Accurate rotating speed control and double-threshold wear self-diagnosis method for oil motor of injection molding machine

Abstract

The invention relates to the technical field of injection molding equipment intelligent control and hydraulic system health management, in particular to an injection molding machine oil motor accurate rotating speed control and double-threshold wear self-diagnosis method. According to the invention, a control system based on multi-dimensional signal acquisition of a human-computer interaction interface, magnetic induction feedback, pressure and temperature sensing and the like is constructed, so that real-time sensing, dynamic compensation and self-diagnosis management of the running state of the oil motor are realized. According to the method, the steady state condition can be judged according to the multi-source feedback signal under the complex working condition, the high-frequency closed-loop compensation strategy is executed after the steady state is met, and high-precision maintenance and response correction of the target rotating speed are achieved through the dual-joint control algorithm. Meanwhile, the system calculates the volumetric efficiency according to operation data and flow characteristics of the oil motor and automatically completes a dual-threshold wear diagnosis algorithm and a maintenance decision, so that intelligent closed-loop management of equipment from operation control to health assessment is realized.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of intelligent control of injection molding equipment and health management of hydraulic systems, and particularly relates to a precise rotational speed control and double-threshold wear self-diagnosis method for an oil motor of an injection molding machine. BACKGROUND

[0002] With the development of injection molding equipment towards high precision, high response and high reliability, the control performance of the hydraulic drive system of the injection molding machine has become a key factor affecting the molding quality and energy efficiency level of the whole machine. The traditional injection molding machine generally uses proportional valves or servo valves to control the hydraulic flow, and the rotational speed of the oil motor is adjusted through simple open-loop control or low-frequency feedback. However, in actual production process, the injection cycle changes frequently, the load disturbance is significant, and the oil temperature fluctuates greatly, so that the rotational speed control of the oil motor is difficult to maintain in the ideal steady state interval, and overshoot, fluctuation and response lag phenomena are easy to occur, resulting in increased energy consumption of the plasticizing section and decreased product size stability. In addition, after long-time operation of the hydraulic system, problems such as oil pollution, seal aging and wear of friction pairs will cause the volumetric efficiency of the oil motor to decrease, and the flow and rotational speed characteristics to deviate, and if there is no effective state monitoring mechanism, maintenance can only be carried out by experience or regular maintenance, which not only increases the maintenance cost, but also may cause serious shutdown accidents when the hidden faults of the equipment are not discovered in time.

[0003] At present, the improvement of the oil motor control in the industry mainly focuses on improving the sampling frequency of the controller and optimizing the PID parameter setting, but due to the lack of comprehensive utilization of multi-dimensional feedback signals of the system, this kind of method still has the problem of insufficient adaptability under complex working conditions. At the same time, the research on the health status evaluation of the oil motor still stays in the offline detection stage, such as judging the wear degree through laboratory disassembly analysis or regular oil sampling detection, which is difficult to realize real-time diagnosis and adaptive protection in the running process. Under the background of the rapid development of intelligent manufacturing and industrial Internet of Things, the traditional control method of the injection molding machine cannot meet the dual needs of high-precision molding and intelligent maintenance.

[0004] In addition, with the intensification of the trend of large-scale and multi-cavity of the injection molding machine, the mechanical load borne by the oil motor is heavier, and small rotational speed fluctuations or wear changes of the oil motor may have an amplification effect on the mold opening and closing, screw plasticizing and injection precision. If there is no precise rotational speed closed-loop regulation and wear determination mechanism, it is easy to cause the decrease of the repeated precision of products and even mechanical failure. The traditional control system often cannot distinguish between the transient deviation caused by working condition disturbance and the performance degradation caused by wear due to the failure to fully integrate multi-dimensional signals such as temperature, pressure and rotational speed, so that there is great uncertainty in fault warning and maintenance timing. SUMMARY

[0005] One purpose of the present application is to solve the problems of insufficient speed control accuracy, response lag and difficulty in realizing online wear state diagnosis of existing injection molding machine oil motor during operation, and to propose a comprehensive method that can realize precise speed control and double-threshold wear self-diagnosis, thereby improving the intelligent level and operation reliability of the injection molding equipment.

[0006] To achieve the above purpose, the first aspect of the present application provides an injection molding machine oil motor precise speed control and double-threshold wear self-diagnosis method, comprising the following steps: S1: configuring parameters through a human-computer interaction interface; S2: collecting multi-dimensional data and feeding back to the control system and preprocessing the multi-dimensional data; S3: the control system judges whether the steady-state condition is met based on the collected multi-dimensional data: If yes, start high-frequency closed-loop compensation; If not, feed back to the control system and repeat step S2; S4: After completing the high-frequency closed-loop compensation, the control system reads the multi-dimensional data to judge whether the wear self-diagnosis condition is met: If yes, start double-threshold wear self-diagnosis algorithm and judge whether the wear protection threshold is met; If not, continue high-frequency closed-loop compensation until the wear self-diagnosis condition is met.

[0007] Further, in the above S1 step, the parameters include oil motor basic parameters, target speed n target , PID control parameters and wear protection threshold.

[0008] Further, the oil motor basic parameters include oil motor convex tooth number a and oil motor displacement V, and the unit of the oil motor displacement V is L / r.

[0009] Further, the PID control parameters include proportional gain Kp, integral time Ti and derivative time Td, and the units of the integral time Ti and the derivative time Td are both s; the proportional gain Kp=2.5, the integral time Ti=0.1, and the derivative time Td=0.01.

[0010] Further, the wear protection threshold includes maintenance threshold η v1 and replacement threshold η v2 ; the maintenance threshold η v1 ranges from 80% to 85%, and the replacement threshold η v2 ranges from 70% to 75%.

[0011] Further, in the step S2, the multi-dimension data includes pulse signal f from the magnetic induction head, oil temperature signal from the oil temperature sensor and pressure signal of the hydraulic system from the pressure sensor.

[0012] Further, in the step S2, the pre-processing procedure is filtering the multi-dimension data and storing.

[0013] Further, the step S3 is implemented as follows: S301: reading pulse signal f from the magnetic induction head; S302: calculating the oil motor speed fluctuation in the last 3 control cycles respectively; S303: judging whether the steady state condition is met according to the obtained oil motor speed fluctuation and pulse signal f: If yes, high frequency closed loop compensation is started; If no, feedback signal to the control system and repeat step S2.

[0014] Further, the calculation of the oil motor speed fluctuation is as follows: The control system calculates the actual speed in 3 control cycles respectively and calculates the average value according to the pulse signal f; The maximum and minimum values are selected from the calculated actual speed in the last 3 control cycles and the difference between the maximum and minimum values and the average value is calculated to obtain the maximum deviation and minimum deviation; The oil motor speed fluctuation is the difference between the maximum deviation and minimum deviation.

[0015] Further, the steady state condition is that the oil motor speed fluctuation in any 3 consecutive control cycles in the current running stage of the oil motor is ≤±0.5% and there is no continuous jitter, and / or pulse loss, and / or frequency mutation in the pulse signal.

[0016] Further, the implementation process of the high frequency closed loop compensation is as follows: The control system collects pulse signal f from the magnetic induction head and calculates the actual speed n actual in r / min according to formula ①: ①, where a is the number of oil motor convex gear; The control system calculates the speed deviation ∣δ∣ according to the actual speed n actual and target speed n target and formula ②: ②; The control system calculates the actual demand flow Q according to the obtained speed deviation ∣δ∣ and formula ③: ③; The control system calculates the compensated output flow rate Q(t) using a dual joint algorithm based on the speed deviation |δ| and the actual required flow rate Q, where t represents time; The control system converts the compensated output flow rate Q(t) into the inverter's target frequency specified f. set The output is sent to the vector frequency converter, which then adjusts the oil motor to increase its speed from the initial speed to the target speed.

[0017] Furthermore, the control system acquires the pulse signal f from the magnetic induction head by sampling in 16ms cycles.

[0018] Furthermore, the dual joint algorithm comprises a PID control algorithm and a feedforward control algorithm.

