Oil filter digital intelligent control system based on sensor

Abstract

The invention relates to the technical field of oil filter control, in particular to an oil filter digital intelligent control system based on sensors, which comprises a fusion monitoring unit, an oil temperature control unit and a feedback regulation unit. The oil temperature control unit calculates the optimal heating rate and the target temperature range through a self-adaptive algorithm according to the environment and the initial temperature of oil, compares the optimal heating rate and the target temperature range with the actual oil temperature in the heating process, adjusts the heating power through pulse heating according to the result, judges the working load according to the specific heat capacity of oil and adjusts the frequency of a vacuum pump. And the feedback regulation unit evaluates the system stability based on the target operation frequency and the heating power of the vacuum pump, generates an optimization strategy and feeds back the optimization strategy to the oil temperature control unit, so that accurate oil temperature control is realized, the equipment stability and the energy utilization efficiency are improved, and efficient operation of the oil filter is guaranteed.

Description

Technical Field

[0001] The invention relates to the technical field of oil filter control, in particular to a sensor-based digital intelligent control system for an oil filter. Background Art

[0002] Industrial production is an important technology. In the field of industrial production, oil filters are of key significance for maintaining oil quality and ensuring the normal operation of equipment. With the development of science and technology, the performance requirements for oil filters are constantly increasing.

[0003] Traditional oil filter control systems have obvious limitations in oil temperature control. The performance of the sensor will shift under different working environments and temperature conditions, that is, the deviation between the output value and the true value will change, making it difficult to accurately calculate based on the ambient temperature and the initial temperature of the oil, and unable to obtain the optimal heating rate and a reasonable target temperature range, resulting in a lack of accuracy in oil temperature control. In actual operation, the oil temperature is prone to being too high or too low. When the oil temperature is too high, the seals will age faster and reduce the service life of the equipment; if the oil temperature is too low, the oil viscosity will increase, thereby increasing the workload of the equipment and significantly reducing the filtration efficiency. In order to solve this technical problem, we provide a sensor-based digital intelligent control system for oil filters. Summary of the invention

[0004] The purpose of the present invention is to provide a digital intelligent control system for an oil filter based on a sensor to solve the problems raised in the above background technology.

[0005] The present invention uses an adaptive oil temperature control algorithm to calculate the optimal heating rate and target temperature range, continuously compares the oil temperature during heating, and adjusts the heater power in a pulse heating manner according to the temperature state. At the same time, the operating frequency of the vacuum pump is adjusted by combining the specific heat capacity of the oil, the equipment operation history data and the oil flow rate to judge the workload, thereby solving the oil temperature control problem.

[0006] To achieve the above purpose, a sensor-based digital intelligent control system for oil filter is provided, including a fusion monitoring unit, an oil temperature control unit and a feedback adjustment unit; The fusion monitoring unit is composed of a fusion of multiple sensors, wherein the pressure sensor and flow sensor are used to monitor the pressure and flow value of the oil in real time, and the temperature sensor is used to obtain the external environment temperature value and the oil temperature; The oil temperature control unit calculates the optimal heating rate and target temperature range according to the ambient temperature and the initial temperature of the oil using an adaptive oil temperature control algorithm. During the heating process, the actual oil temperature is continuously compared with the target temperature range to obtain the temperature state of the oil temperature. According to the temperature state of the oil temperature, the heater power is automatically adjusted by pulse heating. At the same time, the workload of the oil filter is automatically determined according to the specific heat capacity of different oil products, the equipment operation history data and the oil flow rate. The operating frequency of the vacuum pump is adjusted according to the load condition to obtain the target operating frequency of the vacuum pump. The feedback regulation unit constructs a comprehensive performance evaluation model based on the target operating frequency and heating power of the vacuum pump, and evaluates the stability of the current system according to the model. Finally, an optimization adjustment strategy is generated according to the evaluation results and sent to the oil temperature control unit.

[0007] As a further improvement of the technical solution, the oil temperature control unit includes a data processing module, which is used to calculate the difference between the ambient temperature and the initial temperature of the oil in the adaptive oil temperature control algorithm, as follows: Use the temperature sensor to collect the ambient temperature and the initial temperature of the oil, and calculate their initial difference; A temperature offset characteristic curve is set, wherein the temperature offset characteristic curve is used to describe the performance change of the oil under different temperature conditions, and the ambient temperature and the initial temperature of the oil are corrected using the temperature offset characteristic curve, and the difference between the corrected ambient temperature and the initial temperature of the oil is recalculated.

