A method and system for online monitoring temperature of dynamic coil of large thrust vibration table

Abstract

The present invention discloses a method and system for online monitoring the temperature of a dynamic coil of a large-thrust vibration table. By arranging a limited number of thermocouple temperature sensors on the drive coil, a single fitting function is avoided. According to the real-time current and cooling water flow conditions of the vibration table, combined with the data collected by the thermocouple temperature sensor, a fitting function that is more in line with the actual working conditions is used to estimate the temperature of each position on the drive coil. The method and system for online monitoring the temperature of a dynamic coil of a large-thrust vibration table of the present invention can better obtain the overall temperature of the drive coil, thereby accurately evaluating the working state of the drive coil and ensuring the safe and reliable operation of the system.

Description

Technical Field

[0001] The present invention relates to the technical field of vibration tables, and in particular to an online monitoring method and system for the temperature of a dynamic coil of a large-thrust vibration table. Background Art

[0002] The electric vibration table is mainly used for vibration environment reliability test of complete machines or parts, and is widely used in aviation, aerospace, weapons, ships, vehicles and other fields. As the key core component of the electric vibration table, the dynamic coil inputs the alternating set current signal into the dynamic coil, and then generates the expected exciting force on the vibration table under the magnetic field, so as to carry out the vibration fatigue reliability test of the test piece.

[0003] With the increasing demand for vibration testing of large structural parts in the aerospace and other fields, electric vibration tables are gradually developing in the direction of large-scale, and the demand for the thrust of vibration tables is increasing sharply. The increase in the thrust of the vibration table is often achieved by increasing the driving current. The increase in current causes the heat generated by the dynamic coil to increase sharply during use. Real-time monitoring of the heat generated by the dynamic coil is crucial to ensure the safe and reliable operation of the system.

[0004] At present, the existing vibration table products generally monitor the temperature of the dynamic coil by arranging thermocouple temperature sensors at specific positions on the dynamic coil to achieve online temperature monitoring, or estimate the temperature by real-time monitoring of the cooling water temperature during operation. This method can only obtain the temperature of individual points on the dynamic coil, while in reality, there is a difference in the temperature of the dynamic coil at different positions. The existing method cannot evaluate and judge the entire temperature distribution of the dynamic coil, resulting in inaccurate temperature monitoring, which brings certain safety hazards to the long-term and high-thrust operation of the electric vibration table. Summary of the invention

[0005] In response to the above technical problems, the present invention proposes an online monitoring method and system for the dynamic coil temperature of a high-thrust vibration table. The method and system can better obtain the overall temperature condition of the drive coil, thereby accurately evaluating the working state of the coil and ensuring the safe and reliable operation of the system.

[0006] In order to achieve the above technical objectives, the present invention adopts the following technical solutions:

[0007] A method for online monitoring temperature of a dynamic coil of a large-thrust vibration table, wherein the driving coil adopts a cooling structure with water inlet at both ends and water outlet in the middle, comprising the following steps:

[0008] S1. Set The temperature sensor is used to collect the temperature of the lower layer of the driving coil when the vibration test bench is working. The temperature data at different positions, as well as the angular coordinates of the position from the starting point of the driving coil along the direction of the driving coil, The temperature data at each location is recorded as , No. The angle coordinates at the temperature sensor locations are denoted by ,in ;

[0009] S2. Record the real-time current and cooling water flow conditions of the vibration table and calculate the cooling performance evaluation parameters ;

[0010] S3, set For low cooling coefficient, For high cooling coefficient, ,when When , a linear function is used to fit the temperature of each point on the lower layer of the driving coil;

[0011] S4. When When the temperature of each point on the lower layer of the driving coil is fitted by a piecewise function, the piecewise points are set along with the cooling performance evaluation parameters. 1. Make changes according to the differences;

[0012] S5. Solve the temperature fitting function of the upper layer of the driving coil according to the temperature fitting function of the lower layer of the driving coil obtained in steps S1 to S4, so as to perform temperature fitting on the entire driving coil.

