Control method and system for high-temperature protection of hydraulic cylinder

Abstract

The invention provides a control method and system for high-temperature protection of a hydraulic cylinder, and relates to the field of hydraulic cylinders, and the control method specifically comprises the steps that data are collected through temperature sensors arranged in a cylinder body, a piston rod, oil and the environment, and a three-dimensional temperature field model is constructed based on the Fourier heat conduction law; an oil temperature threshold value is set, a graded cooling mechanism is started when the threshold value is exceeded, and cooling heat is calculated according to a Newton cooling formula and a logarithmic average temperature difference method. Fuzzy PI D control is combined with a neural network prediction model, the cooling intensity is dynamically adjusted according to the temperature rising rate and the load state, and the high-temperature risk is pre-judged. The failure of the sensor is processed by a Kalman filtering algorithm, and the cooling system is automatically switched to a standby loop and alarms if the cooling system fails. The system comprises a temperature acquisition module, a control module, a cooling execution module, an alarm module and a remote communication module, and can solve the problems that an existing protection method is poor in passive cooling effect and unreasonable in timing cooling.

Description

Technical Field

[0001] The present invention relates to the technical field of hydraulic cylinders, and in particular to a control method and system for high temperature protection of hydraulic cylinders. Background Art

[0002] In the industrial fields of metallurgy, forging, injection molding, mining, etc., hydraulic cylinders, as key actuators, often face the challenge of high temperature environments. Under high temperatures, the viscosity of hydraulic oil will decrease. The existing control methods for high temperature protection of hydraulic cylinders are not effective. Passive cooling, such as installing heat sinks, relies on natural convection and radiation. In high-temperature environments such as forging workshops, it can only take away part of the heat, and the effect is not good. In addition, the existing control methods for high temperature protection of hydraulic cylinders are difficult to effectively deal with timed cooling, and often over-cooling at low temperatures and insufficient cooling at high temperatures occurs. Summary of the invention

[0003] In view of this, the present invention provides a control method for high temperature protection of a hydraulic cylinder and the purpose and efficacy of the system thereof, which specifically includes the following steps:

[0004] Step 1: Use the temperature sensors (2) arranged on the hydraulic cylinder body, the piston rod surface and the hydraulic oil to collect temperature data in real time, and combine the ambient temperature sensor data to construct a three-dimensional temperature field model; in the Cartesian coordinate system, based on Fourier's heat conduction law, the non-steady-state three-dimensional heat conduction equation is: Where T is temperature, t is time, α is thermal diffusivity, x, y, z are spatial coordinates, and q v is the internal heat source intensity, ρ is the density, c p is the specific heat capacity at constant pressure; by setting boundary conditions and numerically solving the data collected by each sensor, a three-dimensional temperature field model that accurately reflects the temperature distribution of the hydraulic cylinder and its surrounding environment is constructed;

[0005] Step 2: Set the oil temperature threshold T th , when the oil temperature T oil Exceeding this threshold, i.e., T oil >T th The hierarchical cooling mechanism is started; hierarchical cooling includes the first-level cooling of the cylinder surface circulating water cooling system, the second-level cooling of the hydraulic oil external circulating cooler, and the third-level cooling of the linkage equipment shutdown protection. During the cooling process, the heat Q taken away by the water cooling system during the first-level cooling is 1 It can be calculated by Newton's cooling formula: Q 1 =h 1 A 1 (T cylinder -T water ), where h 1 is the convection heat transfer coefficient of the water cooling system to the cylinder surface, A 1is the contact surface area between the cylinder block and the water cooling system, T cylinder is the surface temperature of the cylinder block, T water is the cooling water temperature; during secondary cooling, the heat Q carried away by the hydraulic oil external circulation cooler 2 can be calculated according to the logarithmic mean temperature difference method of the heat exchanger: Q 2 = K 2 A 2 ΔT lm , where K 2 is the total heat transfer coefficient of the cooler, A 2 is the heat exchange area of the cooler, ΔT lm is the logarithmic mean temperature difference;

[0006] Step 3: Apply the fuzzy PID control algorithm to dynamically adjust the cooling intensity according to the temperature rise rate and the load status obtained through the pressure sensor. Let the load force be F. The output u(t) of the fuzzy PID control is determined by the proportional term K p , the integral term K i and the derivative term K d . Its control law formula is: where e(t) is the temperature deviation, i.e., (e(t) = T set - T actual ), T set is the set temperature, T actual is the actually measured temperature; at the same time, a neural network prediction model is introduced to predict the high-temperature risk in advance and then pre-start the cooling; the neural network prediction model is trained through the backpropagation algorithm to minimize the mean square error MSE between the predicted temperature and the actual temperature T. Its formula is: where n is the number of training samples;

[0007] Step 4: When a certain sensor fails, use the Kalman filter algorithm to fuse the remaining sensor data for state estimation; the Kalman filter performs iterative calculations through the state equation x k = A k x k-1 + B k u k + w k and the observation equation z k = H k x k + v k , where x k is the state vector, A k is the state transition matrix, B k is the control input matrix, u k is the control input, w k is the process noise, z kis the observation vector, and H k is the observation matrix, and v k is the observation noise; when the cooling system fails, it automatically switches to the standby cooling circuit and issues an alarm; assume that the switching time between the main cooling circuit and the standby cooling circuit is t switch During the switching process, to ensure the stable operation of the system, the change rate of the cooling power needs to satisfy where ΔP is the change in cooling power before and after switching, Δt is the switching time interval, and P rate is the maximum allowable change rate of cooling power.

[0008] Furthermore, the temperature sensor in the first step is a thermocouple, and temperature acquisition points are arranged at the upper, middle, and lower ends of the hydraulic cylinder block, two temperature acquisition points are arranged in the hydraulic oil, and one temperature acquisition point is arranged in the environment; the layout of the temperature acquisition points is optimized according to the heat flux density distribution of the temperature field model where λ is the thermal conductivity, ensuring that the temperature change trend can be accurately captured; for the thermocouple sensor, the relationship between its output thermoelectromotive force E and temperature T follows the Seebeck effect and can be approximately expressed as E = aT + bT 2 + cT 3 +…, where a, b, c, etc. are constants related to the thermocouple material.

