A method, device and medium for online identification of air compressor energy efficiency

Abstract

The application discloses a kind of methods, devices and media for identifying the energy efficiency of air compressor online.The method includes: after a certain historical time period of air compressor system including multiple air compressors runs, the historical operation data in a predetermined number of historical time periods is searched, the running combination of different air compressors, the gas supply flow of each air compressor running combination and the power consumption of each air compressor in air compressor running combination are determined;According to each air compressor running combination and its gas supply flow, the air compressor running state and the gas supply flow equation set are established;According to the solving method corresponding to the type of air compressor running state and gas supply flow equation set, the air compressor running state and gas supply flow equation set are solved, and the gas supply flow value of each air compressor in air compressor system is determined;According to the gas supply flow value and power consumption of each air compressor, the air compressor energy efficiency of each air compressor in current historical time period is determined.

Description

Technical Field

[0001] This invention relates to the field of air compressor energy efficiency evaluation technology, and more specifically, to a method, apparatus and medium for online identification of air compressor energy efficiency. Background Technology

[0002] An air compressor is a device that converts the mechanical energy of a prime mover into gas pressure energy. It is widely used in industrial applications such as pneumatics, gas transportation, refrigeration and drying, and control and braking. Air compressor energy efficiency testing is generally conducted at the factory or during acceptance testing. After use, due to limitations such as standard operating conditions, production rhythm, or consumption costs, testing is usually not repeated. However, its performance is affected as its service life increases. Therefore, in production activities such as economic evaluation, equipment monitoring and diagnosis, and energy-saving scheduling, it is necessary to obtain the latest equipment energy efficiency indicators. One way to obtain current energy efficiency is through rigorous testing according to equipment acceptance and energy efficiency assessment standards. This method yields the most accurate results, but it requires significant manpower and resources and may disrupt the normal air supply demand for production.

[0003] Currently, most air compressors only have a power measurement module and not a flow measurement module. Another method is to temporarily or permanently install a single flow measurement device, such as... Figure 1 As shown, measuring the flow rate of a single unit also increases costs and downtime. Another method is to use a commonly installed main pipe flow meter and run the air compressor one by one in turn to measure the flow rate of a single unit. However, this method cannot be used for long-term measurement and monitoring because it will affect the gas supply demand for production, in addition to increasing the cost. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a method, apparatus, and medium for online identification of air compressor energy efficiency.

[0005] According to one aspect of the present invention, a method for online identification of the energy efficiency of an air compressor is provided, comprising:

[0006] After an air compressor system comprising multiple air compressors has been running for a certain number of historical time periods, historical operating data within a predetermined number of historical time periods are retrieved to determine different air compressor operating combinations, the air supply flow of each air compressor operating combination, and the power consumption of each air compressor in the air compressor operating combination.

[0007] Based on the operating combinations of each air compressor and its air supply flow, establish a set of equations for the operating status and air supply flow of the air compressor.

[0008] Based on the solution method corresponding to the type of air compressor operating status and air supply flow equation set, the air compressor operating status and air supply flow equation set are solved to determine the air supply flow value of each air compressor in the air compressor system.

[0009] Based on the air supply flow rate and power consumption of each air compressor, determine the air compressor energy efficiency of each air compressor within the current historical time period.

[0010] Optionally, it also includes:

[0011] Read historical operating data of the air compressor system within a historical time period, and perform filtering and cleaning operations on the historical operating data.

[0012] Optionally, the solution methods corresponding to the types of air compressor operating conditions and air supply flow rate equations include:

[0013] When the air compressor is in operation and the air supply flow rate equations are positive definite equations, the solution methods are matrix transformation, Gaussian elimination, Jacobi iteration, or least squares.

[0014] When the air compressor is in operation and the air supply flow rate equations are overdetermined, the solution methods are matrix transformation, least squares, or singular value decomposition.

[0015] When the air compressor is in operation and the air supply flow rate equations are underdetermined, the solution methods are matrix transformation, minimum infinite norm, minimum standard deviation, or the power ratio method.

[0016] Optionally, based on the air supply flow rate and power consumption of each air compressor, the air compressor energy efficiency for the current historical time period is determined, including:

[0017] Based on the air supply flow rate and power consumption of each air compressor, determine the current specific power of each air compressor within the current historical time period.

[0018] The air compressor energy efficiency of each air compressor is determined based on its current specific power and the historical specific power of the previous historical time period.

[0019] Optionally, the air compressor energy efficiency of each air compressor is determined based on its current specific power and its historical specific power in the previous historical time period, including:

[0020] The current specific power and historical specific power are fused according to a preset fusion method to determine the air compressor energy efficiency. The fusion method includes arithmetic average method, moving average method and exponential decrease method.

[0021] According to another aspect of the present invention, an apparatus for online identification of the energy efficiency of an air compressor is provided, comprising:

[0022] The first determining module is used to retrieve historical operating data within a predetermined number of historical time periods after an air compressor system including multiple air compressors has been running for a certain historical time period, and to determine different air compressor operating combinations, the air supply flow of each air compressor operating combination, and the power consumption of each air compressor in the air compressor operating combination.

