Intelligent control method and system for motor of nitrogen compressor

Abstract

This invention provides an intelligent control method and system for a nitrogen compressor motor, comprising: obtaining the theoretical efficiency of the equipment based on its theoretical parameters; randomly generating multiple equipment parameter schemes as individual schemes within a preset parameter range of the theoretical parameters; performing multiple rounds of optimization iterations on all individual schemes based on the theoretical efficiency to obtain a globally optimal individual scheme; applying the equipment parameter scheme of the globally optimal individual scheme to the equipment parameters, so that the equipment operates in a relatively optimal state; by generating multiple parameter schemes for the nitrogen compressor, iterating on these parameter schemes, updating all parameter schemes towards a local optimum in each iteration, and finally generating a globally optimal individual scheme, intelligent control can be achieved and operating efficiency improved without modifying the components of the nitrogen compressor.

Description

Technical Field

[0001] This invention belongs to the field of intelligent control technology for nitrogen compressors, and more specifically, relates to an intelligent control method and system for a nitrogen compressor motor. Background Technology

[0002] Existing centrifugal nitrogen compressors are typically used for nitrogen compression in air separation processes. They are high-energy-consuming equipment. Currently, energy-saving technologies or measures for centrifugal nitrogen compressors mainly focus on improving gas flow characteristics, such as adjusting the inlet guide vanes and optimizing aerodynamic design. However, the modification process is complex, requires frequent shutdowns for modification, affects production efficiency, and the effects after modification are unstable, making it difficult to guarantee the achievement of relatively optimal operating efficiency.

[0003] Therefore, overcoming the shortcomings of the existing technology is an urgent problem to be solved in this technical field. Summary of the Invention

[0004] The problem this invention aims to solve is how to improve the operating efficiency of a nitrogen compressor.

[0005] Firstly, a method for intelligent control of a nitrogen compressor motor is provided, including: The theoretical efficiency of the equipment is obtained based on its theoretical parameters. Multiple equipment parameter schemes are randomly generated within the preset parameter range of the theoretical parameters as individual schemes; Based on the theoretical efficiency, multiple rounds of optimization iterations are performed on all individual solutions to obtain the globally optimal individual solution. The device parameter scheme of the global optimal solution is applied to the device parameters so that the device operates in a relatively optimal state.

[0006] Preferably, the step of performing multiple rounds of optimization iterations on all individual solutions towards the theoretical efficiency to obtain the globally optimal solution specifically includes: The randomly generated scheme individuals are used as the initial population, and the initial population is used as the input population in the first round of iteration; Each iteration includes: obtaining the actual efficiency of each scheme individual in the input population; comparing the actual efficiency of each scheme individual with the theoretical efficiency; taking the scheme individual with the smallest difference between actual efficiency and theoretical efficiency among all scheme individuals in all iterations as the global optimal individual; and determining whether the termination condition is met. When the termination condition is met, the current global optimum is output as the optimum solution. When the termination condition is not met, the current input population is filtered according to the actual efficiency of each scheme individual, and all the scheme individuals obtained by the filtering are cross-mutated to obtain a new population. The new population is used as the input population for the next round of iteration and is input into the next round of iteration.

[0007] Preferably, obtaining the actual efficiency corresponding to each individual scheme in the input population specifically includes: The equipment parameter schemes in the corresponding individual schemes are applied to the equipment to obtain real-time exhaust pressure, real-time flow rate, exhaust temperature, intake temperature and pressure change rate; The equivalent load rate of each individual scheme is obtained based on the equipment parameter scheme, real-time exhaust pressure, real-time flow rate, exhaust temperature, intake temperature and pressure change rate. The actual efficiency of the corresponding scheme individual is obtained based on the equivalent load rate.

[0008] Preferably, the expression for the equivalent load rate corresponding to each individual scheme is: β r =k p × +k q × +k t ×Φ(T discharge T inlet )+k d × +C; Where, β r The equivalent load rate is... For real-time exhaust pressure, For the rated exhaust pressure, k p As pressure weight, For real-time traffic, For the rated flow rate, k q Let Φ be the flow rate weight, Φ be the temperature effect function, and T be the flow rate weight. discharge T represents the exhaust temperature. inlet For intake air temperature, k t Temperature weighting, k is the rate of change of pressure. d is the pressure change rate weight, and C is the calibration constant.

[0009] Preferably, the individual components of the scheme include: pressure weight, flow rate weight, temperature weight, pressure change rate weight, rated exhaust pressure, and rated flow rate.

[0010] Preferably, the intelligent control method for the nitrogen compressor motor further includes: The system applies the individual device parameter schemes of the globally optimal solution to the device parameters and obtains the actual efficiency and equivalent load rate in real time. The optimal terminal voltage and desired terminal current are obtained based on the actual efficiency and equivalent load factor. The optimal terminal voltage and desired terminal current are then applied to the corresponding device.

[0011] Secondly, a nitrogen compressor motor intelligent control system is provided for applying the aforementioned nitrogen compressor motor intelligent control method, comprising: an intelligent control unit, wherein: The intelligent control unit is used to obtain the theoretical efficiency of the device based on the theoretical parameters of the device; randomly generate multiple device parameter schemes as individual schemes within the preset parameter range of the theoretical parameters; perform multiple rounds of optimization iteration on all individual schemes based on the theoretical efficiency to obtain the globally optimal individual scheme; and apply the device parameter scheme of the globally optimal individual scheme to the device parameters so that the device operates in a relatively optimal state.

