Motor overload heating detection method, system, equipment and medium

Abstract

The invention provides a motor overload heating detection method, system and device and a medium, and the method comprises the steps: obtaining a specific heat capacity parameter, a density parameter and a volume parameter of a target node thermal element in a to-be-detected motor, and a real-time operation parameter of the to-be-detected motor; according to the specific heat capacity parameter, the density parameter and the volume parameter of the target node thermal element, a thermal network model is constructed based on a lumped parameter method, an initial motor lumped parameter thermal network model is obtained, model simplification is performed through a zero-pole cancellation method, and a target thermal network model is obtained; determining thermal parameters of the to-be-detected motor based on the real-time operation parameters and a target thermal network model, so as to determine an overload state of the to-be-detected motor according to the thermal parameters of the to-be-detected motor; according to the method, the heat distribution condition is more accurately simulated through the key node thermal elements in the motor, the model is simplified, the calculation efficiency and practicability are improved, the problem that a traditional motor protector is not sensitive enough when detecting slight overload and frequent overload is solved, and the motor is better protected against damage.

Description

Technical Field

[0001] The present application relates to the field of safety control, and in particular to a method, system, device and medium for detecting overload and heating of a motor. Background Art

[0002] In the motor operation system, the low-voltage motor protector is a device that plays a key protective role. The low-voltage motor protector can not only provide protection for the motor against common faults such as overload, short circuit and phase loss, but also monitor the operating parameters of the motor, and perform motion control and data communication. It integrates multiple functions, such as current and voltage detection, signal amplification, delay processing, parameter adjustment, etc., and cuts off the power supply by executing relays to ensure the safe operation of the motor. It can replace traditional thermal relays, ammeters, voltmeters, transmitters and other equipment, simplifying the complexity and maintenance costs of the system.

[0003] However, although most of the existing motor protectors use digital thermal elements to protect the motor from overload and have inverse time characteristics, that is, the more severe the overload, the faster the protection action, there are still some shortcomings in some cases, especially for those motors that are often in a state of slight overload or frequently encounter overload conditions. Since traditional protection principles make it difficult to accurately simulate the actual thermal state changes of the motor, existing protectors may not be able to provide sufficient protection effects, resulting in unsatisfactory protection effects. Summary of the invention

[0004] The purpose of the embodiments of the present invention is to provide a motor overload heating detection method, system, device and medium to solve the above technical problems.

[0005] The present invention provides a motor overload heating detection method, which comprises: obtaining specific heat capacity parameters, density parameters and volume parameters of a target node thermal element in a motor to be detected, as well as real-time operating parameters of the motor to be detected; constructing a thermal network model based on a lumped parameter method according to the specific heat capacity parameters, density parameters and volume parameters of the target node thermal element, to obtain an initial motor lumped parameter thermal network model; simplifying the initial motor lumped parameter thermal network model by a zero-pole cancellation method, to obtain a target thermal network model; determining the thermal parameters of the motor to be detected based on the real-time operating parameters and the target thermal network model, so as to determine the overload state of the motor to be detected according to the thermal parameters of the motor to be detected.

[0006] In one embodiment of the present invention, the target node thermal element is a heat source element of the motor to be tested, including a stator core and a housing, a stator slot winding, a stator winding end, a rotor bar and a rotor core.

[0007] In one embodiment of the present invention, the construction process of constructing a thermal network model based on the lumped parameter method according to the specific heat capacity parameter, density parameter and volume parameter of the target node thermal element includes: constructing a heat transfer equation of the motor to be detected, the formula is as follows:

[0008]

[0009] Wherein, C is the heat capacity matrix of the target node thermal element, A is the thermal conductivity matrix between the target node thermal elements, Q is the motor power, θ is the motor temperature rise, and t is the time; the heat transfer equation of the motor to be detected is simplified to obtain the motor state equation of the motor to be detected, and the formula is as follows:

[0010]