[0023] A module is established to create a set of equations for the operating status and air supply flow of air compressors based on each air compressor operating combination and its air supply flow.

[0024] The second determining module is used to solve the air compressor operating status and air supply flow equation set according to the solution method corresponding to the type of air compressor operating status and air supply flow equation set, and to determine the air supply flow value of each air compressor in the air compressor system.

[0025] The third determining module is used to determine the air compressor energy efficiency of each air compressor within the current historical time period based on the air supply flow rate and power consumption of each air compressor.

[0026] According to another aspect of the present invention, a computer-readable storage medium is provided, the storage medium storing a computer program for performing the methods described in any of the above aspects of the present invention.

[0027] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising: a processor; a memory for storing executable instructions of the processor; the processor being configured to read the executable instructions from the memory and execute the instructions to implement the method described in any of the preceding aspects of the present invention.

[0028] Therefore, this invention provides a method for online identification of air compressor energy efficiency. The method retrieves historical operating data of the air compressor system within a predetermined data period to determine different air compressor operating combinations, the air supply flow rate of each operating combination, and the power consumption of each air compressor in the operating combination. Based on each air compressor operating combination and its air supply flow rate, a set of equations for air compressor operating status and air supply flow rate is established. The equations are then solved using the solution method corresponding to the type of the equations, determining the air supply flow rate value of each air compressor in the system. Based on the air supply flow rate value and power consumption of each air compressor, the specific power of each air compressor in the current period is calculated. Finally, based on the specific power of each air compressor and its historical specific power, the air compressor energy efficiency of each air compressor is determined. Under existing widespread IoT conditions, this method utilizes data from normal air compressor system production to continuously evaluate and monitor air compressor energy efficiency indicators over a long period without increasing equipment costs or affecting normal production. Attached Figure Description

[0029] Exemplary embodiments of the present invention can be more fully understood by referring to the following figures:

[0030] Figure 1 This is a schematic diagram of the structure of temporarily or permanently installing a single flow measurement device on an air compressor, as described in the background section of this invention.

[0031] Figure 2 This is a flowchart illustrating a method for online identification of air compressor energy efficiency provided in an exemplary embodiment of the present invention;

[0032] Figure 3 This is a schematic diagram of the structure of a device for online identification of air compressor energy efficiency provided in an exemplary embodiment of the present invention;

[0033] Figure 4 This is the structure of an electronic device provided in an exemplary embodiment of the present invention. Detailed Implementation

[0034] Hereinafter, exemplary embodiments according to the present invention will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of the present invention, and not all embodiments of the present invention. It should be understood that the present invention is not limited to the exemplary embodiments described herein.

[0035] It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps described in these embodiments do not limit the scope of the invention.

[0036] Those skilled in the art will understand that the terms "first," "second," etc., in the embodiments of the present invention are only used to distinguish different steps, devices, or modules, and do not represent any specific technical meaning, nor do they indicate a necessary logical order between them.

[0037] It should also be understood that in the embodiments of the present invention, "multiple" can refer to two or more, and "at least one" can refer to one, two or more.

[0038] It should also be understood that any component, data or structure mentioned in the embodiments of the present invention can generally be understood as one or more unless there is an explicit limitation or the contrary teaching is given in the context.

[0039] Furthermore, the term "and / or" in this invention is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this invention generally indicates that the preceding and following related objects have an "or" relationship.

[0040] It should also be understood that the description of the various embodiments in this invention emphasizes the differences between the various embodiments, and the similarities or similarities can be referred to each other. For the sake of brevity, they will not be described in detail.

[0041] At the same time, it should be understood that, for ease of description, the dimensions of the various parts shown in the accompanying drawings are not drawn according to actual scale.

[0042] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the invention or its application or use.

[0043] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, they should be considered part of the specification.

[0044] It should be noted that similar labels and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be discussed further in subsequent figures.

[0045] The embodiments of this invention can be applied to electronic devices such as terminal devices, computer systems, and servers, and can operate together with a wide range of other general-purpose or special-purpose computing system environments or configurations. Well-known examples of terminal devices, computing systems, environments, and / or configurations suitable for use with electronic devices such as terminal devices, computer systems, and servers include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputer systems, mainframe computer systems, and distributed cloud computing environments including any of the above systems, etc.

[0046] Electronic devices such as terminal devices, computer systems, and servers can be described in the general context of computer system executable instructions (such as program modules) executed by a computer system. Typically, program modules can include routines, programs, object programs, components, logic, data structures, etc., which perform specific tasks or implement specific abstract data types. Computer systems / servers can be implemented in distributed cloud computing environments, where tasks are executed by remote processing devices linked through communication networks. In distributed cloud computing environments, program modules can reside on local or remote computing system storage media, including storage devices.