[0012] Preferably, it also includes: a soft starter unit, a frequency converter unit, and a bypass switching unit, wherein: The soft-start unit is used to gradually increase the voltage value of the device to a preset voltage value by a preset voltage difference, and is also used to gradually increase the frequency value of the device to a preset frequency value by a preset frequency difference, so as to start the motor of the device; The frequency converter is used to convert the load parameters of the equipment into load electrical signals, compare the load electrical signals with preset load values ​​to obtain comparison results, and adjust the motor of the equipment according to the comparison results. The bypass switching unit is used to switch the equipment between the power frequency branch and the energy-saving branch.

[0013] Preferably, the bypass switching unit includes a power frequency branch, an energy-saving branch, and a main circuit breaker QF, wherein: The main circuit breaker QF is connected to the power frequency branch and the energy-saving branch respectively; The energy-saving branch is sequentially equipped with a first switch KM1, an energy-saving device, and a second switch KM2, and the power frequency branch is equipped with a third switch KM3. When the main circuit breaker QF is closed, and both the first switch KM1 and the second switch KM2 are closed, and the third switch KM3 is open, the equipment switches to operation on the energy-saving branch. When the main circuit breaker QF is closed, and both the first switch KM1 and the second switch KM2 are open, and the third switch KM3 is closed, the equipment switches to operate on the energy-saving power frequency branch.

[0014] Preferably, the energy-saving branch is further equipped with a first circuit breaker QS1 and a second circuit breaker QS2, wherein: The first circuit breaker QS1 is disposed between the first switch KM1 and the main circuit breaker QF, and the second circuit breaker QS2 is disposed between the energy saver and the second switch KM2; When the main circuit breaker QF is closed, and the first switch KM1, the second switch KM2, the first circuit breaker QS1 and the second circuit breaker QS2 are all closed, and the third switch KM3 is open, the equipment switches to operation on the energy-saving branch. When the main circuit breaker QF is closed, and the first switch KM1, the second switch KM2, the first circuit breaker QS1 and the second circuit breaker QS2 are all open, and the third switch KM3 is closed, the equipment switches to operation on the energy-saving power frequency branch.

[0015] Unlike existing technologies, the present invention has at least the following beneficial effects: Multiple parameter schemes are randomly generated based on the theoretical parameters of the equipment, and these parameter schemes are iteratively adjusted towards the theoretical efficiency to make the generated parameter schemes converge towards the theoretical efficiency, and finally obtain the relatively optimal parameter scheme. This avoids errors caused by the equipment itself and the environment, so that the equipment can operate at a relatively ideal efficiency in actual operation, thereby improving the operating efficiency of the nitrogen compressor. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments of the present invention will be briefly described below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0017] Figure 1 This is a flowchart of a method for intelligent control of a nitrogen compressor motor provided in this embodiment; Figure 2 This is a flowchart illustrating the practical application of an intelligent control method for a nitrogen compressor motor provided in this embodiment; Figure 3 This is a flowchart illustrating the iterative process in an intelligent control method for a nitrogen compressor motor provided in this embodiment; Figure 4 This is a schematic diagram illustrating the process of obtaining the actual efficiency of an individual scheme in a nitrogen compressor motor intelligent control method provided in this embodiment; Figure 5 This is a schematic diagram of the voltage and current acquisition process in a nitrogen compressor motor intelligent control method provided in this embodiment; Figure 6 This is a flowchart illustrating the practical application of feedback regulation in an intelligent control method for a nitrogen compressor motor provided in this embodiment; Figure 7This is a schematic diagram of the control cabinet in an intelligent control system for a nitrogen compressor motor provided in this embodiment; Figure 8 This is a schematic diagram of the control cabinet in another intelligent control system for a nitrogen compressor motor provided in this embodiment; Figure 9 This is a flowchart illustrating the practical application of intelligent control in an intelligent control system for a nitrogen compressor motor, as provided in this embodiment. Figure 10 This is a flowchart illustrating the practical application of intelligent control in another intelligent control system for a nitrogen compressor motor provided in this embodiment; Figure 11 This is a practical application diagram of feedback regulation in an intelligent control system for a nitrogen compressor motor provided in this embodiment; Figure 12 This is a schematic diagram of a bypass switching unit in an intelligent control system for a nitrogen compressor motor provided in this embodiment; Figure 13 This is a schematic diagram of an intelligent control system for a nitrogen compressor motor provided in this embodiment. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0019] Unless the context otherwise requires, throughout the specification and claims, the term "comprising" is interpreted as openly inclusive, meaning "including, but not limited to." In the description of the specification, terms such as "one embodiment," "some embodiments," "exemplary embodiment," "example," "specific example," or "some examples" are intended to indicate that a particular feature, structure, material, or characteristic associated with that embodiment or example is included in at least one embodiment or example of this disclosure. The illustrative representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics mentioned may be included in any suitable manner in any one or more embodiments or examples; that is, although they may be incorporated into embodiments or examples using the above terms for reasons such as order and position, it does not limit them to be incorporated in combination by a single embodiment or example.

[0020] In the description of this invention, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined with "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of embodiments of this disclosure, unless otherwise stated, "a plurality of" means two or more. Furthermore, for example, the description may use the prefix "A" or "B" to describe the same type of nouns as two independent entities. In this case, the corresponding features defined with "A" and "B" are used only to distinguish between similar entities and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features.

[0021] In the description of this invention, the expression “A and / or B” (where A and B are used to formally represent specific features) will be used. The corresponding expression includes the following three combinations: only A, only B, and a combination of A and B.

[0022] As used in this invention, “about,” “approximately,” or “approximately” includes the stated value and the average value within an acceptable range of deviation from a particular value, wherein the acceptable range of deviation is determined by a person skilled in the art taking into account the measurement under discussion and the error associated with the measurement of the particular quantity (i.e., the limitations of the measurement system).