[0019] Furthermore, the specific implementation process of the dual joint algorithm for calculating the compensated output flow rate Q(t) is as follows: First, the feedforward control algorithm is calculated to obtain the feedforward compensation amount u. ff (t); Then, the PID control algorithm is calculated to obtain the PID output u. PID (t); Combined with PID output u PID (t) and feedforward compensation u ff Thus, the total control quantity u(t) is obtained; The control system converts the total control quantity u(t) into the corresponding compensated output flow rate Q(t) based on formula ③.

[0020] Furthermore, the specific calculation process of the PID control algorithm is as follows: The control system performs proportional, integral, and derivative operations sequentially on the real-time speed deviation e(t) to obtain the PID output u. PID Formula ④ (t): ④, where e(t)=n target -n actual ; Substituting the PID control parameters into formula ④ yields formula ⑤: ⑤.

[0021] Furthermore, the specific operation process of the feedforward control algorithm is as follows: The control system reads the actual speed n of the hydraulic motor in the previous operating phase. actual Reaching the target rotational speed n target And the pulse signal f and actual flow rate Q within any 10 consecutive control cycles after stable operation actual And the historical average speed deviation |δ| was calculated.his wherein the initial historical speed deviation mean value |δ| his is 0, the actual flow Q actual is calculated according to the compensated output flow Q(t); based on the historical speed deviation mean value |δ| his is substituted into formula ⑥, i.e. the feedforward compensation amount u ff (t) is obtained: ⑥; wherein K ff is a feedforward gain coefficient, the value of which is fixed as 1.

[0022] Further, the calculation process of the historical speed deviation mean value |δ| his is as follows: The control system reads the pulse signal f and the corresponding actual flow Q actual of the oil motor in 10 continuous control periods in the last running stage of the oil motor, respectively, and converts the pulse signal f into the actual speed n actual in the corresponding control period according to formula ①; The corresponding actual speed n actual , actual flow Q actual and oil motor displacement V in 10 periods are substituted into formula , i.e. the historical speed deviation |δ| in 10 periods is obtained respectively: ; The historical speed deviation |δ| in 10 periods obtained is averaged, i.e. the historical speed deviation mean value |δ| his is obtained. his

[0023] Further, the feedforward gain coefficient K ff is set according to the wear characteristics of the oil motor and the hydraulic system, for compensating the speed deviation caused by the wear and leakage of the oil motor in advance.

[0024] Further, the calculation formula of the total control amount u(t) is as follows: ⑦; The obtained feedforward compensation amount u ff (t) and PID output amount u PID (t) are substituted into formula ⑦, i.e. formula ⑧ is obtained: ⑧.

[0025] Further, the calculation formula of the compensated output flow Q(t) is as follows: ⑨. ​

[0026] Further, the change of the oil motor from the initial speed to the target speed is linearly increased within 5 control cycles to achieve smooth compensation.

[0027] Further, in the S4 step, the specific implementation process of the double-threshold wear self-diagnosis algorithm is as follows: The control system reads the actual speed n actual , the actual flow Q actual , the displacement V of the oil motor and the speed deviation ∣δ∣, and substitutes them into formula (10) to obtain the volumetric efficiency η v of the oil motor: (10); Wherein, Q actual is the actual flow output by the oil pump in the current control cycle; The control system continuously records the volumetric efficiency in ten control cycles and calculates the average value of the volumetric efficiency η v , and judges whether the wear protection threshold is met: If met, output the running data through the man-machine interaction interface; If not met, continue to perform high-frequency closed-loop compensation.

[0028] Further, the specific judgment process of the average value of the volumetric efficiency η v and the wear protection threshold is as follows: Compare the average value of the volumetric efficiency η v with the preset maintenance threshold η v1 and the replacement threshold η v2 : When η v1 ≥ the average value of the volumetric efficiency η v > η v2 , the system enters the maintenance warning state; When the average value of the volumetric efficiency η v ≤ η v2 , the system enters the lock protection state.

[0029] Further, the wear self-diagnosis condition is as follows: When the oil temperature is greater than 60°C or the pressure fluctuation is greater than ±0.2MPa in the current running stage of the oil motor for 10 consecutive control cycles, and the oil temperature difference is less than or equal to 8°C and the pressure difference fluctuation rate is less than or equal to 1MPa / s, the wear self-diagnosis condition is suspended and the working condition is restored to prevent false triggering of the wear condition.

[0030] Further, when the injection molding machine is in the maintenance warning mode, the specific working process is as follows: The control system outputs an intermittent alarm signal to the audible and visual alarm. The human-machine interface displays "maintenance prompt" information, and automatically generates a "wear analysis report"; the report includes a volumetric efficiency curve, a differential pressure fluctuation record, and a recommended maintenance time.

[0031] Further, when the injection molding machine is in the lock protection mode, the specific working process is as follows: The controller executes the lock instruction to prohibit the oil motor from starting; The human-machine interface displays a "system lock, please replace the oil motor" prompt.

[0032] The application also provides an injection molding machine oil motor precise speed control and double threshold wear self-diagnosis system, which applies the injection molding machine oil motor precise speed control and double threshold wear self-diagnosis method, and comprises: A magnetic induction head is installed at an axial position of the oil motor, used for detecting a pulse signal generated by the rotation of the oil motor and outputting to the control system; A pressure sensor is installed on the main oil circuit, used for detecting a system differential pressure signal; An oil temperature sensor is an oil temperature sensor provided by the injection molding machine, used for detecting a hydraulic oil temperature signal; A control system is provided with a high-speed counting module and a control algorithm module, used for collecting the magnetic induction head, pressure sensor and oil temperature sensor signals and executing an algorithm; A vector frequency converter is connected with the control system through RS485 communication, used for adjusting the speed of the oil pump motor according to the target frequency instruction output by the control system, so as to realize precise speed control of the oil motor; A touch screen is connected with the control system, used for parameter setting, real-time data display and alarm prompt; An audible and visual alarm is used for sending an alarm signal when maintenance warning or system lock is triggered.

[0033] The application embodiment has the following technical effects: (1) The application realizes real-time sensing and high-precision control of the operating state of the oil motor by establishing a multi-dimensional data acquisition system with magnetic induction head pulse signal, oil temperature and pressure signal as the core. The system introduces continuous three-cycle speed fluctuation calculation and pulse signal stability judgment mechanism in the process of judging steady state condition, effectively eliminates the misjudgment caused by transient disturbance or external noise, and ensures the accurate and reliable starting time of high-frequency closed-loop compensation. The traditional injection molding machine oil motor control mode generally uses single PID algorithm for speed regulation, which is limited by sampling frequency and feedback lag, and its response ability to fast load disturbance is limited, which is prone to over-compensation, under-compensation and system oscillation. The application combines PID control and feedforward control through double joint algorithm, so that the control system can maintain steady state accuracy while having forward-looking prediction characteristics, compensating for speed deviation caused by oil motor wear and leakage in advance, and correcting the response lag caused by viscosity change or pressure fluctuation in advance, so as to realize faster control response and smoother speed transition. This design significantly reduces the speed fluctuation rate of the oil motor, so that the system can maintain stable operation under complex load changes and ensure the speed accuracy and torque consistency of the plasticizing section during the injection molding process. In addition, through 16ms high-frequency sampling and multi-cycle average algorithm, the system can dynamically adjust the output flow after compensation, realize continuous linear acceleration and flexible adjustment, and avoid the mechanical impact caused by traditional step control. After the scheme is processed, the steady-state fluctuation control of the oil motor is within ±0.5%, the control response time is significantly shortened, and the driving efficiency and energy utilization rate are significantly improved, so as to realize high-precision, low-energy consumption and high-reliable operation of the hydraulic drive part of the injection molding machine.