[0011] Wherein, B is the state output matrix, y is the output variable; taking the temperature rise of the rotor bars as the output variable y, the state output matrix B = [0 0 0 1 0], when the initial time t = 0, the initial state is θ (0), the solution of the motor state equation of the motor to be tested is:

[0012]

[0013]

[0014] The heat capacity matrix C of the target node thermal element is a symmetric positive definite matrix, and the heat capacity matrix C of the target node thermal element is characterized as:

[0015]

[0016] Wherein, ci, ρi, and vi are the specific heat capacity, density, and volume of the target node thermal element i (1, 2, 3, 4, and 5), respectively; the thermal conductivity matrix A between the target node thermal elements is a symmetric positive definite matrix, and the thermal conductivity matrix A between the target node thermal elements is characterized as follows:

[0017]

[0018] The thermal conductivity formula between the motor stator slot winding and the rotor core is expressed as:

[0019]

[0020] Among them, S1 is the contact area between the motor stator slot winding and the rotor core, δ i is the equivalent thickness of various insulating materials, λ i is the average thermal conductivity of various insulating materials; the thermal conductivity formula between the motor housing and the surrounding air is characterized by:

[0021]

[0022] Among them, a is the heat dissipation coefficient of the motor housing surface, a = 9.73 + 14v 0.62 , v is the wind speed on the surface of the casing, S2 is the heat dissipation surface area of ​​the motor casing; the thermal conductivity calculation between the stator and the rotor is to convert the convection heat transfer into the conduction heat transfer, which can be expressed as:

[0023]

[0024] Where D2 is the outer diameter of the rotor, D1 is the inner diameter of the stator core, and g is the air gap thickness. Based on the physical thermal conductivity between the rotor core and the rotor bars, we define

[0025] In one embodiment of the present invention, the zero-pole cancellation method includes simplification of model functions based on Pull transformation, and the model simplification of the initial motor lumped parameter thermal network model by the zero-pole cancellation method includes: solving the initial motor lumped parameter thermal network model to obtain the motor temperature rise analytical expression, which is characterized as:

[0026]

[0027] Based on the motor temperature rise analytical expression after the pull-type transformation, the transfer function of the motor state equation of the motor to be detected is obtained, which is characterized as:

[0028]

[0029] The transfer function of the motor state equation of the motor to be detected is reduced and simplified to obtain a target second-order simplified function, which is characterized as:

[0030]

[0031] Based on the above target second-order simplified function, a second-order thermal network model is obtained through Laplace inverse transformation, and the target thermal network model is determined according to the second-order thermal network model, which is characterized as follows:

[0032]

[0033] In one embodiment of the present invention, determining the target thermal network model according to the second-order thermal network model includes: discretizing the second-order thermal network model to obtain a target thermal network model, which is characterized as:

[0034]

[0035] Among them, k is the current sampling point.

[0036] In one embodiment of the present invention, determining the thermal parameters of the motor to be detected based on the real-time operating parameters and the target thermal network model includes: writing the target thermal network model into a target protector, the target protector being used to provide protection against motor overload faults; inputting the real-time operating parameters into the target protector, and solving them by the target protector to obtain the thermal parameters of the motor to be detected.

[0037] In one embodiment of the present invention, determining the overload state of the motor to be detected based on the thermal parameters of the motor to be detected includes: if the thermal parameters of the motor to be detected are greater than or equal to a preset detection threshold, controlling the motor to be detected to perform a power-off operation; if the thermal parameters of the motor to be detected are less than the preset detection threshold, keeping the motor to be detected running.

[0038] An embodiment of the present invention also provides a motor overload and heating detection system, which includes: a detection parameter acquisition module, which is used to obtain the specific heat capacity parameters, density parameters and volume parameters of the target node thermal element in the motor to be detected, as well as the real-time operating parameters of the motor to be detected; a detection model construction module, which is used to construct a thermal network model based on the lumped parameter method according to the specific heat capacity parameters, density parameters and volume parameters of the target node thermal element, so as to obtain an initial motor lumped parameter thermal network model; the initial motor lumped parameter thermal network model is simplified by the zero-pole cancellation method to obtain a target thermal network model; a motor overload detection module, which is used to determine the thermal parameters of the motor to be detected based on the real-time operating parameters and the target thermal network model, so as to determine the overload state of the motor to be detected according to the thermal parameters of the motor to be detected.