[0023] Furthermore, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0024] Example 1: In existing nitrogen compressors, to ensure relatively ideal efficiency and energy-saving effects, ideal equipment parameters are used in different scenarios to achieve these optimal operating efficiency and energy-saving results. These settings are calculated under ideal conditions at the factory. However, due to environmental and equipment-specific errors during actual operation, using the corresponding ideal equipment parameters in different scenarios typically fails to achieve the desired efficiency and energy-saving effects. In this embodiment, relevant parameters from the equipment are collected and input into an intelligent control model. The intelligent control model then adjusts the parameters applied to the equipment, enabling the equipment to operate at efficiency and energy-saving levels that are closer to the ideal. The specific details are as follows.

[0025] This embodiment provides an intelligent control method for a nitrogen compressor motor, such as... Figure 1 As shown, the method flow includes the following.

[0026] In step 101, the theoretical efficiency of the equipment is obtained based on the theoretical parameters of the equipment.

[0027] In this embodiment, the theoretical parameters of the device are a parameter scheme set before the device leaves the factory, which enables the device to achieve ideal efficiency in a specific scenario. This parameter scheme includes device parameters such as current, voltage, and frequency. The theoretical efficiency is the theoretically optimal efficiency that the device can achieve when operating in the current specific scenario. It is important to note that the theoretical parameters and corresponding theoretical efficiencies can be set before the device leaves the factory. In this step, the theoretical efficiency is used as a reference when adjusting the parameter values ​​subsequently, so that the adjustment effect of the parameters can converge towards the theoretical efficiency.

[0028] In step 102, multiple equipment parameter schemes are randomly generated within the preset parameter range of the theoretical parameters as individual schemes.

[0029] In this embodiment, the preset parameter range is set by those skilled in the art based on actual conditions. For each parameter type in the theoretical parameters, a new parameter is obtained within the corresponding parameter range. All parameters after randomization are used as the generated new equipment parameter scheme, i.e., a scheme individual. Multiple scheme individuals are generated for subsequent iterative optimization. Scheme individuals include: pressure weight, flow weight, temperature weight, pressure change rate weight, rated exhaust pressure, and rated flow.

[0030] In step 103, multiple rounds of optimization iterations are performed on all individual schemes based on the theoretical efficiency to obtain the globally optimal individual scheme.

[0031] In this embodiment, after obtaining multiple individual solutions, the actual efficiency of each individual solution when applied to the device is obtained. The actual efficiency is compared with the theoretical efficiency to determine the relative excellence of the individual solution. The closer the actual efficiency is to the theoretical efficiency, the better the individual solution is. In each iteration, the individual solution with the highest excellence is selected, and all other individual solutions are updated according to the individual solution with the highest excellence, so that all individual solutions converge in the direction of higher relative excellence. All updated individual solutions are then used for the next iteration. After multiple iterations, the individual solution with the highest excellence is the globally optimal individual solution.

[0032] In step 104, the device parameter scheme of the individual global optimal solution is applied to the device parameters so that the device operates in a relatively optimal state.

[0033] The globally optimal solution is the theoretically optimal parameter solution after multiple rounds of optimization and iteration. When this parameter solution is applied to the device in the corresponding scenario, the device's operating effect is the best state that it can operate in that scenario.

[0034] In this embodiment, the above method is used to randomly generate multiple parameter schemes based on the theoretical parameters of the equipment, and these parameter schemes are iteratively adjusted towards the theoretical efficiency, so that the generated parameter schemes converge towards the theoretical efficiency, and finally obtain a relatively optimal parameter scheme. This avoids errors caused by the equipment itself and the environment, enabling the equipment to operate at a relatively ideal efficiency in actual operation, thereby improving the operating efficiency of the nitrogen compressor. Figure 2 The diagram shown is a flowchart illustrating the practical application of the intelligent control method in this embodiment.

[0035] Furthermore, in this embodiment, the actual efficiency of all individual solutions needs to converge towards the ideal efficiency during the optimization iteration process, so that the excellence of the individual solutions can become higher and higher. Therefore, this embodiment also involves the following design: performing multiple rounds of optimization iteration on all individual solutions based on the theoretical efficiency to obtain the globally optimal individual solution, such as... Figure 3 As shown, the method flow includes the following.

[0036] In step 201, the randomly generated scheme individuals are used as the initial population, and the initial population is used as the input population in the first round of iteration.

[0037] In step 202, each iteration includes: obtaining the actual efficiency of each scheme individual in the input population, comparing the actual efficiency of each scheme individual with the theoretical efficiency, taking the scheme individual with the smallest difference between actual efficiency and theoretical efficiency among all scheme individuals in all iterations as the global optimal individual; and determining whether the termination condition is met.

[0038] In step 203, when the termination condition is met, the current global optimal value individual is output as the optimal solution individual.

[0039] In step 204, when the termination condition is not met, the current input population is filtered according to the actual efficiency of each scheme individual, and all the scheme individuals obtained by the filtering are cross-mutated to obtain a new population. The new population is used as the input population for the next round of iteration and input into the next round of iteration.

[0040] In this embodiment, by inputting the corresponding parameters of the individual scheme into the model, the actual efficiency of the individual scheme can be obtained. The smaller the difference between the actual efficiency and the theoretical efficiency, the better the individual scheme is. In each iteration, the best individual scheme in all iterations is selected as the global optimal individual. In each iteration, relatively better individual schemes are selected for cross-mutation and used as the input population for the next iteration until the termination condition is met. The global optimal individual at this time is the optimal parameter scheme required. When applied to the device, it can achieve relatively more ideal operating efficiency and energy saving efficiency.

[0041] In this embodiment, the termination condition can be: setting a preset number of iterations. In this embodiment, the preset number of iterations is set by those skilled in the art based on actual conditions. It is determined whether the current iteration round is greater than or equal to the preset number of iterations. When the current iteration round is greater than or equal to the preset number of iterations, the termination condition is met. When the current iteration round is less than the preset number of iterations, the termination condition is not met.

