Production line vacuum pump energy-saving control method based on vacuum degree feedback and PI algorithm

Abstract

The invention belongs to the technical field of vacuum pump control, and relates to a production line vacuum pump energy-saving control method based on vacuum degree feedback and a PI algorithm. A stability index is constructed based on the vacuum change rate, the effective deviation and the vibration intensity to divide the system state, and the proportion and integral gain of the PI algorithm are dynamically adjusted according to the system state, the effective deviation and the temperature influence coefficient, so that the control parameters can adapt to different states and temperature interference of the system. The problem of response lag or overshoot of a traditional fixed parameter PI algorithm during working condition fluctuation is solved, and the working condition adaptability is improved; and finally, overshoot is avoided by adjusting an integral term, energy efficiency optimization constraints are superposed, and on the premise that surge and temperature safety threshold values are met, unnecessary high-frequency operation is limited, and redundant energy consumption under a stable working condition is reduced.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of vacuum pump control, and more particularly to a production line vacuum pump energy-saving control method based on vacuum degree feedback and PI algorithm. BACKGROUND

[0002] In modern industrial production lines such as semiconductor manufacturing, precision electronics, pharmaceuticals, and food packaging, a vacuum environment is a core condition for process precision and product quality. As the power source of the vacuum system, the energy consumption of the vacuum pump accounts for 20%-35% of the total energy consumption of the production line, making it a key object of industrial energy saving. To maintain a stable process vacuum degree, the vacuum pump usually uses closed-loop feedback control. Proportional-integral control, with its simple structure and strong robustness, has become the mainstream control strategy.

[0003] The current production line vacuum pump control system drives the variable frequency motor to adjust the speed through fixed proportional gain and integral gain to achieve stable vacuum degree. However, in actual industrial scenarios, the vacuum degree demand of the production line process varies dynamically with batch and process. The traditional PI controller uses fixed parameters, which is difficult to match the load characteristics of different vacuum degree intervals. For example, when the vacuum degree switches from low vacuum to high vacuum, a fixed high proportional gain can easily cause the motor speed to surge, causing the vacuum degree to overshoot, which requires additional energy consumption to pull back the vacuum degree through high-speed operation. In low load, a fixed integral gain can cause the integral term to accumulate continuously, resulting in the motor maintaining a higher speed than necessary, causing low load and high energy consumption. SUMMARY

[0004] The present application provides a production line vacuum pump energy-saving control method based on vacuum degree feedback and PI algorithm, which aims to solve the technical problems of poor working condition adaptability and serious energy consumption redundancy caused by the current vacuum pump control method.

[0005] The production line vacuum pump energy-saving control method based on vacuum degree feedback and PI algorithm includes the following steps: S1. Collect the current signal of the vacuum gauge tube, the voltage signal of the vibration sensor, and the pump body temperature signal, and preprocess the collected signals to obtain the actual vacuum degree, vibration intensity, and pump body temperature; S2. Dynamically adjust the dead zone width according to the deviation between the preset vacuum degree and the actual vacuum degree, and then extract the effective deviation based on the absolute value of the deviation between the actual vacuum degree and the set vacuum degree and the dead zone width. Then, calculate the vacuum change rate based on the current actual vacuum degree and the actual vacuum degree of the last period, and calculate the temperature influence coefficient based on the body temperature; S3. Weight and sum the absolute value of the vacuum change rate, the absolute value of the effective deviation, and the vibration intensity to obtain a stability index, and divide the system state based on the stability index; S4. Dynamically adjust the proportional gain and integral gain based on the divided system state, the effective deviation, and the temperature influence coefficient; S5. Adjusting the integral term according to the effective deviation size and the integral accumulation value state, and then summing the proportional term and the integral term to obtain a preliminary output frequency; S6. Building a surge protection constraint, a temperature protection constraint and an energy efficiency optimization constraint to constrain the preliminary calculation frequency to obtain a final execution frequency.