[0009] Furthermore, the oil temperature threshold T in the second step th is set according to the actual working conditions, and during normal operation, the oil temperature fluctuation is controlled within the range; by adjusting the cooling power P of the cooling system cool to maintain the stability of the oil temperature, the relationship between the cooling power and the oil temperature deviation can be expressed as P cool = K T ΔT, where K T is the proportionality coefficient, and ΔT is the oil temperature deviation; in practical applications, considering the dynamic response characteristics of the system, the adjustment of the cooling power also needs to satisfy This is the discrete form of the PID adjustment formula, which is used to more precisely control the cooling power.

[0010] Furthermore, the cooling intensity in the second step is positively correlated with the temperature deviation and the temperature change rate, and the dynamic adjustment of the cooling intensity is achieved by adjusting the flow rate Q of the cooling medium in the cooling system; the relationship between the cooling medium flow rate and the cooling power is P cool = c m QΔT m where c m is the specific heat capacity of the cooling medium, and ΔT m is the temperature difference between the inlet and outlet of the cooling medium; if the cooling medium is water, its specific heat capacity c m is approximately When adjusting the flow rate of the cooling medium, the variable frequency control technology is adopted, and the relationship between the flow rate Q and the motor frequency f is approximately By changing the motor frequency, the flow rate of the cooling medium is accurately controlled, and then the cooling intensity is precisely adjusted.

[0011] Furthermore, when the oil temperature is lower than the set low temperature threshold T low , the heating device is started to heat the hydraulic oil; the heating power P of the heating device heat is determined according to the mass m, specific heat capacity c of the hydraulic oil and the desired heating rate by the formula to accurately control the heating process and ensure that the oil temperature quickly rises back to the appropriate range.

[0012] The present invention provides a high-temperature protection system for a hydraulic cylinder, which specifically includes: a temperature acquisition module, a control module, a cooling execution module, an alarm module and a remote communication module;

[0013] The temperature acquisition module is composed of temperature sensors arranged on the surface of the hydraulic cylinder block, piston rod, hydraulic oil and the environment, and is used to acquire temperature data;

[0014] The control module includes a fuzzy PID control unit and a neural network prediction unit, and is used to perform control operations according to the acquired temperature data and load data;

[0015] The cooling execution module includes a circulating water cooling system on the surface of the cylinder block, an external circulating cooler for hydraulic oil and a standby cooling circuit, and performs cooling operations according to the instructions of the control module;

[0016] The alarm module issues an alarm signal when the sensor fails or the cooling system malfunctions; the control module performs data interaction with the temperature acquisition module, the cooling execution module and the alarm module through a communication protocol, and the communication data transmission rate R meets the real-time requirement, which can be expressed as where L i is the length of data transmitted each time, m is the number of transmissions per unit time, and t max is the maximum allowable transmission delay; assuming that the communication adopts the industrial Ethernet protocol, its data transmission rate can reach 100 Mbps or even higher, which can effectively meet the stringent real-time requirements of the system for data.

[0017] Furthermore, for the water cooling system in the cooling execution module, the head H of the circulating water pump needs to satisfy the formula where ΔP system is the pressure difference that the system needs to overcome, ρ water is the density of water, g is the acceleration due to gravity, and ∑h f is the sum of the frictional resistance losses along the pipeline, so as to ensure the stable circulation of the cooling water flow and achieve effective heat dissipation.

[0018] Further, the system is provided with a data storage module for storing temperature data, load data, cooling system operation data, fault alarm records, etc.; the storage capacity C of the data storage module is estimated according to the data type, storage frequency f, and storage duration T. For temperature data, assuming the amount of data collected each time is L T , then the storage capacity C of the temperature data T = L T × f × T. The same applies to other types of data. By reasonably planning the storage capacity, the long-term stable operation of the system is ensured and the data is not lost.

[0019] Further, the remote communication module transmits the system operation status data to the remote monitoring terminal through a wireless communication protocol; the signal strength S and transmission distance d during data transmission follow the free space propagation loss formula S = S 0 -20log 10 (d)-20log 10 (f c )-147.55, where S 0 is the signal strength at the transmitting end, f c is the carrier frequency. Through this formula, the signal quality can be evaluated to ensure the reliability of remote monitoring. The remote monitoring terminal can remotely set and modify the oil temperature threshold, cooling intensity adjustment parameters, etc. of the system.

[0020] Beneficial effects:

[0021] Precise temperature control:

[0022] Multi-dimensional monitoring: Temperature sensors on the surface of the hydraulic cylinder block, piston rod, and in the hydraulic oil can comprehensively capture the temperature information of various parts of the hydraulic cylinder. At the same time, combined with the data of the ambient temperature sensor, an advanced algorithm is used to construct a three-dimensional temperature field model. Compared with the traditional method of only monitoring temperature at a single point or a small number of points, the temperature monitoring accuracy of the present invention has a qualitative leap, and the improvement range can reach 30%-50%. This accurate temperature data acquisition provides a solid and reliable basis for subsequent precise control. For example, in the metallurgical hot rolling production line, the single-point monitoring in the past could not accurately reflect the temperature difference of different parts of the hydraulic cylinder, resulting in a large error in temperature control. After adopting the multi-dimensional monitoring of the present invention, it can clearly show that during the high-temperature rolling process of the hydraulic cylinder, the temperature of the cylinder block on the side close to the steel billet is 10°C - 15°C higher than that on the other side, providing key data for targeted cooling control.

[0023] Dynamic Cooling Regulation: The fuzzy PID control algorithm is employed. This algorithm acts like an intelligent "commander" that dynamically adjusts the cooling intensity based on the real-time temperature rise rate and the load status precisely measured by the pressure sensor. Through this precise control strategy, the oil temperature fluctuation can be stably controlled within the range of ±2°C. It effectively avoids the damage to the hydraulic system caused by large oil temperature fluctuations. For example, when the oil temperature is too high, the viscosity of the oil decreases, leading to leakage and poor lubrication. When the oil temperature is too low, the fluidity of the oil becomes poor, affecting the system response speed. In practical applications, taking the metallurgical hot rolling production line as an example, after adopting the method of the present invention, the number of equipment shutdowns caused by oil temperature fluctuations is reduced by more than 60%. In the hot rolling workshop of a large steel plant, the average number of shutdowns caused by oil temperature problems was 8 times per month in the past. After adopting the technology of the present invention, the number of shutdowns per month is reduced to less than 3 times, greatly improving the equipment operation stability and ensuring the continuity of production.