[0034] (2) The double joint control algorithm proposed in the application is based on PID control and introduces feedforward compensation mechanism, which realizes the transformation from traditional passive adjustment to active predictive control through the cooperative calculation of speed deviation |δ| and historical deviation average |δ| his . PID (t) and feedforward compensation amount u ff(t), and is synthesized into total control quantity u(t) according to formula 7, and then high-precision solution of the output flow Q(t) after dynamic compensation is realized. The introduction of feedforward control enables the system to correct the oil motor flow instruction in advance according to the historical trend before the obvious deviation occurs, greatly improving the response speed and anti-disturbance ability. Compared with the system that simply relies on the PID algorithm, the algorithm proposed in the application can still maintain the output stable under complex conditions such as load mutation, oil viscosity change and system pressure difference fluctuation, and the speed deviation recovery time is shortened from 1.5s of the traditional control mode to less than 0.4s, effectively avoiding the system oscillation caused by control lag. In addition, the algorithm uses the optimal matching of proportional gain Kp, integral time Ti and differential time Td, and takes into account the system rapidity and stability, so that the control curve has good damping characteristics in the transition section, thereby avoiding the overshoot problem caused by too fast response. Through the high-precision cooperation of the controller and the frequency converter, the application realizes the linear acceleration compensation process of the oil motor, so that the flow regulation and the speed change are strictly synchronized, greatly improving the smoothness and mechanical life of the system. Overall, the introduction of the double joint algorithm not only improves the real-time control accuracy and response speed of the oil motor, but also provides a self-adaptive dynamic optimization mechanism for the hydraulic system, which has obvious engineering popularization value.

[0035] (3) In the long-term running of the injection molding equipment, the wear of the oil motor is often the main reason for performance degradation and fault shutdown. The traditional wear detection mostly relies on manual inspection or shutdown detection method, which cannot realize real-time monitoring and early warning. The application introduces a double threshold wear self-diagnosis algorithm in the control system, which reads the actual speed n actual , actual flow Q actual and displacement V of the oil motor in real time his , and calculates the volumetric efficiency η v combined with the historical speed deviation ∣δ∣ v , so as to evaluate the internal wear state of the oil motor online. This method can effectively eliminate the judgment error caused by single fluctuation through the analysis of the average value of volumetric efficiency of ten continuous sampling periods, and realize high-credibility wear identification. When the average value of volumetric efficiency η vWhen the average value is lower than the replacement threshold, the system automatically executes the locking instruction to prevent the equipment from continuing to run in a serious wear state. Through this self-diagnosis and protection mechanism, the equipment can be maintained or replaced in advance before a significant performance decline occurs, avoiding production interruptions caused by sudden failures. At the same time, the system can also determine whether the stable working condition for wear diagnosis is met according to the oil temperature, pressure difference, and temperature difference, thereby preventing false judgments caused by external disturbances. This scheme realizes the transition from traditional "after-maintenance" to "predictive maintenance", significantly improving the running safety, maintenance economy, and production continuity of the injection molding machine. BRIEF DESCRIPTION OF DRAWINGS

[0036] The accompanying drawings, which are part of the specification, serve to further understand the present application, and the illustrative embodiments of the present application and their descriptions serve to explain the present application but do not constitute an improper limitation on the present application. Obviously, the drawings described below are only some embodiments, and other drawings can be obtained from these drawings by those of ordinary skill in the art without creating labor. In the drawings: Figure 1 A flowchart of an injection molding machine oil motor precise speed control and double-threshold wear self-diagnosis method of the present application. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. The following embodiments are used to illustrate the present application but not to limit the scope of the present application.

[0038] In the description of the present application, it should be noted that the terms "upper", "lower", "front", "rear", "left", "right", "vertical", "inner", "outer" and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation on the present application.

[0039] In the description of the present application, it should be noted that unless otherwise explicitly specified and limited, the terms "mounting", "connecting", "connection" should be understood broadly, for example, it can be fixed connection, or detachable connection, or integrally connected; it can be mechanical connection, or electrical connection; it can be directly connected, or indirectly connected through an intermediate medium. For those of ordinary skill in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0040] Those skilled in the art will understand that the embodiments described below are only a part of the embodiments of the present application, and are not the whole embodiments of the present application, and the part of the embodiments are intended to explain the technical principles of the present application, and are not intended to limit the protection scope of the present application. Based on the embodiments provided in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor shall fall within the protection scope of the present application.

[0041] The conventional hydraulic drive system of an injection molding machine adopts a proportional valve or a servo valve for flow control, and is limited by the sampling frequency and feedback delay of the controller, and the control mode is often low-frequency closed loop or approximate open loop structure, and the self-adaptive ability to oil temperature change, load disturbance and viscosity fluctuation is extremely limited, so that the oil motor speed is prone to fluctuation and overshoot in actual operation, affecting the product consistency and energy efficiency level. The present application achieves comprehensive optimization beyond the prior art in control logic, algorithm design and system safety through deep integration of multi-dimensional data acquisition and intelligent control strategy.

[0042] Firstly, in terms of dynamic control accuracy and response speed, the present application realizes high-resolution real-time acquisition of the actual working condition of the oil motor by comprehensively preprocessing the pulse signal output by the magnetic induction head, the oil temperature sensor and the pressure sensor signal. The control system constructs a steady state recognition mechanism through the speed fluctuation calculation and pulse signal stability determination of three consecutive control periods, so that the starting time of closed loop compensation is more accurate. Compared with the traditional control method relying on a single speed feedback signal, this method can effectively avoid false control triggering caused by transient disturbance, thereby significantly improving the system operation stability. When the system enters the steady state, a double joint control algorithm is used for high-frequency closed loop adjustment, organically combining the steady state performance of the PID algorithm and the fast response characteristics of the feedforward algorithm, realizing the control mode change from passive correction to active prediction. Especially in the case of rapid load fluctuation or rapid change of oil temperature, the feedforward compensation can calculate the correction amount in advance according to the historical deviation trend, and correct the response delay caused by hydraulic inertia or flow lag in advance, so that the system can complete the pre-adjustment before the disturbance fully appears. The speed recovery time of the method of the present application is shortened by more than 60% compared with the traditional PID control, the steady state error is controlled within ±0.5%, and the dynamic response ability and anti-interference performance of the control system are significantly improved, which provides a key technical guarantee for the stable plasticization of the injection molding machine under complex working conditions.

[0043] Secondly, in terms of system energy efficiency and mechanical reliability, the application realizes smooth transition and low impact operation by optimizing the flow compensation process and control period. Traditional control methods mostly use step or sudden flow adjustment, which causes obvious mechanical impact and pressure fluctuation during speed change. Long-term operation will cause accelerated wear of seals and bearing fatigue, shortening the service life of components. The application adopts a linear incremental flow adjustment strategy to smoothly complete the transition from the initial speed to the compensation speed in 5 control periods, greatly reducing mechanical impact and hydraulic oscillation, reducing system noise and energy loss. At the same time, through real-time calculation and adjustment of the relationship between flow and speed by the control system, the hydraulic drive energy utilization rate is improved by about 15%, and the oil pump load fluctuation is reduced by more than 20%, fundamentally improving the energy efficiency and operation stability of the injection molding machine hydraulic system. In addition, the signal filtering mechanism using high-frequency sampling and multi-cycle average algorithm can effectively weaken the abnormal reading fluctuation caused by sensor noise or electromagnetic interference, making the control signal more accurate, thereby ensuring the stable execution of the compensation command. This scheme not only improves the energy use structure, but also prolongs the service life of the oil motor and pump valve system at the mechanical level, achieving double improvement of energy saving and reliability.

[0044] Thirdly, in terms of equipment health management and wear warning, the application introduces a double-threshold wear self-diagnosis mechanism, breaking through the limitations of traditional hydraulic equipment relying on manual inspection and shutdown detection. By calculating the volumetric efficiency η v of the oil motor, the system can grade and dynamically manage the wear degree. This diagnosis mechanism is based on multi-cycle average algorithm and real-time data fusion, and comprehensively analyzes parameters such as speed deviation |δ|, oil temperature, flow Q actual and displacement V, to accurately assess the trend of volumetric efficiency. When the average value of volumetric efficiency drops below 85%, the system automatically triggers a maintenance prompt and generates a wear analysis report, which includes the volumetric efficiency curve and pressure difference fluctuation record to help operators make scientific decisions. When the average value of volumetric efficiency drops below 75%, the system automatically enters a lock protection mode to prevent the equipment from running in a severely worn state, avoiding potential hydraulic failure and safety risks. This self-diagnosis method realizes real-time visualization and automatic judgment of the wear state of the oil motor, changing equipment maintenance from passive response to active prevention. Compared with existing manual detection relying on experience, the double-threshold wear self-diagnosis accuracy of the application is improved by about 30%, and the maintenance timeliness is improved by about 40%, greatly reducing unplanned downtime and maintenance costs, ensuring the continuity and safety of production.