[0013] Beneficial effect: The online monitoring method for the dynamic coil temperature of a large-thrust vibration table proposed in the present invention avoids the use of a single fitting function. According to the real-time current and cooling water flow conditions of the vibration table, combined with the data collected by the thermocouple temperature sensor, a fitting function that is more in line with the actual conditions is used to estimate the temperature of each position on the drive coil. The fitting result is more accurate, thereby realizing real-time monitoring of the temperature of the vibration table drive coil.

[0014] In an optional embodiment, step S2 specifically includes:

[0015] S21. Calculate cooling performance evaluation parameters ,in, , , is the current value at that moment, is the cooling water flow rate at that moment, is the rated current of the driving coil, is the rated cooling water flow rate.

[0016] Beneficial effect: The higher the current, the lower the cooling water flow, and the more drastic the increase in the temperature of the drive coil. Through the above steps, the present invention can comprehensively consider the influence of the two factors on the coil temperature and better evaluate the cooling performance of the drive coil.

[0017] In an optional embodiment, step S3 specifically includes:

[0018] S31. Constructor The temperature of each point on the lower layer of the driving coil is fitted with a function, where: is the temperature at the position corresponding to the angle on the driving coil, is the first temperature change rate, is the first reference temperature value; the collected temperature data is subjected to linear regression analysis to obtain , .

[0019] Beneficial effect: When the current increases and the cooling effect is better, that is, when When the temperature of the drive coil changes with the angle The more the change increases, the more linear the relationship becomes. At this time, it is better to use a linear function to fit the temperature on the driving coil.

[0020] In an optional embodiment, step S4 specifically includes:

[0021] S41, determining the cooling performance evaluation parameter at this moment Is it satisfied? If satisfied, execute step S411, if not satisfied, execute step S42;

[0022] S411, Calculation , if satisfied , then the constructor ,in, is the second temperature change rate, is the second reference temperature value, is the number of temperature data collected at and before the segmentation point in step S411, is the symbol of the floor rounding function; The temperature data were analyzed by linear regression to obtain , ; Constructor ,in, is the first corrected temperature change rate, For the The angular coordinates of the temperature sensor position are The temperature data were analyzed by linear regression to obtain ;

[0023] exist When, through the function Perform function fitting on the temperature of each point on the lower layer of the driving coil;

[0024] exist When, through the function Perform function fitting on the temperature of each point on the lower layer of the driving coil; if it does not meet , then execute step S412;

[0025] S412, Constructor The temperature of each point on the lower layer of the driving coil is fitted with a function, where: is the third temperature change rate, is the third reference temperature value; the collected temperature data is subjected to linear regression analysis to obtain , ;

[0026] S42: At this moment, if the cooling performance evaluation parameter satisfy , execute step S421 to perform function fitting on the temperature of each point on the lower layer of the driving coil:

[0027] S421, Calculation , if satisfied , then the constructor ,in, is the fourth temperature change rate, is the fourth reference temperature value, is the number of temperature data collected at and before the segmentation point in step S421, is the symbol of the floor rounding function; The temperature data were analyzed by linear regression to obtain , , constructor ,in, is the second corrected temperature change rate, For the The angular coordinates of the temperature sensor position are The temperature data were analyzed by linear regression to obtain ;

[0028] exist When, through the function Perform function fitting on the temperature of each point on the lower layer of the driving coil;

[0029] exist When, through the function , perform function fitting on the temperature of each point on the lower layer of the driving coil; if it does not meet , then execute step S422;

[0030] S422, Constructor The temperature of each point on the lower layer of the driving coil is fitted with a function, where: is the fifth temperature change rate, is the fifth reference temperature value; the collected temperature data is subjected to linear regression analysis to obtain , .