[0024] High-efficiency Energy-saving Cooling:

[0025] Hierarchical Cooling Strategy: The present invention innovatively designs a hierarchical cooling mechanism. This mechanism, based on the real-time state of the oil temperature, like an experienced dispatcher, orderly starts different cooling measures in sequence. When the oil temperature just exceeds the set threshold, the first-level cooling is started first, and the circulating water cooling system on the cylinder body surface is turned on. This system uses the heat exchange between the cooling water and the cylinder body surface to specifically reduce the cylinder body temperature, and can quickly take away 30%-40% of the heat generated by the cylinder body. When the oil temperature continues to rise and the first-level cooling alone cannot meet the demand, the hydraulic oil external circulation cooler is then timely started for the second-level cooling. This hierarchical cooling method precisely matches the oil temperature change and the cooling demand, avoiding the problems of either over-cooling and wasting energy or insufficient cooling and ineffective temperature control in traditional timed forced cooling, thus greatly reducing the cooling energy consumption.

[0026] Remarkable Energy-saving Effect: Through actual tests, compared with the traditional cooling method, the cooling energy consumption of the present invention is reduced by 25%-40%. In factories where equipment such as injection molding machines runs intensively, this energy-saving effect is particularly significant. Taking a factory with 100 injection molding machines as an example, the power of the cooling system equipped for each injection molding machine is 10 kW. If it operates according to the traditional cooling method, working 16 hours a day and 22 days a month, the monthly cooling power consumption is 100×10×16×22 = 352000 kW·h. After adopting the hierarchical cooling mechanism of the present invention, the cooling energy consumption is reduced by 30%, and the monthly electricity can be saved by 352000×0.3 = 105600 kW·h. A large amount of electricity costs can be saved every year, bringing considerable economic benefits to the enterprise.

[0027] Prolong Equipment Life:

[0028] Protect the performance of hydraulic oil: Precise temperature control and efficient cooling measures are like putting a "protective coat" on the hydraulic oil. Stable oil temperature avoids the decrease in the viscosity of the hydraulic oil and maintains good lubrication performance. Within the normal operating temperature range, the hydraulic oil can form a stable oil film between moving parts, effectively reducing friction and wear between parts. For example, in mining equipment, the working environment of hydraulic cylinders is harsh, with large load changes and easy increase in oil temperature. In the past, due to too high oil temperature, the viscosity of the hydraulic oil decreased, the oil film thickness thinned, component wear increased, and the service life of the equipment was shortened. After adopting the method of the present invention, the oil temperature is effectively controlled, the viscosity of the hydraulic oil is stable, and the component wear rate is reduced by 40%-50%.

[0029] Delay the aging of seals: At the same time, the stable oil temperature also slows down the aging speed of seals. Seals are usually made of high-molecular materials such as rubber, and high temperature is one of the main inducements for their aging. Excessive temperature will cause the rubber molecular chains to break and crosslink, resulting in the loss of elasticity and sealing performance of the seals. However, through precise temperature control, the present invention maintains the oil temperature within an appropriate range, effectively delaying the aging process of the seals. Taking the hydraulic cylinder in mining equipment as an example, after using the method of the present invention, the replacement cycle of the seals is extended by 1.5-2.5 times. Originally, the seals needed to be replaced every 3 months, but now it can be extended to 6-9 months, greatly reducing the equipment maintenance cost and downtime. According to statistics, in a large-scale mining project, after adopting the technology of the present invention, the maintenance cost saved annually due to replacing seals is as high as 500,000 yuan. At the same time, the normal operating time of the equipment has increased significantly, and the production efficiency has increased by more than 20%.

[0030] Enhance system reliability:

[0031] Fault tolerance of sensors: When a certain sensor fails, the Kalman filtering algorithm plays a key role. It is like an intelligent data fusion expert who can fuse the remaining sensor data for state estimation to ensure the accuracy of temperature monitoring is not affected. In a complex industrial environment, sensors may malfunction due to electromagnetic interference, mechanical vibration, etc. In a traditional system, when a sensor fails, it is often unable to accurately obtain temperature information, resulting in control errors. However, the Kalman filtering algorithm of the present invention can accurately calculate the temperature at the position of the faulty sensor based on historical data and the remaining sensor data, with the error controlled within ±3°C. For example, in the hydraulic cylinder system of a chemical production plant, there has been a situation where the oil temperature was misjudged due to a sensor failure, which in turn caused the cooling system to malfunction. After adopting the technology of the present invention, even if a sensor fails, the system can still operate stably, and no abnormal shutdowns due to sensor problems have occurred.

[0032] Cooling System Failure Response: In case of a cooling system failure, it automatically switches to the standby cooling circuit and alarms to ensure that the system can still maintain the basic cooling function in case of emergencies. The standby cooling circuit is like an "emergency rescue force", always on standby. Once the main cooling system fails, the system can quickly switch to the standby cooling circuit within 0.5 seconds, continue to provide cooling protection for the hydraulic cylinder, and avoid damage to the hydraulic cylinder due to high temperature caused by sensor or cooling system failures. In industrial production, the number of abnormal shutdowns caused by sensor or cooling failures of the system is reduced by more than 70%. In a stamping workshop of an automobile manufacturing factory, the average number of shutdowns caused by cooling system failures was 10 times per year in the past. After adopting the standby cooling circuit design of the present invention, there has been no long-term shutdown caused by cooling system failures in the past two years, enhancing the reliability and stability of the entire production system.

[0033] Early Risk Prediction:

[0034] Intelligent Prediction Model: The introduced neural network prediction model is deeply trained based on a large amount of historical temperature data, load data, and cooling system operation data. Like an experienced "prophet", it can predict high-temperature risks in advance and pre-start cooling. By learning and analyzing complex data, the model establishes the internal relationship between oil temperature changes and various factors. For example, during the operation of forging equipment, the model can predict potential high-temperature risks 3 - 5 minutes in advance. This is because it can capture the correlation laws between factors such as load changes and heating time in the forging process and the rise in oil temperature. When detecting an upcoming high-temperature risk, the system can pre-start cooling measures, reducing the risk of out-of-control oil temperature by more than 80%.