[0045] The application provides an injection molding machine oil motor precise speed control and double-threshold wear self-diagnosis method, including the following steps: S1: configure parameters through a human-computer interaction interface; S2: Collect multi-dimensional data feedback to the control system and pre-process the multi-dimensional data; S3: The control system judges whether the steady-state condition is met based on the above-mentioned collected multi-dimensional data: If yes, start high-frequency closed-loop compensation; If no, feedback to the control system and repeat step S2; S4: After completing the high-frequency closed-loop compensation, the control system reads the multi-dimensional data to judge whether the wear self-diagnosis condition is met: If yes, start the double-threshold wear self-diagnosis algorithm and judge whether the wear protection threshold is met; If no, continue high-frequency closed-loop compensation until the wear self-diagnosis condition is met.

[0046] Specifically, the overall flow of the precise speed control and double-threshold wear self-diagnosis method of the injection molding machine oil motor provided by the present application is as follows: The operator first completes parameter configuration through a human-machine interface to provide basic settings and control logic basis for the operation of the system; then, the control system collects multi-dimensional operation data including magnetic induction head pulse signal, oil temperature signal and pressure signal and performs filtering and pre-processing to ensure the accuracy of subsequent judgment and control; then, the system calculates the speed fluctuation of multiple control periods in real time based on the data and judges whether the steady-state condition is met, wherein the system takes 16 ms as a control period to determine whether to start high-frequency closed-loop compensation; high-frequency closed-loop compensation is a logic that is executed in a loop, and after each execution of high-frequency closed-loop compensation, the control system reads the multi-dimensional data to judge whether the wear self-diagnosis condition is met; if yes, the control system automatically enters the double-threshold wear self-diagnosis algorithm, calculates the average value of the volume efficiency and judges whether the wear protection threshold is met to realize the health status evaluation and maintenance determination of the oil motor; if yes, the human-machine interface displays the data of the system in real time at this time to form a complete control closed loop and health management system. If no, continue to execute high-frequency closed-loop compensation and double-threshold wear self-diagnosis in a loop.

[0047] Specifically, in step S1, the basic parameters of the oil motor control system are configured through a human-machine interface, which is a preparation link for the operation of the entire system. The operator first inputs the basic structural parameters of the oil motor in the main interface, including the number of oil motor teeth a and the displacement V, the displacement unit is L / r, which is used to determine the corresponding relationship between the magnetic induction head pulse signal and the speed calculation. Then, the control target parameters, i.e. the target speed n target, which represents the stable running speed of the oil motor in the injection molding process, is the core parameter of the system control algorithm. At the same time, the system also needs to configure PID control parameters, including proportional gain Kp, integral time Ti and derivative time Td, whose initial values are Kp = 2.5, Ti = 0.1 s and Td = 0.01 s, to ensure that the controller has the ability of fast response and stable regulation. In addition, the wear protection threshold in the system also needs to be entered, including maintenance threshold η v1 and replacement threshold η v2 , the former is set in the range of 80%-85%, and the latter is set in the range of 70%-75%. The threshold is directly related to the judgment standard of the system entering the warning or locking state. After all the parameters are entered, the control system saves the parameters in the storage area to ensure that the set data can be retained after power failure. At this time, the human-computer interface displays the real-time state and prompts "parameter configuration completed". At this time, the control system enters the standby state and waits for data signal acquisition. The completion of this step not only establishes the boundary conditions for algorithm running, but also provides quantitative control targets and safety protection logic for the system.

[0048] Specifically, in the above S2 step, the control system starts to collect and preprocess multi-dimensional data of the oil motor running state.

[0049] Specifically, the sensor network in the system is composed of a magnetic induction head, an oil temperature sensor and a pressure sensor, which are installed at the shaft end of the oil motor, the hydraulic circuit and the inlet and outlet positions of the oil circuit, respectively.

[0050] Specifically, the pulse signal f output by the magnetic induction head represents the rotation state of the oil motor, which is the main basis for calculating the actual speed n actual . The oil temperature signal is used to reflect the change of viscosity characteristics of the hydraulic system, and the pressure signal output by the pressure sensor reflects the load fluctuation and hydraulic state.

[0051] Specifically, the control system is embedded with a high-speed counting module, so that the pulse signal output by the magnetic induction head is read at high speed every 16 ms. The control system takes 16 ms as the sampling period, and converts the analog signal into a digital signal through an A / D conversion module. Traditional injection molding machines usually have a sampling period of 50-100 ms. Because of the low sampling frequency, the system cannot capture the instantaneous speed change of the oil motor under dynamic working conditions in time, resulting in coexistence of response lag, overshoot and undershoot. Therefore, the present application takes 16 ms as the high-frequency sampling period, so that the control system can capture the pulse frequency change of the oil motor speed in real time with millisecond-level precision, quickly complete the actual speed calculation and deviation judgment, and thus shorten the response time of the closed-loop compensation command to within a single control period. This high-frequency sampling not only significantly improves the sensitivity of the system to transient factors such as oil temperature fluctuations, load disturbances and leakage changes, but also effectively suppresses speed fluctuations, ensuring that the steady-state deviation of the oil motor remains within ±0.8%. Through continuous collection and filtering of high-frequency data, the system can realize real-time discrimination of pulse signal jitter, loss and frequency mutation, avoiding false compensation or false alarms caused by noise interference. At the same time, the data density under the 16 ms sampling period provides high-resolution basic data for subsequent double-threshold wear self-diagnosis, making the volumetric efficiency calculation more accurate and the wear judgment more reliable.

[0052] Specifically, in the above S1 step, due to the existence of noise sources such as electromagnetic interference, oil pulsation and mechanical vibration in the industrial field, the original signal needs to be filtered and abnormal value corrected through the preprocessing link. The filtered signal is stored in the data buffer for subsequent judgment and calling. Compared with the traditional single speed collection method, this multi-dimensional collection mode can more comprehensively reflect the real working condition of the oil motor, providing reliable data basis for steady-state judgment and wear diagnosis. After preprocessing, the control system updates the data curve in real time according to the sampling results, and displays the temperature, pressure and speed waveform through the human-machine interface for the operator to observe the system running trend.

[0053] Specifically, in the above S3 step, the specific implementation process is as follows: S301: reading the pulse signal f output from the magnetic induction head.

[0054] S302: calculating the oil motor speed fluctuation in the continuous three control periods respectively.

[0055] Specifically, the control system first collects the pulse signal f output from the magnetic induction head and calculates the actual speed in the continuous three control periods according to formula ① to calculate the average value, then selects the maximum value and the minimum value from the calculated actual speed in the continuous three control periods, and calculates the maximum deviation and the minimum deviation by respectively subtracting the average value from the maximum value and the minimum value, and then calculates the oil motor speed fluctuation by subtracting the maximum deviation from the minimum deviation, and comprehensively judges in combination with the stability of the pulse signal of the magnetic induction head.

[0056] S303: Determine whether the steady-state condition is met according to the obtained oil motor speed fluctuation and pulse signal.

[0057] If yes, start high-frequency closed-loop compensation; If not, feedback the signal to the control system and repeat step S2 after processing.

[0058] Specifically, the steady-state condition is that the oil motor speed fluctuation is less than or equal to ±0.5% in any 3 consecutive control periods in the current operating stage of the oil motor, and there is no pulse loss, jitter or frequency mutation in the pulse signal in the consecutive three periods. The system determines that the current state meets the steady-state condition. If not, feedback the signal to the control system and re-execute the data acquisition and preprocessing process of S2 until the steady-state condition is met. After meeting the condition, the system starts the high-frequency closed-loop compensation process to accurately adjust the oil motor flow through the PID and feedforward control double joint algorithm to realize dynamic tracking of the target speed n target .

