by using the linear motion member 801, and then clamp and limit the flange or tool holder by using the three pressing blocks 802, and the pressure sensor can detect the clamping force of the pressing block 802 in real time.

[0117] Preferably, the driving assembly 6 comprises a lead screw 601 and a motor B (not shown in the figure), the lead screw 601 is rotatably installed on the rack 1, the output shaft of the driving A is fixedly connected with the lead screw 601 which is rotatably installed on the rack 1, and the lead screw 601 is in threaded connection with the carrier plate B3. The purpose of this arrangement is to drive the lead screw 601 to rotate and then drive the carrier plate B3 to move linearly in the vertical direction by using the motor B, so as to adjust the depth of cut for flange milling or drill the flange.

[0118] Preferably, the milling and drilling mechanism 7 comprises a spindle 701, a spindle holder 702 and a motor A 703, the spindle 701 is rotatably installed on the spindle holder 702, the spindle holder 702 is detachably installed on the support frame 704 which is detachably installed on the carrier plate B3, and the motor A 703 is detachably installed on the support frame 704 and its output shaft is in transmission connection with the spindle 701 through a belt wheel pair. The purpose of this arrangement is that the technician can install a milling cutter or a drill bit on the spindle 701, and the motor A 703 drives the spindle 701 to rotate in the vertical direction through the belt wheel pair, thereby driving the milling cutter or the drill bit to rotate in the vertical direction.

[0119] Preferably, the turning mechanism 5 comprises a motor C mounted on the frame 1, a three-jaw chuck and a tailstock, the motor C is detachably mounted on the frame 1 and the output shaft of the motor C is fixedly connected with the three-jaw chuck, the tailstock is in sliding fit with the slide rail A mounted on the frame 1 and can be limited on the frame 1 by a bolt assembly, the purpose of such arrangement is to turn the flange mounted on the three-jaw chuck by the turning tool holder mounted on the carrier plate C4 and provided with a turning tool.

[0120] It is to be noted that the relative terms such as first and second, and the like, are used herein only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between such entities or operations. Moreover, the terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can include other elements not expressly listed or inherent to such process, method, article, or apparatus.

[0121] While the embodiments of the application have been shown and described, it is to be understood that the embodiments can be varied, modified, substituted and otherwise changed without departing from the principles and spirit of the application, the scope of which is to be determined only by the claims and their equivalents.

Claims

1. A turning-milling-drilling combined machine tool for machining a flange, comprising a machine frame, a carrier plate A, a carrier plate B, a carrier plate C, and a turning mechanism, characterized in that, Also comprising: A clamping limiting assembly detachably mounted on the carrier plate C for clamping and limiting the flange; A driving assembly provided with three groups of identical structures and mounted on the carrier plate A in horizontal and vertical directions of the rack for driving the carrier plate A, the carrier plate B and the carrier plate C to linearly move; A milling and drilling mechanism mounted on the carrier plate B for milling and drilling the flange; A milling machining cutting depth optimization system for optimizing and adjusting the cutting depth of the flange subjected to milling machining, comprising: A data acquisition module for acquiring flange basic information, milling machining basic information and flange state information; A clamping force optimization module for constructing a clamping force evaluation model by the flange basic information and the flange temperature information to output a clamping force evaluation factor, and acquiring a target clamping force according to the clamping force evaluation factor and the current clamping force; A machining state analysis module for constructing a vibration mark evaluation model by the flange state information to output a vibration mark evaluation coefficient and compare it with a vibration mark coefficient threshold to determine whether the machining is qualified; A rotational speed-feeding speed analysis module for constructing a rotational speed-feeding speed coordination model based on the target clamping force and the rotational speed and the feeding speed under the vibration mark evaluation coefficient to output a rotational speed-feeding speed coordination coefficient; A cutting depth analysis module for constructing a cutting depth optimization model by the current cutting depth and the rotational speed-feeding speed coordination coefficient to output a target cutting depth and adjust the current cutting depth to the target cutting depth.

2. The machining flange turn-mill-finish combined machine tool according to claim 1, characterized in that, The cutting depth optimization model is expressed as: wherein, a tar represents the target depth of cut, a cur represents the current depth of cut, K W represents the speed-feed synergy coefficient, P max represents the maximum power of milling, P cur represents the current cutting power of milling, τ represents the safety margin ratio, K v represents the vibration mark evaluation coefficient.

