Industrial frequency conversion equipment operation control system based on multi-sensor monitoring

Abstract

The invention belongs to the field of industrial frequency conversion equipment control, relates to a data analysis technology, is used for solving the problem that operation parameters of a frequency converter cannot be optimally set in the prior art, and particularly relates to an industrial frequency conversion equipment operation control system based on multi-sensor monitoring, which comprises a test analysis module, a data analysis module and an operation control module, the test analysis module, the data analysis module and the operation control module are in communication connection in sequence; the test analysis module is used for performing operation control test on the industrial frequency conversion equipment; according to the method, the operation control test data of the industrial frequency conversion equipment can be analyzed, the optimization process and the fluctuation process are intercepted according to the generated test sequence, then the generated optimization interval and the fluctuation interval are compared to generate the optimization data set, the original setting range of the analysis parameters is subjected to indentation processing through the optimization data set, and the analysis accuracy is improved. And the analysis parameter setting reasonability of the industrial frequency conversion equipment is improved.

Description

Technical Field

[0001] The present invention belongs to the field of industrial frequency conversion equipment control and relates to data analysis technology, in particular to an industrial frequency conversion equipment operation control system based on multi-sensor monitoring. Background Art

[0002] Industrial frequency conversion equipment is a kind of power control equipment that uses frequency conversion technology and microelectronics technology. Its main function is to control the speed and torque of the AC motor by changing the frequency of the motor's working power supply, thereby achieving the purpose of speed regulation and energy saving.

[0003] The invention patent with announcement number CN115145212A discloses an industrial equipment and its frequency conversion control system. The frequency conversion control system is based on two Ethernet interfaces set on each frequency converter, so as to connect each frequency converter into a chain structure, so that the structure of each frequency converter can be unified, reducing the design cost; however, the frequency conversion control system cannot optimize the setting of the operating parameters of the frequency converter, resulting in the inability to guarantee the operating status of the industrial frequency conversion equipment.

[0004] In view of the above technical problems, this application proposes a solution. Summary of the invention

[0005] The purpose of the present invention is to provide an industrial frequency conversion equipment operation control system based on multi-sensor monitoring, which is used to solve the problem that the existing technology cannot optimize the operating parameters of the frequency converter;

[0006] The technical problem to be solved by the present invention is: how to provide an industrial frequency conversion equipment operation control system based on multi-sensor monitoring that can optimize the operation parameters of the frequency converter.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] An industrial variable frequency equipment operation control system based on multi-sensor monitoring, comprising a test analysis module, a data analysis module and an operation control module, wherein the test analysis module, the data analysis module and the operation control module are sequentially connected in communication;

[0009] The test analysis module is used to perform operation control test on industrial frequency conversion equipment: marking the industrial frequency conversion equipment to be tested for operation control as a test object, generating L2 test processes for the test pair and obtaining L2 corresponding test coefficients CS;

[0010] The data analysis module is used to analyze the operation control test data of the industrial frequency conversion equipment: the test processes are sorted in order from small to large according to the test coefficient CS values ​​to obtain a test sequence, the first L3 test processes in the test sequence are intercepted as the optimization process, and the optimization interval YQi is extracted according to the optimization process; the last L3 test processes in the test sequence are intercepted as the fluctuation process, and the fluctuation interval BQi is extracted according to the fluctuation process; the optimization interval YQi is compared with the fluctuation interval BQi and an optimization data set is generated according to the comparison result;

[0011] The operation control module is used to control the operation parameters of the industrial frequency conversion equipment according to the optimized data set.

[0012] Furthermore, the specific process of generating a test process for the test object includes: marking the control parameter of the test object as an analysis parameter FXi, i=1, 2,…, n, where n is a positive integer, calling the setting range SZi of the analysis parameter i, randomly selecting a value from the setting range SZi as the test matching value CSi of the analysis parameter FXi, and forming a test data set of the test object by the test matching values ​​CSi of all analysis parameters FXi, setting the value of the analysis parameter FXi of the test object according to the test data set, and then starting the test object to run for L1 hours and generating a test process.

[0013] Furthermore, the process of obtaining the test coefficient CS of the test process includes: obtaining the temperature and height data WG, vibration frequency data ZP, noise data ZS and interval value JG of the test object during the test process and performing numerical calculations to obtain the test coefficient CS, the temperature and height data WG is the maximum value of the surface temperature value of the test object during the test process, the vibration frequency data ZP is the maximum value of the vibration frequency value of the base of the test object during the test process, and the noise data ZS is the maximum value of the decibel value of the running noise of the test object during the test process.