[0035] Ensuring Equipment Safety: In actual production, pre-starting cooling in advance can effectively prevent the occurrence of excessively high oil temperature and ensure the safe and stable operation of equipment. Take a large forging enterprise as an example. In the past, the equipment damage accidents caused by excessively high oil temperature in the forging equipment of this enterprise occurred an average of 3 times per year, resulting in direct economic losses of about 500,000 yuan. After adopting the neural network prediction model of the present invention, there have been no equipment damage accidents caused by excessively high oil temperature in the past two years. It not only avoids high equipment repair and replacement costs but also ensures the continuity of production, improving the economic benefits and production efficiency of the enterprise. Brief Description of the Drawings

[0036] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings of the embodiments will be briefly introduced below.

[0037] The drawings in the following description only relate to some embodiments of the present invention and do not limit the present invention.

[0038] In the drawings:

[0039] Figure 1It is a schematic flow diagram of the control method for high-temperature protection of the hydraulic cylinder in the embodiment of the present invention.

[0040] Figure 2 It is a schematic flow diagram of the high-temperature protection system of the hydraulic cylinder in the embodiment of the present invention.

[0041] Figure 3 It is a schematic overall structure diagram of the hydraulic cylinder, piston rod (101) and temperature sensor (2) of the present invention.

[0042] Reference numerals:

[0043] 1. Cylinder block;

[0044] 2. Piston rod;

[0045] 3. Temperature sensor. Detailed implementation manners

[0046] The following further describes the implementation manners of the present invention in detail with reference to the drawings and embodiments.

[0047] Embodiment: Please refer to Figures 1 to 2 as shown:

[0048] The present invention provides a control method and system for high-temperature protection of a hydraulic cylinder, including the following steps:

[0049] Step 1: Using the temperature sensors 2 arranged on the surface of the cylinder block 1 and piston rod 101 of the hydraulic cylinder and in the hydraulic oil, collect temperature data in real time, and at the same time, combine the data of the ambient temperature sensor 2 to construct a three-dimensional temperature field model; in the Cartesian coordinate system, based on Fourier's law of heat conduction, the unsteady three-dimensional heat conduction equation is: In the formula, T is the temperature, t is the time, α is the thermal diffusivity, x, y, z are the spatial coordinates, q v is the intensity of the internal heat source, ρ is the density, c p is the specific heat capacity at constant pressure; by setting the boundary conditions and numerically solving the data collected by each sensor, a three-dimensional temperature field model that accurately reflects the temperature distribution of the hydraulic cylinder and its surrounding environment is constructed;

[0050] Step 2: Set the oil temperature threshold T th , when the oil temperature T oil exceeds this threshold, that is, T oil > T th ), start the hierarchical cooling mechanism; the hierarchical cooling includes triggering the primary cooling of the surface circulating water cooling system of the cylinder block, the secondary cooling of the external circulation cooler of the hydraulic oil, and the tertiary cooling of the shutdown protection of the associated equipment in sequence; during the cooling process, during the primary cooling, the heat Q 1 carried away by the water cooling system can be calculated by Newton's cooling formula: Q 1 = h 1 A1 (T cylinder -T water ), where h 1 is the convective heat transfer coefficient of the water cooling system to the cylinder block surface, A 1 is the surface area of contact between the cylinder block and the water cooling system, T cylinder is the cylinder block surface temperature, T water is the cooling water temperature; during secondary cooling, the heat Q 2 carried away by the hydraulic oil external circulation cooler can be calculated according to the logarithmic mean temperature difference method of the heat exchanger: Q 2 = K 2 A 2 ΔT lm , where K 2 is the total heat transfer coefficient of the cooler, A 2 is the heat transfer area of the cooler, and ΔT lm is the logarithmic mean temperature difference;

[0051] Step 3: Apply the fuzzy PID control algorithm to dynamically adjust the cooling intensity according to the temperature rise rate and the load status obtained through the pressure sensor. Let the load force be F. The output u(t) of the fuzzy PID control is determined by the proportional term K p , the integral term K i and the derivative term K d . Its control law formula is: where e(t) is the temperature deviation, i.e., (e(t)=T set -T actual ), T set is the set temperature, and T actual is the actually measured temperature; at the same time, a neural network prediction model is introduced to predict the high-temperature risk in advance and then pre-start the cooling; the neural network prediction model is trained through the backpropagation algorithm to minimize the mean square error MSE between the predicted temperature and the actual temperature T. Its formula is: where n is the number of training samples;

[0052] Step 4: When a certain sensor fails, use the Kalman filter algorithm to fuse the remaining sensor data for state estimation; the Kalman filter performs iterative calculations through the state equation x k = A k x k-1 + B k u k + w k and the observation equation z k = H k x k + v k . Among them, x k is the state vector, Ak is the state transition matrix, B k is the control input matrix, u k is the control input, w k is the process noise, z k is the observation vector, H k is the observation matrix, v k is the observation noise; when the cooling system fails, it automatically switches to the standby cooling circuit and issues an alarm; assume the switching time between the main cooling circuit and the standby cooling circuit is t switch , during the switching process, to ensure the stable operation of the system, the change rate of the cooling power needs to satisfy where, ΔP is the change in cooling power before and after switching, Δt is the switching time interval, P rate is the maximum allowable change rate of cooling power.

[0053] Among them, the temperature sensor 2 in step one is a thermocouple, and temperature acquisition points are arranged at the upper end, middle end, and lower end of the hydraulic cylinder block respectively, two temperature acquisition points are arranged in the hydraulic oil, and one temperature acquisition point is arranged in the environment; the layout of the temperature acquisition points is optimized according to the heat flux density distribution of the temperature field model, where λ is the thermal conductivity, ensuring that the temperature change trend can be accurately captured; for the thermocouple sensor, the relationship between its output thermoelectromotive force E and temperature T follows the Seebeck effect and can be approximately expressed as E = aT + bT + cT 2 +…, where a, b, c, etc. are constants related to the thermocouple material. 3 +…, where a, b, c, etc. are constants related to the thermocouple material.

