Track fastener bolt automatic tightening method and system based on looseness detection

Abstract

The invention discloses a track fastener bolt automatic tightening method and system based on looseness detection, and the method comprises the steps: setting a fastener bolt looseness degree detection model, and calculating the looseness degree of a fastener bolt; a required torque estimation model is set, and the torque required for tightening the fastener bolt is calculated according to the looseness degree of the fastener bolt and the standard torque when the fastener bolt is not loosened; a servo motor rotation angle estimation model is set, and the rotation angle of the servo motor is calculated according to the initial angle of the servo motor, the torque needed for tightening the fastener bolt in the previous control period, the maximum torque capable of being provided by the motor and the torque needed for tightening the fastener bolt; and setting an automatic tightening control signal adjustment model, calculating a control signal value of the servo motor, and when the control signal value of the servo motor exceeds a preset threshold value, sending a signal to the servo motor, so that the servo motor performs rotation control on the fastener bolt according to the rotation angle until the control signal value of the servo motor is smaller than the preset threshold value.

Description

Technical Field

[0001] The present invention belongs to the technical field of automatic tightening of railway track fasteners, and more specifically, relates to a method and system for automatically tightening rail fastener bolts based on looseness detection. Background Art

[0002] Rail fastener bolts are crucial fastening components in railway track systems, primarily used to securely connect the track to the sleeper (or track base). They play a crucial role in supporting and securing the track during rail transportation, making their performance and safety paramount. Because railway tracks are subject to multiple factors over time, such as temperature, vibration, and load, bolts can loosen, compromising the stability of the track structure. Therefore, the design of intelligent monitoring and tightening systems is crucial.

[0003] However, the fastener bolts are still tightened manually, which will increase the labor cost and the tightening accuracy is not high. Summary of the Invention

[0004] To solve the above technical problems, the present invention proposes a method for automatically tightening rail fastener bolts based on looseness detection, comprising:

[0005] Monitor the status of fastener bolts in real time, obtain information about the fastener bolts, set a fastener bolt looseness detection model, and calculate the looseness of the fastener bolts, wherein the information includes: the speed, acceleration, ambient noise, and ambient temperature of the fastener bolts;

[0006] A required torque estimation model is set up to calculate the torque required to tighten the fastener bolts based on the looseness of the fastener bolts and the standard torque when the fastener bolts are not loosened;

[0007] Set up a servo motor rotation angle estimation model and calculate the servo motor rotation angle based on the servo motor's initial angle, the torque required to tighten the fastener bolts in the previous control cycle, the maximum torque that the motor can provide, and the torque required to tighten the fastener bolts;

[0008] An automatic tightening control signal adjustment model is set to calculate the control signal value of the servo motor. When the control signal value of the servo motor exceeds a preset threshold, a signal is sent to the servo motor to cause the servo motor to rotate the fastener bolt according to the rotation angle until the control signal value of the servo motor is less than the preset threshold.

[0009] Furthermore, the fastener bolt looseness detection model includes:

[0010]

[0011] Wherein, ΔL(t) is the looseness of the fastener bolt at time t, V(t) is the velocity of the fastener bolt at time t, α1 is the first adjustment factor of the fastener bolt looseness detection model, A(τ) is the acceleration of the fastener bolt at time τ, β1 is the second adjustment factor of the fastener bolt looseness detection model, Noise(t) is the ambient noise at time t, γ1 is the third adjustment factor of the fastener bolt looseness detection model, T env (t) is the ambient temperature at time t, and T0 is the reference temperature.

[0012] Furthermore, the required torque estimation model includes:

[0013]

[0014] Among them, T(t) is the torque required to tighten the fastener bolt at time t, T0 is the standard torque when the fastener bolt is not loose, α2 is the first adjustment factor of the required torque estimation model, β2 is the second adjustment factor of the required torque estimation model, β3 is the third adjustment factor of the required torque estimation model, λ2 is the fourth adjustment factor of the required torque estimation model, η1 is the fifth adjustment factor of the required torque estimation model, γ2 is the sixth adjustment factor of the required torque estimation model, and ω1 is the seventh adjustment factor of the required torque estimation model.