[0039] An embodiment of the present invention also provides an electronic device, comprising: one or more processors; a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the electronic device implements a motor overload heating detection method as described in any one of the above embodiments.

[0040] An embodiment of the present invention further provides a computer-readable storage medium having computer-readable instructions stored thereon. When the computer-readable instructions are executed by a processor of a computer, the computer is enabled to execute the motor overload heating detection method as described in any one of the above embodiments.

[0041] The present invention provides a motor overload heating detection method, system, device and medium. The method obtains the specific heat capacity parameters, density parameters and volume parameters of the target node thermal element in the motor to be detected, as well as the real-time operating parameters of the motor to be detected. A thermal network model is constructed based on the lumped parameter method according to the specific heat capacity parameters, density parameters and volume parameters of the target node thermal element, an initial motor lumped parameter thermal network model is obtained, and the model is simplified by the zero-pole cancellation method to obtain a target thermal network model. The thermal parameters of the motor to be detected are determined based on the real-time operating parameters and the target thermal network model, so as to determine the overload state of the motor to be detected according to the thermal parameters of the motor to be detected. The method obtains the specific physical parameters of the key node thermal element in the motor and the real-time operating data of the motor, so as to more accurately simulate the heat distribution inside the motor, better reflect the heat conduction condition inside the motor, and further simplify the initial model by using the zero-pole cancellation method to improve the calculation efficiency and the practicality of the model. The above process can solve the problem that the traditional motor protector is not sensitive enough when detecting slight overload and frequent overload, so that the protector can respond in time when the motor is slightly overloaded or frequently overloaded, thereby better protecting the motor from damage.

[0042] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The drawings herein are incorporated into the specification and constitute a part of the specification, showing embodiments consistent with the present application, and together with the specification, are used to explain the principles of the present application. Obviously, the drawings described below are only some embodiments of the present application, and for those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0044] Figure 1 is a schematic diagram of an exemplary system architecture shown in an exemplary embodiment of the present application;

[0045] Figure 2 is a flow chart of a motor overload heating detection method shown in an exemplary embodiment of the present application;

[0046] Figure 3 is a schematic diagram of a motor overload heating detection system shown in an exemplary embodiment of the present application;

[0047] Figure 4 It is a structural diagram of a computer system of an electronic device shown in an exemplary embodiment of the present application. DETAILED DESCRIPTION

[0048] The following will describe the implementation of the present invention with reference to the accompanying drawings and specific embodiments. Those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific implementations, and the details in this specification can also be based on Different viewpoints and Various modifications or changes may be made without departing from the spirit of the present invention. It should be understood that the preferred embodiments are only for illustrating the present invention rather than for limiting the protection scope of the present invention.

[0049] It should be noted that the illustrations provided in the following embodiments are only used to illustrate the basic concept of the present invention in a schematic manner, and thus the illustrations only show components related to the present invention rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

[0050] In the following description, numerous details are discussed to provide a more thorough explanation of the embodiments of the present invention. However, it is obvious to those skilled in the art that the embodiments of the present invention can be implemented without these specific details. In other embodiments, well-known structures and devices are shown in the form of block diagrams rather than in detail to avoid making the embodiments of the present invention difficult to understand.

[0051] The "and / or" mentioned in this application describes the association relationship of the associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the associated objects before and after are in an "or" relationship.

[0052] First of all, it should be noted that most motor protector products currently use digital thermal elements to replace conventional thermal elements to protect motors from overload and heating, which have inverse time characteristics. The thermal element model is: t = [K / (Ir / Ie)2-1], where t represents the protection action time, K represents the time factor (heating time constant), Ir represents the motor equivalent current, and Ie represents the motor rated current. However, the model established for the motor thermal field cannot be well consistent with the actual situation. Although conventional inverse time overcurrent relays can realize the overload protection function, due to the defects of the protection principle, they cannot realize the protection of the motor during slight overload detection and frequent overload operation.