[0054] Among them, the oil temperature threshold T in step two th is set according to the actual working conditions, and during normal operation, the oil temperature fluctuation is controlled within the range; by adjusting the cooling power P of the cooling system cool to maintain the stability of the oil temperature, the relationship between the cooling power and the oil temperature deviation can be expressed as P cool = K T ΔT, where K T is the proportionality coefficient, and ΔT is the oil temperature deviation; in practical applications, considering the dynamic response characteristics of the system, the adjustment of the cooling power also needs to satisfy This is the discrete form of the PID adjustment formula, which is used to more precisely control the cooling power.

[0055] Among them, the cooling intensity in step two is positively correlated with the temperature deviation and the temperature change rate, and the dynamic adjustment of the cooling intensity is realized by adjusting the flow rate Q of the cooling medium in the cooling system; the relationship between the cooling medium flow rate and the cooling power is P cool = c m QΔT m , where cm is the specific heat capacity of the cooling medium, and ΔT m is the temperature difference between the inlet and outlet of the cooling medium; if the cooling medium is water, its specific heat capacity c m is approximately When adjusting the flow rate of the cooling medium, the variable frequency control technology is adopted, and the relationship between the flow rate Q and the motor frequency f is approximately By changing the motor frequency, the flow rate of the cooling medium is accurately controlled, and then the cooling intensity is precisely adjusted.

[0056] Among them, when the oil temperature is lower than the set low temperature threshold T low , the heating device is started to heat the hydraulic oil; the heating power P of the heating device heat is determined according to the mass m, specific heat capacity c of the hydraulic oil and the desired heating rate by the formula to accurately control the heating process and ensure that the oil temperature quickly rises back to the appropriate range.

[0057] The present invention provides a high-temperature protection system for a hydraulic cylinder, including a temperature acquisition module, a control module, a cooling execution module, an alarm module and a remote communication module;

[0058] The temperature acquisition module is composed of temperature sensors 2 arranged on the surface of the cylinder block of the hydraulic cylinder, the piston rod 101, the hydraulic oil and the environment, and is used to acquire temperature data;

[0059] The control module includes a fuzzy PID control unit and a neural network prediction unit, and is used to perform control operations according to the acquired temperature data and load data;

[0060] The cooling execution module includes a circulating water cooling system on the surface of the cylinder block, an external circulation cooler for hydraulic oil and a standby cooling circuit, and performs cooling operations according to the instructions of the control module;

[0061] The alarm module issues an alarm signal when the sensor fails or the cooling system malfunctions; the control module performs data interaction with the temperature acquisition module, the cooling execution module and the alarm module through a communication protocol, and the communication data transmission rate R meets the real-time requirement, and can be expressed as where L i is the length of data transmitted each time, m is the number of transmissions per unit time, and t max is the maximum allowable transmission delay; assuming that the communication uses the industrial Ethernet protocol, its data transmission rate can reach 100 Mbps or even higher, which can effectively meet the strict requirements of the system for data real-time performance.

[0062] Among them, for the water cooling system in the cooling execution module, the head H of the circulating water pump needs to meet the formula where ΔP systemis the pressure difference that the system needs to overcome, ρ water is the density of water, g is the acceleration due to gravity, ∑h f is the sum of the frictional resistance losses along the pipeline, so as to ensure the stable circulation of the cooling water flow and achieve effective heat dissipation.

[0063] Among them, the system is equipped with a data storage module for storing temperature data, load data, cooling system operation data, fault alarm records, etc.; the storage capacity C of the data storage module is estimated according to the data type, storage frequency f, and storage duration T. For temperature data, assuming that the amount of data collected each time is L T , then the storage capacity C of the temperature data T = L T × f × T. The same applies to other types of data. By reasonably planning the storage capacity, the long-term stable operation of the system is ensured and the data is not lost.

[0064] Among them, the remote communication module transmits the system operation status data to the remote monitoring terminal through a wireless communication protocol; the signal strength S and the transmission distance d during the data transmission follow the free space propagation loss formula S = S 0 -20log 10 (d)-20log 10 (f c )-147.55, where S 0 is the signal strength at the transmitting end, f c is the carrier frequency. Through this formula, the signal quality can be evaluated to ensure the reliability of remote monitoring. The remote monitoring terminal can remotely set and modify the oil temperature threshold, cooling intensity adjustment parameters, etc. of the system.

[0065] Experiment 1: Comparison of oil temperature control accuracy

[0066] Experiment purpose: Accurately compare the control accuracy of the oil temperature of the hydraulic cylinder by using the high-temperature protection system of the present invention and the traditional passive heat sink protection method under high-temperature working conditions, and intuitively show the excellent performance of this system in stabilizing the oil temperature.

[0067] Experimental equipment:

[0068] Two groups of hydraulic cylinders of the CD250H series, with a cylinder diameter of 125 mm, a stroke of 600 mm, and a rated working pressure of 25 MPa, have good versatility and representativeness. One group is equipped with this high-temperature protection system (experimental group), and the other group is only installed with a traditional passive heat sink (control group).

[0069] Select a PT100 high-precision temperature sensor 2 with a measurement accuracy of up to ±0.1°C, which can sensitively capture the subtle changes in the oil temperature. It is paired with an Advantech ADAM-4017 data collector, which can automatically and accurately collect and store the oil temperature data at a set interval of 10 minutes. The model of the simulated high-temperature environment test chamber is GDJS-1000, which can stably create a high-temperature environment of 80°C ± 2°C and accurately simulate the harsh high-temperature working conditions in the industrial field.

[0070] Experimental process: Place the hydraulic cylinders of the experimental group and the control group stably in the simulated high-temperature environment test chamber. Apply the same load to the two groups of hydraulic cylinders through a hydraulic loading pump station to simulate the load situation in actual work, and the load force is set to 60 kN. Start the hydraulic cylinder and make it run continuously at a reciprocating frequency of 40 times per minute for 2 hours. During the operation, the Advantech ADAM-4017 data collector automatically collects and records the oil temperature data at a preset interval of 10 minutes to ensure the continuity and integrity of the data. At the same time, to ensure the stability of the experimental environment, check and fine-tune the temperature in the test chamber every 30 minutes to keep it always within the range of 80°C ± 2°C.

[0071] Experimental data:

[0072] Experimental group: During the 2-hour operation, the average oil temperature is calculated to be 72.5°C. After detailed analysis of the collected oil temperature data, it is found that the oil temperature fluctuation range is between 70 - 75°C, and the maximum fluctuation amplitude is 5°C. By drawing a line graph of the oil temperature changing with time, it can be clearly seen that the oil temperature curve is relatively stable with small fluctuations. Further statistical analysis of the data shows that the standard deviation of the oil temperature data is 1.2°C, indicating that this high-temperature protection system can effectively stabilize the oil temperature with high control precision.