[0015] Furthermore, the servo motor rotation angle estimation model includes:

[0016]

[0017] Where θ(t) is the rotation angle of the servo motor at time t, θ0 is the initial angle of the servo motor, κ1 is the first adjustment factor of the servo motor rotation angle estimation model, ζ1 is the second adjustment factor of the servo motor rotation angle estimation model, T prev is the torque required to tighten the fastener bolts in the previous control cycle, γ3 is the third adjustment factor of the servo motor rotation angle estimation model, κ2 is the fourth adjustment factor of the servo motor rotation angle estimation model, T max is the maximum torque that the motor can provide, λ3 is the fifth adjustment factor of the servo motor rotation angle estimation model, ω2 is the sixth adjustment factor of the servo motor rotation angle estimation model, and β4 is the seventh adjustment factor of the servo motor rotation angle estimation model.

[0018] Furthermore, the automatic tightening control signal adjustment model includes:

[0019]

[0020] Where u(t) is the control signal value of the servo motor at time t, K p is the proportional coefficient of adaptive PID control, Tmeasured (t) is the actual torque measured at time t, K i is the integral coefficient of adaptive PID control, K d is the differential coefficient of the adaptive PID control, η2 is the first adjustment factor of the automatic tightening control signal adjustment model, and λ4 is the second adjustment factor of the automatic tightening control signal adjustment model.

[0021] The present invention also proposes a rail fastener bolt automatic tightening system based on looseness detection, comprising:

[0022] a looseness calculation module for monitoring the status of fastener bolts in real time, obtaining information about the fastener bolts, setting a fastener bolt looseness detection model, and calculating the looseness of the fastener bolts, wherein the information includes: the speed, acceleration, ambient noise, and ambient temperature of the fastener bolts;

[0023] A torque calculation module is used to set a required torque estimation model and calculate the torque required to tighten the fastener bolts based on the looseness of the fastener bolts and the standard torque when the fastener bolts are not loose;

[0024] A rotation angle calculation module is used to set a servo motor rotation angle estimation model and calculate the rotation angle of the servo motor based on the initial angle of the servo motor, the torque required to tighten the fastener bolts in the previous control cycle, the maximum torque that the motor can provide, and the torque required to tighten the fastener bolts;

[0025] The control module is used to set an automatic tightening control signal adjustment model, calculate the control signal value of the servo motor, and when the control signal value of the servo motor exceeds a preset threshold, send a signal to the servo motor to rotate the fastener bolt according to the rotation angle until the control signal value of the servo motor is less than the preset threshold.

[0026] Furthermore, the fastener bolt looseness detection model includes:

[0027]

[0028] Wherein, ΔL(t) is the looseness of the fastener bolt at time t, V(t) is the velocity of the fastener bolt at time t, α1 is the first adjustment factor of the fastener bolt looseness detection model, A(τ) is the acceleration of the fastener bolt at time τ, β1 is the second adjustment factor of the fastener bolt looseness detection model, Noise(t) is the ambient noise at time t, γ1 is the third adjustment factor of the fastener bolt looseness detection model, T env (t) is the ambient temperature at time t, and T0 is the reference temperature.

[0029] Furthermore, the required torque estimation model includes:

[0030]

[0031] Among them, T(t) is the torque required to tighten the fastener bolt at time t, T0 is the standard torque when the fastener bolt is not loose, α2 is the first adjustment factor of the required torque estimation model, β2 is the second adjustment factor of the required torque estimation model, β3 is the third adjustment factor of the required torque estimation model, λ2 is the fourth adjustment factor of the required torque estimation model, η1 is the fifth adjustment factor of the required torque estimation model, γ2 is the sixth adjustment factor of the required torque estimation model, and ω1 is the seventh adjustment factor of the required torque estimation model.

[0032] Furthermore, the servo motor rotation angle estimation model includes:

[0033]

[0034] Where θ(t) is the rotation angle of the servo motor at time t, θ0 is the initial angle of the servo motor, κ1 is the first adjustment factor of the servo motor rotation angle estimation model, ζ1 is the second adjustment factor of the servo motor rotation angle estimation model, T prev is the torque required to tighten the fastener bolts in the previous control cycle, γ3 is the third adjustment factor of the servo motor rotation angle estimation model, κ2 is the fourth adjustment factor of the servo motor rotation angle estimation model, T max is the maximum torque that the motor can provide, λ3 is the fifth adjustment factor of the servo motor rotation angle estimation model, ω2 is the sixth adjustment factor of the servo motor rotation angle estimation model, and β4 is the seventh adjustment factor of the servo motor rotation angle estimation model.

[0035] Furthermore, the automatic tightening control signal adjustment model includes:

[0036]

[0037] Where u(t) is the control signal value of the servo motor at time t, K p is the proportional coefficient of adaptive PID control, T measured (t) is the actual torque measured at time t, K i is the integral coefficient of adaptive PID control, K d is the differential coefficient of the adaptive PID control, η2 is the first adjustment factor of the automatic tightening control signal adjustment model, and λ4 is the second adjustment factor of the automatic tightening control signal adjustment model.