[0059] The closed-loop control period of the traditional injection molding machine system is usually between 50ms and 100ms, which means that the system can only perform 10 to 20 control iterations per second, and cannot capture the high-frequency disturbance caused by changes in hydraulic oil temperature, pressure difference and load. The high-frequency closed-loop compensation period of the present application is 16ms, i.e. about 62.5 real-time control operations per second, so that the control system can sample and process the pulse signal fed back by the magnetic induction head in almost continuous time sequence. In this way, when the oil motor is affected by starting inertia, load mutation or oil temperature viscosity fluctuation, the system can calculate the speed deviation and adjust the output flow after compensation within 16ms, significantly shortening the response time and ensuring that the speed change of the oil motor is always highly consistent with the target speed.

[0060] More importantly, high-frequency closed-loop compensation improves the system's anti-disturbance ability. The hydraulic system itself has strong non-linear characteristics, and its performance is easily affected by changes in oil temperature, load fluctuation and leakage. Under high-frequency closed-loop control, the control system can detect and respond to the above disturbances every 16ms, with the fast response of the PID proportional term and the predictive compensation of the feedforward term, the system can complete flow correction before the disturbance accumulates to affect the output, thereby maintaining the smoothness and stability of the system output. Especially in the load mutation stage of melt glue and glue injection in the injection cycle, high-frequency closed-loop compensation makes the oil motor speed curve continuous and smooth, avoiding the common "tooth wave" oscillation problem in traditional control methods.

[0061] Specifically, the specific implementation process of the high-frequency closed-loop compensation is: The control system collects the pulse signal f from the magnetic induction head and calculates the actual speed n actual according to formula ①, unit: r / min: ①, where a is the number of oil motor convex gear teeth.

[0062] Specifically, the control system calculates the real-time rotating speed n actual according to formula ①, where a is the number of oil motor convex gear teeth, and f is the frequency of pulse signal.

[0063] The control system calculates the rotating speed deviation |δ| according to the real-time rotating speed n actual and the target rotating speed n target . ②.

[0064] The control system calculates the actual demand flow according to the obtained rotating speed deviation |δ| by using formula ③: ③. The control system calculates the compensated output flow Q(t) according to the rotating speed deviation and the actual demand flow by using a double joint algorithm. The control system converts the compensated output flow Q(t) into a frequency specification f set target of the frequency converter and outputs it to the vector frequency converter, so as to adjust the oil motor from the initial rotating speed to the compensated rotating speed.

[0065] Specifically, the change of the oil motor from the initial rotating speed to the target rotating speed is linearly increased within 5 control cycles to achieve smooth compensation.

[0066] Specifically, the specific implementation process of the double joint algorithm for calculating the compensated output flow Q(t) is as follows: First, the feedforward control algorithm is operated to obtain the feedforward compensation amount u ff (t). Then, the PID control algorithm is operated to obtain the PID output amount u PID (t). The total control amount u(t) is obtained by combining the PID output amount u PID (t) and the feedforward compensation amount u ff (t). The control system converts the total control amount u(t) into the corresponding compensated output flow Q(t) based on formula ③.

[0067] Specifically, the specific operation process of the PID control algorithm is as follows: The control system performs proportional operation, integral operation and differential operation on the real-time rotating speed deviation e(t) in turn, i.e. the PID output amount u PID (t) formula ④: ④, where e(t)=n target (t) - nactual (t); n target (t) represents the real-time target rotational speed, n actual (t) represents the actual rotational speed in real time; Substituting the PID control parameters into formula ④ yields formula ⑤: ⑤.

[0068] Specifically, the specific operation process of the feedforward control algorithm is as follows: The control system reads the actual speed n of the hydraulic motor in the previous operating phase. actual Reaching the target rotational speed n target And the pulse signal f and actual flow rate Q within any 10 consecutive control cycles after stable operation actual And the historical average speed deviation |δ| was calculated. his The initial historical speed deviation mean |δ| his The actual flow rate Q is 0. actual The output flow rate Q(t) is calculated based on the compensated output flow rate. This is particularly relevant during the initial start-up of the hydraulic motor, i.e., the first start-up, when the historical speed deviation average |δ| is reached. his The lack of data means that the initial value of the hydraulic motor is 0 when it is first started. At this point, due to the absence of feedforward compensation, the motor speed may deviate significantly after startup. However, the PID control algorithm still exists during the first run, and it will adjust the speed to the target speed. Therefore, the actual flow rate Q for the next running stage of the hydraulic motor can be obtained during the initial run of the first hydraulic motor operation. actual and actual rotational speed n actual This allows us to calculate the historical average speed deviation |δ| for the next operating phase. his .

[0069] Based on the historical average speed deviation |δ| his Substituting into formula ⑥, we obtain the feedforward compensation amount u. ff (t): ⑥; Where K ff This is the feedforward gain coefficient, and its value is fixed at 1.

[0070] Specifically, the feedforward gain coefficient is set according to the wear characteristics of the oil motor and the hydraulic system, and is used to compensate in advance for the speed deviation caused by wear and leakage of the oil motor.

[0071] Specifically, the historical average speed deviation |δ| his The calculation process is as follows: The control system reads the pulse signal f and the corresponding actual flow Q in 10 consecutive control cycles in the last running stage of the oil motor actual , and converts the pulse signal f into the actual speed n in the corresponding control cycle according to formula ① actual ; The corresponding actual speed n actual , actual flow Q actual and oil motor displacement V in 10 cycles are substituted into formula , respectively, to obtain the historical speed deviation ∣δ∣ in 10 cycles ; The average value of the historical speed deviation ∣δ∣ in 10 cycles is obtained by averaging the historical speed deviation ∣δ∣ in 10 cycles his , and the average historical speed deviation ∣δ∣ is obtained his .

[0072] Specifically, the calculation formula of the total control amount u(t) is: ⑦; The obtained feedforward compensation amount u ff (t) and PID output amount u PID (t) are substituted into formula ⑦ to obtain formula ⑧: ⑧.

[0073] Specifically, the calculation formula of the compensated output flow Q(t) is: ⑨.

[0074] Specifically, the control system calculates the speed deviation ∣δ∣ according to formula ② and substitutes it into formula ③ to calculate the actual demand flow Q.

[0075] In the precise speed control and wear self-diagnosis system of the oil motor of the injection molding machine, the application adopts a double combined algorithm to calculate the compensated output flow, which significantly improves the control accuracy and stability of the hydraulic system. The core advantage of this algorithm is that it combines two control strategies to deal with various dynamic disturbances and nonlinear behaviors that may occur during the operation of the oil motor, thereby achieving precise control of the speed of the oil motor and optimizing the wear monitoring and protection function.

[0076] PID control algorithm can adjust the output flow after compensation by real-time calculation of speed deviation, and its proportional, integral and derivative elements deal with the instantaneous error, steady-state deviation and the trend of speed change of the system, respectively. This design can effectively eliminate the error of the system in static work, control the speed deviation within a very small range, usually not more than ±0.8%, and ensure the precision requirement in injection molding process, especially for precision injection molded products such as medical and electronic products, which have high requirements for size tolerance and surface quality. Especially in the face of load changes, oil temperature fluctuations and other disturbances, PID control can make the speed of the oil motor almost unaffected by external interference through its strong feedback regulation ability, greatly improving the robustness and stability of the system.

[0077] However, PID control alone still cannot better handle the overshoot when PID is involved, such as load impact and regulation lag in the starting stage. To solve this problem, the present application introduces a feedforward control algorithm to compensate non-overshoot and quickly. Feedforward control predicts the speed deviation at startup by using historical speed deviation data and compensates the system output in advance. Unlike PID control, feedforward control does not rely on feedback information, but rather on historical data to speculate on possible changes at startup, thereby allowing adjustments to be made before problems occur. This design can significantly improve the response speed of the system, especially when dealing with insufficient system output during the startup phase, it can quickly adjust within the control cycle to prevent large fluctuations or overshoot in the speed.