[0006] The application avoids invalid control actions under small deviations by collecting vacuum degree, vibration intensity and body temperature to realize real-time sensing of current working condition deviation, and quantifies the dynamic characteristics of working conditions by calculating the vacuum change rate and the temperature influence coefficient to improve the sensing accuracy of complex working conditions. Secondly, a stability index division system state is constructed based on the vacuum change rate, the effective deviation and the vibration intensity, and the proportional and integral gains of the PI algorithm are dynamically adjusted according to the system state, the effective deviation and the temperature influence coefficient, so that the control parameters can adapt to different states such as system stability / dynamic adjustment and temperature interference, solving the problem of response lag or overshoot of the traditional fixed parameter PI algorithm under working condition fluctuation and improving the working condition adaptability. Finally, the integral term is adjusted to avoid overshoot, and the energy efficiency optimization constraint is superimposed to limit unnecessary high-frequency operation under the premise of meeting the surge and temperature safety threshold, reduce the redundant energy consumption under stable working conditions; at the same time, the design of dynamic dead zone reduces the frequent adjustment under small deviation, further reduces the invalid energy consumption.

[0007] Preferably, obtaining the actual vacuum degree comprises the following steps: An analog-to-digital conversion is performed on the current signal collected by the vacuum gauge to obtain a vacuum degree original value; then Kalman filtering is performed on the vacuum degree original value to obtain a filtered vacuum degree value; during the Kalman filtering process, the process noise is increased when the vacuum degree change rate increases; and the observation noise is increased when the vibration intensity increases. The original vacuum degree values of the last n sampling points are taken to obtain an arithmetic mean trend value of the original signal; if the vibration intensity is less than or equal to a preset threshold, the Kalman filtered vacuum degree value is directly used as the actual vacuum degree output; if the vibration intensity is greater than the preset threshold, the Kalman filtered vacuum degree value and the trend value of the original signal are weighted and summed to obtain a fusion vacuum degree as the actual vacuum degree output.

[0008] Preferably, the dynamic adjustment of the dead zone width comprises: The dead zone width is obtained by adding the absolute value of the deviation to the base dead zone width multiplied by an adjustment coefficient; wherein the absolute value of the deviation is the absolute value of the difference between the current actual vacuum degree and the set vacuum degree.

[0009] Preferably, the extraction of the effective deviation comprises the following steps: If the absolute value of the deviation between the actual vacuum degree and the set vacuum degree is less than the dead zone width, it is considered that the deviation is within the allowable range, and the effective deviation is set to 0; otherwise, the effective deviation is equal to the set vacuum degree minus the actual vacuum degree, and the negative value represents insufficient vacuum, and the positive value represents excessive vacuum.

[0010] Preferably, the system state includes a stable state, a disturbance state, and a high-risk state. When the stability index is less than a first stability threshold, the system state is the stable state; when the stability index is less than a second stability threshold, the system state is the disturbance state, wherein the first stability threshold is less than the second stability threshold. When the stability index is greater than or equal to the second stability threshold, the system state is the high-risk state, wherein the high-risk state is divided into a surge risk and a mutation state. If the vibration intensity is greater than the intensity threshold and the absolute value of the vacuum change rate is greater than the change rate threshold, the system state is the surge risk, otherwise, the system is the mutation state.

[0011] Preferably, the step S4 includes the following steps: When the system state is the stable state, the proportional gain is reduced, and the integral gain is increased. When the system state is the disturbance state, the proportional gain is increased, and the integral gain is reduced. When the system state is the surge risk, the proportional gain is reduced by a fixed proportion, and the integral gain is minimized. When the system state is the mutation state, the proportional gain is increased, and the maximum value of the integral gain is limited. Based on the corresponding system state, the corresponding proportional integral calculation method is selected to obtain the preliminary adjusted proportional gain and the integral gain; then the preliminary proportional gain is multiplied by the temperature influence coefficient to obtain the adjusted proportional gain, and the preliminary integral gain is divided by the temperature coefficient to obtain the adjusted integral gain.