[0042] Furthermore, in this embodiment, for each individual scheme, obtaining its actual efficiency requires the pressure weight, flow weight, temperature weight, pressure change rate weight, rated exhaust pressure, and rated flow rate of the individual scheme, as well as real-time parameters from the equipment. The corresponding design is as follows: The actual efficiency corresponding to each individual scheme in the input population is obtained as follows... Figure 4 As shown, the method flow includes the following.

[0043] In step 301, the equipment parameter schemes in the corresponding schemes are applied to the equipment to obtain real-time exhaust pressure, real-time flow rate, exhaust temperature, intake temperature and pressure change rate.

[0044] In step 302, the equivalent load rate of the corresponding scheme individual is obtained based on the equipment parameter scheme, real-time exhaust pressure, real-time flow rate, exhaust temperature, intake temperature and pressure change rate.

[0045] The expression for the equivalent load rate for each individual scheme is: β r =k p × +k q × +k t ×Φ(T discharge T inlet )+k d × +C; Where, β r The equivalent load rate is... For real-time exhaust pressure, For the rated exhaust pressure, k p As pressure weight, For real-time traffic, For the rated flow rate, k q Let Φ be the flow rate weight, Φ be the temperature effect function, and T be the flow rate weight. discharge T represents the exhaust temperature. inlet For intake air temperature, k t Temperature weighting, k is the rate of change of pressure. dis the pressure change rate weight, and C is the calibration constant.

[0046] In step 303, the actual efficiency of the corresponding scheme individual is obtained based on the equivalent load rate.

[0047] In this embodiment, the motor efficiency η and the real-time equivalent load rate β r Relationship: η(β r ) =α0+α1β r +α2β r 2 +α3β r 3 ; η(β r ) represents the equivalent load factor β r The motor efficiency is determined by α0, α1, α2, and α3, which are all correlation coefficients. A cubic polynomial is used to more accurately fit the peak region of the efficiency curve, ensuring that the motor always operates within the high-efficiency region β. r ∈[β opt_min ,β opt_max [Running nearby.]

[0048] Furthermore, considering that after obtaining the optimal solution and its corresponding actual efficiency, it is necessary to obtain the corresponding current and voltage based on the actual efficiency for subsequent regulation and monitoring, the corresponding method is designed as follows. Figure 4 As shown, the intelligent control method for the nitrogen compressor motor further includes: In step 401, the device parameter scheme of the globally optimal solution is applied to the device parameters, and the actual efficiency and equivalent load rate are obtained in real time.

[0049] In step 402, the optimal terminal voltage and the desired terminal current are obtained based on the actual efficiency and the equivalent load factor.

[0050] In step 403, the optimal terminal voltage and desired terminal current are applied to the corresponding device.

[0051] In this embodiment, the optimal terminal voltage U opt With equivalent load factor β r The function expression is: U opt (β r )=γ0+γ1β r +γ2β r 2 ; The above function expression defines the optimal terminal voltage U required to achieve maximum efficiency under a specific load. opt , among which, U opt (β r ) represents the equivalent load factor βr The optimal terminal voltage is given by γ0, γ1, and γ2, which are all relationship coefficients.

[0052] In this embodiment, the desired terminal current I exp With β r The function expression is: I exp (β r )=δ0+δ1β r +δ2β r 2 ; The above function expression defines the expected healthy current value under a specific load and optimal voltage, where I exp (β r ) represents the equivalent load factor β r The desired terminal current is given by δ0, δ1, and δ2, which are all relationship coefficients.

[0053] Furthermore, in this embodiment, after obtaining the optimal terminal voltage and desired terminal current based on the actual efficiency and equivalent load rate, and applying them to the corresponding equipment, the corresponding ideal efficiency can be achieved. However, the problem is that in actual applications, the nitrogen compressor not only needs to pursue efficiency, but also needs to ensure the stability of the nitrogen compressor, and needs to have anti-surge and corresponding control functions. Therefore, this embodiment also involves the following design.

[0054] By monitoring the parameters of the equipment, some parameters are processed and input into the corresponding model to determine whether the equipment will trigger a surge warning. When a surge warning is triggered, the corresponding adjustment amount is output to adjust the current, voltage and frequency of the equipment to avoid surge.

[0055] The input variables include the following: 1. Efficiency deviation e η : e η =η opt (β r ) η actual ; Where, η opt (β r ) represents the corresponding equivalent load factor β r The optimal efficiency obtained by searching below, η actual The actual efficiency; the efficiency deviation e η Used to guide the system toward its most efficient operating point.

[0056] 2. Pressure stability deviation e p : e p =P set Pactual ; Among them, P set The target pressure set for the system, P actual The actual exhaust pressure; the pressure stability deviation e p It is an important process control target for nitrogen compressors, and is directly related to the stability of downstream processes.

[0057] 3. Surge margin index S m : ; Among them, Q surge (P actual ) is the actual exhaust pressure P actual Below, the surge point flow rate on the compressor performance curve. This index quantifies the relative distance between the current operating point and the surge line. When S m When the voltage approaches a set threshold (e.g., 0.15), a surge warning is triggered, and the device's priority is switched from energy-saving mode to anti-surge mode. This requires outputting corresponding adjustment values ​​to adjust the device's current, voltage, and frequency to prevent surge.

[0058] Furthermore, regarding the setting of the adjustment amount, the adjustment amount includes: voltage adjustment amount ΔU and current limiting adjustment amount ΔI. lim Regarding the frequency adjustment amount Δf, this embodiment involves the following design for the application of each adjustment amount.

[0059] 1. For the voltage adjustment amount ΔU, after the voltage adjustment amount ΔU is obtained from the output, the voltage adjustment amount ΔU is directly added to the current target voltage setting value. The corresponding expression is as follows: U set (k)=U set (k 1)+ΔU; Among them, U set (k) represents the target voltage setting value at the k-th time node, U set (k 1) The target voltage setting value at the (k-1)th time node.