[0047] Exemplary methods

[0048] Figure 2 This is a schematic flowchart illustrating a method for online identification of air compressor energy efficiency provided by an exemplary embodiment of the present invention. This embodiment can be applied to electronic devices, such as... Figure 2 As shown, the method 200 for online identification of air compressor energy efficiency includes the following steps:

[0049] Step 201: After the air compressor system, which includes multiple air compressors, has been running for a certain number of historical time periods, historical operating data within those periods is retrieved to determine different air compressor operating combinations, the air supply flow rate of each air compressor operating combination, and the power consumption of each air compressor in the air compressor operating combination.

[0050] The historical time period for the predetermined quantity can be one period, or it can be two or three time periods set by the user.

[0051] Optionally, it also includes:

[0052] Read historical operating data of the air compressor system within a historical time period, and perform filtering and cleaning operations on the historical operating data.

[0053] Specifically, this invention applies to air compressor systems with two or more industrial frequency air compressors. Each air compressor has a power or current measuring device (but no separate flow measurement), and the main pipe of the air compressor system has a flow measuring device. The air compressor system's capacity has a certain margin relative to the required air supply for production, or the required air supply fluctuates to some extent.

[0054] Furthermore, historical data for a certain period is read, and the data is filtered and cleaned. Different air compressor operating combinations are retrieved, and the corresponding power consumption and air supply flow are calculated.

[0055] Step 202: Based on the operating combination of each air compressor and its air supply flow, establish a set of equations for the operating status and air supply flow of the air compressor.

[0056] Step 203: Solve the air compressor operating status and air supply flow equation set according to the solution method corresponding to the type of air compressor operating status and air supply flow equation set, and determine the air supply flow value of each air compressor in the air compressor system.

[0057] Optionally, the solution methods corresponding to the types of air compressor operating conditions and air supply flow rate equations include:

[0058] When the air compressor is in operation and the air supply flow rate equations are positive definite equations, the solution methods are matrix transformation, Gaussian elimination, Jacobi iteration, or least squares.

[0059] When the air compressor is in operation and the air supply flow rate equations are overdetermined, the solution methods are matrix transformation, least squares, or singular value decomposition.

[0060] When the air compressor is in operation and the air supply flow rate equations are underdetermined, the solution methods are matrix transformation, minimum infinite norm, minimum standard deviation, or the power ratio method.

[0061] Specifically, i) If the system of equations is a positive definite system of equations, such coincidences are relatively rare, but there are many conventional solution methods. The air production of each air compressor can be solved according to the corresponding solution method.

[0062] ii) If the system of equations is an overdetermined system of equations, such cases are relatively rare, especially for periodic solutions, where the data time span is not very long and there are not many combinations of operating conditions. Although it is a contradictory system of equations with no solution, there are some methods to find approximate solutions. The air production of each air compressor can be calculated according to the corresponding solution method.

[0063] iii) If the system of equations is an underdetermined system of equations, this is a common situation in production comparisons. However, from a mathematical perspective, it is generally impossible to obtain a unique solution (there are infinitely many solutions). But by combining production or equipment background knowledge and supplementing some relational equations or constraints, the air output of each air compressor under the corresponding conditions can be solved.

[0064] Furthermore, the solution methods for different types of equation systems in this invention are not limited to the methods provided above, and may also be other solution methods that can solve the above-mentioned types of equation systems. This invention does not limit these methods.

[0065] Step 204: Determine the air compressor energy efficiency of each air compressor within the current historical time period based on the air supply flow rate and power consumption of each air compressor.

[0066] Optionally, based on the air supply flow rate and power consumption of each air compressor, the air compressor energy efficiency for the current historical time period is determined, including:

[0067] Based on the air supply flow rate and power consumption of each air compressor, determine the current specific power of each air compressor within the current historical time period.

[0068] The air compressor energy efficiency of each air compressor is determined based on its current specific power and the historical specific power of the previous historical time period.

[0069] The energy efficiency index of the present invention is not limited to specific power, but can also be other energy efficiency indexes calculated by gas supply flow rate and power consumption.

[0070] Optionally, the air compressor energy efficiency of each air compressor is determined based on its current specific power and its historical specific power in the previous historical time period, including:

[0071] The current specific power and historical specific power are fused according to a preset fusion method to determine the air compressor energy efficiency. The fusion method includes arithmetic average method, moving average method and exponential decrease method.

[0072] Implementation Example 1:

[0073] 1. Read the operating data of the air compressor within a certain period. Assuming there are 4 air compressors, the power consumption of the 4 air compressors and the air supply flow of the main pipe can be read. Filter and remove the data during the start-up and shutdown process, and only keep the data during the stable operation period (such as the data after the air compressor has been loaded for 5 minutes). At the same time, remove the data with missing samples or abnormal values.