[0008] As a further improvement of the technical solution, the oil temperature control unit includes an analysis and calculation module, and the method for calculating the optimal heating rate in the adaptive oil temperature control algorithm by the analysis and calculation module is as follows: Determine the oil quality, heat transfer area, heat transfer distance and initial oil specific heat capacity based on the equipment data, obtain the temperature difference from the data processing module, finally set the heating time and target temperature range, and calculate the difference between the target temperature and the initial temperature; Preset the initial heating rate and start the iterative cycle. Calculate the temperature change according to the current heating rate and heating time. Then calculate the current specific heat capacity according to the current temperature and the formula of oil specific heat capacity changing with temperature. Substitute it into the heat conduction formula to calculate the estimated heat transfer amount. Finally, calculate the theoretical heat demand. Compare the estimated heat transfer with the theoretical heat demand and obtain the optimal heating rate based on the comparison results.

[0009] As a further improvement of the technical solution, the analysis and calculation module uses the adaptive oil temperature control algorithm to calculate the target temperature range, as follows: Extract the viscosity-temperature characteristic curve data of the current oil and the current ambient temperature from the oil database, and set the upper and lower limits of the oil temperature range corresponding to the optimal viscosity range of the equipment operation; On the viscosity-temperature characteristic curve, three data points adjacent to the current ambient temperature value are selected, and the piecewise linear interpolation algorithm is used for calculation to obtain the straight line equation between the points. The upper and lower limits of the equipment's optimal viscosity range are substituted into the above straight line equation respectively, and the corresponding temperature value is calculated. Finally, the target temperature range of this heating process is determined accordingly.

[0010] As a further improvement of the technical solution, the oil temperature control unit includes a pulse heating module, which automatically adjusts the heater power by pulse heating according to the temperature state of the oil temperature, as follows: The actual oil temperature value of the oil is obtained from the fusion monitoring unit, and the sampling period is set. At each sampling moment, the temperature sensor collects the current actual oil temperature value; Then the actual oil temperature value collected is compared with the upper and lower limits of the target temperature range, and divided into a low temperature state and a high temperature state according to the comparison result; When in a low temperature state, the difference between the actual oil temperature and the lower limit of the target temperature range is calculated, and the proportional coefficient is adjusted according to the difference. The power adjustment amount can then be calculated according to the proportional control algorithm formula; When in a high temperature state, the degree to which the oil temperature exceeds the upper limit of the target temperature range is determined by calculating the difference between the actual oil temperature and the upper limit of the target temperature range. The integral time is determined based on the degree to which the oil temperature exceeds the upper limit, and then the integral control algorithm formula is used to calculate the heating power adjustment amount.

[0011] As a further improvement of the technical solution, the oil temperature control unit includes a load judgment module, which judges the working load of the oil filter according to the specific heat capacity of different oil products, the equipment operation history data and the oil flow rate, as follows: Get the specific heat capacity value of the current oil from the oil database Measure the oil flow rate through the flow sensor , and then use the energy conservation law formula to calculate the amount of heat absorbed by the oil per unit time; Then, the standard heat absorption per unit time is extracted from the equipment operation history data, and the actual heat absorption is compared with the standard heat absorption per unit time to obtain the difference. Finally, the workload coefficient is obtained by using the weighted average algorithm based on the difference.

[0012] As a further improvement of the technical solution, the vacuum pump operating frequency adjustment algorithm is based on the workload coefficient, as follows: Get the current working load factor of the vacuum pump , and set a high load threshold and low load threshold ; when When the vacuum pump is at a high temperature, the exponential growth algorithm is used to calculate the difference between the maximum vacuum degree of the vacuum pump and the current vacuum degree. The vacuum degree is the degree to which the gas pressure is lower than the atmospheric pressure. The exponential base is determined according to the difference. Then, the target operating frequency of the vacuum pump is calculated according to the exponential growth formula, and the operating frequency of the vacuum pump is adjusted to the target operating frequency of the vacuum pump. when When the vacuum pump is running at a constant speed, the target operating frequency of the vacuum pump is calculated according to the linear decreasing formula, and the operating frequency of the vacuum pump is adjusted to the target operating frequency of the vacuum pump.