[0012] Preferably, the adjusted integral term is to stop the integral when there is a large deviation, to decay the integral value when the integral is saturated, and to normally update the integral under normal conditions. When the absolute value of the effective deviation is greater than the threshold, it is considered as the large deviation, and the use of the integral term is stopped. When the absolute value of the historical integral is greater than the threshold, it is considered that the integral is saturated, and the integral value decay operation is performed. If it does not belong to the above conditions, it is considered that it is under normal conditions, and the integral is updated by accumulating the product of the current deviation and the time step. Based on the determined integral term and the proportional term, the output frequency is calculated to obtain the preliminary output frequency.

[0013] Preferably, the surge protection constraint sets a lower limit on the frequency base by dynamically setting the vibration intensity, and adds a safety margin value to the lower limit of the frequency base to obtain an absolute minimum frequency; Temperature protection constraint: limit the maximum operating frequency based on the body temperature, by setting a temperature threshold, when the pump body temperature is less than or equal to the temperature threshold, the frequency is the upper limit of the working frequency; if the pump body temperature is greater than the temperature threshold, the maximum frequency decreases by nHz for every 1 degree Celsius increase; based on this, the maximum frequency under temperature constraint is obtained; Energy efficiency optimization constraint: according to the deviation ratio of the set vacuum degree and the actual vacuum degree, the theoretical frequency that meets the vacuum demand is calculated, and a predetermined proportion of margin is added to the theoretical frequency to obtain the upper limit of the energy efficiency optimization frequency.

[0014] Preferably, the final execution frequency is obtained based on the following steps: Based on the preliminary output frequency and the absolute minimum frequency, the maximum value is selected to obtain the first candidate value; Based on the maximum frequency under temperature constraint and the upper limit of the energy efficiency optimization frequency, the minimum value is selected to obtain the second candidate value; The theoretical demand frequency is taken as the third candidate value; The first, second and third candidate values are sorted, and the middle value is taken as the final execution frequency.

[0015] The beneficial effects of the present application include: The present application collects the vacuum degree, vibration intensity and body temperature, and perceives the current working condition deviation in real time, avoids invalid control actions under small deviation, calculates the vacuum change rate and temperature influence coefficient, quantifies the dynamic characteristics of the working condition, improves the perception accuracy of complex working conditions, secondly, based on the vacuum change rate, effective deviation and vibration intensity, a stability index is constructed to divide the system state, and according to the system state, effective deviation and temperature influence coefficient, the proportional and integral gain of the PI algorithm is dynamically adjusted, so that the control parameters can adapt to different states such as system stability / dynamic adjustment and temperature disturbance, solving the problem of response lag or overshoot of traditional fixed parameter PI algorithm under working condition fluctuation, improving the working condition adaptability; finally, by adjusting the integral term to avoid overshoot, and superimposing the energy efficiency optimization constraint, under the premise of meeting the surge and temperature safety threshold, unnecessary high frequency operation is limited, and redundant energy consumption under stable working condition is reduced; at the same time, the design of dynamic dead zone reduces the frequent adjustment under small deviation, further reducing the invalid energy consumption. BRIEF DESCRIPTION OF DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creating labor.

[0017] Figure 1 The overall step block diagram provided for the embodiment of the present application.

[0018] Figure 2 The step block diagram of step S1 provided for the embodiment of the present application. DETAILED DESCRIPTION

[0019] In order to make the technical problems, technical solutions and beneficial effects to be solved in the present application more clear and explicit, the present application will be further described in detail below in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and do not limit the present application.