[0060] The target voltage setting value U set (k) Physically, it is used to adjust the magnetic flux intensity of the motor. When the load rate decreases, appropriately reducing the voltage can reduce iron loss and excitation current, and improve light-load efficiency; when a rapid response to pressure changes is required, the frequency should be adjusted first for coordinated fine-tuning.

[0061] 2. Regarding the current limiting adjustment amount ΔI lim The current limiting adjustment amount ΔI lim The expression for dynamically setting the upper limit of the inverter's output current is as follows: I lim (k)=I lim_base +ΔI lim ; Wherein, the I lim (k) represents the current limiting value at the k-th time node; I lim_base This is the current limit value set according to the motor's rated current. Its core function is to actively limit the motor torque and compressor power when approaching the surge zone or abnormal operating conditions, forcing the operating point away from the surge line to ensure safety. In the normal, high-efficiency range, the limit is relaxed, allowing the motor to fully utilize its performance.

[0062] 3. For the frequency dominance factor λ, where λ∈[0,1]; the frequency dominance factor λ is used to coordinate the weight allocation of voltage adjustment and frequency adjustment, and is the key to achieving synchronous and directional adjustment of voltage and current.

[0063] Based on the frequency dominance factor λ mentioned above, the corresponding expression for the frequency adjustment Δf can be obtained as follows: Δf=λ×K f ×ΔU+(1 λ)×K p ×e p ; Among them, K f K is the coupling coefficient between voltage and frequency, determined by the motor characteristics. p e is the proportional coefficient for pressure deviation and frequency adjustment. p This is due to pressure stability deviation.

[0064] Furthermore, in this embodiment, the adjustment principle for anti-surge is as follows.

[0065] When the pressure is stable (i.e., the pressure stability deviation is approximately 0) and far from the surge zone, the equipment aims to optimize efficiency. At this time, the frequency adjustment Δf is mainly used to respond to the voltage adjustment ΔU, so as to achieve fine adjustment of the weak coupling between voltage and frequency, enabling the motor to operate on the high-efficiency curve.

[0066] When pressure stability deviation e p When the pressure is relatively large, the equipment aims to quickly stabilize the pressure. In this case, the frequency adjustment Δf is primarily used to respond to the pressure stability deviation e. p The voltage adjustment ΔU is then used as an auxiliary variable, based on the new load point (which is determined by the new frequency) from the optimal voltage model U. opt (β r The fast follow setting ensures constant magnetic flux, avoids stalling or overcurrent, and achieves fast and stable load tracking.

[0067] When the surge margin index S mWhen the voltage approaches a set threshold (e.g., 0.15), the control system automatically switches from energy-saving mode to anti-surge mode, immediately reducing voltage and current limits, suppressing power, and forcibly exiting the surge danger zone.

[0068] Furthermore, this embodiment also provides the following fuzzy rule library for the parameters calculated above, which is used to adjust the parameters for different situations of the equipment, so as to ensure the high-efficiency operation of the equipment while taking into account the function of anti-surge. The fuzzy rule library is as follows.

[0069] If the pressure stability deviation is e p For pressure less than a preset threshold, and surge margin index S m If the voltage adjustment ΔU is within the preset safety range, the frequency dominance factor λ will be increased first.

[0070] If the pressure stability deviation is e p Stable, and with efficiency deviation e η If the efficiency is lower than the preset value, the voltage adjustment ΔU will be slightly increased while the frequency dominance factor λ will remain unchanged.

[0071] If the surge margin index S m If the distance between the surge zone and the current limit adjustment ΔI is less than the preset distance, the voltage adjustment ΔU will be reduced, and the current limit adjustment ΔI will be reduced. lim Implement current limiting; this rule has the highest priority to prevent surge.

[0072] The preset threshold, preset safety range, preset efficiency, and preset distance are all set by those skilled in the art based on actual conditions.

[0073] Through the above mechanism, the equipment achieves a dynamic balance and optimization of the three objectives of anti-surge, pressure control, and high efficiency.

[0074] like Figure 5 The diagram shown is a flowchart illustrating the actual application of the above method in this embodiment. By collecting load parameters in real time, the device is regulated through feedback adjustment.

[0075] Example 2: This embodiment provides an intelligent control system for a nitrogen compressor motor based on Embodiment 1, used to apply the intelligent control method for a nitrogen compressor motor as described in Embodiment 1, including: an intelligent control unit, wherein: The intelligent control unit is used to obtain the theoretical efficiency of the device based on the theoretical parameters of the device; randomly generate multiple device parameter schemes as individual schemes within the preset parameter range of the theoretical parameters; perform multiple rounds of optimization iteration on all individual schemes based on the theoretical efficiency to obtain the globally optimal individual scheme; and apply the device parameter scheme of the globally optimal individual scheme to the device parameters so that the device operates in a relatively optimal state.

[0076] In this embodiment, after obtaining multiple individual solutions, the actual efficiency of each solution applied to the device is obtained. The actual efficiency is compared with the theoretical efficiency to determine the relative excellence of the solution. The closer the actual efficiency is to the theoretical efficiency, the better the solution. In each iteration, the solution with the highest excellence is selected, and all other solutions are updated according to this highest-excellent solution, causing all solutions to converge towards a higher relative excellence. The updated solutions then proceed to the next iteration. After multiple iterations, the solution with the highest excellence is the globally optimal solution. In this embodiment, the intelligent control unit is installed in a control cabinet, which contains a controller (including a fiber optic board, main control board, signal board, and power board, etc.), an I / O interface board, and user secondary wiring terminals, etc. Figure 7 and Figure 8 The diagram shown is a schematic of the control cabinet.