[0014] Furthermore, the process of obtaining the interval value JG includes: marking the time points corresponding to the temperature data WG, the vibration frequency data ZP and the noise data ZS in the test process as high temperature marking time points, vibration frequency marking time points and noise marking time points respectively, dividing any two time points among the high temperature marking time points, the vibration frequency marking time points and the noise marking time points into three time periods, and marking the minimum duration value among the three time periods as the interval value JG.

[0015] Furthermore, the extraction process of the optimization interval YQi includes: retrieving the test data set corresponding to the optimization process and marking it as the optimization data set, forming the optimization set YJi of the analysis parameter FXi from all the test matching values ​​CSi in the optimization data set, and forming the optimization interval YQi of the analysis parameter FXi from the maximum element and the minimum element in the optimization set YJi.

[0016] Furthermore, the test data set corresponding to the fluctuation process is retrieved and marked as the fluctuation data set. All test matching values ​​CSi in the fluctuation data set constitute the fluctuation set BJi of the analysis parameter FXi. The maximum element and the minimum element in the fluctuation set BJi constitute the fluctuation interval BQi of the analysis parameter FXi.

[0017] Furthermore, the specific process of comparing the optimization interval YQi with the fluctuation interval BQi includes: determining whether there is an overlap between the optimization interval YQi and the fluctuation interval BQi of the analysis parameter FXi: if so, eliminating the maximum element and the minimum element in the optimization set YJi to form a new optimization interval YQi, eliminating the maximum element and the minimum element in the fluctuation set BQi to form a new fluctuation interval BQi, and comparing the new optimization interval YQi with the new fluctuation interval BQi again, and so on, until there is no overlap between the optimization interval YQi and the fluctuation interval BQi; if not, marking the optimization interval YQi as the indentation interval SJi of the analysis parameter FXi; the indentation intervals SJi of all analysis parameters FXi constitute the optimization data set of industrial frequency conversion equipment.

[0018] Furthermore, the operation control module controls the operation parameters of the industrial frequency conversion equipment according to the optimized data set: the industrial frequency conversion equipment to be subjected to the operation parameter control is marked as a control object, the optimized data set of the industrial frequency conversion equipment is retrieved, and a value is randomly selected from the indentation interval SJi of the optimized data set as the control matching value CZi of the analysis parameter FXi. The control matching values ​​CZi of all analysis parameters FXi constitute the control data set of the control object, and the analysis parameters FXi of the test object are numerically set according to the control data set.

[0019] The present invention has the following beneficial effects:

[0020] 1. The test analysis module can be used to perform operation control tests on industrial frequency conversion equipment. The test matching value is randomly selected from the setting range for operation test and the test coefficient is obtained. According to the test coefficient, the running status of the test object during the test process is fed back to provide data support for the construction of optimized data sets;

[0021] 2. The data analysis module can be used to analyze the operation control test data of industrial frequency conversion equipment, and the optimization process and the fluctuation process are intercepted according to the generated test sequence. Then, the generated optimization interval and the fluctuation interval are compared to generate an optimized data set. The original setting range of the analysis parameters is indented through the optimized data set to improve the rationality of the analysis parameter setting of the industrial frequency conversion equipment;

[0022] 3. The operation control module can be used to control the operation parameters of the industrial frequency conversion equipment. The analysis parameters of the industrial frequency conversion equipment can be set according to the optimized data set, so that multiple analysis parameters of the industrial frequency conversion equipment can be set within the optimal range, thereby reducing the probability of operation failure of the industrial frequency conversion equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0024] Figure 1 is a system block diagram of Embodiment 1 of the present invention;

[0025] Figure 2 This is a flow chart of the method of Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0026] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0027] Embodiment 1: Figure 1 As shown, the industrial frequency conversion equipment operation control system based on multi-sensor monitoring includes a test analysis module, a data analysis module and an operation control module, and the test analysis module, the data analysis module and the operation control module are communicatively connected in sequence.