[0074] 2. Group the historical data according to the operating status of each air compressor, and calculate the air compressor power and main pipe flow rate for each group. Although the instantaneous flow rate of the main pipe is mainly affected by the air consumption, the statistical results of a large amount of data show that the air consumption and air production are balanced, and it can be used as the value of air production.

[0075] 3. List the equations for the air compressor's operating status and air supply volume: Considering actual production, air consumption cannot always be the same as air production, and the equipment's designed capacity will have a certain margin compared to production needs. We assume there are at least two combinations (it's simpler when there's only one combination; this solution can be applied or an easily conceived method can be used to solve it):

[0076] i) Example 1: Assume the statistical combinations of working states are as shown in Table 1 below:

[0077] Table 1

[0078]

[0079] In the table, 1# to 4# are the air compressor numbers. In the status, 1 represents that it is in the gas production state (loaded), and 0 represents that it is not in the gas production state (unloaded or stopped). The main pipe air supply flow rate is the average air supply flow rate of the corresponding gas production state combination.

[0080] In Example 1, compressor #4 was never turned on and can be ignored. The remaining operating air compressors can be combined to obtain the corresponding set of equations for their operating status and air supply flow rate:

[0081]

[0082] In the formula, x1, x2, and x3 represent the air production rates of the air compressor under its air production state. Alternatively, its coefficient matrix A can be listed:

[0083]

[0084] Flow matrix b:

[0085]

[0086] Power matrix P:

[0087]

[0088] ii) Example 2: Assume the working state combinations are as shown in Table 2 below:

[0089] Table 2

[0090]

[0091] The augmented matrix B = (A, b) for air compressors #1 to #3 can be listed:

[0092]

[0093] Power matrix P:

[0094]

[0095] iii) Example 3: Assume the working state combinations are as shown in Table 3 below:

[0096] Table 3

[0097]

[0098] The augmented matrix B for air compressors #1 to #3 can be listed:

[0099]

[0100] Power matrix P:

[0101]

[0102] iv) Example 4: Assume the working state combinations are as shown in Table 4 below:

[0103] Table 4

[0104]

[0105]

[0106] The augmented matrix B for air compressors #1 to #3 can be listed:

[0107]

[0108] Power matrix P:

[0109]

[0110] 5. Solving the system of equations (with case studies)

[0111] i) The operating states of each air compressor can be easily determined as in Example 1. This system of equations is full-rank positive definite, meaning the number of equations is the same as the number of unknowns. There are many solutions for this situation, such as matrix transformation, Gaussian elimination, Jacobi iteration, and least squares methods, all of which can yield the values ​​of x1, x2, and x3. For example, using matrix form for calculation:

[0112] X = A -1 b

[0113] Solve for X = [10, 20, 30].

[0114] ii) When the operating state is as in Example 2, the system of equations is incompatible and overdetermined, meaning the rank of the coefficient matrix is ​​less than the rank of the augmented matrix, and there is no exact solution. However, an approximate solution can be found using various methods, such as least squares method and singular value decomposition. For example, the matrix form used to calculate the air compressor flow rate is as follows:

[0115] X = (A T A) -1 A T b

[0116] Solving for X, we get X = [10.67, 20, 67, 29.33]. This method can also be used to solve the positive definite equation in Example i).

[0117] iii) When the operating state is as in Example 3, the system of equations is underdetermined and compatible, meaning the rank of the coefficient matrix is ​​the same as the rank of the augmented matrix and less than the number of unknowns. The system of equations can be solved infinitely. Therefore, additional conditions need to be added before solving. For example, in Example 3, only unit #1 can be solved, while units #2 and #3 can have infinitely many combinations. If we introduce the ratio of the rated flow (or power) of units #2 and #3: x2 / x3 = 2 / 3, it's equivalent to adding a row to their augmented matrix.

[0118]

[0119] To make the equation positive definite, X = [10, 20, 30] can be solved using the above method.

[0120] Alternatively, the air compressor flow rate can be calculated using the weighted least-two norm, and its matrix form is as follows:

[0121]

[0122] Where W is the weighting coefficient for each air compressor, which can be set according to parameters such as rated flow rate and rated power, so that the calculation results are distributed proportionally. A′ is the Hadamard product of A and W, i.e. If W = [1, 1, 1] (i.e., equal weights), the solution is: X = [10, 25, 25]. Machine #1 is still a definite solution, while machines #2 and #3 are equal (sharing their common flow). The weights are set according to the effective current (square root of power), and the solution is: X = [10, 20, 30]. That is, the solution for #1 remains unchanged, and the flow ratio of #2 and #3 is consistent with the power ratio, so the final calculated energy efficiency is the same.

[0123] This method can also be used to solve the positive definite equation in Example i).

[0124] iv) When the operating state is as in Example 4, although the equations are underdetermined, they are also incompatible, meaning the number of equations is less than the number of unknowns, but there are also contradictory equations. Similarly, the ratio of the rated flow rate can be introduced and solved using the method in Example 2. Alternatively, the generalized inverse matrix form can also be used to solve the problem.