[0077] Furthermore, in this embodiment, the actual efficiency of all individual solutions needs to converge towards the ideal efficiency during the optimization iteration process, so that the excellence of the individual solutions can become higher and higher. Therefore, this embodiment also involves the following design: performing multiple rounds of optimization iteration on all individual solutions based on the theoretical efficiency to obtain the globally optimal individual solution, such as... Figure 3 As shown, the method flow includes the following.

[0078] Randomly generated scheme individuals are used as the initial population, and this initial population is input into the first iteration. Each iteration includes: obtaining the actual efficiency of each scheme individual in the input population; comparing the actual efficiency of each scheme individual with the theoretical efficiency; selecting the scheme individual with the smallest difference between actual and theoretical efficiency among all scheme individuals in all iterations as the globally optimal individual; and determining whether the termination condition is met. If the termination condition is met, the currently globally optimal individual is output as the optimal scheme individual. If the termination condition is not met, the current input population is filtered according to the actual efficiency of each scheme individual, and all the filtered scheme individuals are cross-mutated to obtain a new population, which is used as the input population for the next iteration.

[0079] In this embodiment, by inputting the corresponding parameters of the individual scheme into the model, the actual efficiency of the individual scheme can be obtained. The smaller the difference between the actual efficiency and the theoretical efficiency, the better the individual scheme is. In each iteration, the best individual scheme in all iterations is selected as the global optimal individual. In each iteration, relatively better individual schemes are selected for cross-mutation and used as the input population for the next iteration until the termination condition is met. The global optimal individual at this time is the optimal parameter scheme required. When applied to the device, it can achieve relatively more ideal operating efficiency and energy saving efficiency.

[0080] In this embodiment, the termination condition can be: setting a preset number of iterations. In this embodiment, the preset number of iterations is set by those skilled in the art based on actual conditions. It is determined whether the current iteration round is greater than or equal to the preset number of iterations. When the current iteration round is greater than or equal to the preset number of iterations, the termination condition is met. When the current iteration round is less than the preset number of iterations, the termination condition is not met.

[0081] Furthermore, considering that existing nitrogen compressors are typically used for nitrogen compression in air separation processes and are high-energy-consuming devices, their energy costs far exceed their purchase costs, nitrogen compressors also have the following problems: (1) High energy consumption and gas compression characteristics: Centrifugal nitrogen compressors need to continuously compress nitrogen in air separation processes, and their energy consumption accounts for more than 60% of the total energy consumption of the system, and they are extremely sensitive to fluctuations in gas flow and pressure. (2) Surge problem: Nitrogen compressors are prone to surge (i.e., gas backflow causes severe vibration) when running at low flow rates. (3) Complex operating conditions: Nitrogen compressors need to remain stable under high pressure, high temperature, and continuous operation conditions, which places relatively higher demands on the reliability of the control system; In summary, in order to solve the above problems, this embodiment also involves the following design.

[0082] The intelligent control system for the nitrogen compressor motor also includes a soft start unit, a frequency converter unit, and a bypass switching unit. The soft start unit is used to gradually increase the voltage of the equipment to a preset voltage value by a preset voltage difference, and is also used to gradually increase the frequency of the equipment to a preset frequency value by a preset frequency difference, so as to start the motor of the equipment.

[0083] In this embodiment, the preset voltage difference and the preset frequency difference are set by those skilled in the art according to actual conditions. By gradually increasing the voltage and frequency to start the device's motor, the inrush current and mechanical shock to the power grid during device startup are reduced.

[0084] The frequency converter is used to convert the load parameters of the equipment into load electrical signals, compare the load electrical signals with preset load values ​​to obtain comparison results, and adjust the motor of the equipment according to the comparison results.

[0085] In this embodiment, sensors can be installed in the equipment to collect and monitor load parameters such as pressure and flow rate. The monitored data is converted into electrical signals and provided to a PID intelligent regulator. The monitored data is compared with a pre-set value to obtain the difference. The PID intelligent regulator adjusts the equipment parameters (such as pressure, flow closed-loop, current, voltage closed-loop, motor speed, and power output) based on the difference, which can prevent the nitrogen compressor from entering the surge zone. For example, when the sensor detects that the flow rate is lower than the safety threshold, the intelligent control system automatically increases the motor frequency to ensure that the nitrogen compressor always operates in the high-efficiency zone. Furthermore, considering the gas compression characteristics of the nitrogen compressor, the PID intelligent regulator dynamically matches the motor output power with the load demand, reducing reactive power loss. In this embodiment, the equipment can be monitored at a frequency of 2000 times per second to achieve 30-second start-up and speed adjustment of the centrifugal nitrogen compressor, thus solving the surge problem. Figure 11 The diagram shows the priority adjustment of speed regulation, voltage regulation, and current regulation by the frequency converter unit. The priority of parameter adjustment is determined by the change of load, so as to achieve the user's ideal adjustment effect.

[0086] The bypass switching unit is used to switch the equipment between the power frequency branch and the energy-saving branch.

[0087] In this embodiment, when the equipment is working normally, the energy-saving branch is usually used to reduce energy consumption during normal operation. When the energy-saving part of the equipment malfunctions or needs maintenance, it automatically switches to bypass operation to ensure the safe and continuous operation of the system and avoid equipment downtime.

[0088] Furthermore, such as Figure 12 As shown, the bypass switching unit includes a power frequency branch, an energy-saving branch, and a main circuit breaker QF, wherein: the main circuit breaker QF is connected to both the power frequency branch and the energy-saving branch; the energy-saving branch is sequentially equipped with a first switch KM1, an energy-saving device, and a second switch KM2, and the power frequency branch is equipped with a third switch KM3; when the main circuit breaker QF is closed, if both the first switch KM1 and the second switch KM2 are closed and the third switch KM3 is open, the equipment switches to operate on the energy-saving branch; when the main circuit breaker QF is closed, if both the first switch KM1 and the second switch KM2 are open and the third switch KM3 is closed, the equipment switches to operate on the energy-saving power frequency branch.