[0053] Since the motor overload protection model based on heat accumulation treats the motor as an isothermal body, that is, it is considered that the temperature inside the motor is uniformly distributed, a mathematical thermal model of the motor is established in the present application according to the law of conservation of thermal energy. This thermal model takes into account the heat accumulation effect of the motor, so it can well estimate the average temperature rise of the motor. On the basis of the motor overload protection model based on heat accumulation, the lumped parameter method is applied according to the different heat sources inside the motor to establish a lumped parameter thermal network model, and then the thermal network model is reduced and simplified by using the zero-pole cancellation method, thereby obtaining a low-order thermal model with high accuracy and easy calculation. Finally, a method for discretizing the continuous thermal model is used to enable the thermal network model to be applied to the motor protector, thereby solving the technical defects of the prior art.

[0054] Figure 1 It is a schematic diagram of an exemplary system architecture shown in an exemplary embodiment of the present application.

[0055] Reference Figure 1 As shown, the system architecture may include a motor to be detected 110 and a computer device 120. The computer device 120 obtains the specific heat capacity parameters, density parameters and volume parameters of the target node thermal element in the motor to be detected 110, as well as the real-time operating parameters of the motor to be detected, and constructs a thermal network model based on the lumped parameter method according to the specific heat capacity parameters, density parameters and volume parameters of the target node thermal element, to obtain an initial motor lumped parameter thermal network model, and simplifies the initial motor lumped parameter thermal network model by the zero-pole cancellation method to obtain a target thermal network model, and determines the thermal parameters of the motor to be detected based on the real-time operating parameters and the target thermal network model, so as to determine the overload state of the motor to be detected according to the thermal parameters of the motor to be detected. The computer device 120 may be at least one of a microcomputer, an embedded computer, a network computer, a single-chip microcomputer, etc.; the motor to be detected 110 includes a three-phase motor with an AC voltage of 380V, a frequency of 50Hz, and a current of less than 800A.

[0056] Schematically, the computer device 120 obtains the specific heat capacity parameters, density parameters and volume parameters of the target node thermal element in the motor to be detected 110, as well as the real-time operating parameters of the motor to be detected, and constructs a thermal network model based on the lumped parameter method according to the specific heat capacity parameters, density parameters and volume parameters of the target node thermal element, obtains an initial motor lumped parameter thermal network model, and simplifies the model through the zero-pole cancellation method to obtain a target thermal network model, determines the thermal parameters of the motor to be detected based on the real-time operating parameters and the target thermal network model, and determines the overload state of the motor to be detected according to the thermal parameters of the motor to be detected; this method aims to more accurately simulate the heat distribution inside the motor and better reflect the heat conduction condition inside the motor by obtaining the specific physical parameters of the thermal elements at key nodes in the motor and the real-time operating data of the motor, and further simplifies the initial model by using the zero-pole cancellation method to improve the calculation efficiency and the practicality of the model. The above process can solve the problem that the traditional motor protector is not sensitive enough when detecting slight overload and frequent overload, so that the protector can respond in time when the motor is slightly overloaded or frequently overloaded, thereby better protecting the motor from damage.

[0057] Figure 2 is a flow chart of a motor overload heating detection method shown in an exemplary embodiment of the present application. The motor overload heating detection method can be Figure 1 The implementation environment may be implemented in other implementation environments, and the above implementation environments are not specifically limited here. Figure 2 As shown, the flowchart of the motor overload heating detection method includes at least steps S210 to S240, which are described in detail as follows:

[0058] In step S210, the specific heat capacity parameter, density parameter and volume parameter of the thermal element of the target node in the motor to be detected, as well as the real-time operating parameters of the motor to be detected are obtained.