[0073] Control group: Under the same experimental conditions, the average oil temperature of the hydraulic cylinder in the control group reaches 78°C. The oil temperature fluctuation range is relatively large, between 74 - 82°C, and the maximum fluctuation amplitude is 8°C. It can be clearly seen from the line graph of the oil temperature change that the oil temperature fluctuates violently. After calculation, the standard deviation of its oil temperature data is 3.5°C, indicating that the traditional passive heat sink protection method has limited control ability for the oil temperature under high-temperature working conditions and the oil temperature stability is poor.

[0074] Experiment 2: Comparison of cooling energy consumption

[0075] Experimental purpose: Scientifically test the energy consumption difference between the high-temperature protection system of the present invention and the traditional timed forced cooling system during the cooling process under the same working conditions, and highlight the significant energy-saving advantages of this system.

[0076] Experimental equipment:

[0077] Two Haitian MA1200 / 320 injection molding machines are selected, with a clamping force of 1200 kN, an injection volume of 400 g, and a motor power of 45 kW. All performance parameters are the same to ensure the comparability of the experiments. One is equipped with this high-temperature protection system (experimental group), and the other uses a traditional timed forced cooling system (control group).

[0078] Use a FLUKE435II power quality analyzer with a measurement accuracy of up to 0.1% to accurately measure the real-time power consumption of the cooling system during operation. It is equipped with a K-type thermocouple oil temperature sensor to monitor the oil temperature change in real time. At the same time, using the built-in operating status monitoring system of the injection molding machine, the operating parameters such as the working cycle, injection pressure, and holding time of the injection molding machine can be accurately recorded for subsequent analysis of the relationship between energy consumption and working conditions.

[0079] Experimental process: To ensure the accuracy and reliability of the experiment, the two injection molding machines perform exactly the same injection molding process. The process parameters are set as follows: injection pressure 90 MPa, holding pressure 70 MPa, injection time 3.5 s, holding time 6 s, cooling time 12 s, and cycle period 25 s. Start the injection molding machine and let it run continuously for 8 hours. During operation, the FLUKE435II power quality analyzer records the power consumption of the cooling system in real time. Combining with the running time, the cooling energy consumption is calculated through integral operation. At the same time, the K-type thermocouple oil temperature sensor monitors the oil temperature in real time to ensure the comparison of energy consumption under the same oil temperature conditions. Every 1 hour, check and record the operating parameters of the injection molding machine to ensure the stability of the process parameters.

[0080] Experimental data:

[0081] Experimental group: After 8 hours of continuous operation, the cooling energy consumption of the injection molding machine in the experimental group is statistically 50 kW·h by the FLUKE435II power quality analyzer. Through in-depth analysis of the real-time power data recorded by the power quality analyzer, it is found that the cooling system can adjust the power output according to the oil temperature in real time, automatically reducing the power when the oil temperature is low, avoiding unnecessary energy waste. When the oil temperature is in the range of 70 - 75 °C, the average power of the cooling system is 3.2 kW; when the oil temperature rises to 75 - 80 °C, the average power increases to 4.5 kW.

[0082] Control group: The injection molding machine in the control group runs for 8 hours under the same injection molding process, and the cooling energy consumption is as high as 80 kW·h. The traditional timed forced cooling system starts the cooling device at a preset time interval, and the cooling power is constant regardless of the oil temperature, resulting in a large amount of energy consumption even when the oil temperature is low. During the entire 8-hour operation, the power of the cooling system always remains at about 6.5 kW. By comparison, the energy consumption of the experimental group is reduced by 37.5% compared with the control group, fully demonstrating the remarkable energy-saving effect of this high-temperature protection system.

[0083] Experiment 3: Comparison of the Influence on Equipment Life

[0084] Experiment Purpose: To long-term observe the influence of the high-temperature protection system of the present invention and the traditional protection method on the hydraulic cylinder seal and the overall equipment life during actual use, so as to provide a strong reference basis for the service life for users.

[0085] Experiment Equipment:

[0086] Select 8 SWP-630 type forging equipment of the same model, and randomly divide them into two groups, with 4 in each group. One group installs this high-temperature protection system (experimental group), and the other group adopts traditional protection measures (control group). The key parameters of the forging equipment are: forging force 6300 kN, slider stroke 500 mm, and number of forging times per minute 8 times.

[0087] Equip with a MarSurfPS10 stylus surface roughness measuring instrument, and accurately evaluate the wear amount by measuring the change of the surface roughness of the seal, and the measurement accuracy can reach 0.01 μm. At the same time, install a Tongtai MCGS-TPC1062KX equipment fault monitoring system to monitor the operation status of the equipment in real time. Once a fault occurs, immediately record the fault type, occurrence time and related operation parameters, especially the faults related to high temperature.

[0088] Experiment Process: The two groups of forging equipment continuously operate for 6 months in a normal production environment. During the operation, at the beginning of each month, use the MarSurfPS10 stylus surface roughness measuring instrument to comprehensively detect the hydraulic cylinder seal, measure the surface roughness of different positions of the seal, and calculate the wear degree of the seal according to the change amount of the roughness. At the same time, the Tongtai MCGS-TPC1062KX equipment fault monitoring system records in real time the number of shutdowns of the equipment due to high-temperature related faults. Through long-term tracking and analysis of these data, evaluate the influence of different protection methods on the equipment life. In addition, conduct a comprehensive maintenance on the equipment every two months to ensure the good operation status of the equipment and eliminate the interference of other factors on the experimental results.

[0089] Experiment Data:

[0090] Experimental Group: After 6 months of continuous operation, statistical analysis of the seal wear detection data shows that the wear degree of the seal is 20%. The record of the equipment fault monitoring system shows that the number of shutdowns due to high-temperature related faults is 2 times. Further analysis of the seal wear data shows that the wear is relatively uniform, mainly concentrated on the edge part where the seal contacts the cylinder barrel. After evaluation, the remaining service life of the seal is expected to reach more than 12 months.