[0013] As a further improvement of the technical solution, the feedback regulation unit constructs a comprehensive performance evaluation model based on the target operating frequency and heating power of the vacuum pump, and evaluates the stability of the current system according to the model, as follows: Obtain the target operating frequency and current heating power of the vacuum pump from the oil temperature control unit, set the time interval, and build a comprehensive performance evaluation model; The current specific heat capacity and mass flow rate of the oil and the change in oil temperature within a fixed time are extracted, and the system energy loss is calculated based on the law of conservation of energy. The stability coefficient is then calculated based on the system energy loss, and finally compared with the preset stability coefficient threshold to determine the current stability state of the system.

[0014] Compared with the prior art, the present invention has the following beneficial effects: In the sensor-based digital intelligent control system of the oil filter, the oil temperature control unit adopts an adaptive oil temperature control algorithm to accurately calculate the optimal heating rate and target temperature range, effectively avoiding the adverse effects of excessively high or low oil temperature on the equipment, greatly improving the stability and reliability of equipment operation, and extending the service life of the equipment. During the heating process, the oil temperature is continuously compared and the heater power is automatically adjusted to ensure that the oil temperature is always in an ideal state, thereby improving the quality of oil processing. At the same time, the operating frequency of the vacuum pump is adjusted according to the workload determined by various factors, thereby achieving rational use of energy and reducing energy consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is an overall block diagram of the present invention.

[0016] The meaning of each number in the figure is: 1. Fusion monitoring unit; 2. Oil temperature control unit; 21. Data processing module; 22. Analysis and calculation module; 23. Pulse heating module; 24. Load judgment module; 3. Feedback adjustment unit. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] The present invention provides a digital intelligent control system for oil filter based on sensors, please refer to Figure 1 As shown, it includes a fusion monitoring unit 1, an oil temperature control unit 2 and a feedback adjustment unit 3; The fusion monitoring unit 1 is composed of a fusion of multiple sensors, wherein the pressure sensor and the flow sensor are used to monitor the pressure and flow value of the oil in real time, and the temperature sensor is used to obtain the external environment temperature value and the oil temperature.

[0019] The oil temperature control unit 2 calculates the optimal heating rate and target temperature range according to the ambient temperature and the initial temperature of the oil using an adaptive oil temperature control algorithm. The oil temperature control unit 2 includes a data processing module 21, an analysis and calculation module 22, a pulse heating module 23 and a load judgment module 24.

[0020] The data processing module 21 is used to calculate the difference between the ambient temperature and the initial oil temperature in the adaptive oil temperature control algorithm, as follows: In the oil temperature control unit 2, the difference between the ambient temperature and the initial oil temperature is one of the key parameters for the subsequent calculation of the optimal heating rate and the target temperature range. The slight temperature measurement error will be amplified in the subsequent complex control algorithm, resulting in inaccurate oil temperature control and failure to meet the equipment's requirements for oil temperature accuracy.

[0021] Therefore, the temperature sensor is calibrated and tested in a laboratory environment in advance, that is, the actual output value of the sensor is recorded at different known standard temperature points. Based on these measurement data, a mathematical model of the temperature offset characteristic curve is established using the polynomial fitting method. The expression of the mathematical model is: ; Where y is the measurement error of the sensor, x is the measured temperature value, are the coefficients obtained by fitting to ensure that the model can describe the temperature offset characteristics of the sensor.

[0022] In actual operation, when the sensor obtains the ambient temperature value and initial oil temperature Then, substitute it into the mathematical model of the temperature offset characteristic curve to calculate the corresponding measurement error and .

[0023] Since the ambient temperature changes rapidly, the original measured value needs to be corrected to obtain the corrected ambient temperature value. and initial oil temperature Finally, calculate the difference between the corrected ambient temperature and the initial oil temperature In this way, the measurement error of the temperature sensor can be effectively reduced, and the accuracy of the calculation of the difference between the ambient temperature and the initial oil temperature can be improved, thereby providing more reliable basic data for the subsequent adaptive oil temperature control algorithm and ensuring the accuracy and stability of the entire oil temperature control process.