[0089] In this embodiment, the purpose of setting a first switch KM1 and a second switch KM2 at both ends of the energy saver is to ensure that when the energy saver needs to be repaired, the switches at both ends can fully ensure that the power is cut off on both sides of the energy saver, and isolate the energy saver from the high voltage power supply to ensure safety during maintenance.

[0090] In this embodiment, in order to further improve the safety of maintenance of the energy-saving branch, more switches need to be installed at both ends of the energy-saving device to reduce the possibility of connection between the energy-saving device and the power supply when maintenance is required. Therefore, this embodiment also involves the following design.

[0091] like Figure 12 As shown, the energy-saving branch is also equipped with a first circuit breaker QS1 and a second circuit breaker QS2, wherein: the first circuit breaker QS1 is located between the first switch KM1 and the main circuit breaker QF, and the main circuit breaker QF is located between the energy-saving device and the second switch KM2; when the first switch KM1, the second switch KM2, the first circuit breaker QS1 and the second circuit breaker QS2 are all closed, and the third switch KM3 is open, the equipment switches to operation on the energy-saving branch; when the first switch KM1, the second switch KM2, the first circuit breaker QS1 and the second circuit breaker QS2 are all open, and the third switch KM3 is closed, the equipment switches to operation on the energy-saving power frequency branch.

[0092] In this embodiment, mechanical and electrical interlocks can be set between the second switch KM2 and the third switch KM3 to ensure that the power frequency power supply is not directly supplied to the output terminal of the energy-saving device. By setting the second switch KM2 and the third switch KM3 on the incoming and outgoing sides of the energy-saving device respectively, the energy-saving device can be isolated from the high-voltage power supply when operating in power frequency branch mode, which facilitates the maintenance and repair of the energy-saving device.

[0093] In this embodiment, when the power frequency branch or energy-saving branch is used, the main circuit breaker QF can only be closed when all switches on the power frequency branch or energy-saving branch are closed. When a fault occurs in the energy-saving branch, the switch on the energy-saving branch is opened, and at the same time the switch on the power frequency branch is closed, realizing the jump from the energy-saving branch to the power frequency branch, ensuring the continuous and stable operation of the equipment.

[0094] Furthermore, the acquisition unit collects signals at a frequency of 2000 times per second and transmits them to the Digital Signal Processor (DSP) central processing unit. After processing by the DSP, commands are transmitted to the power factor adjustment unit. Through real-time dynamic adjustment of the motor's output power, the power factor during motor operation is improved by approximately 20%, ensuring optimal matching between the motor's output power and the load power. The power factor module can autonomously adjust when circuit deviations occur, minimizing the power margin during operation, and then transmits this information to the DSP for centralized processing. Simultaneously, the harmonic absorption module ensures stable and normal operation of the entire circuit and protects the energy-saving module to achieve optimal energy-saving effects. Figure 13 The diagram shown is a schematic of the system.

[0095] The CPU is used to perform high-frequency detection and scanning of the linear and nonlinear loads of the motor. By monitoring the operating conditions and power changes of the AC motor, the power supplied to the motor is dynamically adjusted in real time to ensure that the motor output power is always in the best matching state with the motor load.

[0096] In practical applications, the intelligent control system for the nitrogen compressor motor provided in this embodiment is used. First, the input power is purified by isolating the transformer. Then, a soft-start unit smoothly starts the motor, avoiding the large current surge during startup. When production line demands change, the intelligent control unit responds quickly, adjusting the motor's operating current, voltage, and frequency in real time based on sensor feedback (such as pressure and flow rate) via a PID controller. This precisely controls the nitrogen compressor motor's output power, ensuring production continuity and stability while achieving significant energy savings.

[0097] When the sensor detects that the flow rate of the nitrogen compressor has dropped to a preset critical value, the intelligent control system unit increases the motor speed within 0.05 seconds through the PID regulator, while reducing the voltage to reduce energy consumption and avoid surge.

[0098] Furthermore, the intelligent control system for the nitrogen compressor motor is also equipped with an isolation transformer unit to protect the subsequent circuits from grid fluctuations and ensure stable power quality for the electrical equipment. The isolation transformer system is designed to withstand high temperatures (above 150°C) and high voltages (above 10kV) to adapt to the high-voltage operating environment of the nitrogen compressor. The terminals of the isolation transformer unit are made of ceramic insulating material to ensure no leakage risk under 10kV high voltage conditions. The power unit is equipped with a heat dissipation duct to adapt to the high-temperature working environment of the nitrogen compressor.

[0099] Furthermore, the energy-saving device is integrated with the distributed control system of the nitrogen compressor to receive production process parameters (such as nitrogen purity and compression ratio) in real time, which are used to dynamically optimize the motor operating curve.

[0100] In this embodiment, the self-learning algorithm in the intelligent control unit continuously collects various parameters during the motor's operation, and after analysis, continuously optimizes the control strategy, further improving energy-saving efficiency and equipment reliability.

[0101] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for intelligent control of a nitrogen compressor motor, characterized in that, include: The theoretical efficiency of the equipment is obtained based on its theoretical parameters. Multiple equipment parameter schemes are randomly generated within the preset parameter range of the theoretical parameters as individual schemes; Based on the theoretical efficiency, multiple rounds of optimization iterations are performed on all individual solutions to obtain the globally optimal individual solution. The device parameter scheme of the global optimal solution is applied to the device parameters so that the device operates in a relatively optimal state.