[0020] Referring to Figure 1 As shown in the figure, the energy-saving control method of the production line vacuum pump based on the vacuum degree feedback and the PI algorithm comprises the following steps: S1. Collecting the current signal of the vacuum gauge tube, the voltage signal of the vibration sensor and the pump body temperature signal, and pre-processing the collected signals to obtain the actual vacuum degree, vibration intensity and pump body temperature; Referring to Figure 2 As shown in the figure, in the present embodiment, analog-to-digital conversion is first performed, and the signals collected by the vacuum gauge tube, the vibration sensor and the PT100 platinum resistance sensor are respectively converted into the vacuum degree original value, the vibration intensity and the pump body temperature; wherein the vibration sensor is used to collect the vibration signal of the pump body; In the present embodiment, Kalman filtering is adopted to filter the vacuum degree original value to obtain the smoothed vacuum degree filtered value, which is specifically as follows: Assuming that the vacuum degree change is a first-order inertia process, the state quantity represents the current vacuum degree, the state transition matrix represents the process noise , and the state equation is as follows: ; in the formula: represents the state quantity at the current time, and represents the vacuum degree at k time; represents the state quantity at the last time; represents the state transition matrix; process noise; The observation equation is that the observation value is , the observation matrix , and the observation noise : in the formula: represents the observation value at k time; represents the observation matrix;

[0021] represents the observation noise; In the present embodiment, the vacuum degree change rate , dynamically adjusting process noise covariance , the greater the rate of change of vacuum, the greater the process noise covariance: According to the vibration intensity adjust the observation noise covariance , the greater the vibration intensity, the greater the observation noise covariance: In this embodiment, the rate of change of vacuum can be seen from step S2, since steps S1 to S6 of the present application are constantly iterated, the vacuum change rate here can be the vacuum change rate obtained in step S2 in the last iteration.

[0022] Based on the above Kalman filtering, the filtered vacuum is obtained, and when the vibration intensity exceeds the threshold, the confidence of the Kalman filtering result needs to be reduced, and the moving average of the original signal is introduced as an auxiliary to avoid distortion of the single filtering result, as follows: The original value of the vacuum is averaged by a sliding window (window size N=5, i.e. the average of the last 5 sampling points, the sampling interval is determined by the timestamp t): In the formula: represents the original value of the vacuum in the i-th time window; represents the trend value of the original signal; When the vibration intensity , the filtered vacuum output by the Kalman filter is directly used as the actual vacuum; When the vibration intensity , the filtered vacuum output by the Kalman filter and the trend value of the signal are weighted and summed, as follows: In the formula: represents the fusion vacuum, which is used as the actual vacuum; represents the vacuum output by the Kalman filter.

[0023] S2. According to the deviation between the preset vacuum and the actual vacuum, the dead zone width is dynamically adjusted, and then the effective deviation is extracted based on the absolute value of the deviation between the actual vacuum and the set vacuum and the dead zone width; then the vacuum change rate is calculated according to the current actual vacuum and the actual vacuum of the last period, and the temperature influence coefficient is calculated based on the body temperature; Dead zone width calculation: In the formula: represents the dynamic dead zone width; is the set basic dead zone width; is the dead zone scaling factor; ​​​​​represents a set vacuum degree; represents an actual vacuum degree; The dead zone width is dynamically adjusted to avoid the control system being too sensitive at small deviation, and to properly relax the dead zone to enhance stability at large deviation, and the dead zone width increases with the increase of the absolute value of the deviation, which meets the engineering requirement that the control action should be reduced when the deviation is large, for example, to prevent oscillation caused by sudden change of the vacuum degree.

[0024] Based on the dynamic dead zone, the effective control deviation is calculated, when the deviation is within the dead zone, the zero deviation is returned to avoid triggering the control action by slight fluctuation, otherwise, the real deviation is returned for subsequent PI control, and the effective deviation expression is as follows: ; In the formula: represents the effective deviation; The rate of change of the vacuum degree is calculated according to the following formula: ; In the formula: represents the rate of change of the vacuum degree; represents the actual vacuum degree at the current time point; represents the actual vacuum degree at the last sampling time point; The temperature influence coefficient is used to quantify the influence of the pump body temperature on the control gain, and is used for temperature compensation in fuzzy self-adaptive adjustment. When the temperature rises, the system gain changes, and the temperature coefficient is used as a compensation coefficient to ensure that the PI parameters adapt to temperature changes, and the calculation formula of the temperature influence coefficient is as follows: ; In the formula: represents the temperature influence coefficient; represents the pump body temperature; and 40 is the set reference temperature.