[0024] The method for calculating the optimal heating rate in the adaptive oil temperature control algorithm by the analysis and calculation module 22 is as follows: After completing the correction of the difference between the ambient temperature and the initial oil temperature, extract the difference between the corrected ambient temperature value and the initial oil temperature value. , and set the heating time to , based on the heat conduction formula ;in For heat, is the oil quality, The formula for the specific heat capacity and thermal power of oil is ; For the thermal power, an expression related to the heating rate can be preliminarily constructed, which provides a reasonable framework for the heating rate calculation.

[0025] Then the iterative calculation begins, initializing an estimate of the heating rate , in each iteration: Based on the current estimated heating rate and time step , calculate the estimated increase in oil temperature after this time step ; By estimating the heating effect and knowing the temperature change trend in advance, it is helpful to adjust the heating rate strategy in time.

[0026] Correction factor to take into account the change in oil heat capacity with temperature This coefficient can be obtained by fitting the experimental data of the heat capacity of the oil at different temperatures in advance, and correcting the estimated temperature rise value to obtain the corrected temperature rise value ,in The current oil temperature. The oil characteristics change with the temperature and need to be accurately corrected to improve the accuracy of temperature calculation and make the oil temperature control more in line with the actual oil conditions. The current oil temperature is updated according to the corrected temperature rise value. ;in For the updated oil temperature, follow up the temperature changes in real time to ensure that the calculation is based on the latest status, provide an accurate basis for subsequent judgment, and calculate the updated oil temperature and the lower limit of the target temperature range Distance The lower limit of the target temperature range is determined by the adaptive oil temperature control algorithm to obtain the target temperature range, which clarifies the gap with the target, facilitates measuring the heating progress, and helps to judge whether the expected heating effect is achieved.

[0027] if , then according to the iterative update formula Update the current estimated heating rate if , then the current estimated heating rate is the desired optimal heating rate, where is the preset temperature error range, The weight coefficient is obtained based on historical experience, and the optimal value is approximated through iteration, the calculation results are gradually optimized, and the optimal heating rate is accurately obtained to achieve efficient oil temperature control. The above iterative process is repeated until the convergence criterion is met, and finally the optimal heating rate that can make the oil temperature reach the target temperature range within the preset time is obtained, ensuring the reliability of the results and effectively ensuring the stable operation of the entire oil temperature control unit 2.

[0028] The analysis and calculation module 22 uses the adaptive oil temperature control algorithm to calculate the target temperature range, as follows: After obtaining the optimal heating rate, the target temperature range of this heating process needs to be limited. In the oil filter, too high oil temperature may cause aging of the seals, while too low oil temperature will increase the viscosity of the oil, increase the workload of the equipment, and reduce the filtration efficiency.

[0029] First, retrieve the viscosity-temperature characteristic curve data of the currently processed oil from the pre-stored oil database. Different oils have different viscosity-temperature characteristics. Calculation accuracy can be ensured based on specific oil data, providing an accurate oil characteristic basis for subsequent calculations.

[0030] Next, get the current ambient temperature value The ambient temperature will affect the heat dissipation of the oil. Obtaining its value can determine the target temperature range more in line with the actual working conditions, which helps to improve the adaptability of the entire oil temperature control system and make the calculated target temperature range more in line with the actual operating environment requirements.

[0031] Then, according to the design parameters and operation requirements of the equipment, the upper and lower limits of the oil temperature range corresponding to the optimal viscosity range of the equipment are determined and set as and This is because the equipment operates most efficiently and with minimal wear in a specific viscosity range. Determining the oil temperature range in this way can ensure the equipment operates well, effectively extend the service life of the equipment and improve the stability of its operation.

[0032] Then, on the viscosity-temperature characteristic curve, select the value that matches the current ambient temperature. Three close data points are set as points ,point And point ,in and , Represents viscosity. By using local data points, the calculation can be simplified and the viscosity-temperature relationship near the current ambient temperature can be better reflected. The amount of calculation is relatively small and the accuracy can meet the requirements, providing a suitable data basis for piecewise linear interpolation.

[0033] The piecewise linear interpolation algorithm is used for calculation. First, the value of the point To point And from point To point The equation of the straight line from point To point The equation of the straight line is set as ; where the slope ; Similarly, we can get from point To point The equation of the line , ;in is the current ambient temperature value, Points ,point And point The ambient temperature value, For point ,point And point The viscosity of Expressed as slope.