[0059] In one embodiment of the present application, the target node thermal element is a heat source element of the motor to be tested, including a stator core and housing, a stator slot winding, a stator winding end, a rotor bar and a rotor core.

[0060] In one embodiment of the present application, the real-time operating parameters of the motor to be detected are collected by a sensor in real time by collecting at least one parameter of current, voltage, power, temperature, speed and vibration.

[0061] In step S220, a thermal network model is constructed based on a lumped parameter method according to specific heat capacity parameters, density parameters and volume parameters of the thermal element of the target node, and an initial motor lumped parameter thermal network model is obtained.

[0062] In one embodiment of the present application, the process of constructing a thermal network model includes:

[0063] Construct a heat transfer equation for the motor to be tested. Specifically, according to the law of conservation of thermal energy, construct a heat transfer equation for the motor to be tested that satisfies the heat transfer of the three-phase asynchronous motor. The formula is as follows:

[0064]

[0065] Among them, C is the heat capacity matrix of the target node thermal element, A is the thermal conductivity matrix between the target node thermal elements, Q is the motor power, θ is the motor temperature rise, and t is the time;

[0066] The heat transfer equation of the motor to be detected is simplified to obtain the motor state equation of the motor to be detected, which is as follows:

[0067]

[0068] Among them, B is the state output matrix, y is the output variable;

[0069] Taking the temperature rise of the rotor bars as the output variable y, the state output matrix B = [0 0 0 1 0]. When the initial time t = 0 and the initial state is θ(0), the solution of the motor state equation of the motor to be tested is:

[0070]

[0071] in,

[0072] According to the lumped parameter thermal network model, all heat capacities are greater than zero, and the heat capacity matrix C of the target node thermal element is a symmetric positive definite matrix. The heat capacity matrix C of the target node thermal element is characterized as:

[0073]

[0074] Wherein, ci, ρi, vi are the specific heat capacity, density, and volume of the target node thermal element i (1, 2, 3, 4, 5), respectively;

[0075] The thermal conductivity matrix A between the thermal elements of the target node is a symmetric positive definite matrix. Since the thermal network is a passive network and has reciprocity, the thermal conductivity matrix A between the thermal elements of the target node is characterized as:

[0076]

[0077] The thermal conductivity formula between the motor stator slot winding and the rotor core is expressed as:

[0078]

[0079] Among them, S1 is the contact area between the motor stator slot winding and the rotor core, δi is the equivalent thickness of various insulating materials, λ i is the average thermal conductivity of various insulating materials;

[0080] The thermal conductivity formula between the motor housing and the surrounding air is characterized by:

[0081]

[0082] Among them, a is the heat dissipation coefficient of the motor housing surface, a = 9.73 + 14v 0.62 ,v is the wind speed on the casing surface, S2 is the heat dissipation surface area of ​​the motor casing;

[0083] The calculation of thermal conductivity between the stator and rotor is to convert the convection heat transfer into conduction heat transfer, which can be characterized as:

[0084]

[0085] Where D2 is the outer diameter of the rotor, D1 is the inner diameter of the stator core, and g is the air gap thickness;

[0086] In one embodiment of the present application, based on the physical thermal conductivity between the rotor core and the rotor bars, specifically, the temperature rise difference inside the motor under actual working conditions is very large, especially the temperature rise between the rotor and the stator, while the temperature difference between the rotor core and the rotor bars is very small. This is because the loss of the rotor bars and the rotor core is very large, but the thermal conductivity of the air gap between the stator and the rotor is very small, which makes the heat dissipation condition very poor, resulting in a large temperature difference in the air gap. The thermal conductivity between the rotor bars and the rotor core is very large, and the thermal conductivity is very good, so the temperature difference between the rotor core and the rotor bars is very small. In order to simplify the model, define

[0087] In step S230, the initial motor lumped parameter thermal network model is simplified by zero-pole cancellation to obtain a target thermal network model. Zero-pole cancellation is a technique used in control system design to simplify the system model by eliminating the same zeros and poles in the transfer function. It involves analyzing the zeros and poles of the system transfer function. When there are matching zeros and poles, they can be removed by mathematical simplification to simplify the dynamic characteristics of the system. Zero-pole cancellation can be used to reduce the complexity of the system and improve the performance of the system, such as improving stability or adjusting frequency response.