[0038] In general, the above technical solutions conceived by the present invention have the following beneficial effects compared with the prior art:

[0039] The present invention sets a fastener bolt looseness detection model, a required torque estimation model, a servo motor rotation angle estimation model and an automatic tightening control signal adjustment model, thereby being able to calculate the control signal value of the servo motor, and control the servo motor to rotate the fastener bolt according to the rotation angle through the control signal, so as to tighten the fastener bolt, thereby accurately and automatically completing the fastener tightening, reducing labor costs and improving work efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 is a flow chart of the method of embodiment 1 of the present invention;

[0041] Figure 2 This is a system structure diagram of Example 2 of the present invention. DETAILED DESCRIPTION

[0042] In order to better understand the above technical solution, the above technical solution will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0043] The method provided by the present invention can be implemented in the following terminal environment, wherein the terminal may include one or more of the following components: a processor, a storage medium, and a display screen. The storage medium stores at least one instruction, which is loaded and executed by the processor to implement the method described in the following embodiments.

[0044] A processor can include one or more processing cores. It connects various components within the terminal using various interfaces and circuits. It executes instructions, programs, code sets, or instruction sets stored in storage media, and accesses data stored in storage media to perform various terminal functions and process data.

[0045] The storage medium may include a random access memory (RAM) or a read-only memory (ROM). The storage medium may be used to store instructions, programs, codes, code sets, or instructions.

[0046] The display is used to show the user interface of each application.

[0047] In addition, those skilled in the art will appreciate that the structure of the terminal described above does not limit the terminal. The terminal may include more or fewer components, or a combination of certain components, or a different arrangement of components. For example, the terminal may also include a radio frequency circuit, an input unit, a sensor, an audio circuit, a power supply, and other components, which will not be described in detail here.

[0048] Example 1

[0049] like Figure 1As shown, an embodiment of the present invention provides a method for automatically tightening rail fastener bolts based on looseness detection, comprising:

[0050] Step 101: monitor the status of fastener bolts in real time, obtain information about the fastener bolts, set a fastener bolt looseness detection model, and calculate the looseness of the fastener bolts, wherein the information includes: the speed, acceleration, ambient noise, and ambient temperature of the fastener bolts;

[0051] Specifically, the fastener bolt looseness detection model includes:

[0052]

[0053] Wherein, ΔL(t) is the looseness of the fastener bolt at time t, V(t) is the velocity of the fastener bolt at time t, α1 is the first adjustment factor of the fastener bolt looseness detection model, A(τ) is the acceleration of the fastener bolt at time τ, β1 is the second adjustment factor of the fastener bolt looseness detection model, Noise(t) is the environmental noise (such as vibration interference) at time t, γ1 is the third adjustment factor of the fastener bolt looseness detection model, T env (t) is the ambient temperature at time t, and T0 is the reference temperature.

[0054] Step 102: Setting a required torque estimation model and calculating the torque required to tighten the fastener bolts based on the looseness of the fastener bolts and the standard torque when the fastener bolts are not loose.

[0055] Specifically, the required torque estimation model includes:

[0056]

[0057] Among them, T(t) is the torque required to tighten the fastener bolt at time t, T0 is the standard torque when the fastener bolt is not loose, α2 is the first adjustment factor of the required torque estimation model, β2 is the second adjustment factor of the required torque estimation model, β3 is the third adjustment factor of the required torque estimation model, λ2 is the fourth adjustment factor of the required torque estimation model, η1 is the fifth adjustment factor of the required torque estimation model, γ2 is the sixth adjustment factor of the required torque estimation model, and ω1 is the seventh adjustment factor of the required torque estimation model.

[0058] Step 103: Setting a servo motor rotation angle estimation model and calculating the servo motor rotation angle based on the servo motor's initial angle, the torque required to tighten the fastener bolt in the previous control cycle, the maximum torque that the motor can provide, and the torque required to tighten the fastener bolt;

[0059] Specifically, the servo motor rotation angle estimation model includes:

[0060]

[0061] Where θ(t) is the rotation angle of the servo motor at time t, θ0 is the initial angle of the servo motor, κ1 is the first adjustment factor of the servo motor rotation angle estimation model, ζ1 is the second adjustment factor of the servo motor rotation angle estimation model, T prev is the torque required to tighten the fastener bolts in the previous control cycle, γ3 is the third adjustment factor of the servo motor rotation angle estimation model, κ2 is the fourth adjustment factor of the servo motor rotation angle estimation model, T max is the maximum torque that the motor can provide, λ3 is the fifth adjustment factor of the servo motor rotation angle estimation model, ω2 is the sixth adjustment factor of the servo motor rotation angle estimation model, and β4 is the seventh adjustment factor of the servo motor rotation angle estimation model.