[0078] The application combines PID control and feedforward control through a double joint algorithm, so that the control system can not only quickly respond to dynamic changes, but also maintain precise control in steady state. In practical applications, the algorithm updates the flow compensation command every 16 ms under high-frequency closed-loop control, thereby achieving rapid and accurate adjustment of the speed, avoiding the lag phenomenon caused by the long control period in traditional injection molding motor speed control. This high-frequency update not only improves the accuracy of speed control, but also effectively shortens the response time of the system, making the operation of the oil motor more stable and accurate. In addition, the design of the double joint algorithm also provides more accurate data support for the wear self-diagnosis of the oil motor. By calculating the deviation between the speed and the target speed in real time, combined with the volumetric efficiency of the oil motor, the wear of the oil motor can be detected in time. As the degree of wear of the oil motor increases, the volumetric efficiency of the system will decrease, resulting in insufficient flow or increased speed deviation. Through the double joint algorithm, the control system can dynamically adjust the output flow after compensation to offset the impact of wear, and monitor the wear by setting maintenance and replacement thresholds. Once the volumetric efficiency falls below the set threshold, the system will automatically trigger a warning or lock protection mechanism to prevent the equipment from continuing to operate under inappropriate working conditions, thereby avoiding equipment failure and production interruption caused by excessive wear. This wear monitoring based on volumetric efficiency not only improves the safety of the equipment, but also significantly prolongs the service life of the oil motor.

[0079] Specifically, the control system simultaneously executes PID control and feedforward control algorithms. The PID part corrects the real-time deviation through proportional, integral, and differential terms, and its calculation formula is .

[0080] Specifically, the feedforward control algorithm is based on the pulse signal f and the actual flow Q in any 10 consecutive control periods after the actual speed n actual reaches the target speed n target and stabilizes in the last running stage of the oil motor actual . his Thus, the historical speed deviation average |δ| is calculated ff (t)=K ff* |δ|, where K ff is the feedforward gain coefficient determined according to the viscosity of the oil and the load characteristics. The control system combines the outputs of the two parts according to the formula u(t)=u PID (t)+u ff (t)+1 to form the total control amount, and substitutes it into formula (9) to convert it into the corresponding output flow Q(t) after compensation. Finally, the control system converts this flow into the target frequency f setThe oil motor is driven to adjust the rotating speed. To prevent hydraulic impact caused by rapid change, the system divides the adjustment process of the oil motor from the initial rotating speed to the target rotating speed into linear increments in five control periods, so that the speed change curve is smoothly transitioned.

[0081] Specifically, the process is executed in each 16 ms sampling period, so that the control system always maintains accurate control and adaptive compensation of the rotating speed. Through this control logic, the oil motor can maintain high stable operation under complex load and temperature change conditions, and the control error is maintained within ±0.5% for a long time.

[0082] After completing the steady-state control, the system automatically enters step S4. After completing the high-frequency closed-loop compensation, the control system reads the multi-dimensional data to determine whether the wear self-diagnosis condition is met: If it is met, the double-threshold wear self-diagnosis algorithm is started, and it is determined whether the wear protection threshold is met. If it is not met, the high-frequency closed-loop compensation is continued until the wear self-diagnosis condition is met.

[0083] Specifically, the specific implementation process of the double-threshold wear self-diagnosis algorithm is as follows: The control system reads the actual rotating speed n actual , the actual flow Q actual , the displacement V of the oil motor, and the rotating speed deviation |δ| v , and substitutes them into formula (10) to obtain the volumetric efficiency η actual : (10); wherein Q v is calculated according to the compensated output flow Q(t) in the current control period; The control system continuously records the volumetric efficiency η v in ten control periods, calculates the average value of the volumetric efficiency η v , and determines whether the wear protection threshold is met: If it is met, the operation data is output through the human-computer interaction interface. If it is not met, the high-frequency closed-loop compensation is continued.

[0084] Specifically, the specific determination process of the average value of the volumetric efficiency η v and the wear protection threshold is as follows: The average value of the volumetric efficiency η v1 is compared with the preset maintenance threshold η v2 and the replacement threshold η v1 : When η v average value > η v2When the volumetric efficiency η When the volumetric efficiency η v When the average value of η v2 When the average value of η v The system enters the maintenance warning state.

[0085] In the injection molding machine oil motor precise speed control and wear self-diagnosis system of the present application, the double-threshold wear self-diagnosis algorithm is a major improvement over the traditional hydraulic drive system health monitoring method. The algorithm takes the average value of the volumetric efficiency η v The system enters the maintenance warning state.

[0086] Traditional injection molding machines lack a quantitative wear diagnosis mechanism and usually rely on manual experience inspection to determine whether the oil motor is aging through appearance, noise, or vibration. Since internal leakage, seal aging, and other factors in the hydraulic system often have a slow cumulative nature, manual detection often has delays and subjective errors, which can easily cause overrunning or premature replacement, thereby increasing equipment wear and maintenance costs. The present application converts complex flow changes, speed deviations, and oil motor structural characteristics into a single quantifiable parameter through real-time calculation of the average value of the volumetric efficiency η v The control system collects and calculates the volumetric efficiency every 16 ms, and after ten consecutive sampling periods, the average value is compared with the wear protection threshold, enabling the system to identify wear trends at millisecond precision and accurately warn at the early stage of wear.

[0087] For the present application, the double-threshold design is particularly critical in the wear protection strategy. The maintenance threshold η v1 is used to prompt preventive maintenance in the mild wear stage. When the average value of the volumetric efficiency η v is lower than η v1 and higher than η v2 , the system automatically enters the maintenance warning state, triggers an audible and visual alarm, and displays "maintenance prompt" on the touch screen. It also automatically generates a "wear analysis report" recording the volumetric efficiency change curve, pressure difference fluctuation record, and recommended maintenance time. This mechanism realizes early warning of oil motor wear, avoids deterioration out of control due to continuous operation, and enables operators to plan maintenance when the device performance is still acceptable, thereby minimizing the impact of downtime on production. The replacement threshold η v2 corresponds to the severe wear state. When the average value of the volumetric efficiency η v drops to η v2 , the system enters the lock protection state, automatically prohibits oil motor startup, and prevents leakage expansion, pump body overload, or thermal runaway due to seal failure.

[0088] More importantly, the double-threshold wear self-diagnosis algorithm greatly improves the accuracy of judgment by combining multi-source data cross-validation. Before performing wear judgment, the system automatically detects oil temperature and pressure fluctuation. When the oil temperature exceeds 60°C or the pressure difference fluctuation exceeds ±0.2MPa, the control system automatically suspends wear calculation, and resumes sampling after the working condition is restored to stable. This interference elimination mechanism effectively avoids misjudgment caused by changes in oil viscosity or transient load fluctuations, ensuring that the wear diagnosis result only comes from the real structural wear change.

[0089] Specifically, the core purpose of the double-threshold wear self-diagnosis is to determine the wear degree of the oil motor by calculating the volumetric efficiency η v of the oil motor in real time

[0090] Specifically, in the above S4 step, the control system first determines whether the current wear self-diagnosis condition is met: when the oil temperature is greater than 60°C or the pressure fluctuation exceeds ±0.2MPa for 10 consecutive control periods in the current operating phase of the oil motor, the system does not perform diagnosis to prevent external interference from causing misjudgment; only when the oil temperature difference is ≤8°C and the pressure difference fluctuation rate is ≤1MPa / s, the system enters the diagnosis state.

[0091] Specifically, during the self-diagnosis process, the control system continuously reads the real-time rotational speed n actual , actual flow Q actual , displacement V and rotational speed deviation ∣δ∣, and substitutes them into formula (10) to calculate the volumetric efficiency.

[0092] Specifically, the calculation result is updated every 16ms, and the average value is taken within ten sampling periods to weaken the influence of transient disturbance. According to the comparison of the average value of the volumetric efficiency η v with the preset thresholds η v1 and η v2 , the system automatically determines the wear state.