[0088] In one embodiment of the present application, various physical parameters are brought into the thermal network model to solve the initial motor lumped parameter thermal network model, and an analytical formula for the motor temperature rise is obtained, which is characterized as:

[0089]

[0090] Based on the Laplace transform of the motor temperature rise analytical expression, the transfer function of the motor state equation of the motor to be detected is obtained, wherein the Laplace transform, also known as the Laplace transform, is a mathematical tool for converting a function defined on a non-negative real axis into a function of a complex variable s, which is defined by an integral operation. The Laplace transform can simplify the solution process of the differential equation, and is characterized as follows after the transformation:

[0091]

[0092] When the motor load does not change frequently, it is accurate to use the second-order thermal model to calculate the motor rotor temperature rise equivalently, because the second-order thermal model has the same frequency domain response as the high-order thermal model only in the low-frequency band. The transfer function of the motor state equation of the motor to be tested is reduced and simplified to obtain the target second-order simplified function, which is characterized as:

[0093]

[0094] Based on the above target second-order simplified function, a second-order thermal network model is obtained through Laplace inverse transformation, and the target thermal network model is determined according to the second-order thermal network model, which is characterized as follows:

[0095]

[0096] In one embodiment of the present application, determining the target thermal network model according to the second-order thermal network model further includes:

[0097] The second-order thermal network model is discretized to obtain the target thermal network model, which is characterized as follows:

[0098]

[0099] Among them, k is the current sampling point.

[0100] In step S240 , thermal parameters of the motor to be detected are determined based on the real-time operating parameters and the target thermal network model, so as to determine the overload state of the motor to be detected according to the thermal parameters of the motor to be detected.

[0101] In one embodiment of the present application, the target thermal network model is written into a target protector, which is used to provide protection against motor overload faults. The real-time operating parameters are input into the target protector and solved by the target protector to obtain the thermal parameters of the motor to be detected.

[0102] In one embodiment of the present application, if the thermal parameter of the motor to be detected is greater than or equal to a preset detection threshold, the motor to be detected is controlled to perform a power-off operation; if the thermal parameter of the motor to be detected is less than the preset detection threshold, the motor to be detected is kept running.

[0103] The present invention provides a motor overload heating detection method, system, device and medium. The method obtains the specific heat capacity parameters, density parameters and volume parameters of the target node thermal element in the motor to be detected, as well as the real-time operating parameters of the motor to be detected. A thermal network model is constructed based on the lumped parameter method according to the specific heat capacity parameters, density parameters and volume parameters of the target node thermal element, an initial motor lumped parameter thermal network model is obtained, and the model is simplified by the zero-pole cancellation method to obtain a target thermal network model. The thermal parameters of the motor to be detected are determined based on the real-time operating parameters and the target thermal network model, so as to determine the overload state of the motor to be detected according to the thermal parameters of the motor to be detected. The method is The specific physical parameters of the thermal components at key nodes in the motor and the real-time operating data of the motor are obtained in order to more accurately simulate the heat distribution inside the motor and better reflect the heat conduction conditions inside the motor. The initial model is further simplified by using the zero-pole cancellation method to improve the calculation efficiency and practicality of the model. The above process can solve the problem that traditional motor protectors are not sensitive enough when detecting slight overloads and frequent overloads, so that the protector can respond in time when the motor is slightly overloaded or frequently overloaded, thereby better protecting the motor from damage. Finally, the method of discretizing the continuous thermal model is proposed for application in the motor protector.

[0104] The following introduces the system embodiment of the present application, which can be used to execute the motor overload heating detection method in the above embodiment of the present application. For details not disclosed in the system embodiment of the present application, please refer to the above embodiment of the motor overload heating detection method of the present application.