[0025] S3. The absolute values of the vacuum change rate, the effective deviation and the vibration intensity are weighted and summed to obtain a stability index, and the system state is divided based on the stability index; The calculation formula of the stability index is as follows: ; In the formula: represents the stability index; is a weight coefficient of the vacuum change rate, and is 0.6; is a weight coefficient of the effective deviation, and is 0.3; is a weight coefficient of the vibration intensity, and is 0.1; The current state of the system is determined based on the value of the stability index, and the details are as follows: If the value of the stability index is less than 0.8, the system is in a stable state, indicating that the fluctuation, deviation and vibration are small, and the system runs smoothly. If the value of the stability index is less than 2.5, the system is in a perturbed state, indicating a moderate level of fluctuation and deviation, the system receives interference but is not out of control; If the value of the stability index is greater than or equal to 2.5, the system is in a high-risk state, and if it is in a high-risk state, it needs to be determined whether the system is in a surge risk or a catastrophe state, as follows: If the vibration intensity is greater than 40 and is greater than 5, the system is in a surge risk, where surge is a dangerous state of the pump system involving severe pressure and flow oscillation; otherwise, the system is in a catastrophe state, indicating that the system parameters change rapidly or substantially, but do not meet the surge conditions.

[0026] S4. Dynamically adjusting the proportional gain and integral gain based on the divided system state, effective deviation, and temperature influence coefficient; In this embodiment, a fuzzy-PI fusion mechanism is introduced, and PI parameters are adapted to different working conditions through a fuzzy rule base and temperature compensation, so as to improve the response speed, stability and robustness of the system, as follows: Four states are included in the fuzzy rule base, namely stable state, perturbed state, surge risk and catastrophe state; When the system is in a stable state, the proportional gain is reduced to reduce overshoot, and the integral gain is increased to eliminate steady-state error, wherein the adjustment formula of the proportional gain is as follows: ; In the formula: represents the proportional gain before temperature compensation; represents the basic proportional gain, with a value of 0.5; represents the effective deviation; The adjustment formula of the integral gain is as follows: ; In the formula: represents the integral gain before temperature compensation; represents the basic integral gain, with a value of 0.1; When the system is in a perturbed state, the proportional gain is increased to quickly suppress the deviation, and the integral gain is reduced to avoid integral saturation, wherein the adjustment formula of the proportional gain is as follows: ; The adjustment formula of the integral gain is as follows: ; In this embodiment, when the system is in a perturbed state, the integral gain is directly set to 60% of the basic integral gain to reduce the integral effect and prevent oscillation under disturbance.

[0027] When the system is in a surge risk state, conservative parameters are used to avoid triggering surge, wherein the adjustment formula of the proportional gain is as follows: ; By setting the proportional gain to 20% of the base integral gain, the proportional action is greatly reduced, making the control more gentle; The adjustment formula of the integral gain is as follows: ; By setting the integral gain to 10% of the base integral gain, the integral action is minimized to avoid rapid accumulation of errors; When the system is in a mutation state, the proportional gain is increased while the integral gain is limited to prevent overshoot, as follows: Proportional gain calculation and limitation: ; Integral gain calculation and limitation: ; In this embodiment, the response is enhanced by a base gain of 2.5, and the instability caused by excessive gain is avoided by a limit of 3.0; secondly, the basic integral action is ensured by the minimum integral gain to avoid excessive gain.