[0091] Control group: During the same operating time of the forging equipment in the control group, the wear degree of the seal reached 45%. The number of shutdowns due to high-temperature related failures was 8 times. Judging from the wear condition of the seals, the wear was uneven, with local severe wear, and obvious leakage signs appeared in some seals. After evaluation, the remaining service life of the seals was only expected to be 4 - 6 months. By comparison, the wear rate of the seals in the experimental group decreased by 55.6%, and the number of shutdowns due to high-temperature failures decreased by 75%. This fully shows that this high-temperature protection system can significantly extend the service life of the hydraulic cylinder seals, reduce the number of shutdowns of the equipment caused by high-temperature failures, and improve the overall operating stability and reliability of the equipment.

[0092] Specific usage mode and functions of this embodiment: In the data acquisition stage, the thermocouple temperature sensor 2 in the temperature acquisition module acquires data according to a specific layout. Temperature acquisition points are set at the upper, middle, and lower positions of the hydraulic cylinder block, in the hydraulic oil, and in the environment. The layout of these acquisition points is optimized to accurately capture the temperature change trend, while the pressure sensor obtains the load status data. Based on the acquired temperature data, the system constructs a three-dimensional temperature field model. This model is based on Fourier's law of heat conduction and the principle of unsteady three-dimensional heat conduction. By setting boundary conditions and numerically solving the sensor data, it accurately reflects the temperature distribution of the hydraulic cylinder and its surrounding environment. When the oil temperature exceeds the set threshold, the system activates a hierarchical cooling mechanism. First, it triggers the surface circulating water cooling system of the cylinder block for primary cooling. If the effect is not good, it activates the external circulating cooler of the hydraulic oil for secondary cooling. If the secondary cooling still cannot effectively reduce the oil temperature, it will link the equipment to stop for protection. At the same time, the fuzzy PID control algorithm is used to dynamically adjust the cooling intensity according to the temperature rise rate and the load status, which is achieved by adjusting the flow rate of the cooling medium, and the variable frequency control technology is used to accurately control the flow rate. In addition, a neural network prediction model is introduced, which is trained based on historical data to predict the high-temperature risk in advance and pre-start the cooling measures. In terms of fault handling, if a certain sensor fails, the Kalman filter algorithm is used to fuse the data of the remaining sensors for state estimation; if the cooling system fails, it automatically switches to the standby cooling circuit and issues an alarm, and ensures that the change rate of the cooling power is within the allowable range during the switching process. When the oil temperature is lower than the set low-temperature threshold, the system activates the heating device to heat the hydraulic oil, accurately controls the heating power, and quickly raises the oil temperature to the appropriate range. The system is also equipped with a data storage module for storing various operating data and fault records, and the storage capacity is reasonably estimated according to the data type, storage frequency, and duration. The remote communication module transmits the system operating status data to the remote monitoring terminal through a wireless communication protocol, can evaluate the signal quality to ensure the reliability of remote monitoring, and the remote monitoring terminal can remotely set and modify the oil temperature threshold, cooling intensity adjustment parameters, etc. of the system.

Claims

1. A control method for high temperature protection of a hydraulic cylinder, characterized in that: The steps include: Step 1: Using temperature sensors (2) arranged on the hydraulic cylinder body (1), the surface of the piston rod (101) and the hydraulic oil, real-time temperature data is collected, and the data of the ambient temperature sensor (2) is combined to construct a three-dimensional temperature field model; in a Cartesian coordinate system, based on Fourier's heat conduction law, the non-steady-state three-dimensional heat conduction equation is: Where T is temperature, t is time, α is thermal diffusivity, x, y, z are spatial coordinates, and q v is the internal heat source intensity, ρ is the density, c p is the specific heat capacity at constant pressure; by setting boundary conditions and numerically solving the data collected by each sensor, a three-dimensional temperature field model that accurately reflects the temperature distribution of the hydraulic cylinder and its surrounding environment is constructed; Step 2: Set the oil temperature threshold T th , when the oil temperature T oil Exceeding this threshold, i.e., T oil >t th When the cylinder body (1) is turned on, the graded cooling mechanism is started; the graded cooling includes sequentially triggering the first-stage cooling of the circulating water cooling system on the surface of the cylinder body (1), the second-stage cooling of the hydraulic oil external circulating cooler, and the third-stage cooling of the linkage equipment shutdown protection; during the cooling process, during the first-stage cooling, the heat Q1 taken away by the water cooling system can be calculated by the Newton cooling formula: Q1 = h1A1 (T cylinder -T water ), where h1 is the convection heat transfer coefficient of the water cooling system to the surface of the cylinder (1), A1 is the surface area of ​​the cylinder (1) in contact with the water cooling system, T cylinder is the surface temperature of the cylinder (1), T water is the cooling water temperature; in the secondary cooling, the heat Q2 taken away by the hydraulic oil external circulation cooler can be calculated according to the logarithmic mean temperature difference method of the heat exchanger: Q2=K2A2ΔT lm , where K2 is the total heat transfer coefficient of the cooler, A2 is the heat exchange area of ​​the cooler, ΔT lm is the logarithmic mean temperature difference; Step 3: Use fuzzy PID control algorithm to control the temperature according to the temperature rise rate. As well as the load state obtained by the pressure sensor, let the load force be F, and dynamically adjust the cooling intensity; the output u(t) of the fuzzy PID control is determined by the proportional term K p , integral term K i and the differential term K d The control law formula is: Where e(t) is the temperature deviation, that is, (e(t) = T set -T actual ), T set is the set temperature, T actual To measure the actual temperature; at the same time, a neural network prediction model is introduced to predict the high temperature risk in advance and then start cooling in advance; the neural network prediction model is trained through the back propagation algorithm to minimize the predicted temperature The mean square error MSE between the actual temperature T is as follows: Where n is the number of training samples; Step 4: When a sensor fails, the Kalman filter algorithm is used to fuse the remaining sensor data for state estimation; Kalman filter uses the state equation x k =A k x k-1 +B k u k +w k and the observation equation z k =H k x k +v k Perform iterative calculations, where x k is the state vector, A k is the state transfer matrix, B k is the control input matrix, u k is the control input, w k is the process noise, z k is the observation vector, H k is the observation matrix, v k To observe the noise; when the cooling system fails, it automatically switches to the backup cooling circuit and issues an alarm; assuming that the switching time between the main cooling circuit and the backup cooling circuit is t switch During the switching process, in order to ensure the stable operation of the system, the change rate of cooling power must meet Among them, ΔP is the change of cooling power before and after switching, Δt is the switching time interval, P reate is the maximum allowable cooling power change rate.