[0062] Step 104, set an automatic tightening control signal adjustment model, calculate the control signal value of the servo motor, and when the control signal value of the servo motor exceeds a preset threshold, send a signal to the servo motor to rotate the fastener bolt according to the rotation angle until the control signal value of the servo motor is less than the preset threshold.

[0063] Specifically, the automatic tightening control signal adjustment model includes:

[0064]

[0065] Where u(t) is the control signal value of the servo motor at time t, K p is the proportional coefficient of adaptive PID control, T measured (t) is the actual torque measured at time t, K i is the integral coefficient of adaptive PID control, K d is the differential coefficient of the adaptive PID control, η2 is the first adjustment factor of the automatic tightening control signal adjustment model, and λ4 is the second adjustment factor of the automatic tightening control signal adjustment model.

[0066] All the above adjustment factors are fitted by gradient descent method or ant colony algorithm.

[0067] Example 2

[0068] like Figure 2 As shown, an embodiment of the present invention further provides a rail fastener bolt automatic tightening system based on looseness detection, comprising:

[0069] a looseness calculation module for monitoring the status of fastener bolts in real time, obtaining information about the fastener bolts, setting a fastener bolt looseness detection model, and calculating the looseness of the fastener bolts, wherein the information includes: the speed, acceleration, ambient noise, and ambient temperature of the fastener bolts;

[0070] Specifically, the fastener bolt looseness detection model includes:

[0071]

[0072] Wherein, ΔL(t) is the looseness of the fastener bolt at time t, V(t) is the velocity of the fastener bolt at time t, α1 is the first adjustment factor of the fastener bolt looseness detection model, A(τ) is the acceleration of the fastener bolt at time τ, β1 is the second adjustment factor of the fastener bolt looseness detection model, Noise(t) is the ambient noise at time t, γ1 is the third adjustment factor of the fastener bolt looseness detection model, T env (t) is the ambient temperature at time t, and T0 is the reference temperature.

[0073] A torque calculation module is used to set a required torque estimation model and calculate the torque required to tighten the fastener bolts based on the looseness of the fastener bolts and the standard torque when the fastener bolts are not loose;

[0074] Specifically, the required torque estimation model includes:

[0075]

[0076] Among them, T(t) is the torque required to tighten the fastener bolt at time t, T0 is the standard torque when the fastener bolt is not loose, α2 is the first adjustment factor of the required torque estimation model, β2 is the second adjustment factor of the required torque estimation model, β3 is the third adjustment factor of the required torque estimation model, λ2 is the fourth adjustment factor of the required torque estimation model, η1 is the fifth adjustment factor of the required torque estimation model, γ2 is the sixth adjustment factor of the required torque estimation model, and ω1 is the seventh adjustment factor of the required torque estimation model.

[0077] A rotation angle calculation module is used to set a servo motor rotation angle estimation model and calculate the rotation angle of the servo motor based on the initial angle of the servo motor, the torque required to tighten the fastener bolts in the previous control cycle, the maximum torque that the motor can provide, and the torque required to tighten the fastener bolts;

[0078] Specifically, the servo motor rotation angle estimation model includes:

[0079]

[0080] Where θ(t) is the rotation angle of the servo motor at time t, θ0 is the initial angle of the servo motor, κ1 is the first adjustment factor of the servo motor rotation angle estimation model, ζ1 is the second adjustment factor of the servo motor rotation angle estimation model, T previs the torque required to tighten the fastener bolts in the previous control cycle, γ3 is the third adjustment factor of the servo motor rotation angle estimation model, κ2 is the fourth adjustment factor of the servo motor rotation angle estimation model, T max is the maximum torque that the motor can provide, λ3 is the fifth adjustment factor of the servo motor rotation angle estimation model, ω2 is the sixth adjustment factor of the servo motor rotation angle estimation model, and β4 is the seventh adjustment factor of the servo motor rotation angle estimation model.