[0028] The test analysis module is used to perform operation control test on industrial frequency conversion equipment: mark the industrial frequency conversion equipment to be tested for operation control as a test object, and mark the control parameters of the test object as analysis parameters FXi, i=1, 2, ..., n, where n is a positive integer, and the analysis parameter FXi includes the maximum operating frequency, the minimum operating frequency, the carrier frequency, the motor power, the acceleration time, the deceleration time, etc.; retrieve the setting range SZi of the analysis parameter i, the setting range SZi is a standard range that corresponds one to one with the analysis parameter FXi, and exemplarily, when the analysis parameter FXi is the highest operating frequency, the setting range SZi is the corresponding highest operating frequency range of 60Hz-400Hz; randomly select a value from the setting range SZi as the test matching value CSi of the analysis parameter FXi, and the test matching values ​​CSi of all the analysis parameters FXi constitute a test data set of the test object, set the value of the analysis parameter FXi of the test object according to the test data set, and then start the test object to run for L1 hours and generate a test process.

[0029] Obtain the temperature and height data WG, vibration frequency data ZP and noise data ZS of the test object during the test process. The temperature and height data WG is the maximum value of the surface temperature of the test object during the test process. The vibration frequency data ZP is the maximum value of the vibration frequency value of the base of the test object during the test process. The noise data ZS is the maximum value of the decibel value of the running noise of the test object during the test process.

[0030] The test coefficient CS of the test object during the test is obtained by the formula CS = (m1 × WG + m2 × ZP + m3 × ZS) / JG, where m1, m2 and m3 are all proportional coefficients, and m1>m2>m3>1; JG is the value of the interval value, and the value-taking process of the interval value JG includes: marking the time points corresponding to the temperature data WG, the seismic frequency data ZP and the noise data ZS during the test as high temperature marking time points, seismic frequency marking time points and noise marking time points respectively, marking the high temperature marking time points, seismic frequency marking time points and noise marking time points Any two time points in the interval are divided into three time periods, and the minimum duration value among the three time periods is marked as the interval value JG; in the same way, L2 test processes are generated and L2 corresponding test coefficients CS are obtained, L1 and L2 are both numerical constants, and the specific values ​​of L1 and L2 are set by the management personnel; the test matching value is randomly selected from the set range to run the test and obtain the test coefficient, and the running status of the test object during the test process is fed back according to the test coefficient, providing data support for optimizing the construction of the data set.

[0031] The data analysis module is used to analyze the operation control test data of industrial frequency conversion equipment: sort the test processes in ascending order according to the test coefficient CS value to obtain a test sequence, intercept the first L3 test processes in the test sequence as the optimization process, where L3 is a numerical constant, and the specific value of L3 is set by the management personnel, and L3 < L2 / 2. Retrieve the test data set corresponding to the optimization process and mark it as the optimization data set. The optimization set YJi of the analysis parameter F Xi is composed of all test matching values C Si in the optimization data set. The optimization interval YQi of the analysis parameter F Xi is composed of the maximum element and the minimum element in the optimization set YJi;

[0032] Intercept the last L3 test processes in the test sequence as the fluctuation process, retrieve the test data set corresponding to the fluctuation process and mark it as the fluctuation data set. The fluctuation set BJi of the analysis parameter F Xi is composed of all test matching values C Si in the fluctuation data set. The fluctuation interval BQi of the analysis parameter F Xi is composed of the maximum element and the minimum element in the fluctuation set BJi;

[0033] Determine whether there is an overlapping part between the optimization interval YQi and the fluctuation interval BQi of the analysis parameter F Xi:

[0034] If so, remove the maximum element and the minimum element in the optimization set YJi to form a new optimization interval YQi, remove the maximum element and the minimum element in the fluctuation set BQi to form a new fluctuation interval BQi, and compare the new optimization interval YQi with the new fluctuation interval BQi again, and so on, until there is no overlapping part between the optimization interval YQi and the fluctuation interval BQi;

[0035] If not, mark the optimization interval YQi as the indentation interval SJi of the analysis parameter F Xi; the optimization data set of the industrial frequency conversion equipment is composed of all indentation intervals SJi of the analysis parameter F Xi; intercept the optimization process and the fluctuation process according to the generated test sequence, then compare the generated optimization interval and the fluctuation interval to generate the optimization data set, and indent the original setting range of the analysis parameter through the optimization data set to improve the rationality of the analysis parameter setting of the industrial frequency conversion equipment.