[0093] Specifically, when η v1 ≥ volumetric efficiency η v average value > η v2 , the system enters the maintenance warning mode; when the average value of the volumetric efficiency η v is less than or equal to η v2 , the system enters the lock protection mode.

[0094] Specifically, in the maintenance warning state, the control system outputs an intermittent alarm signal to the audible and visual alarm, and displays the "maintenance prompt" information on the human-machine interface, and automatically generates a "wear analysis report", which includes the volumetric efficiency change curve, the pressure difference fluctuation record and the recommended maintenance time.

[0095] Specifically, if the system enters the lockout protection mode, the controller immediately executes a lockout command, preventing the hydraulic motor from restarting and displaying a message on the interface: "System locked, please replace the hydraulic motor." This prevents severe wear from causing system failure. Through this self-diagnostic mechanism, the control system can issue early warnings before equipment performance significantly deteriorates, allowing maintenance personnel to scientifically formulate maintenance plans based on the report, thereby avoiding sudden downtime, extending equipment life, and ensuring production stability.

[0096] Specifically, during the entire system operation, the system displays operating data in real time through a human-machine interface. The human-machine interface displays the hydraulic motor operating parameters in both curve and numerical form, including key indicators such as current speed, target speed, speed deviation, oil temperature, pressure, volumetric efficiency, and compensated output flow rate. Operators can observe the system response and control effect in real time.

[0097] This application also provides a precision speed control and dual-threshold wear self-diagnosis system for an injection molding machine oil motor. The system utilizes the aforementioned precision speed control and dual-threshold wear self-diagnosis method for an injection molding machine oil motor, including: A magnetic induction head is installed in the axial position of the oil motor to detect the pulse signal generated by the rotation of the oil motor and output it to the control system; A pressure sensor, installed on the main oil line, is used to detect the system differential pressure signal; Oil temperature sensor, which is the oil temperature sensor built into the injection molding machine, is used to detect the hydraulic oil temperature signal; The control system has a built-in high-speed counting module and a control algorithm module, which are used to acquire signals from the magnetic induction head, pressure sensor and oil temperature sensor and execute the algorithm. The vector frequency converter is connected to the control system via RS485 communication and is used to adjust the speed of the oil pump motor according to the target frequency command output by the control system, so as to achieve precise speed control of the oil motor. The touch screen is connected to the control system and is used for parameter setting, real-time data display, and alarm prompts. Audible and visual alarms are used to issue alarm signals when maintenance warnings are triggered or the system is locked.

[0098] The above merely describes the preferred embodiments of the present application, and is not intended to limit the present application in any form. Although the present application has been disclosed with the preferred embodiments as above, it is not intended to limit the present application, and any person skilled in the art can make some minor changes or modifications to the above-mentioned technical content without departing from the technical solution of the present application, and the equivalent embodiments with equivalent changes can be obtained. The embodiments in the above examples can be further combined or replaced, as long as they do not deviate from the technical solution of the present application. Any simple modification, equivalent change and modification of the above examples according to the technical essence of the present application are still within the scope of the present application.

Claims

1. A method for precise speed control and dual-threshold wear self-diagnosis of an injection molding machine oil motor, characterized in that, Includes the following steps: S1: Configure parameters through the human-computer interaction interface; S2: Collect multi-dimensional data and feed it back to the control system, and preprocess the multi-dimensional data; S3: The control system determines whether the steady-state condition is met based on the multi-dimensional data collected above. If the conditions are met, then high-frequency closed-loop compensation is activated; If the condition is not met, a feedback signal is sent to the control system and step S2 is repeated. S4: After completing the high-frequency closed-loop compensation, the control system reads the multi-dimensional data to determine whether the wear self-diagnosis conditions are met. If satisfied, enable the dual-threshold wear self-diagnosis algorithm and determine whether the wear protection threshold is met. If the conditions are not met, high-frequency closed-loop compensation will continue until the wear self-diagnosis conditions are met.

2. The method for precise speed control and dual-threshold wear self-diagnosis of an injection molding machine oil motor according to claim 1, characterized in that, In step S1 above, the parameters include the basic parameters of the hydraulic motor and the target speed n. target PID control parameters and wear protection thresholds.

3. The method for precise speed control and dual-threshold wear self-diagnosis of an injection molding machine oil motor according to claim 2, characterized in that, The basic parameters of the hydraulic motor include the number of hydraulic motor teeth a and the hydraulic motor displacement V, with the unit of hydraulic motor displacement V being L / r.

4. The method for precise speed control and dual-threshold wear self-diagnosis of an injection molding machine oil motor according to claim 2, characterized in that, The PID control parameters include proportional gain Kp, integral time Ti, and derivative time Td, where the units of integral time Ti and derivative time Td are both seconds. The proportional gain Kp = 2.5, the integral time Ti = 0.1, and the derivative time Td = 0.

01.

5. The method for precise speed control and dual-threshold wear self-diagnosis of an injection molding machine oil motor according to claim 2, characterized in that, The wear protection threshold includes the maintenance threshold and the replacement threshold η. v2 The maintenance threshold η v1 The range is 80% to 85%, and the replacement threshold η v2 The range is 70% to 75%.

6. The method for precise speed control and dual-threshold wear self-diagnosis of an injection molding machine oil motor according to claim 2, characterized in that, In step S2 above, the multi-dimensional data includes the pulse signal f output from the magnetic induction head, the oil temperature signal output from the oil temperature sensor, and the pressure signal of the hydraulic system output from the pressure sensor.

7. The method for precise speed control and dual-threshold wear self-diagnosis of an injection molding machine oil motor according to claim 6, characterized in that, In step S2 above, the preprocessing process involves filtering the multi-dimensional data and then storing it.

8. The method for precise speed control and dual-threshold wear self-diagnosis of an injection molding machine oil motor according to claim 6, characterized in that, The specific implementation process of step S3 is as follows: S301: Read the pulse signal f from the magnetic induction head output; S302: Calculate the speed fluctuation of the hydraulic motor in three consecutive control cycles; S303: Determine whether the steady-state condition is met based on the obtained oil motor speed fluctuation and pulse signal f: If the conditions are met, then high-frequency closed-loop compensation is activated; If the condition is not met, the feedback signal is sent to the control system and step S2 is repeated.

9. The method for precise speed control and dual-threshold wear self-diagnosis of an injection molding machine oil motor according to claim 8, characterized in that, The calculation process for the speed fluctuation of the hydraulic motor is as follows: The control system calculates the actual rotational speed for each of the three control cycles and calculates the average value based on the pulse signal f. The maximum and minimum values ​​are selected from the actual rotational speeds within three consecutive control cycles obtained from the calculation, and the difference between them and the average value is calculated to obtain the maximum and minimum deviations. The fluctuation in the oil motor speed is the difference between the maximum deviation and the minimum deviation.

10. A method for precise speed control and dual-threshold wear self-diagnosis of an injection molding machine oil motor according to claim 8, characterized in that, The steady-state conditions are that the speed fluctuation of the oil motor is ≤ ±0.5% within any 3 consecutive control cycles during the current operating phase of the oil motor, and that the pulse signal has no continuous jitter, and / or pulse loss, and / or frequency mutation.

11. The method for precise speed control and dual-threshold wear self-diagnosis of an injection molding machine oil motor according to claim 8, characterized in that, The specific implementation process of the high-frequency closed-loop compensation is as follows: The control system acquires the pulse signal f from the magnetic induction head and calculates the actual rotational speed n according to formula ①. actual The unit is r / min: ①, where a is the number of cams in the oil motor; The control system based on the actual rotational speed n actual With the target rotational speed n target Substituting into formula ②, we can calculate the speed deviation |δ|: ②； Substituting the obtained speed deviation |δ| into formula ③, the actual required flow rate Q can be calculated: ③； The control system calculates the compensated output flow rate Q(t) using a dual joint algorithm based on the speed deviation |δ| and the actual required flow rate Q, where t represents time; The control system converts the compensated output flow rate Q(t) into the inverter's target frequency specified f. set The output is sent to the vector frequency converter, which then adjusts the oil motor to increase its speed from the initial speed to the target speed.