[0105] Figure 3 FIG. 1 is a schematic diagram of a motor overload heating detection system shown in an exemplary embodiment of the present application. The system can be applied to Figure 2 The method implementation process shown in the figure can be based on Figure 1 The system is executed in the implementation environment shown in the figure, and may also be applicable to other exemplary implementation environments and specifically configured in other devices. This embodiment does not limit the implementation environment to which the system is applicable.

[0106] like Figure 3 As shown, the exemplary motor overload heating detection system includes: a detection parameter acquisition module 301 , a detection model construction module 302 and a motor overload detection module 303 .

[0107] Among them, the detection parameter acquisition module 301 is used to obtain the specific heat capacity parameters, density parameters and volume parameters of the target node thermal element in the motor to be detected, as well as the real-time operating parameters of the motor to be detected; the detection model construction module 302 is used to construct a thermal network model based on the lumped parameter method according to the specific heat capacity parameters, density parameters and volume parameters of the target node thermal element, and obtain an initial motor lumped parameter thermal network model; the initial motor lumped parameter thermal network model is simplified by the zero-pole cancellation method to obtain a target thermal network model; the motor overload detection module 303 is used to determine the thermal parameters of the motor to be detected based on the real-time operating parameters and the target thermal network model, so as to determine the overload state of the motor to be detected according to the thermal parameters of the motor to be detected.

[0108] An embodiment of the present application also provides an electronic device, comprising: one or more processors; a storage device for storing one or more programs, when the one or more programs are executed by one or more processors, the electronic device implements the motor overload heating detection method provided in the above-mentioned embodiments.

[0109] Figure 4 is a schematic diagram of the structure of a computer system of an electronic device according to an exemplary embodiment of the present application. It should be noted that: Figure 4 The computer system 400 of the electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0110] like Figure 4 As shown, computer system 400 includes a central processing unit (CPU) 401, which can perform various appropriate actions and processes according to the program stored in read-only memory (ROM) 402 or the program loaded from the storage part to random access memory (RAM) 403, such as executing the method in the above embodiment. In RAM 403, various programs and data required for system operation are also stored. CPU 401, ROM 402 and RAM 403 are connected to each other through a bus. Input / output (I / O) interface 405 is also connected to bus 404.

[0111] The following components are connected to the I / O interface 405: an input section 406 including a keyboard, a mouse, etc.; an output section 407 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker; a storage section 408 including a hard disk, etc.; and a communication section 409 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section performs communication processing via a network such as the Internet. A drive is also connected to the I / O interface 405 as needed. A removable medium 411, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 410 as needed so that a computer program read therefrom is installed into the storage section 408 as needed.

[0112] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication section 409, and / or installed from a removable medium 411. When the computer program is executed by a central processing unit (CPU) 401, various functions defined in the system of the present application are executed.

[0113] It should be noted that the computer-readable medium shown in the embodiment of the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, wherein a computer-readable computer program is carried. This propagated data signal may take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. A computer program contained on a computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0114] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. Among them, each box in the flowchart or block diagram can represent a module, a program segment, or a part of the code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0115] In the corresponding drawings of the above embodiments, connecting lines may indicate the connection relationship between the various components to indicate more constituent signal paths (constituent_signalpath) and / or one or more ends of some lines may have arrows to indicate the main information flow direction. Connecting lines, as a mark, are not a limitation to the scheme itself, but the use of these lines in combination with one or more exemplary embodiments helps to connect circuits or logic units more easily. Any represented signal (determined by design requirements or preferences) may actually include one or more signals that can be transmitted in either direction and implemented with any appropriate type of signal scheme.

[0116] The units involved in the embodiments described in this application may be implemented by software or hardware, and the units described may also be set in a processor. The names of these units do not, in some cases, constitute limitations on the units themselves.

[0117] Another aspect of the present application further provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the above method is implemented. The computer-readable storage medium may be included in the electronic device described in the above embodiment, or may exist independently without being assembled into the electronic device.