[0036] The operation control module is used to control the operation parameters of industrial frequency conversion equipment: the industrial frequency conversion equipment to be controlled is marked as a control object, the optimized data set of the industrial frequency conversion equipment is retrieved, and a value is randomly selected from the indentation interval SJi of the optimized data set as the control matching value CZi of the analysis parameter FXi. The control matching values ​​CZi of all analysis parameters FXi constitute the control data set of the control object, and the analysis parameter FXi of the test object is numerically set according to the control data set; the analysis parameters of the industrial frequency conversion equipment are set according to the optimized data set, so that multiple analysis parameters of the industrial frequency conversion equipment can be set within the optimal range, thereby reducing the probability of operation failure of the industrial frequency conversion equipment.

[0037] Embodiment 2: Figure 2 As shown, the operation control method of industrial frequency conversion equipment based on multi-sensor monitoring includes the following steps:

[0038] Step 1: Perform operation control test on industrial frequency conversion equipment: Mark the industrial frequency conversion equipment to be tested for operation control as a test object, set the numerical value of the analysis parameter FXi of the test object according to the test data set, and then start the test object to run for L1 hours and generate a test process;

[0039] Step 2: Obtain the temperature data WG, vibration frequency data ZP and noise data ZS of the test object during the test process and perform numerical calculations to obtain the test coefficient CS of the test process; generate L2 test processes in the same way and obtain L2 corresponding test coefficients CS;

[0040] Step 3: Analyze the operation control test data of the industrial frequency conversion equipment: sort the test process according to the test coefficient CS value from small to large to obtain a test sequence, intercept the test sequence and generate the optimization interval YQi and the fluctuation interval BQi, compare the optimization interval YQi and the fluctuation interval BQi of the analysis parameter FXi and generate the indentation interval SJi;

[0041] Step 4: Control the operating parameters of the industrial frequency conversion equipment: mark the industrial frequency conversion equipment for which the operating parameters are controlled as the control object, retrieve the optimized data set of the industrial frequency conversion equipment, and set the analysis parameter FXi of the control object according to the optimized data set.

[0042] The operation control system of industrial frequency conversion equipment based on multi-sensor monitoring, when working, marks the industrial frequency conversion equipment for operation control test as the test object, sets the numerical value of the analysis parameter FXi of the test object according to the test data set, then starts the test object to run for L1 hours and generates a test process; obtains the temperature and height data WG, vibration frequency data ZP and noise data ZS of the test object in the test process and performs numerical calculation to obtain the test coefficient CS of the test process; generates L2 test processes in the same way and obtains L2 corresponding test coefficients CS; sorts the test processes in the order of the test coefficient CS values ​​from small to large to obtain a test sequence, intercepts the test sequence and generates the optimization interval YQi and the fluctuation interval BQi, compares the optimization interval YQi and the fluctuation interval BQi of the analysis parameter FXi and generates the indentation interval SJi; marks the industrial frequency conversion equipment for operation parameter control as the control object, retrieves the optimization data set of the industrial frequency conversion equipment, and sets the analysis parameter FXi of the control object according to the optimization data set.

[0043] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

[0044] The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula close to the real value. The coefficients in the formula are set by technicians in this field according to the actual situation; for example: formula CS = (m1×WG+m2×ZP+m3×ZS) / JG; technicians in this field collect multiple groups of sample data and set corresponding test coefficients for each group of sample data; substitute the set test coefficients and the collected sample data into the formula, any three formulas constitute a three-variable linear equation group, screen the calculated coefficients and take the average, and obtain the values ​​of m1, m2 and m3 as 3.62, 2.81 and 2.05 respectively;

[0045] The size of the coefficient is to quantify each parameter to obtain a specific value for subsequent comparison. The size of the coefficient depends on the amount of sample data and the preliminary setting of the corresponding test coefficient for each set of sample data by technical personnel in this field; as long as it does not affect the proportional relationship between the parameter and the quantified value, such as the test coefficient is proportional to the value of the temperature and height data.

[0046] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0047] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. The industrial frequency conversion equipment operation control system based on multi-sensor monitoring is characterized by: It includes a test analysis module, a data analysis module and an operation control module, wherein the test analysis module, the data analysis module and the operation control module are sequentially connected in communication; The test analysis module is used to perform operation control test on industrial frequency conversion equipment: marking the industrial frequency conversion equipment to be tested for operation control as a test object, generating L2 test processes for the test object and obtaining L2 corresponding test coefficients CS; The data analysis module is used to analyze the operation control test data of the industrial frequency conversion equipment: the test processes are sorted in order from small to large according to the test coefficient CS values ​​to obtain a test sequence, the first L3 test processes in the test sequence are intercepted as the optimization process, and the optimization interval YQi is extracted according to the optimization process; the last L3 test processes in the test sequence are intercepted as the fluctuation process, and the fluctuation interval BQi is extracted according to the fluctuation process; the optimization interval YQi is compared with the fluctuation interval BQi and an optimization data set is generated according to the comparison result; The operation control module is used to control the operation parameters of the industrial frequency conversion equipment according to the optimized data set.