[0034] Set the lower limit of the equipment's optimal viscosity range Substitute into the above straight line equation and calculate the temperature values ​​corresponding to point 1 and point 2 respectively. and , if the temperature value obtained by substituting into the first linear equation is greater than , then discard the result and use the temperature value calculated by the second linear equation. Similarly, set the upper limit of the equipment's optimal viscosity range Substitute the straight line equation to calculate the temperature values ​​corresponding to points 3 and 4 and Finally, the target temperature range of this heating process is determined to be ,in , , Indicated as the lower limit of the target temperature range, Expressed as the upper limit of the target temperature range, the target temperature range is determined in this way, taking into account the oil characteristics, ambient temperature and equipment requirements, and can accurately determine the target temperature range that meets a variety of conditions, so that the oil temperature control can adapt to different oils and environments while ensuring the normal operation of the equipment, thereby improving the versatility and reliability of the system and ensuring that the entire oil system operates in the best condition.

[0035] During the heating process, the pulse heating module 23 continuously compares the actual oil temperature with the target temperature range to obtain the temperature state of the oil temperature, and automatically adjusts the heater power by pulse heating according to the temperature state of the oil temperature, as follows: First, a high-precision temperature sensor is set up to collect the actual oil temperature value of the oil, because accurate oil temperature measurement is the basis of the entire comparison algorithm. Its high-precision characteristics can provide a reliable data source for subsequent judgments, reduce the impact of measurement errors on control, and enable the system to grasp the actual oil temperature situation more accurately.

[0036] Next, the sampling period is set based on the preliminary analysis of the oil temperature change rate and the control accuracy required by the system. , at each sampling moment , For the At each sampling moment, the temperature sensor collects the actual oil temperature value , The actual oil temperature is then compared with the upper and lower limits of the target temperature range. When the oil temperature is low, the current oil temperature state is marked as low temperature state, and the direction of oil temperature deviation from the target range is clear, which is convenient for subsequent targeted heating control strategies, making the control logic clear and concise, and can quickly start the corresponding heating power enhancement mechanism to promote the oil temperature to rise. When the oil temperature is too high, the current oil temperature state will be marked as a high temperature state, and the oil temperature will be discovered in time so that cooling measures can be taken, enhancing the system's early warning capability for abnormally high temperatures, effectively preventing equipment damage or oil performance degradation caused by excessive oil temperature, and ensuring the safe and stable operation of the entire system.

[0037] When in low temperature state, calculate Lower limit of target oil temperature range The difference Only by clarifying the deviation can the adjustment range of the heating power be reasonably determined, so that the control is targeted and the heating power can be accurately increased according to the oil temperature conditions.

[0038] Then according to Dynamically adjust the scale factor ,in ; is a constant, the larger the difference, The larger the value, the greater the power increase is required to quickly compensate for the insufficient oil temperature. The heating intensity can be flexibly adjusted according to actual needs, and the oil temperature can be efficiently brought closer to the target range.

[0039] Next, according to the proportional control algorithm formula ; Calculate the heating power adjustment, is the heating power adjustment amount. The pulse width is adjusted according to this formula. Since the pulse width is proportional to the heating power, the power can be adjusted by changing the pulse width. The pulse signal can be used to accurately control the heating power, effectively heating the oil temperature under low temperature conditions, and gradually raising the oil temperature to the target range.

[0040] When in a high temperature state, first determine the extent to which the oil temperature exceeds the upper limit of the target temperature range, and calculate ; In order to measure the degree of excessive oil temperature in order to determine the appropriate power reduction strategy, different degrees of excess require different cooling rates, making the cooling control more adaptable and avoiding adverse effects on the system due to too fast or too slow cooling.

[0041] Determine the integral time according to the degree to which the oil temperature exceeds the upper limit , so that it can smoothly and effectively reduce the oil temperature and stabilize the oil temperature within the target range to ensure the normal operation of the system.

[0042] Adopting integral control algorithm formula ; Calculate the heating power adjustment, where The integral time variable is used to adjust the pulse width to reduce power. Through integral control, the oil temperature exceeding the limit within a period of time can be comprehensively considered to avoid excessive adjustment due to instantaneous fluctuations, and the oil temperature can be smoothly controlled under high temperature conditions, so that the oil temperature gradually falls back to the target range.