12. The method for precise speed control and dual-threshold wear self-diagnosis of an injection molding machine oil motor according to claim 11, characterized in that, The control system acquires the pulse signal f from the magnetic induction head in a control cycle of 16ms.

13. The method for precise speed control and dual-threshold wear self-diagnosis of an injection molding machine oil motor according to claim 11, characterized in that, The dual joint algorithm consists of a feedforward control algorithm and a PID control algorithm.

14. The method for precise speed control and dual-threshold wear self-diagnosis of an injection molding machine oil motor according to claim 11, characterized in that, The specific implementation process of the dual joint algorithm for calculating the compensated output flow rate Q(t) is as follows: First, the feedforward control algorithm is calculated to obtain the feedforward compensation amount u. ff (t); Then, the PID control algorithm is calculated to obtain the PID output u. PID (t); Combined with PID output u PID (t) and feedforward compensation u ff Thus, the total control quantity u(t) is obtained; The control system converts the total control quantity u(t) into the corresponding compensated output flow rate Q(t) based on formula ③.

15. The method for precise speed control and dual-threshold wear self-diagnosis of an injection molding machine oil motor according to claim 13, characterized in that, The specific calculation process of the PID control algorithm is as follows: The control system performs proportional, integral, and derivative operations sequentially on the real-time speed deviation e(t) to obtain the PID output u. PID Formula ④ (t): ④, where e(t)=n target (t) -n actual (t), n target (t) represents the real-time target rotational speed, n actual (t) represents the actual rotational speed in real time; Substituting the PID control parameters into formula ④ yields formula ⑤: ⑤。 16. The method for precise speed control and dual-threshold wear self-diagnosis of an injection molding machine oil motor according to claim 14, characterized in that, The specific calculation process of the feedforward control algorithm is as follows: The control system reads the actual speed n of the hydraulic motor in the previous operating phase. actual Reaching the target rotational speed n target And the pulse signal f and actual flow rate Q within any 10 consecutive control cycles after stable operation actual And the historical average speed deviation |δ| was calculated. his The average historical speed deviation during the initial operation phase |δ| his The actual flow rate Q is 0. actual It is calculated based on the compensated output flow rate Q(t); Based on the historical average speed deviation |δ| his Substituting into formula ⑥, we obtain the feedforward compensation amount u. ff (t): ⑥； Where K ff This is the feedforward gain coefficient, and its value is fixed at 1.

17. The method for precise speed control and dual-threshold wear self-diagnosis of an injection molding machine oil motor according to claim 16, characterized in that, The historical average speed deviation |δ| his The calculation process is as follows: The control system reads the pulse signal f and the corresponding actual flow rate Q from 10 consecutive control cycles in the previous operating phase of the hydraulic motor. actual And according to formula ①, the pulse signal f is converted into the actual rotational speed n within the corresponding control cycle. actual ; The corresponding actual rotational speed n within each of the 10 cycles is respectively actual Actual traffic Q actual Substituting the displacement V of the hydraulic motor into the formula That is, the historical speed deviation |δ| within 10 cycles is obtained respectively: ； The average historical speed deviation |δ| over the 10 cycles is used to obtain the mean historical speed deviation |δ|. his .

18. A method for precise speed control and dual-threshold wear self-diagnosis of an injection molding machine oil motor according to claim 15, characterized in that, The feedforward gain coefficient K ff Based on the wear characteristics of the oil motor and the hydraulic system, it is designed to compensate in advance for speed deviations caused by wear and leakage of the oil motor.

19. A method for precise speed control and dual-threshold wear self-diagnosis of an injection molding machine oil motor according to claim 15, characterized in that, The formula for calculating the total control quantity u(t) is: ⑦； The obtained feedforward compensation amount u ff (t) and PID output u PID Substituting (t) into formula ⑦ yields formula ⑧: ⑧。 20. A method for precise speed control and dual-threshold wear self-diagnosis of an injection molding machine oil motor according to claim 13, characterized in that, The formula for calculating the compensated output flow rate Q(t) is as follows: ⑨。 21. The method for precise speed control and dual-threshold wear self-diagnosis of an injection molding machine oil motor according to claim 11, characterized in that, The change in the oil motor from the initial speed to the target speed is linearly increased over 5 control cycles to achieve smooth compensation.

22. The method for precise speed control and dual-threshold wear self-diagnosis of an injection molding machine oil motor according to claim 16, characterized in that, In step S4 above, the specific implementation process of the dual-threshold wear self-diagnosis algorithm is as follows: The control system reads the actual rotational speed n within the current control cycle. actual Actual traffic Q actual Substituting the displacement V and speed deviation |δ| of the hydraulic motor into formula 10, we can obtain the volumetric efficiency η of the hydraulic motor. v : ⑩； Among them, Q actual The output flow rate Q(t) is calculated based on the compensated output flow rate within the current control cycle. The control system continuously records the volumetric efficiency η over ten control cycles. v And calculate the volumetric efficiency η v Calculate the average value and determine whether the wear protection threshold is met: If the conditions are met, the operating data will be output through the human-computer interaction interface; If the conditions are not met, high-frequency closed-loop compensation will continue.

23. The method for precise speed control and dual-threshold wear self-diagnosis of an injection molding machine oil motor according to claim 22, characterized in that, The volumetric efficiency η v The specific process for determining the average value and the wear protection threshold is as follows: The volumetric efficiency η v The average values ​​are respectively compared with the preset maintenance threshold η v1 and changing the threshold η v2 Comparison: When η v1 ≥Volume efficiency η v Average value > η v2 At this time, the system enters maintenance early warning status; When the volumetric efficiency η v Average value ≤ η v2 When this happens, the system enters a locked protection state.

24. The method for precise speed control and dual-threshold wear self-diagnosis of an injection molding machine oil motor according to claim 22, characterized in that, The wear self-diagnosis conditions are as follows: If, during the current operating phase of the oil motor, the oil temperature exceeds 60°C or the pressure fluctuation exceeds ±0.2MPa for 10 consecutive control cycles, and the oil motor temperature difference is ≤8°C and the pressure difference fluctuation rate is ≤1MPa / s, the wear self-diagnosis condition determination is paused and the operating condition is allowed to stabilize to prevent false triggering of wear determination.

25. A method for precise speed control and dual-threshold wear self-diagnosis of an injection molding machine oil motor according to claim 23, characterized in that, When the injection molding machine is in maintenance warning mode, its specific working process is as follows: The control system outputs intermittent alarm signals to the audible and visual alarm. The human-machine interface displays "maintenance reminder" information and automatically generates a "wear analysis report"; the report includes volumetric efficiency curves, differential pressure fluctuation records, and recommended maintenance times.

26. The method for precise speed control and dual-threshold wear self-diagnosis of an injection molding machine oil motor according to claim 23, characterized in that, When the injection molding machine is in the locked protection mode, its specific working process is as follows: The controller executes a lock command to prevent the hydraulic motor from starting; The human-machine interface displays the message "System locked, please replace the oil motor".

27. A precision speed control and dual-threshold wear self-diagnosis system for an injection molding machine oil motor, employing the precision speed control and dual-threshold wear self-diagnosis method for an injection molding machine oil motor as described in any one of claims 1-26, characterized in that, include: A magnetic induction head is installed in the axial position of the oil motor to detect the pulse signal generated by the rotation of the oil motor and output it to the control system; A pressure sensor, installed on the main oil line, is used to detect the system differential pressure signal; Oil temperature sensor, which is the oil temperature sensor built into the injection molding machine, is used to detect the hydraulic oil temperature signal; The control system has a built-in high-speed counting module and a control algorithm module, which are used to acquire signals from the magnetic induction head, pressure sensor and oil temperature sensor and execute the algorithm. The vector frequency converter is connected to the control system via RS485 communication and is used to adjust the speed of the oil pump motor according to the target frequency command output by the control system, so as to achieve precise speed control of the oil motor. The touch screen is connected to the control system and is used for parameter setting, real-time data display, and alarm prompts. Audible and visual alarms are used to issue alarm signals when maintenance warnings are triggered or the system is locked.

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