[0028] After the above steps, the preliminary adjusted proportional gain and integral gain are obtained, and further adjustment is made through the temperature influence coefficient to obtain the final proportional gain and integral gain, wherein the adjustment formula of the proportional gain is as follows: ; In the formula: is the dynamically adjusted proportional gain; represents the temperature influence coefficient; when the temperature is greater than 40℃, is greater than 1, increases, enhancing the control strength at high temperature; when the temperature is less than 40℃, is less than 1, decreases, avoiding overshoot at low temperature; The adjustment formula of the integral gain is as follows: ; In the formula: is the dynamically adjusted integral gain; In this embodiment, at high temperature decreases to prevent rapid integration, and at low temperature increases to accelerate error elimination.

[0029] S5. Adjust the integral term according to the effective deviation size and integral accumulation value state, and then sum the proportional term and the integral term to obtain the preliminary output frequency; In this embodiment, the integral term is dynamically adjusted according to the deviation size, i.e. the integral is disabled when the deviation is large, the integral value is attenuated when the integral is saturated, and the integral is updated under normal conditions, as follows: Condition 1: When the absolute value of the effective deviation is greater than the threshold value (5kPa), indicating that the deviation is too large, the integral term is disabled at this time to avoid overshoot or oscillation caused by integral; Condition 2: when the absolute history integral is greater than a preset threshold (50 kPa·s), indicating that the integral is saturated, the integral value is decayed to avoid the control system rigid; wherein the absolute history integral is the cumulative integral of the deviation

[0030]

[0031] S6. Build a surge protection constraint, temperature protection constraint and energy efficiency optimization constraint, and constrain the preliminary calculation frequency to obtain the final execution frequency.

[0032] Surge protection constraint: dynamically adjust the frequency lower limit according to the vibration intensity to prevent the pump from surging, and when the vibration is too high, increase the minimum frequency to enhance the system stability, the specific steps are as follows: First, calculate the basic frequency lower limit: That is, when the vibration intensity is greater than 40, it is a high vibration risk, at this time the basic frequency lower limit is set to 30Hz, and the lower limit is increased to avoid surging; otherwise, set the basic frequency lower limit to 25Hz; Absolute minimum frequency calculation

[0033] ​​​​​​​​​​​​​​​​​​​​​​​Temperature protection constraint: limit the maximum frequency based on the pump body temperature to prevent overheating damage, when the temperature exceeds the threshold, linearly reduce the frequency to control the heat load, the specific calculation formula is as follows: ; In the formula: Indicates the maximum frequency limited by the pump body temperature; Indicates the pump body temperature; Energy efficiency optimization constraint: optimize the frequency based on the vacuum demand to improve energy efficiency, through the theoretical demand frequency and the upper limit of energy efficiency, ensure that the system meets the performance while reducing energy consumption, specifically, the calculation formula of the theoretical demand frequency is as follows: ; In the formula: Indicates the theoretical demand frequency; Indicates the set vacuum degree; Indicates the fusion vacuum degree, i.e. the actual vacuum degree; The upper limit of energy efficiency optimization frequency is determined based on the theoretical demand frequency: ; In the formula: Indicates the upper limit of energy efficiency optimization frequency; Based on the above three constraints and the frequency output in step S5, the final execution frequency is generated, first generate three candidate frequencies, as follows: Candidate frequency 1: ; Candidate frequency 2: ; Candidate frequency 3: ; Median fusion: ; Sort the candidate frequencies 1 to 3, and take the middle value as the final execution frequency.