[0043] At the same time, the load judgment module 24 automatically judges the working load of the oil filter according to the specific heat capacity of different oil products, the equipment operation history data and the oil flow rate, and adjusts the operating frequency of the vacuum pump according to the load condition, as follows: First, obtain the specific heat capacity value of the oil being processed Then, the flow sensor accurately measures the oil flow value , using the energy conservation law formula ; Calculate the amount of heat absorbed by the oil per unit time , where the oil inlet and outlet temperature difference is The reason for the calculation based on the law of conservation of energy is to follow the principles of physics to ensure the scientific nature of the calculation, accurately reflect the energy absorption of the oil, and obtain the heat absorption data that is closely related to the actual working conditions.

[0044] Then, the standard heat absorption per unit time is extracted from the equipment operation history data storage module , the calculated heat absorption per unit time Standard heat absorption per unit time Compare and get the difference ; Comparing the difference can directly reflect the degree of deviation between the current heat absorption and the standard situation, which is a key step in judging the workload change. Measuring the workload change through the deviation can simply and directly reflect the workload status and provide effective data input for the subsequent weighted average algorithm.

[0045] Finally, the workload coefficient is obtained by using the weighted average algorithm The weighted average algorithm is conducive to comprehensively judging the workload based on multiple factors, avoiding the one-sidedness of single factor judgment, and obtaining a coefficient that can accurately reflect the comprehensive workload of the oil filter, so as to reasonably adjust the operating frequency of the vacuum pump according to this coefficient to ensure efficient and stable operation of the equipment.

[0046] Among them, the vacuum pump operating frequency adjustment algorithm is based on the workload factor, as follows: Get the current vacuum pump workload factor , and set a high load threshold and low load threshold , clarify the workload limits in order to determine when the vacuum pump operating frequency needs to be adjusted and what adjustment strategy to adopt, to ensure that the vacuum pump operates within the appropriate workload range and avoid overwork or underwork.

[0047] when When calculating the maximum vacuum degree of the vacuum pump, first calculate The current vacuum The difference ; Determine the exponent base based on this difference , ; It is a functional relationship determined according to the characteristics of the equipment. The reason for determining the base number in this way is that a larger difference means that the performance of the vacuum pump needs to be improved more significantly to cope with high loads. The exponential growth algorithm can quickly increase the operating frequency of the vacuum pump and quickly enhance the vacuum pump's exhaust capacity under high loads to meet the system's vacuum requirements under high load conditions.

[0048] Then according to the exponential growth formula ; Calculate the target operating frequency of the vacuum pump , and adjust the current vacuum pump operating frequency to the target operating frequency of the vacuum pump ,in is the initial operating frequency of the vacuum pump, is a time-dependent variable.

[0049] when Calculate the minimum stable operating vacuum degree of the vacuum pump The current vacuum The difference , according to this difference, the decreasing slope of the linear decreasing algorithm is determined , , It is a functional relationship determined according to the characteristics of the equipment. The reason for determining the slope is that a larger difference means that the vacuum pump can reduce the operating frequency more significantly to save energy and reduce wear. The operating frequency of the vacuum pump can be smoothly reduced under low load. While meeting the basic vacuum requirements of the system, it reduces equipment energy consumption and operating noise, and extends the service life of the vacuum pump.

[0050] Finally, according to the linear decreasing formula ; Calculate the target operating frequency of the vacuum pump ,in is a time variable, and adjusts the current operating frequency of the vacuum pump to the target operating frequency of the vacuum pump .

[0051] The feedback adjustment unit 3 obtains the target operating frequency of the vacuum pump from the oil temperature control unit 2 And heating power adjustment At the same time, set the time interval for data collection , in order to obtain enough data points to accurately evaluate system performance.

[0052] Next, a comprehensive performance evaluation model is constructed. To determine the system stability evaluation index, a stability coefficient is defined based on energy balance and equipment operation characteristics. , which is calculated with the operating power of the vacuum pump , Heating power adjustment And it is related to the thermophysical properties of the oil. Assume that the specific heat capacity of the oil is , the mass flow rate is , the oil temperature change over a period of time is , according to the law of conservation of energy , quantifying system stability through mathematical relationships can provide early warning of unstable conditions and provide a scientific basis for system optimization.