[0125] X = A' + b

[0126] Where A′+ is the Moore-Penrose inverse (pseudo-inverse) of A′, and A′ is the Hadamard product of A and W. The Moore-Penrose inverse can be obtained using full-rank decomposition, singular value decomposition, etc. If W = [1, 1, 1], the solution is: X = [10.67, 24.83, 24.83], that is, the least squares solution of the contradiction equation for machine #1, while the flow rates of machines #2 and #3 are the same; if ... The solution is: X = [10.67, 19.87, 29.8], which means that the solution for unit #1 remains unchanged, and the flow ratio and power ratio of units #2 and #3 are consistent.

[0127] The formal equation systems of Examples 1, 2, and 3 can also be solved uniformly using this method. However, considering the complexity and efficiency of the generalized inverse solution, it is preferable to solve them separately using the original method.

[0128] The equations / matrices obtained during the solution process can be stored in memory for later fusion when constructing new periodic equations / matrices in subsequent historical time periods.

[0129] 5. Based on the calculated air supply flow rate of each air compressor and the corresponding statistical power consumption, the energy efficiency evaluation indicators such as the specific power of each air compressor in the current period can be calculated and output directly, or the results can be combined with the historical specific power and other energy efficiency evaluation indicators to output as a comprehensive evaluation indicator.

[0130] i) If there are no historical specific power solutions, but there are current specific power solutions, such as for Unit 1, then the new results will be saved in the historical results.

[0131] ii) If there is no specific power solution in this case, but there are historical specific power solutions, such as for Unit 4, then keep the original results unchanged;

[0132] iii) Assuming there is a specific power solution available this time, and there are existing historical specific power solutions, such as for Unit #2, then fusion can be performed. There are many methods available, such as the arithmetic mean method, the moving average method, and the exponential decreasing method. When averaging, appropriate weights can be selected. The weights can be specified according to the new and old attributes, calculated according to the duration or amount of data included in the solution, or calculated according to the degree of influence of the supplementary equations during the solution process.

[0133] 6. After a certain number of air compressor production cycles, proceed to step 1 to recalculate. The interval period and the recalculated data period can be different. The matrix can be constructed directly based on the working state combinations of the new cycle, or the stored results of the working state combinations from the previous cycle can be added to the matrix for joint construction.

[0134] a) If a certain combination of working states of an air compressor does not appear in the current cycle, the data or state matrix of working state combinations that have appeared in the previous cycle or other cycles can be directly merged into it.

[0135] b) Assuming that all working states of the air compressor occur, the air supply flow and power consumption can be calculated on average according to weight (such as statistical duration) and then merged.

[0136] Implementation Example 2:

[0137] 1. Read the air compressor operation data within a certain period. Assuming there are 4 air compressors, the power of 4 compressors and the flow of the main pipe can be read. Filter and remove the data during the start-up and shutdown process, and only keep the data during the stable operation period (such as the data after the air compressor has been loaded for 5 minutes). At the same time, remove the data with missing samples or abnormal values.

[0138] 2. Group the historical data according to the operating status of each air compressor, and calculate the air compressor power and main pipe flow rate for each group. Although the instantaneous flow rate of the main pipe is mainly affected by the air consumption, the statistical results of a large amount of data show that the air consumption and air production are balanced, and it can be used as the value of air production.

[0139] 3. List the equations for the air compressor's operating status and air supply volume: Considering actual production, air consumption cannot always be the same as air production, and the equipment's designed capacity will have a certain margin compared to production needs. We assume there are at least two combinations:

[0140] i) Example 1: Assume the statistical work status combinations are as shown in Table 5 below:

[0141] Table 5

[0142]

[0143]

[0144] Its coefficient matrix A can be listed:

[0145]

[0146] Flow matrix b:

[0147]

[0148] Power matrix P:

[0149]

[0150] ii) Example 2: Assume the working state combinations are as shown in Table 6 below:

[0151] Table 6

[0152]

[0153] The augmented matrix B = (A, b) for air compressors #1 through #4 can be listed:

[0154]

[0155] Power matrix P:

[0156]

[0157] iii) Example 3: Assume the working state combinations are as shown in Table 7 below:

[0158] Table 7

[0159]

[0160]

[0161] The augmented matrix B for air compressors #1 through #4 can be listed:

[0162]

[0163] Power matrix P:

[0164]

[0165] iv) Example 4: Assume the working state combinations are as shown in Table 8 below:

[0166] Table 8

[0167]

[0168] The augmented matrix B for air compressors #1 through #4 can be listed:

[0169]

[0170] Power matrix P:

[0171]

[0172] 4. Solving the system of equations (step by step)

[0173] 1) Transform the given augmented matrix into its simplest row echelon form B′=(A′,b′), and calculate the rank r of the augmented matrix B′. B The rank r of the coefficient matrix A′ A And the number of unknowns (the number of columns in the coefficient matrix A′): n. From the calculation process and its properties, we know that: r A ≤n and r A ≤r B .