2. The intelligent control method for a nitrogen compressor motor according to claim 1, characterized in that, The step of performing multiple rounds of optimization iterations on all individual solutions based on the theoretical efficiency to obtain the globally optimal individual solution specifically includes: The randomly generated scheme individuals are used as the initial population, and the initial population is used as the input population in the first round of iteration; Each iteration includes: obtaining the actual efficiency of each scheme individual in the input population; comparing the actual efficiency of each scheme individual with the theoretical efficiency; taking the scheme individual with the smallest difference between actual efficiency and theoretical efficiency among all scheme individuals in all iterations as the global optimal individual; and determining whether the termination condition is met. When the termination condition is met, the current global optimum is output as the optimum solution. When the termination condition is not met, the current input population is filtered according to the actual efficiency of each scheme individual, and all the scheme individuals obtained by the filtering are cross-mutated to obtain a new population. The new population is used as the input population for the next round of iteration and is input into the next round of iteration.

3. The intelligent control method for a nitrogen compressor motor according to claim 2, characterized in that, The process of obtaining the actual efficiency corresponding to each individual scheme in the input population specifically includes: The equipment parameter schemes in the corresponding individual schemes are applied to the equipment to obtain real-time exhaust pressure, real-time flow rate, exhaust temperature, intake temperature and pressure change rate; The equivalent load rate of each individual scheme is obtained based on the equipment parameter scheme, real-time exhaust pressure, real-time flow rate, exhaust temperature, intake temperature and pressure change rate. The actual efficiency of the corresponding scheme individual is obtained based on the equivalent load rate.

4. The intelligent control method for a nitrogen compressor motor according to claim 1, characterized in that, The expression for the equivalent load rate for each individual scheme is: β r =k p × +k q × +k t ×Φ(T discharge T inlet )+k d × +C; Where, β r The equivalent load factor is... For real-time exhaust pressure, For the rated exhaust pressure, k p As pressure weight, For real-time traffic, For the rated flow rate, k q Let Φ be the flow rate weight, Φ be the temperature effect function, and T be the flow rate weight. discharge T represents the exhaust temperature. inlet For intake air temperature, k t Temperature weighting, k is the rate of change of pressure. d is the pressure change rate weight, and C is the calibration constant.

5. The intelligent control method for a nitrogen compressor motor according to claim 1, characterized in that, The individual components of the scheme include: pressure weight, flow weight, temperature weight, pressure change rate weight, rated exhaust pressure, and rated flow.

6. The intelligent control method for a nitrogen compressor motor according to claim 1, characterized in that, The intelligent control method for the nitrogen compressor motor also includes: The system applies the individual device parameter schemes of the globally optimal solution to the device parameters and obtains the actual efficiency and equivalent load rate in real time. The optimal terminal voltage and desired terminal current are obtained based on the actual efficiency and equivalent load factor. The optimal terminal voltage and desired terminal current are then applied to the corresponding device.

7. A nitrogen compressor motor intelligent control system, used to apply the nitrogen compressor motor intelligent control method as described in any one of claims 1-6, characterized in that, include: Intelligent control unit, wherein: The intelligent control unit is used to obtain the theoretical efficiency of the device based on the theoretical parameters of the device; randomly generate multiple device parameter schemes as individual schemes within the preset parameter range of the theoretical parameters; perform multiple rounds of optimization iteration on all individual schemes based on the theoretical efficiency to obtain the globally optimal individual scheme; and apply the device parameter scheme of the globally optimal individual scheme to the device parameters so that the device operates in a relatively optimal state.

8. The intelligent control system for the nitrogen compressor motor according to claim 7, characterized in that, Also includes: The unit consists of a soft starter, a frequency converter, and a bypass switching unit, among which: The soft-start unit is used to gradually increase the voltage value of the device to a preset voltage value by a preset voltage difference, and is also used to gradually increase the frequency value of the device to a preset frequency value by a preset frequency difference, so as to start the motor of the device; The frequency converter is used to convert the load parameters of the equipment into load electrical signals, compare the load electrical signals with preset load values ​​to obtain comparison results, and adjust the motor of the equipment according to the comparison results. The bypass switching unit is used to switch the equipment between the power frequency branch and the energy-saving branch.

9. The intelligent control system for the nitrogen compressor motor according to claim 8, characterized in that, The bypass switching unit includes a power frequency branch, an energy-saving branch, and a main circuit breaker QF, wherein: The main circuit breaker QF is connected to the power frequency branch and the energy-saving branch respectively; The energy-saving branch is sequentially equipped with a first switch KM1, an energy-saving device, and a second switch KM2, and the power frequency branch is equipped with a third switch KM3. When the main circuit breaker QF is closed, and both the first switch KM1 and the second switch KM2 are closed, and the third switch KM3 is open, the equipment switches to operation on the energy-saving branch. When the main circuit breaker QF is closed, and both the first switch KM1 and the second switch KM2 are open, and the third switch KM3 is closed, the equipment switches to operation on the energy-saving power frequency branch.

10. The intelligent control system for the nitrogen compressor motor according to claim 9, characterized in that, The energy-saving branch is also equipped with a first circuit breaker QS1 and a second circuit breaker QS2, wherein: The first circuit breaker QS1 is disposed between the first switch KM1 and the main circuit breaker QF, and the second circuit breaker QS2 is disposed between the energy saver and the second switch KM2; When the main circuit breaker QF is closed, and the first switch KM1, the second switch KM2, the first circuit breaker QS1 and the second circuit breaker QS2 are all closed, and the third switch KM3 is open, the equipment switches to operation on the energy-saving branch. When the main circuit breaker QF is closed, and the first switch KM1, the second switch KM2, the first circuit breaker QS1 and the second circuit breaker QS2 are all open, and the third switch KM3 is closed, the equipment switches to operation on the energy-saving power frequency branch.

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