[0053] Then, the real-time collected vacuum pump operating frequency and heating power data are substituted into the constructed model to calculate the current stability coefficient. , by comparing with the preset stability threshold Compare and judge the current stability of the system. , the system is in a stable state if , it is determined that the system needs to be optimized and adjusted to ensure the continuous and efficient operation of the system. Finally, an optimization adjustment strategy is generated based on the evaluation results and sent to the oil temperature control unit 2.

[0054] In the present invention, a fusion monitoring unit 1 uses multiple sensors to monitor the oil pressure, flow rate and temperature. The oil temperature control unit 2 calculates the optimal heating rate and target temperature range according to the environment and the initial temperature of the oil through an adaptive algorithm, compares the oil temperature during heating, adjusts the power by pulse heating according to the state, and adjusts the vacuum pump frequency according to the workload determined by the specific heat capacity of the oil. The feedback adjustment unit 3 evaluates the system stability based on the vacuum pump frequency and heating power, generates an optimization strategy and sends it back to the oil temperature control unit 2, so as to realize accurate control of the oil temperature, improve the stability of the equipment and the energy utilization efficiency, and ensure the efficient operation of the oil filter.

[0055] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and descriptions are only preferred examples of the present invention and are not intended to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A digital intelligent control system for oil filter based on sensors, characterized in that: It comprises a fusion monitoring unit (1), an oil temperature control unit (2) and a feedback adjustment unit (3); The fusion monitoring unit (1) is composed of a fusion of multiple sensors, wherein the pressure sensor and the flow sensor are used to monitor the pressure and flow value of the oil in real time, and the temperature sensor is used to obtain the external environment temperature value and the oil temperature; The oil temperature control unit (2) calculates the optimal heating rate and target temperature range using an adaptive oil temperature control algorithm based on the ambient temperature and the initial temperature of the oil. During the heating process, the actual oil temperature is continuously compared with the target temperature range to obtain the temperature state of the oil temperature. According to the temperature state of the oil temperature, the heater power is automatically adjusted using a pulse heating method. At the same time, the workload of the oil filter is automatically determined based on the specific heat capacity of different oil products, the equipment operation history data, and the oil flow rate. The operating frequency of the vacuum pump is adjusted according to the load condition to obtain the target operating frequency of the vacuum pump. The feedback regulation unit (3) constructs a comprehensive performance evaluation model based on the target operating frequency and heating power of the vacuum pump, and evaluates the stability of the current system based on the model. Finally, an optimization adjustment strategy is generated based on the evaluation results and sent to the oil temperature control unit (2).

2. The sensor-based digital intelligent control system for oil filter according to claim 1 is characterized in that: The oil temperature control unit (2) comprises a data processing module (21), wherein the data processing module (21) is used to calculate the difference between the ambient temperature and the initial temperature of the oil in the adaptive oil temperature control algorithm, specifically as follows: Use the temperature sensor to collect the ambient temperature and the initial temperature of the oil, and calculate their initial difference; A temperature offset characteristic curve is set, wherein the temperature offset characteristic curve is used to describe the performance change of the oil under different temperature conditions, and the ambient temperature and the initial temperature of the oil are corrected using the temperature offset characteristic curve, and the difference between the corrected ambient temperature and the initial temperature of the oil is recalculated.

3. The sensor-based digital intelligent control system for oil filter according to claim 2 is characterized in that: The oil temperature control unit (2) comprises an analysis and calculation module (22), wherein the analysis and calculation module (22) calculates the optimal heating rate in the adaptive oil temperature control algorithm in the following manner: Determine the oil quality, heat transfer area, heat transfer distance and initial oil specific heat capacity based on the equipment data, obtain the temperature difference from the data processing module (21), finally set the heating time and target temperature range, and calculate the difference between the target temperature and the initial temperature; Preset the initial heating rate and start the iterative cycle. Calculate the temperature change according to the current heating rate and heating time. Then calculate the current specific heat capacity according to the current temperature and the formula of oil specific heat capacity changing with temperature. Substitute it into the heat conduction formula to calculate the estimated heat transfer amount. Finally, calculate the theoretical heat demand. Compare the estimated heat transfer with the theoretical heat demand and obtain the optimal heating rate based on the comparison results.