[0174] Determine the relationship between the number of unknowns in each rank sum:

[0175] If r A =n:

[0176] If r A =r B Solve according to the steps below a).

[0177] Otherwise (i.e., r) A <r B Solve according to step b) below.

[0178] Otherwise (i.e., r) A <n):

[0179] If r A =r B Solve according to step c) below.

[0180] Otherwise (i.e., r) A <r B Solve according to step d) below.

[0181] a) When the working state is as in Example 1, the system of equations is positive definite, that is, the rank of the coefficient matrix is ​​equal to the rank of the augmented matrix and equal to the number of unknowns. The system of equations has a unique solution and can be solved by the corresponding method.

[0182] b) In the working state as in Example 2, the system of equations is overdetermined, meaning the rank of the coefficient matrix is ​​less than the rank of the augmented matrix, but equal to the number of unknowns. The system of equations is incompatible and has no exact solution, but an approximate solution can be found. There are many methods for this, such as least squares and singular value decomposition. For example, using least squares yields a solution that makes the objective function...

[0183] min||Ax-b||2

[0184] The minimized solution. This method can also be used to solve the positive definite conditions in Example 1.

[0185] c) When the working state is as in Example 3, the system of equations is underdetermined and compatible, meaning the rank of the coefficient matrix is ​​the same as the rank of the augmented matrix and less than the number of unknowns. The system of equations can be solved infinitely many times. A measure of the volatility of the product of the unknowns and weights can be used, such as the infinity norm or standard deviation. In this implementation, the minimum standard deviation of the weights is used to solve the problem, even if the objective function...

[0186]

[0187] s.tAx=b

[0188] The solution that minimizes this value. Where w is the weighting coefficient of each air compressor. It is the mean of the product of the unknown and the weight.

[0189] d) When the working state is as in Example 4, the system of equations is both underdetermined and incompatible, meaning the rank of the coefficient matrix is ​​less than the rank of the augmented matrix and less than the number of unknowns, so the equations have no solution. However, it is possible to solve the system so that the objective function...

[0190]

[0191]

[0192] The minimum value. This can be solved using multi-objective optimization or multi-level optimization algorithms, but these are generally complex and the solution is not unique. Alternatively, a maximal linearly independent set of row vectors from the working state matrix can be selected to form a compatible equation, which can then be solved according to step c). In this example, the maximal linearly independent set formed by the working states in the first three rows is obtained, i.e., its augmented matrix is:

[0193]

[0194] The same result as in Example 3 can be obtained.

[0195] The equations / matrices obtained during the solution process can be stored in memory for later fusion when constructing new periodic equations / matrices in subsequent historical time periods.

[0196] 5. The implementation method for solving and fusing energy efficiency results is the same as in the previous example. In particular, when the flow rate proportional to power is calculated using the above method, the calculated energy efficiency is the same. That is, when the energy consumption of the air compressor cannot be solved separately for the time being, the average energy efficiency is taken. Then, by combining it with historical data, the original comparison results of advantages and disadvantages can be kept unchanged.

[0197] 6. After a certain number of air compressor production cycles, proceed to step 1 to recalculate. The interval period and the recalculated data period can be different. The working status of the historical cycle can also be stored and combined with the status of the new cycle for joint solution.

[0198] Therefore, the present invention provides a method for online identification of air compressor energy efficiency. Under the existing common Internet of Things conditions, it uses data from normal air compressor system production to evaluate and monitor air compressor energy efficiency indicators continuously over a long period of time without increasing equipment costs or affecting normal production.

[0199] Exemplary device

[0200] Figure 3 This is a schematic diagram of the structure of a device for online identification of air compressor energy efficiency provided in an exemplary embodiment of the present invention. Figure 3 As shown, the device 300 includes:

[0201] The first determining module 310 is used to retrieve historical operating data within a predetermined number of historical time periods after an air compressor system including multiple air compressors has been running for a certain historical time period, and to determine different air compressor operating combinations, the air supply flow of each air compressor operating combination, and the power consumption of each air compressor in the air compressor operating combination.

[0202] Module 320 is established to create a set of equations for air compressor operating status and air supply flow based on each air compressor operating combination and its air supply flow.

[0203] The second determining module 330 is used to solve the air compressor operating status and air supply flow equation set according to the solution method corresponding to the type of air compressor operating status and air supply flow equation set, and to determine the air supply flow value of each air compressor in the air compressor system.

[0204] The third determining module 340 is used to determine the air compressor energy efficiency of each air compressor within the current historical time period based on the air supply flow rate and power consumption of each air compressor.

[0205] Optionally, the device 300 further includes:

[0206] The reading module is used to read historical operating data of the air compressor system within a historical time period, and to perform filtering and cleaning operations on the historical operating data.