[0034] The present application collects vacuum degree, vibration intensity and body temperature, real-time perceives current working condition deviation, avoids invalid control action under small deviation, at the same time calculates vacuum change rate and temperature influence coefficient, quantifies working condition dynamic characteristics, improves the perception accuracy of complex working conditions, secondly, based on vacuum change rate, effective deviation and vibration intensity, a stability index is constructed to divide system state, and according to system state, effective deviation and temperature influence coefficient, the proportional and integral gain of PI algorithm is dynamically adjusted, so that the control parameters can adapt to different states and temperature interference of system stability / dynamic adjustment, solve the problem of response lag or overshoot of traditional fixed parameter PI algorithm under working condition fluctuation, improve the working condition adaptability; finally, by adjusting the integral term to avoid overshoot, and superimposing the energy efficiency optimization constraint, under the premise of meeting the surge and temperature safety threshold, unnecessary high frequency operation is limited, and redundant energy consumption under stable working condition is reduced; at the same time, the design of dynamic dead zone reduces the frequent adjustment under small deviation, further reduces the invalid energy consumption.

[0035] The above merely provides the preferred embodiment of the present application, and not intended to limit the present application. Accordingly, any modification, equivalent replacement and improvement made without departing from the spirit and principle of the present application shall fall in the scope of protection of the present application.

Claims

1. A line vacuum pump energy-saving control method based on vacuum degree feedback and PI algorithm, characterized in that, The method comprises the following steps: S1. Collecting the current signal of the vacuum gauge tube, the voltage signal of the vibration sensor and the pump body temperature signal, and pre-processing the collected signals to obtain the actual vacuum degree, vibration intensity and pump body temperature; S2. Dynamically adjusting the dead zone width according to the deviation between the preset vacuum degree and the actual vacuum degree, and then extracting the effective deviation based on the absolute value of the deviation between the actual vacuum degree and the set vacuum degree and the dead zone width; then calculating the vacuum change rate according to the current actual vacuum degree and the actual vacuum degree of the last cycle, and calculating the temperature influence coefficient based on the body temperature; S3. Weighted sum of the absolute value of the vacuum change rate, the absolute value of the effective deviation and the vibration intensity to obtain the stability index, and dividing the system state based on the stability index; S4. Dynamically adjusting the proportional gain and integral gain based on the divided system state, the effective deviation and the temperature influence coefficient; S5. Adjusting the integral term according to the effective deviation and the integral cumulative value, and then summing the proportional term and the integral term to obtain the preliminary output frequency; S6. Constructing surge protection constraints, temperature protection constraints and energy efficiency optimization constraints to constrain the preliminary calculation frequency and obtain the final execution frequency.

2. The energy-saving control method of a production line vacuum pump based on vacuum degree feedback and PI algorithm according to claim 1, characterized in that, The actual vacuum degree comprises the following steps: Analog-to-digital conversion is performed on the current signal collected by the vacuum gauge tube to obtain a vacuum degree raw value; Kalman filtering is performed on the vacuum degree raw value to obtain a filtered vacuum degree value; during the Kalman filtering process, when the vacuum degree change rate increases, the process noise increases; when the vibration intensity increases, the observation noise increases; Taking the arithmetic mean of the original vacuum degree values of the last n sampling points to obtain the trend value of the original signal; if the vibration intensity is less than or equal to the preset threshold, the Kalman filtered vacuum degree value is directly used as the actual vacuum degree output; if the vibration intensity is greater than the preset threshold, the Kalman filtered vacuum degree value and the trend value of the original signal are weighted and summed to obtain a fused vacuum degree as the actual vacuum degree output.

3. The energy saving control method of the production line vacuum pump based on vacuum degree feedback and PI algorithm according to claim 1, characterized in that, The dynamic adjustment of the dead zone width comprises: The dead zone width is obtained by adding the absolute value of the deviation multiplied by the adjustment coefficient to the basic dead zone width; wherein the absolute value of the deviation is the absolute value of the difference between the current actual vacuum degree and the set vacuum degree.

4. The energy-saving control method of a production line vacuum pump based on vacuum degree feedback and PI algorithm according to claim 1, characterized in that, The extraction of the effective deviation comprises the following steps: If the absolute value of the deviation between the actual vacuum degree and the set vacuum degree is less than the dead zone width, it is considered that the deviation is within the allowed range, and the effective deviation is set to 0; otherwise, the effective deviation is equal to the set vacuum degree minus the actual vacuum degree, and the negative value represents insufficient vacuum, and the positive value represents excessive vacuum.