[0031] Beneficial effect: When the current increases and the cooling effect is not good, that is, when When As the temperature increases, As the temperature increases, a function with a faster growth rate is used to fit the temperature at each position on the driving coil. At the same time, the segmentation points are set as As the value decreases, the segmentation point keeps approaching the starting point. This fitting method is more in line with the actual working condition of the driving coil and has a better fitting effect.

[0032] In an optional embodiment, step S5 specifically includes:

[0033] S51, in The temperature fitting function is used at ,in, For the The angle coordinates at the temperature sensor locations are The temperature fitting function is used at Perform function fitting on the temperature of each point on the driving coil.

[0034] Beneficial effect: The driving coil of the present invention adopts a cooling method of water inlet at both ends and water outlet in the middle, so only the fitting function of the lower layer of the driving coil needs to be obtained to perform temperature fitting on the entire driving coil, thereby avoiding repeated fitting of the upper layer coil.

[0035] In an optional embodiment, in step S1, the lower part of the acquisition drive coil The temperature data at different positions is evenly distributed in the lower part of the driving coil. Thermocouple temperature sensors are numbered from bottom to top, and the bottom thermocouple temperature sensor is numbered as The value of the thermocouple temperature sensor is ,in .

[0036] Beneficial effects: Thermocouples can cover a wide temperature range, and the response time is usually very short, which can quickly reflect temperature changes. For devices such as drive coils that may experience high operating temperatures, thermocouples can provide reliable temperature measurement. At the same time, due to the small size and simple structure of thermocouples, they can be installed in places with limited space, which can achieve flexible layout.

[0037] In an optional embodiment, in step S2, the high cooling coefficient The value range is 3~5, the low cooling coefficient The value range is 0.7~0.8.

[0038] Beneficial effects: through The value of is evaluated and the optimal value is selected to ensure that it is more in line with the function fitting method involved in this patent and improve the fitting accuracy.

[0039] In an optional embodiment, The temperature data of the temperature sensors at different locations, .

[0040] Beneficial effects: When More accurate temperature monitoring can be achieved to avoid erroneous judgment of the coil temperature status due to neglect of local high-temperature points on the drive coil.

[0041] The present invention further discloses an online monitoring system for the temperature of a large-thrust vibration table moving coil, comprising a driving coil, wherein the middle and lower parts of the driving coil are uniformly distributed temperature sensors, the temperature sensor at the bottom is recorded as the first temperature sensor, and the temperature sensors are numbered from bottom to top. The multiple temperature sensors are electrically connected to the external control module through data lines respectively, and the online monitoring method for the dynamic coil temperature of the high-thrust vibration table is adopted.

[0042] In an optional embodiment, the temperature sensor is a thermocouple temperature sensor.

[0043] In an optional embodiment, the thrust range of the high-thrust vibration table is 400 kN~1000 kN. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 The schematic diagram of temperature function fitting for each point on the driving coil;

[0045] Figure 2 This is a layout diagram of the thermocouple temperature sensor on the drive coil of the present invention;

[0046] Figure 3 This is the flow chart for fitting the temperature function of each point on the driving coil. DETAILED DESCRIPTION

[0047] The technical solution of the present invention is further described in detail below in conjunction with specific embodiments and the accompanying drawings so that those skilled in the art can better understand the present invention and implement it, but the embodiments are not intended to limit the present invention.

[0048] The present invention discloses an online monitoring method for the temperature of a dynamic coil of a large-thrust vibration platform. The driving coil adopts a cooling structure with water inlet at both ends and water outlet in the middle, comprising the following steps:

[0049] S1. Remember The angle of rotation of the coil from the coil starting point to the coil winding direction is collected when the vibration test bench is working. The temperature data at different positions and the angular coordinates of the position from the starting point of the coil along the direction of the coil, The temperature data at each location is recorded as , No. The angle coordinates of the temperature sensor at each position are marked as ,in ; Note that the rated current of the drive coil is , rated cooling water flow is ;

[0050] S2, record the current value at this moment At this moment, the cooling water flow rate is ,remember , , calculate the cooling performance evaluation parameters ,remember For low cooling coefficient, For high cooling coefficient, ;

[0051] It is understandable that this embodiment can determine the cooling condition of the high-thrust vibration table drive coil at that moment by analyzing and measuring the relationship between the current value and the cooling water flow at that moment, and then select different functions to perform function fitting on the temperature at each position on the drive coil.