[0207] Optionally, the solution methods corresponding to the types of air compressor operating conditions and air supply flow rate equations include:

[0208] When the air compressor is in operation and the air supply flow rate equations are positive definite equations, the solution methods are matrix transformation, Gaussian elimination, Jacobi iteration, or least squares.

[0209] When the air compressor is in operation and the air supply flow rate equations are overdetermined, the solution methods are matrix transformation, least squares, or singular value decomposition.

[0210] When the air compressor is in operation and the air supply flow rate equations are underdetermined, the solution methods are matrix transformation, minimum infinite norm, minimum standard deviation, or the power ratio method.

[0211] Optionally, the third determining module 340 includes:

[0212] The first determination submodule is used to determine the current specific power of each air compressor within the current historical time period based on the air supply flow rate and power consumption of each air compressor.

[0213] The second determining submodule is used to determine the air compressor energy efficiency of each air compressor based on its current specific power and the historical specific power of the previous historical time period.

[0214] Optionally, the second determining submodule includes:

[0215] The fusion unit is used to fuse the current specific power and the historical specific power according to a preset fusion method to determine the air compressor energy efficiency. The fusion method includes the arithmetic average method, the moving average method, and the exponential decrease method.

[0216] Exemplary electronic devices

[0217] Figure 4 This is the structure of an electronic device provided in an exemplary embodiment of the present invention. For example... Figure 4 As shown, the electronic device 40 includes one or more processors 41 and a memory 42.

[0218] The processor 41 may be a central processing unit (CPU) or other form of processing unit with data processing and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions.

[0219] The memory 42 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 41 may execute the program instructions to implement the methods of the software programs of the various embodiments of the present invention described above, and / or other desired functions. In one example, the electronic device may also include an input device 43 and an output device 44, these components being interconnected via a bus system and / or other forms of connection mechanisms (not shown).

[0220] In addition, the input device 43 may also include, for example, a keyboard, a mouse, etc.

[0221] The output device 44 can output various information to the outside. The output device 44 may include, for example, a display, a speaker, a printer, and a communication network and its connected remote output devices, etc.

[0222] Of course, for the sake of simplicity, Figure 4 Only some of the components of this electronic device relevant to the present invention are shown, omitting components such as buses, input / output interfaces, etc. In addition, the electronic device may include any other suitable components depending on the specific application.

[0223] Exemplary computer program products and computer-readable storage media

[0224] In addition to the methods and apparatus described above, embodiments of the present invention may also be computer program products, which include computer program instructions that, when executed by a processor, cause the processor to perform the steps of the methods according to various embodiments of the present invention described in the "Exemplary Methods" section above.

[0225] The computer program product can be written in any combination of one or more programming languages ​​to perform the operations of the embodiments of the present invention. The programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0226] Furthermore, embodiments of the present invention may also be computer-readable storage media storing computer program instructions thereon, which, when executed by a processor, cause the processor to perform the steps of the methods according to various embodiments of the present invention described in the "Exemplary Methods" section above.

[0227] The computer-readable storage medium may be any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or any combination thereof. More specific examples (a non-exhaustive list) of readable storage media include: an electrical connection having one or more wires, a portable disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof.

[0228] The basic principles of the present invention have been described above with reference to specific embodiments. However, it should be noted that the advantages, benefits, and effects mentioned in the present invention are merely examples and not limitations, and should not be considered as essential features of each embodiment of the present invention. Furthermore, the specific details disclosed above are for illustrative and facilitative purposes only, and are not limitations. These details do not limit the present invention to the necessity of employing the aforementioned specific details.

[0229] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For system embodiments, since they largely correspond to method embodiments, the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0230] The block diagrams of devices, systems, devices, and systems involved in this invention are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, systems, devices, and systems can be connected, arranged, and configured in any manner. Words such as “comprising,” “including,” “having,” etc., are open-ended terms meaning “including but not limited to,” and are used interchangeably with them. The terms “or” and “and” as used herein refer to the terms “and / or,” and are used interchangeably with them unless the context clearly indicates otherwise. The term “such as” as used herein refers to the phrase “such as but not limited to,” and is used interchangeably with it.

[0231] The methods and systems of the present invention may be implemented in many ways. For example, they may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above-described order of steps for the methods is for illustrative purposes only, and the steps of the methods of the present invention are not limited to the order specifically described above unless otherwise specifically stated. Furthermore, in some embodiments, the present invention may also be implemented as a program recorded on a recording medium, the program comprising machine-readable instructions for implementing the methods according to the present invention. Thus, the present invention also covers recording media storing programs for performing the methods according to the present invention.

[0232] It should also be noted that in the systems, apparatus, and methods of the present invention, the components or steps can be disassembled and / or recombined. These disassemblies and / or recombinations should be considered equivalents of the present invention. The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the invention. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of the invention. Therefore, the invention is not intended to be limited to the aspects shown herein, but rather to be carried out within the widest scope consistent with the principles and novel features disclosed herein.