2. The control method for high temperature protection of a hydraulic cylinder according to claim 1, characterized in that: The temperature sensor (2) in step 1 is a thermocouple, and temperature collection points are arranged at the upper end, middle end and lower end of the hydraulic cylinder body (1), two temperature collection points are arranged in the hydraulic oil, and one temperature collection point is arranged in the environment; the layout of the temperature collection points is based on the heat flux density distribution of the temperature field model Optimize, where λ is the thermal conductivity, to ensure that the temperature change trend can be accurately captured; for thermocouple sensors, the relationship between the output thermoelectric potential E and the temperature T follows the Seebeck effect, which can be approximately expressed as E = aT + bT 2 +cT 3 +…, where a, b, c, etc. are constants related to the thermocouple material.

3. The control method for high temperature protection of a hydraulic cylinder according to claim 1, characterized in that: The oil temperature threshold T of step 2 th According to the actual working conditions, the oil temperature fluctuation is controlled within By adjusting the cooling power P of the cooling system cool To maintain the oil temperature stable, the relationship between cooling power and oil temperature deviation can be expressed as P cool =K T ΔT, where K T is the proportional coefficient, ΔT is the oil temperature deviation; in practical applications, considering the dynamic response characteristics of the system, the adjustment of cooling power must also meet This is a discrete form of the PID regulation formula, which is used to control the cooling power more accurately.

4. The control method for high temperature protection of a hydraulic cylinder according to claim 1, characterized in that: The cooling intensity of step 2 is positively correlated with the temperature deviation and the temperature change rate. The dynamic adjustment of the cooling intensity is achieved by adjusting the flow rate Q of the cooling medium in the cooling system. The relationship between the cooling medium flow rate and the cooling power is P cool =c m QΔT m , where c m is the specific heat capacity of the cooling medium, ΔT m is the temperature difference between the inlet and outlet of the cooling medium; if the cooling medium is water, its specific heat capacity c m At room temperature and pressure, it is about When adjusting the cooling medium flow, frequency conversion control technology is adopted. The relationship between the flow Q and the motor frequency f is approximately Q∝f. The cooling medium flow is accurately controlled by changing the motor frequency, thereby achieving precise adjustment of the cooling intensity.

5. The control method for high temperature protection of a hydraulic cylinder according to claim 1, characterized in that: The neural network prediction model in step 3 is trained based on historical temperature data, load data, and cooling system operation data to improve the accuracy of high temperature risk prediction; in the training data set, the temperature data T train 、Load data F train and cooling system operating data S train The feature vector x is converted into feature vector through feature extraction and input into the neural network for training. Its input-output relationship can be expressed as in To predict the output, W is the weight matrix, b is the bias vector, f is the activation function, and the ReLU activation function is used f(x) = max(0, x); during the training process, the stochastic gradient descent algorithm is used to update the weights and biases, and the weight update formula is The bias update formula is: Where η is the learning rate, is the gradient of the loss function J with respect to the weight or bias.

6. The method for controlling high temperature protection of a hydraulic cylinder according to claim 1, characterized in that: When the oil temperature is lower than the set low temperature threshold T low When the heating device is started to heat the hydraulic oil, the heating power of the heating device is P heat According to the mass m, specific heat c and expected heating rate of hydraulic oil By formula Determine to accurately control the heating process and ensure that the oil temperature quickly returns to the appropriate range.

7. A hydraulic cylinder high temperature protection system, characterized in that: It includes temperature acquisition module, control module, cooling execution module, alarm module and remote communication module; The temperature acquisition module is composed of temperature sensors (2) arranged on the hydraulic cylinder body (1), the surface of the piston rod (101), the hydraulic oil and the environment, and is used to collect temperature data; The control module includes a fuzzy PID control unit and a neural network prediction unit, which are used to perform control operations according to the collected temperature data and load data; The cooling execution module comprises a cylinder body (1) surface circulating water cooling system, a hydraulic oil external circulating cooler and a standby cooling circuit, and executes cooling operations according to instructions of the control module; The alarm module sends out an alarm signal when the sensor fails or the cooling system fails; the control module exchanges data with the temperature acquisition module, the cooling execution module and the alarm module through the communication protocol, and the communication data transmission rate R meets the real-time requirements and can be expressed as Where L i is the data length of each transmission, m is the number of transmissions per unit time, t max is the maximum allowable transmission delay; assuming that the communication adopts the industrial Ethernet protocol, its data transmission rate can reach 100Mbps or even higher, which can effectively meet the system's stringent requirements for data real-time performance.

8. The hydraulic cylinder high temperature protection system according to claim 7, characterized in that: The water cooling system in the cooling execution module has a circulating water pump head H that satisfies the formula Where ΔP system is the pressure difference that the system needs to overcome, ρ water is the density of water, g is the acceleration due to gravity, Σh f It is the sum of the resistance losses along the pipeline, which ensures that the cooling water flow can circulate stably and achieve effective heat dissipation.

9. The hydraulic cylinder high temperature protection system according to claim 7, characterized in that: The system is provided with a data storage module for storing temperature data, load data, cooling system operation data, and fault alarm records, etc.; The storage capacity C of the data storage module is estimated based on the data type, storage frequency f, and storage duration T. For temperature data, it is assumed that the amount of data collected each time is L T , then the temperature data storage capacity c T =L T ×f×T. The same goes for other types of data. By rationally planning the storage capacity, the system can be guaranteed to run stably in the long term and data will not be lost.

10. The hydraulic cylinder high temperature protection system according to claim 7, characterized in that: The remote communication module transmits the system operation status data to the remote monitoring terminal through the wireless communication protocol; the signal strength S and the transmission distance d during the data transmission process follow the free space propagation loss formula s=s0-20log 10 (d)-20log 10 (f c )-147.55, where s0 is the signal strength at the transmitter, f c is the carrier frequency. This formula can be used to evaluate the signal quality and ensure the reliability of remote monitoring. The remote monitoring terminal can remotely set and modify the system's oil temperature threshold, cooling intensity adjustment parameters, etc.

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