[0081] The control module is used to set an automatic tightening control signal adjustment model, calculate the control signal value of the servo motor, and when the control signal value of the servo motor exceeds a preset threshold, send a signal to the servo motor to rotate the fastener bolt according to the rotation angle until the control signal value of the servo motor is less than the preset threshold.

[0082] Specifically, the automatic tightening control signal adjustment model includes:

[0083]

[0084] Where u(t) is the control signal value of the servo motor at time t, K p is the proportional coefficient of adaptive PID control, T measured (t) is the actual torque measured at time t, K i is the integral coefficient of adaptive PID control, K d is the differential coefficient of the adaptive PID control, η2 is the first adjustment factor of the automatic tightening control signal adjustment model, and λ4 is the second adjustment factor of the automatic tightening control signal adjustment model.

[0085] All the above adjustment factors are fitted by gradient descent method or ant colony algorithm.

[0086] Example 3

[0087] An embodiment of the present invention further provides a storage medium storing a plurality of instructions, wherein the instructions are used to implement the aforementioned method for automatically tightening rail fastener bolts based on looseness detection.

[0088] Optionally, in this embodiment, the storage medium may be located in any computer terminal in a computer terminal group in a computer network, or in any mobile terminal in a mobile terminal group.

[0089] Optionally, in this embodiment, the storage medium is configured to store program codes for executing the following steps: Step 101, monitoring the status of the fastener bolt in real time, obtaining information about the fastener bolt, setting a fastener bolt looseness detection model, and calculating the looseness of the fastener bolt, wherein the information includes: speed, acceleration, ambient noise, and ambient temperature of the fastener bolt;

[0090] Specifically, the fastener bolt looseness detection model includes:

[0091]

[0092] Wherein, ΔL(t) is the looseness of the fastener bolt at time t, V(t) is the velocity of the fastener bolt at time t, α1 is the first adjustment factor of the fastener bolt looseness detection model, A(τ) is the acceleration of the fastener bolt at time τ, β1 is the second adjustment factor of the fastener bolt looseness detection model, Noise(t) is the ambient noise at time t, γ1 is the third adjustment factor of the fastener bolt looseness detection model, T env (t) is the ambient temperature at time t, and T0 is the reference temperature.

[0093] Step 102: Setting a required torque estimation model and calculating the torque required to tighten the fastener bolts based on the looseness of the fastener bolts and the standard torque when the fastener bolts are not loose.

[0094] Specifically, the required torque estimation model includes:

[0095]

[0096] Among them, T(t) is the torque required to tighten the fastener bolt at time t, T0 is the standard torque when the fastener bolt is not loose, α2 is the first adjustment factor of the required torque estimation model, β2 is the second adjustment factor of the required torque estimation model, β3 is the third adjustment factor of the required torque estimation model, λ2 is the fourth adjustment factor of the required torque estimation model, η1 is the fifth adjustment factor of the required torque estimation model, γ2 is the sixth adjustment factor of the required torque estimation model, and ω1 is the seventh adjustment factor of the required torque estimation model.

[0097] Step 103: Setting a servo motor rotation angle estimation model and calculating the servo motor rotation angle based on the servo motor's initial angle, the torque required to tighten the fastener bolt in the previous control cycle, the maximum torque that the motor can provide, and the torque required to tighten the fastener bolt;

[0098] Specifically, the servo motor rotation angle estimation model includes:

[0099]

[0100] Where θ(t) is the rotation angle of the servo motor at time t, θ0 is the initial angle of the servo motor, κ1 is the first adjustment factor of the servo motor rotation angle estimation model, ζ1 is the second adjustment factor of the servo motor rotation angle estimation model, T previs the torque required to tighten the fastener bolts in the previous control cycle, γ3 is the third adjustment factor of the servo motor rotation angle estimation model, κ2 is the fourth adjustment factor of the servo motor rotation angle estimation model, T max is the maximum torque that the motor can provide, λ3 is the fifth adjustment factor of the servo motor rotation angle estimation model, ω2 is the sixth adjustment factor of the servo motor rotation angle estimation model, and β4 is the seventh adjustment factor of the servo motor rotation angle estimation model.

[0101] Step 104, set an automatic tightening control signal adjustment model, calculate the control signal value of the servo motor, and when the control signal value of the servo motor exceeds a preset threshold, send a signal to the servo motor to rotate the fastener bolt according to the rotation angle until the control signal value of the servo motor is less than the preset threshold.