3. The machining flange turn-mill-finish combined machine tool according to claim 2, characterized in that, The working steps of the rotational speed-feeding speed analysis module are: Processing the absolute value of the difference between the target clamping force and the current clamping force by the target clamping force to obtain a clamping force adaptation factor; Processing the vibration mark evaluation coefficient by the average value of the upper limit value and the lower limit value of the vibration mark evaluation coefficient threshold to obtain a vibration mark suppression factor; Introducing the clamping force adaptation factor, the current spindle rotational speed, the current feeding speed and the vibration mark suppression factor into the constructed rotational speed-feeding speed coordination model to output the rotational speed-feeding speed coordination coefficient; The rotational speed-feeding speed coordination model is expressed as: where K W represents the speed-feed synergy coefficient, F opt represents the theoretical optimal spindle speed, N opt represents the theoretical optimal feed speed, N cur represents the current spindle speed, F cur represents the current feed speed, K ind represents the vibration signature suppression factor, F ind represents the clamping force adaptation factor.

4. The machining flange hybrid machine tool according to claim 1 or 3, characterized in that, The flange basic information includes the material yield strength at the current temperature, the flange material thermal expansion coefficient and the current flange temperature, the flange state information includes the machining surface roughness and the vibration frequency during machining, and the milling machining basic information includes the spindle rotational speed, the feeding speed and the current cutting depth.

5. The machining flange turn-mill-finish combined machine tool according to claim 4, characterized in that, The working steps of the clamping force optimization module are: Introducing the material yield strength at the current temperature, the flange material thermal expansion coefficient and the current flange temperature into the constructed clamping force evaluation model to output the clamping force evaluation factor, and introducing the clamping force evaluation factor and the current clamping force into the constructed clamping force optimization model to output the target clamping force; The clamping force evaluation model is expressed as: where K F represents a clamping force evaluation factor, σ y (T) represents the yield strength of the material at the current temperature, σ y (T0) represents the yield strength of the material at the reference temperature, α represents the thermal expansion coefficient of the flange material, and ΔT represents the temperature change amount and ΔT = T - T0; The clamping force optimization model is expressed as: where F tar represents a target clamping force, K F represents a clamping force evaluation factor, F cur represents a current clamping force, β represents a roughness compensation coefficient, R a represents a clamping surface roughness, R a0 represents a reference roughness.

6. The machining flange turn-mill-finish combined machine tool according to claim 4, characterized in that, The working steps of the machining state analysis module are: Processing the machining surface roughness by the critical roughness to obtain a roughness index, and processing the vibration frequency during machining by the inherent frequency of the process system to obtain a vibration frequency index; Introducing the roughness index and the vibration frequency index into the vibration mark evaluation model to output the vibration mark evaluation coefficient; The acquired tremor evaluation coefficient is compared with a preset tremor evaluation coefficient threshold value, and if the tremor evaluation coefficient is not within the tremor evaluation coefficient threshold value, it indicates that the processing is unqualified this time; The tremor evaluation model is expressed as: K v = R ind exp(μf ind ) where K v represents a vibration pattern evaluation coefficient, R ind represents a roughness index, μ represents a frequency sensitivity coefficient, f ind represents a vibration frequency index.

7. The machining flange turn-mill-finish combined machine tool according to claim 1, characterized by, The clamping and limiting assembly comprises linear motion members and a pressing block. Three linear motion members are uniformly arranged in a ring shape on a mounting seat, which is detachably mounted on the bearing plate C. The output shaft of the linear motion member is fixedly connected with a pressure sensor embedded in the pressing block. The pressing block is in sliding fit with a limiting sliding groove formed on the bearing plate C.

8. The machining flange turn-mill-finish combined machine tool according to claim 1, characterized by, The driving assembly comprises a lead screw and a motor B. The lead screw is rotatably mounted on the rack. The output shaft of the driving A detachably mounted on the rack is fixedly connected with the lead screw. The lead screw is in screw connection with the bearing plate B.

9. The machining flange turn-mill-finish combined machine tool according to claim 1, characterized by, The milling and drilling mechanism comprises a main shaft, a main shaft seat and a motor A. The main shaft is rotatably mounted on the main shaft seat. The main shaft seat is detachably mounted on the support frame detachably mounted on the bearing plate B. The motor A is detachably mounted on the support frame and its output shaft is in transmission connection with the main shaft through a belt wheel pair.

10. The machining flange turn-mill-finish combined machine tool according to claim 1, characterized by, The turning mechanism comprises a motor C, a three-jaw chuck and a tailstock mounted on the rack. The motor C is detachably mounted on the rack and its output shaft is fixedly connected with the three-jaw chuck. The tailstock is in sliding fit with the slide rail A mounted on the rack and can be limited on the rack through a bolt assembly.

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