[0233] The above description has been given for purposes of illustration and description. Furthermore, this description is not intended to limit the embodiments of the invention to the forms disclosed herein. Although numerous exemplary aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations therein.

Claims

1. A method for online identification of air compressor energy efficiency, characterized in that, include: After an air compressor system comprising multiple air compressors has been running for a certain number of historical time periods, historical operating data within those historical time periods are retrieved to determine different air compressor operating combinations, the air supply flow rate of each air compressor operating combination, and the power consumption of each air compressor in the air compressor operating combination. Based on each of the air compressor operating combinations and its air supply flow rate, establish a set of equations for air compressor operating status and air supply flow rate; Based on the solution method corresponding to the type of the air compressor operating state and air supply flow equation set, the air compressor operating state and air supply flow equation set are solved to determine the air supply flow value of each air compressor in the air compressor system. Based on the air supply flow rate and power consumption of each air compressor, determine the air compressor energy efficiency of each air compressor in the current historical time period. Based on the air supply flow rate and power consumption of each air compressor, determine the air compressor energy efficiency of each air compressor within the current historical time period, including: Based on the air supply flow rate and power consumption of each air compressor, determine the current specific power of each air compressor within the current historical time period. The air compressor efficiency of each air compressor is determined based on its current specific power and the historical specific power of the previous historical time period.

2. The method according to claim 1, characterized in that, Also includes: Read the historical operating data of the air compressor system within the historical time period, and perform filtering and cleaning operations on the historical operating data.

3. The method according to claim 1, characterized in that, The solution methods corresponding to the types of the air compressor operating state and air supply flow rate equations include: When the air compressor operating state and air supply flow equations are positive definite equations, the solution methods are matrix transformation method, Gaussian elimination method, Jacobi iteration method, or least squares method. When the air compressor operating state and air supply flow equations are overdetermined, the solution methods are matrix transformation, least squares, or singular value decomposition. When the air compressor operating state and the air supply flow rate equations are underdetermined, the solution methods are matrix transformation, minimum infinite norm, minimum standard deviation, or power ratio calculation.

4. The method according to claim 1, characterized in that, Based on the current specific power of each air compressor and the historical specific power of the previous historical time period, the air compressor energy efficiency of each air compressor is determined, including: The current specific power and the historical specific power are fused according to a preset fusion method to determine the air compressor energy efficiency, wherein the fusion method includes arithmetic average method, moving average method and exponential decrease method.

5. A device for online identification of air compressor energy efficiency, characterized in that, include: The first determining module is used to retrieve historical operating data within a predetermined number of historical time periods after an air compressor system including multiple air compressors has been running for a certain historical time period, and to determine different air compressor operating combinations, the air supply flow rate of each air compressor operating combination, and the power consumption of each air compressor in the air compressor operating combination. A module is established to establish a set of equations for the air compressor operating status and air supply flow rate based on each of the air compressor operating combinations and their respective air supply flow rates. The second determining module is used to solve the air compressor operating state and air supply flow equation set according to the solution method corresponding to the type of the air compressor operating state and air supply flow equation set, and to determine the air supply flow value of each air compressor in the air compressor system. The third determining module is used to determine the air compressor energy efficiency of each air compressor in the current historical time period based on the air supply flow rate value and the power consumption of each air compressor. The third determining module includes: The first determining submodule is used to determine the current specific power of each air compressor in the current historical time period based on the air supply flow rate value and the power consumption of each air compressor. The second determining submodule is used to determine the air compressor energy efficiency of each air compressor based on the current specific power of each air compressor and the historical specific power of the previous historical time period.

6. The apparatus according to claim 5, characterized in that, Also includes: The reading module is used to read the historical operating data of the air compressor system within the historical time period, and to perform filtering and cleaning operations on the historical operating data.

7. The apparatus according to claim 5, characterized in that, The solution methods corresponding to the types of the air compressor operating state and air supply flow rate equations include: When the air compressor operating state and air supply flow equations are positive definite equations, the solution methods are matrix transformation method, Gaussian elimination method, Jacobi iteration method, or least squares method. When the air compressor operating state and air supply flow equations are overdetermined, the solution methods are matrix transformation, least squares, or singular value decomposition. When the air compressor operating state and the air supply flow rate equations are underdetermined, the solution methods are matrix transformation, minimum infinite norm, minimum standard deviation, or power ratio calculation.

8. The apparatus according to claim 5, characterized in that, The second determination submodule includes: The fusion unit is used to fuse the current specific power and the historical specific power according to a preset fusion method to determine the air compressor energy efficiency of the air compressor, wherein the fusion method includes the arithmetic average method, the moving average method, and the exponential decrease method.

9. A computer-readable storage medium, characterized in that, The storage medium stores a computer program for performing the method described in any one of claims 1-4.

10. An electronic device, characterized in that, The electronic device includes: processor; Memory used to store the processor's executable instructions; The processor is configured to read the executable instructions from the memory and execute the instructions to implement the method described in any one of claims 1-4.

Images