[0102] Specifically, the automatic tightening control signal adjustment model includes:

[0103]

[0104] Where u(t) is the control signal value of the servo motor at time t, K p is the proportional coefficient of adaptive PID control, T measured (t) is the actual torque measured at time t, K i is the integral coefficient of adaptive PID control, K d is the differential coefficient of the adaptive PID control, η2 is the first adjustment factor of the automatic tightening control signal adjustment model, and λ4 is the second adjustment factor of the automatic tightening control signal adjustment model.

[0105] All the above adjustment factors are fitted by gradient descent method or ant colony algorithm.

[0106] Example 4

[0107] An embodiment of the present invention also proposes an electronic device, including a processor and a storage medium connected to the processor, wherein the storage medium stores multiple instructions, which can be loaded and executed by the processor to enable the processor to execute the method for automatically tightening rail fastener bolts based on looseness detection.

[0108] Specifically, the electronic device of this embodiment may be a computer terminal, which may include: one or more processors, and a storage medium.

[0109] Among them, the storage medium can be used to store software programs and modules, such as a method for automatically tightening rail fastener bolts based on looseness detection in an embodiment of the present invention, and the corresponding program instructions / modules. The processor executes various functional applications and data processing by running the software programs and modules stored in the storage medium, that is, realizing the above-mentioned method for automatically tightening rail fastener bolts based on looseness detection. The storage medium may include high-speed random access storage media, and may also include non-volatile storage media, such as one or more magnetic storage systems, flash memory, or other non-volatile solid-state storage media. In some instances, the storage medium may further include storage media remotely located relative to the processor, and these remote storage media may be connected to the terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0110] The processor may call the information and application stored in the storage medium through the transmission system to execute the following steps: Step 101: monitor the status of the fastener bolt in real time, obtain information about the fastener bolt, set a fastener bolt looseness detection model, and calculate the looseness of the fastener bolt, wherein the information includes: the speed, acceleration, ambient noise, and ambient temperature of the fastener bolt;

[0111] Specifically, the fastener bolt looseness detection model includes:

[0112]

[0113] Wherein, ΔL(t) is the looseness of the fastener bolt at time t, V(t) is the velocity of the fastener bolt at time t, α1 is the first adjustment factor of the fastener bolt looseness detection model, A(τ) is the acceleration of the fastener bolt at time τ, β1 is the second adjustment factor of the fastener bolt looseness detection model, Noise(t) is the ambient noise at time t, γ1 is the third adjustment factor of the fastener bolt looseness detection model, T env (t) is the ambient temperature at time t, and T0 is the reference temperature.

[0114] Step 102: Setting a required torque estimation model and calculating the torque required to tighten the fastener bolts based on the looseness of the fastener bolts and the standard torque when the fastener bolts are not loose.

[0115] Specifically, the required torque estimation model includes:

[0116]

[0117] Among them, T(t) is the torque required to tighten the fastener bolt at time t, T0 is the standard torque when the fastener bolt is not loose, α2 is the first adjustment factor of the required torque estimation model, β2 is the second adjustment factor of the required torque estimation model, β3 is the third adjustment factor of the required torque estimation model, λ2 is the fourth adjustment factor of the required torque estimation model, η1 is the fifth adjustment factor of the required torque estimation model, γ2 is the sixth adjustment factor of the required torque estimation model, and ω1 is the seventh adjustment factor of the required torque estimation model.

[0118] Step 103: Setting a servo motor rotation angle estimation model and calculating the servo motor rotation angle based on the servo motor's initial angle, the torque required to tighten the fastener bolt in the previous control cycle, the maximum torque that the motor can provide, and the torque required to tighten the fastener bolt;

[0119] Specifically, the servo motor rotation angle estimation model includes:

[0120]

[0121] Where θ(t) is the rotation angle of the servo motor at time t, θ0 is the initial angle of the servo motor, κ1 is the first adjustment factor of the servo motor rotation angle estimation model, ζ1 is the second adjustment factor of the servo motor rotation angle estimation model, T prev is the torque required to tighten the fastener bolts in the previous control cycle, γ3 is the third adjustment factor of the servo motor rotation angle estimation model, κ2 is the fourth adjustment factor of the servo motor rotation angle estimation model, T max is the maximum torque that the motor can provide, λ3 is the fifth adjustment factor of the servo motor rotation angle estimation model, ω2 is the sixth adjustment factor of the servo motor rotation angle estimation model, and β4 is the seventh adjustment factor of the servo motor rotation angle estimation model.

[0122] Step 104, set an automatic tightening control signal adjustment model, calculate the control signal value of the servo motor, and when the control signal value of the servo motor exceeds a preset threshold, send a signal to the servo motor to rotate the fastener bolt according to the rotation angle until the control signal value of the servo motor is less than the preset threshold.