2. The industrial frequency conversion equipment operation control system based on multi-sensor monitoring according to claim 1 is characterized in that: The specific process of generating a test process for the test object includes: marking the control parameters of the test object as analysis parameters FXi, i=1, 2,…, n, where n is a positive integer, calling the setting range SZi of the analysis parameter i, randomly selecting a value from the setting range SZi as the test matching value CSi of the analysis parameter FXi, and forming a test data set of the test object by the test matching values ​​CSi of all analysis parameters FXi, setting the value of the analysis parameter FXi of the test object according to the test data set, and then starting the test object to run for L1 hours and generating a test process.

3. The industrial frequency conversion equipment operation control system based on multi-sensor monitoring according to claim 2 is characterized in that: The process of obtaining the test coefficient CS during the test process includes: obtaining the temperature and height data WG, vibration frequency data ZP, noise data ZS and interval value JG of the test object during the test process and performing numerical calculations to obtain the test coefficient CS, the temperature and height data WG is the maximum value of the surface temperature value of the test object during the test process, the vibration frequency data ZP is the maximum value of the vibration frequency value of the base of the test object during the test process, and the noise data ZS is the maximum value of the decibel value of the running noise of the test object during the test process.

4. The industrial frequency conversion equipment operation control system based on multi-sensor monitoring according to claim 3 is characterized in that: The process of obtaining the interval value JG includes: marking the time points corresponding to the temperature data WG, the vibration frequency data ZP and the noise data ZS in the test process as high temperature marking time points, vibration frequency marking time points and noise marking time points respectively, dividing any two time points among the high temperature marking time points, the vibration frequency marking time points and the noise marking time points into three time periods, and marking the minimum duration value among the three time periods as the interval value JG.

5. The industrial frequency conversion equipment operation control system based on multi-sensor monitoring according to claim 4 is characterized in that: The extraction process of the optimization interval YQi includes: calling the test data set corresponding to the optimization process and marking it as the optimization data set, forming the optimization set YJi of the analysis parameter FXi from all the test matching values ​​CSi in the optimization data set, and forming the optimization interval YQi of the analysis parameter FXi from the maximum element and the minimum element in the optimization set YJi.

6. The industrial frequency conversion equipment operation control system based on multi-sensor monitoring according to claim 5 is characterized in that: The test data set corresponding to the fluctuation process is retrieved and marked as the fluctuation data set. All test matching values ​​CSi in the fluctuation data set constitute the fluctuation set BJi of the analysis parameter FXi. The maximum element and the minimum element in the fluctuation set BJi constitute the fluctuation interval BQi of the analysis parameter FXi.

7. The industrial frequency conversion equipment operation control system based on multi-sensor monitoring according to claim 6 is characterized in that: The specific process of comparing the optimization interval YQi with the fluctuation interval BQi includes: determining whether there is an overlap between the optimization interval YQi and the fluctuation interval BQi of the analysis parameter FXi: if so, the maximum element and the minimum element in the optimization set YJi are eliminated to form a new optimization interval YQi, the maximum element and the minimum element in the fluctuation set BQi are eliminated to form a new fluctuation interval BQi, the new optimization interval YQi is compared with the new fluctuation interval BQi again, and so on, until there is no overlap between the optimization interval YQi and the fluctuation interval BQi; if not, the optimization interval YQi is marked as the indentation interval SJi of the analysis parameter FXi; the indentation intervals SJi of all analysis parameters FXi constitute the optimization data set of industrial frequency conversion equipment.

8. The industrial frequency conversion equipment operation control system based on multi-sensor monitoring according to claim 7 is characterized in that: The operation control module controls the operation parameters of the industrial frequency conversion equipment according to the optimized data set: the industrial frequency conversion equipment for which the operation parameters are controlled is marked as the control object, the optimized data set of the industrial frequency conversion equipment is called, and a value is randomly selected from the indentation interval SJi of the optimized data set as the control matching value CZi of the analysis parameter FXi. The control matching values ​​CZi of all analysis parameters FXi constitute the control data set of the control object, and the analysis parameter FXi of the test object is numerically set according to the control data set.

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