[0052] Considering that, when the cooling is better, the temperature on the drive coil increases with the angle The more the cooling condition is, the more the temperature on the drive coil increases with the angle. The growth rate of is getting faster and faster, so it is necessary to use a function with a faster growth rate to fit the temperature at each position on the driving coil. This method includes S1~S4, as follows:

[0053] S3, when When , a linear function is used to fit the temperature of each point on the lower layer of the driving coil;

[0054] S31. Constructor The temperature of each point on the lower layer of the driving coil is fitted with a function, where: is the temperature at the position corresponding to the angle on the coil, is the first temperature change rate, is the first reference temperature value; the collected temperature data is subjected to linear regression analysis to obtain , ;

[0055] S4. When When the temperature of each point on the lower layer of the driving coil is fitted by a piecewise function, the piecewise points are set as 1. Make changes according to the differences;

[0056] S41, determining the cooling performance evaluation parameters at this moment Is it satisfied? If satisfied, execute step S411, if not satisfied, execute step S42;

[0057] S411, Calculation , if satisfied , then the constructor ,in, is the second temperature change rate, is the second reference temperature value, is the number of temperature data collected before (including) the segmentation point in step S411, is the symbol of the floor rounding function; The temperature data were analyzed by linear regression to obtain , ; Constructor ,in, is the first corrected temperature change rate, For the The angle coordinates at the position of The temperature data were analyzed by linear regression to obtain ;

[0058] exist When, through the function Perform function fitting on the temperature of each point on the lower layer of the driving coil;

[0059] exist When, through the function Perform function fitting on the temperature of each point on the lower layer of the driving coil; if it does not meet , then execute step S412;

[0060] S412, Constructor The temperature of each point on the lower layer of the driving coil is fitted with a function, where: is the third temperature change rate, is the third reference temperature value; the collected temperature data is subjected to linear regression analysis to obtain , ;

[0061] S42: At this moment, if the cooling performance evaluation parameter satisfy , execute step S421 to perform function fitting on the temperature of each point on the lower layer of the driving coil:

[0062] S421, Calculation , if satisfied , then the constructor ,in, is the fourth temperature change rate, is the fourth reference temperature value, is the number of temperature data collected before (including) the segmentation point in step S421, is the symbol of the floor rounding function; The temperature data were analyzed by linear regression to obtain , , constructor ,in, is the second corrected temperature change rate, For the The angle coordinates at the position of The temperature data were analyzed by linear regression to obtain ;

[0063] exist When, through the function Perform function fitting on the temperature of each point on the lower layer of the driving coil;

[0064] exist When, through the function , perform function fitting on the temperature of each point on the lower layer of the driving coil; if it does not meet , then execute step S422;

[0065] S422, Constructor The temperature of each point on the lower layer of the driving coil is fitted with a function, where: is the fifth temperature change rate, is the fifth reference temperature value; the collected temperature data is subjected to linear regression analysis to obtain , ;

[0066] It is understandable that the drive coil involved in the present invention adopts a cooling method of water inlet at both ends and water outlet in the middle, so it is only necessary to obtain the fitting function of the lower layer of the drive coil to perform temperature fitting on the entire drive coil.

[0067] S5, solving the temperature fitting function of the upper layer of the driving coil according to the temperature fitting function of the lower layer of the driving coil obtained in steps S1 to S4, thereby performing temperature fitting on the entire driving coil;

[0068] S51, in The temperature fitting function is used at ,in, For the The angular coordinates at the position, The temperature fitting function is used at Perform function fitting on the temperature of each point on the driving coil.