[0123] Specifically, the automatic tightening control signal adjustment model includes:

[0124]

[0125] Where u(t) is the control signal value of the servo motor at time t, K p is the proportional coefficient of adaptive PID control, T measured (t) is the actual torque measured at time t, K iis the integral coefficient of adaptive PID control, K d is the differential coefficient of the adaptive PID control, η2 is the first adjustment factor of the automatic tightening control signal adjustment model, and λ4 is the second adjustment factor of the automatic tightening control signal adjustment model.

[0126] All the above adjustment factors are fitted by gradient descent method or ant colony algorithm.

[0127] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0128] In the above embodiments of the present invention, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0129] In the several embodiments provided by the present invention, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the system embodiments described above are merely illustrative. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, and can be electrical or other forms.

[0130] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0131] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0132] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only storage medium (ROM, Read-Only Memory), random access storage medium (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk, etc. Various media that can store program codes.

[0133] Obviously, the above embodiments are merely examples for clarity of explanation and are not intended to limit the implementation methods. Those skilled in the art will readily appreciate that other variations or modifications based on the above descriptions are possible. It is not necessary and impossible to enumerate all implementation methods here. Obvious variations or modifications arising therefrom remain within the scope of protection of the present invention.

Claims

1. A method for automatically tightening rail fastener bolts based on looseness detection, characterized in that: include: Monitor the status of fastener bolts in real time, obtain information about the fastener bolts, set a fastener bolt looseness detection model, and calculate the looseness of the fastener bolts, wherein the information includes: the speed, acceleration, ambient noise, and ambient temperature of the fastener bolts; A required torque estimation model is set up to calculate the torque required to tighten the fastener bolts based on the looseness of the fastener bolts and the standard torque when the fastener bolts are not loosened; Set up a servo motor rotation angle estimation model and calculate the servo motor rotation angle based on the servo motor's initial angle, the torque required to tighten the fastener bolts in the previous control cycle, the maximum torque that the motor can provide, and the torque required to tighten the fastener bolts; An automatic tightening control signal adjustment model is set to calculate the control signal value of the servo motor. When the control signal value of the servo motor exceeds a preset threshold, a signal is sent to the servo motor to cause the servo motor to rotate the fastener bolt according to the rotation angle until the control signal value of the servo motor is less than the preset threshold.

2. The method for automatically tightening rail fastener bolts based on looseness detection according to claim 1, characterized in that: The fastener bolt looseness detection model includes: Wherein, ΔL(t) is the looseness of the fastener bolt at time t, V(t) is the velocity of the fastener bolt at time t, α1 is the first adjustment factor of the fastener bolt looseness detection model, A(τ) is the acceleration of the fastener bolt at time t, β1 is the second adjustment factor of the fastener bolt looseness detection model, Noise(t) is the ambient noise at time T, γ1 is the third adjustment factor of the fastener bolt looseness detection model, T env (t) is the ambient temperature at time t, and T0 is the reference temperature.

3. The method for automatically tightening rail fastener bolts based on looseness detection according to claim 2, characterized in that: The required torque estimation model includes: Among them, T(t) is the torque required to tighten the fastener bolt at time t, T0 is the standard torque when the fastener bolt is not loose, α2 is the first adjustment factor of the required torque estimation model, β2 is the second adjustment factor of the required torque estimation model, β3 is the third adjustment factor of the required torque estimation model, λ2 is the fourth adjustment factor of the required torque estimation model, η1 is the fifth adjustment factor of the required torque estimation model, γ2 is the sixth adjustment factor of the required torque estimation model, and ω1 is the seventh adjustment factor of the required torque estimation model.

4. The method for automatically tightening rail fastener bolts based on looseness detection according to claim 3, characterized in that: The servo motor rotation angle estimation model includes: Where θ(t) is the rotation angle of the servo motor at time t, θ0 is the initial angle of the servo motor, κ1 is the first adjustment factor of the servo motor rotation angle estimation model, ζ1 is the second adjustment factor of the servo motor rotation angle estimation model, T prev is the torque required to tighten the fastener bolts in the previous control cycle, γ3 is the third adjustment factor of the servo motor rotation angle estimation model, κ2 is the fourth adjustment factor of the servo motor rotation angle estimation model, T max is the maximum torque that the motor can provide, λ3 is the fifth adjustment factor of the servo motor rotation angle estimation model, ω2 is the sixth adjustment factor of the servo motor rotation angle estimation model, and β4 is the seventh adjustment factor of the servo motor rotation angle estimation model.