5. The method of claim 1, wherein the PI algorithm is based on a feedback of a vacuum level. The system state comprises a stable state, a disturbance state and a high-risk state; When the stability index is less than a first stability threshold, the system state is the stable state; when the stability index is less than a second stability threshold, the system state is the disturbance state, wherein the first stability threshold is less than the second stability threshold; When the stability index is greater than or equal to the second stability threshold, the system state is the high-risk state, wherein the high-risk state is divided into a surge risk and a mutation state; If the vibration intensity is greater than the intensity threshold and the absolute value of the vacuum change rate is greater than the change rate threshold, the system state is the surge risk, otherwise, the system is the mutation state.

6. The method for energy saving control of a production line vacuum pump based on vacuum degree feedback and PI algorithm according to claim 1, characterized in that, The step S4 comprises the following steps: When the system state is stable state, reduce the proportional gain, and increase the integral gain; When the system state is disturbance state, increase the proportional gain, and reduce the integral gain; When the system state is surge risk state, reduce the proportional gain by a fixed proportion, and minimize the integral gain; When the system state is mutation state, increase the proportional gain, and limit the maximum value of the integral gain; Based on the corresponding system state, the corresponding proportional integral calculation mode is selected to obtain the preliminary adjusted proportional gain and integral gain; then the preliminary proportional gain is multiplied by the temperature influence coefficient to obtain the adjusted proportional gain, and the preliminary integral gain is divided by the temperature coefficient to obtain the adjusted integral gain.

7. The method for energy saving control of a production line vacuum pump based on vacuum degree feedback and PI algorithm according to claim 1, characterized in that, The adjustment integral term is to stop the integral when the large deviation, to decay the integral value when the integral is saturated, and to normally update the integral under normal conditions; When the absolute value of the effective deviation is greater than the threshold value, it is the large deviation, and the use of the integral term is stopped; When the absolute value of the historical integral is greater than the threshold value, it indicates that the integral is saturated, and the integral value decay operation is performed; If it does not belong to the above conditions, it indicates that it is under normal conditions, and the integral is updated by accumulating the product of the current deviation and the time step; Based on the determined integral term and the proportional term, the output frequency is calculated to obtain the preliminary output frequency.

8. The method for energy saving control of a production line vacuum pump based on vacuum degree feedback and PI algorithm according to claim 1, characterized in that, The surge protection constraint sets the frequency basis lower limit dynamically through the vibration intensity, adds the frequency basis lower limit and the safety margin value to obtain the absolute minimum frequency; Temperature protection constraint: based on the body temperature, the maximum operating frequency is limited, by setting a temperature threshold value, when the pump body temperature is less than or equal to the temperature threshold value, the frequency is the upper limit of the power frequency; if the pump body temperature is greater than the temperature threshold value, the maximum frequency decreases by nHz for every 1 degree Celsius increase; based on this, the maximum frequency under temperature constraint is obtained; Energy efficiency optimization constraint: according to the deviation proportion of the set vacuum degree and the actual vacuum degree, the theoretical frequency meeting the vacuum demand is calculated, and a predetermined proportion of margin is added to the theoretical frequency to obtain the upper limit of the energy efficiency optimization frequency.

9. The method according to claim 8, wherein, The final execution frequency is obtained based on the following steps: Based on the preliminary output frequency and the absolute minimum frequency, the maximum value is selected to obtain the first candidate value; Based on the maximum frequency under temperature constraint and the upper limit of the energy efficiency optimization frequency, the minimum value is obtained to obtain the second candidate value; The theoretical demand frequency is taken as the third candidate value; The first, second and third candidate values are sorted, and the middle value is taken as the final execution frequency.

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