[0069] As a preferred technical means of the above technical means of the present invention, in step S1, the lower part of the acquisition drive coil The temperature data at different positions is evenly distributed in the lower part of the driving coil. Thermocouple temperature sensors are numbered from bottom to top, and the bottom thermocouple temperature sensor is numbered as The value of the thermocouple temperature sensor is ,in Preferably, the number of the thermocouple temperature sensors is is 5.

[0070] In step S2 of the present invention, the high cooling coefficient The value range is 3~5, the low cooling coefficient The value range is 0.7~0.8.

[0071] The drive coil temperature estimation and fitting method proposed in the present invention avoids the use of a single fitting function by arranging a limited number of thermocouple temperature sensors on the coil. According to the real-time current and cooling water flow conditions of the vibration table, combined with the data collected by the thermocouple temperature sensors, a fitting function that is more in line with the actual conditions is used to estimate the temperature of each position on the drive coil. The fitting result is more accurate, thereby realizing real-time monitoring of the temperature of the vibration table drive coil.

[0072] Furthermore, different piecewise functions are used for fitting under different working conditions, and the segmentation points are set to change continuously with different working conditions, so as to make the fitting results more accurate.

[0073] Based on the above improvements, the present invention can better obtain the overall temperature condition of the driving coil, thereby accurately evaluating the working state of the coil.

[0074] The present invention further discloses an online monitoring system for the temperature of a large-thrust vibration table moving coil, comprising a driving coil, wherein the middle and lower parts of the driving coil are uniformly distributed temperature sensors, the temperature sensor at the bottom is recorded as the first temperature sensor, and the temperature sensors are numbered from bottom to top. The multiple temperature sensors are electrically connected to the external control module through data lines respectively, and the online monitoring method for the dynamic coil temperature of the high-thrust vibration table is adopted.

[0075] In an optional embodiment, the temperature sensor is a thermocouple temperature sensor.

[0076] In an optional embodiment, the thrust range of the high-thrust vibration table is 400 kN~1000 kN.

[0077] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for online monitoring of the temperature of a dynamic coil of a large-thrust vibration table, wherein the driving coil adopts a cooling structure with water inlet at both ends and water outlet in the middle, characterized in that: The following steps are involved: S1. Set The angle of rotation of the position on the driving coil from the starting point of the driving coil along the winding direction of the driving coil is collected by the temperature sensor when the vibration test bench is working. The temperature data at different positions, as well as the angular coordinates of the position from the starting point of the driving coil along the direction of the driving coil, The temperature data at each location is recorded as , No. The angle coordinates at the temperature sensor locations are denoted by ,in ; S2. Record the real-time current and cooling water flow conditions of the vibration table and calculate the cooling performance evaluation parameters ; S3, set For low cooling coefficient, For high cooling coefficient, ,when When , a linear function is used to fit the temperature of each point on the lower layer of the driving coil; S4. When When the temperature of each point on the lower layer of the driving coil is fitted by a piecewise function, the piecewise points are set along with the cooling performance evaluation parameters.

1. Make changes according to the differences; S5. Solve the temperature fitting function of the upper layer of the driving coil according to the temperature fitting function of the lower layer of the driving coil obtained in steps S1 to S4, so as to perform temperature fitting on the entire driving coil.

2. The method for online monitoring temperature of the dynamic coil of a high-thrust vibration table according to claim 1 is characterized in that: Step S2 specifically includes: S21. Calculate cooling performance evaluation parameters ,in, , , is the current value at that moment, is the cooling water flow rate at that moment, is the rated current of the driving coil, is the rated cooling water flow rate.