4. The sensor-based digital intelligent control system for oil filter according to claim 3 is characterized in that: The analysis and calculation module (22) uses the adaptive oil temperature control algorithm to calculate the target temperature range, specifically as follows: Extract the viscosity-temperature characteristic curve data of the current oil and the current ambient temperature from the oil database, and set the upper and lower limits of the oil temperature range corresponding to the optimal viscosity range of the equipment operation; On the viscosity-temperature characteristic curve, three data points adjacent to the current ambient temperature value are selected, and the piecewise linear interpolation algorithm is used for calculation to obtain the straight line equation between the points. The upper and lower limits of the equipment's optimal viscosity range are substituted into the above straight line equation respectively, and the corresponding temperature value is calculated. Finally, the target temperature range of this heating process is determined accordingly.

5. The sensor-based digital intelligent control system for oil filter according to claim 4 is characterized in that: The oil temperature control unit (2) comprises a pulse heating module (23), and the pulse heating module (23) automatically adjusts the heater power by pulse heating according to the temperature state of the oil temperature, specifically as follows: The actual oil temperature value of the oil is obtained from the fusion monitoring unit (1), and a sampling period is set. At each sampling moment, the temperature sensor collects the current actual oil temperature value; Then the actual oil temperature value collected is compared with the upper and lower limits of the target temperature range, and divided into a low temperature state and a high temperature state according to the comparison result; When in a low temperature state, the difference between the actual oil temperature and the lower limit of the target temperature range is calculated, and the proportional coefficient is adjusted according to the difference. The power adjustment amount can then be calculated according to the proportional control algorithm formula; When in a high temperature state, the degree to which the oil temperature exceeds the upper limit of the target temperature range is determined by calculating the difference between the actual oil temperature and the upper limit of the target temperature range. The integral time is determined based on the degree to which the oil temperature exceeds the upper limit, and then the integral control algorithm formula is used to calculate the heating power adjustment amount.

6. The sensor-based digital intelligent control system for oil filter according to claim 1 is characterized in that: The oil temperature control unit (2) comprises a load judgment module (24), wherein the load judgment module (24) judges the working load of the oil filter according to the specific heat capacity of different oil products, equipment operation history data and oil flow rate, specifically as follows: Get the specific heat capacity value of the current oil from the oil database Measure the oil flow rate through the flow sensor , and then use the energy conservation law formula to calculate the amount of heat absorbed by the oil per unit time; Then, the standard heat absorption per unit time is extracted from the equipment operation history data, and the actual heat absorption is compared with the standard heat absorption per unit time to obtain the difference. Finally, the workload coefficient is obtained by using the weighted average algorithm based on the difference.

7. The sensor-based digital intelligent control system for oil filter according to claim 6 is characterized in that: The operating frequency adjustment algorithm of the vacuum pump is based on the workload factor, as follows: Get the current vacuum pump workload factor , and set a high load threshold and low load threshold ; when When the vacuum pump is at a certain temperature, the exponential growth algorithm is used to calculate the difference between the maximum vacuum degree of the vacuum pump and the current vacuum degree. The vacuum degree is the degree to which the gas pressure is lower than the atmospheric pressure. The exponential base is determined according to the difference. Then, the target operating frequency of the vacuum pump is calculated according to the exponential growth formula, and the current operating frequency of the vacuum pump is adjusted to the target operating frequency of the vacuum pump. when When the vacuum pump is running at a constant speed, the target operating frequency of the vacuum pump is calculated according to the linear decreasing formula, and the current operating frequency of the vacuum pump is adjusted to the target operating frequency of the vacuum pump.

8. The sensor-based digital intelligent control system for oil filter according to claim 1 is characterized in that: The feedback regulation unit (3) constructs a comprehensive performance evaluation model based on the target operating frequency and heating power of the vacuum pump, and evaluates the stability of the current system according to the model, as follows: Obtaining the target operating frequency and current heating power of the vacuum pump from the oil temperature control unit (2), setting a time interval, and constructing a comprehensive performance evaluation model; The current specific heat capacity and mass flow rate of the oil and the change in oil temperature within a fixed time are extracted, and the system energy loss is calculated based on the law of conservation of energy. The stability coefficient is then calculated based on the system energy loss, and finally compared with the preset stability coefficient threshold to determine the current stability state of the system.

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