5. The method for automatically tightening rail fastener bolts based on looseness detection according to claim 4, characterized in that: Automatic tightening control signal adjustment model includes: Where u(t) is the control signal value of the servo motor at time t, K p is the proportional coefficient of adaptive PID control, T measured (t) is the actual torque measured at time t, K i is the integral coefficient of adaptive PID control, K d is the differential coefficient of the adaptive PID control, η2 is the first adjustment factor of the automatic tightening control signal adjustment model, and λ4 is the second adjustment factor of the automatic tightening control signal adjustment model.

6. A rail fastener bolt automatic tightening system based on looseness detection, characterized in that: include: a looseness calculation module for monitoring the status of fastener bolts in real time, obtaining information about the fastener bolts, setting a fastener bolt looseness detection model, and calculating the looseness of the fastener bolts, wherein the information includes: the speed, acceleration, ambient noise, and ambient temperature of the fastener bolts; A torque calculation module is used to set a required torque estimation model and calculate the torque required to tighten the fastener bolts based on the looseness of the fastener bolts and the standard torque when the fastener bolts are not loose; A rotation angle calculation module is used to set a servo motor rotation angle estimation model and calculate the rotation angle of the servo motor based on the initial angle of the servo motor, the torque required to tighten the fastener bolts in the previous control cycle, the maximum torque that the motor can provide, and the torque required to tighten the fastener bolts; The control module is used to set an automatic tightening control signal adjustment model, calculate the control signal value of the servo motor, and when the control signal value of the servo motor exceeds a preset threshold, send a signal to the servo motor to rotate the fastener bolt according to the rotation angle until the control signal value of the servo motor is less than the preset threshold.

7. The rail fastener bolt automatic tightening system based on looseness detection according to claim 6, characterized in that: The fastener bolt looseness detection model includes: Wherein, ΔL(t) is the looseness of the fastener bolt at time t, V(t) is the velocity of the fastener bolt at time t, α1 is the first adjustment factor of the fastener bolt looseness detection model, A(τ) is the acceleration of the fastener bolt at time τ, β1 is the second adjustment factor of the fastener bolt looseness detection model, Noise(t) is the ambient noise at time t, γ1 is the third adjustment factor of the fastener bolt looseness detection model, T env (t) is the ambient temperature at time t, and T0 is the reference temperature.

8. The rail fastener bolt automatic tightening system based on looseness detection according to claim 7, characterized in that: The required torque estimation model includes: Among them, T(t) is the torque required to tighten the fastener bolt at time t, T0 is the standard torque when the fastener bolt is not loose, α2 is the first adjustment factor of the required torque estimation model, β2 is the second adjustment factor of the required torque estimation model, β3 is the third adjustment factor of the required torque estimation model, λ2 is the fourth adjustment factor of the required torque estimation model, η1 is the fifth adjustment factor of the required torque estimation model, γ2 is the sixth adjustment factor of the required torque estimation model, and ω1 is the seventh adjustment factor of the required torque estimation model.

9. The rail fastener bolt automatic tightening system based on looseness detection according to claim 8, characterized in that: The servo motor rotation angle estimation model includes: Where θ(t) is the rotation angle of the servo motor at time t, θ0 is the initial angle of the servo motor, κ1 is the first adjustment factor of the servo motor rotation angle estimation model, ζ1 is the second adjustment factor of the servo motor rotation angle estimation model, T prev is the torque required to tighten the fastener bolts in the previous control cycle, γ3 is the third adjustment factor of the servo motor rotation angle estimation model, κ2 is the fourth adjustment factor of the servo motor rotation angle estimation model, T max is the maximum torque that the motor can provide, λ3 is the fifth adjustment factor of the servo motor rotation angle estimation model, ω2 is the sixth adjustment factor of the servo motor rotation angle estimation model, and β4 is the seventh adjustment factor of the servo motor rotation angle estimation model.

10. The rail fastener bolt automatic tightening system based on looseness detection according to claim 9, characterized in that: Automatic tightening control signal adjustment model includes: Where u(t) is the control signal value of the servo motor at time t, K p is the proportional coefficient of adaptive PID control, T measured (t) is the actual torque measured at time t, K i is the integral coefficient of adaptive PID control, K d is the differential coefficient of the adaptive PID control, η2 is the first adjustment factor of the automatic tightening control signal adjustment model, and λ4 is the second adjustment factor of the automatic tightening control signal adjustment model.

Images