3. The method for online monitoring temperature of the dynamic coil of a high-thrust vibration table according to claim 1 is characterized in that: Step S3 specifically includes: S31. Constructor The temperature of each point on the lower layer of the driving coil is fitted with a function, where: is the temperature at the position corresponding to the angle on the driving coil, is the first temperature change rate, is the first reference temperature value, and the collected temperature data is subjected to linear regression analysis to obtain , .

4. The method for online monitoring temperature of the dynamic coil of a high-thrust vibration table according to claim 1 is characterized in that: Step S4 specifically includes: S41, determining the cooling performance evaluation parameter at this moment Is it satisfied? If satisfied, execute step S411, if not satisfied, execute step S42; S411, Calculation , if satisfied , then the constructor ,in, is the second temperature change rate, is the second reference temperature value, is the number of temperature data collected at and before the segmentation point in step S411, is the symbol of the floor rounding function; The temperature data were analyzed by linear regression to obtain , ; Constructor ,in, is the first corrected temperature change rate, For the The angular coordinates of the temperature sensor position are The temperature data were analyzed by linear regression to obtain ; exist When, through the function Perform function fitting on the temperature of each point on the lower layer of the driving coil; exist When, through the function Perform function fitting on the temperature of each point on the lower layer of the driving coil; if it does not meet , then execute step S412; S412, Constructor The temperature of each point on the lower layer of the driving coil is fitted with a function, where: is the third temperature change rate, The third reference temperature value is obtained by performing linear regression analysis on the collected temperature data. , ; S42: At this moment, if the cooling performance evaluation parameter satisfy , execute step S421 to perform function fitting on the temperature of each point on the lower layer of the driving coil: S421, Calculation , if satisfied , then the constructor ,in, is the fourth temperature change rate, is the fourth reference temperature value, is the number of temperature data collected before (including) the segmentation point in step S421, is the symbol of the floor rounding function; The temperature data were analyzed by linear regression to obtain , , constructor ,in, is the second corrected temperature change rate, For the The angular coordinates of the temperature sensor position are The temperature data were analyzed by linear regression to obtain ; exist When, through the function Perform function fitting on the temperature of each point on the lower layer of the driving coil; exist When, through the function , perform function fitting on the temperature of each point on the lower layer of the driving coil; if it does not meet , then execute step S422; S422, Constructor The temperature of each point on the lower layer of the driving coil is fitted with a function, where: is the fifth temperature change rate, is the fifth reference temperature value; the collected temperature data is subjected to linear regression analysis to obtain , .

5. The method for online monitoring temperature of the dynamic coil of a high-thrust vibration table according to claim 1 is characterized in that: Step S5 specifically includes: S51, in The temperature fitting function is used at ,in, For the The angular coordinates of the temperature sensor positions are The temperature fitting function is used at Perform function fitting on the temperature of each point on the driving coil.

6. The method for online monitoring temperature of the dynamic coil of a high-thrust vibration table according to claim 1 is characterized in that: In step S2, the high cooling coefficient The value range is 3~5, the low cooling coefficient The value range is 0.7~0.

8.

7. The method for online monitoring temperature of the dynamic coil of a high-thrust vibration table according to claim 1 is characterized in that: Said The value range of .

8. An online monitoring system for the temperature of a large-thrust vibration table moving coil, comprising a drive coil, wherein the middle and lower parts of the drive coil are evenly distributed temperature sensors, the temperature sensor at the bottom is the first temperature sensor, and the temperature sensors are numbered from bottom to top, and the plurality of temperature sensors are electrically connected to the external control module through data lines, respectively, wherein: The online monitoring method for the dynamic coil temperature of a high-thrust vibration table as described in any one of claims 1 to 7 is adopted.

9. The high-thrust vibration table dynamic coil temperature online monitoring system according to claim 8 is characterized in that: The temperature sensor is a thermocouple temperature sensor.

10. The high-thrust vibration table dynamic coil temperature online monitoring system according to claim 8, characterized in that: The thrust range of the high-thrust vibration table is 400kN~1000kN.

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