[0118] It should be noted that, although several modules or units of the equipment for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present application, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into being embodied by multiple modules or units.

[0119] Through the description of the above implementation methods, it is easy for those skilled in the art to understand that the example implementation methods described here can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution according to the implementation methods of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the implementation methods of the present application.

[0120] It should be noted that the present application can be used in many general or special computing system environments or configurations, such as personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronic devices, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc.

[0121] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the embodiments disclosed herein. The present application is intended to cover any variations, uses or adaptations of the present application, which follow the general principles of the present application and include common knowledge or customary technical means in the art that are not disclosed in the present application.

[0122] It should be understood that the above content of the present application is only a preferred exemplary embodiment of the present application and is not intended to limit the implementation scheme of the present application. Ordinary technicians in this field can easily make corresponding changes or modifications based on the main concept and spirit of the present application. Therefore, the scope of protection of the present application should be the scope of protection required by the claims.

Claims

1. A method for detecting motor overload heating, characterized in that: The motor overload heating detection method comprises: Obtaining specific heat capacity parameters, density parameters and volume parameters of the thermal element of the target node in the motor to be detected, as well as the real-time operating parameters of the motor to be detected; According to the specific heat capacity parameters, density parameters and volume parameters of the target node thermal element, a thermal network model is constructed based on the lumped parameter method to obtain an initial motor lumped parameter thermal network model; Simplifying the initial motor lumped parameter thermal network model by using the zero-pole cancellation method to obtain a target thermal network model; The thermal parameters of the motor to be detected are determined based on the real-time operating parameters and the target thermal network model, so as to determine the overload state of the motor to be detected according to the thermal parameters of the motor to be detected.

2. The motor overload heating detection method according to claim 1, characterized in that: The target node thermal element is a heat source element of the motor to be detected, including a stator core and a housing, a stator slot winding, a stator winding end, a rotor bar and a rotor core.

3. The motor overload heating detection method according to claim 2, characterized in that: The construction process of constructing a thermal network model based on the lumped parameter method according to the specific heat capacity parameter, density parameter and volume parameter of the thermal element of the target node includes: Construct the heat transfer equation of the motor to be tested. The formula is as follows: Among them, C is the heat capacity matrix of the target node thermal element, A is the thermal conductivity matrix between the target node thermal elements, Q is the motor power, θ is the motor temperature rise, and t is the time; The heat transfer equation of the motor to be detected is simplified to obtain the motor state equation of the motor to be detected, which is as follows: Among them, B is the state output matrix, y is the output variable; Taking the temperature rise of the rotor bars as the output variable y, the state output matrix B = [0 0 0 1 0]. When the initial time t = 0 and the initial state is θ(0), the solution of the motor state equation of the motor to be tested is: in, The heat capacity matrix C of the target node thermal element is a symmetric positive definite matrix, and the heat capacity matrix C of the target node thermal element is characterized as: Wherein, ci, ρi, vi are the specific heat capacity, density, and volume of the target node thermal element i (1, 2, 3, 4, 5), respectively; The thermal conductivity matrix A between the thermal elements of the target node is a symmetric positive definite matrix, and the thermal conductivity matrix A between the thermal elements of the target node is characterized as: The thermal conductivity formula between the motor stator slot winding and the rotor core is expressed as: Among them, S1 is the contact area between the motor stator slot winding and the rotor core, δ i is the equivalent thickness of various insulating materials, λ i is the average thermal conductivity of various insulating materials; The thermal conductivity formula between the motor housing and the surrounding air is expressed as: Among them, a is the heat dissipation coefficient of the motor housing surface, a = 9.73 + 14v 0.62 , v is the wind speed on the surface of the casing, S2 is the heat dissipation surface area of ​​the motor casing; The calculation of thermal conductivity between the stator and rotor is to convert the convection heat transfer into conduction heat transfer, which can be expressed as: Where D2 is the outer diameter of the rotor, D1 is the inner diameter of the stator core, and g is the air gap thickness. Based on the physical thermal conductivity between the rotor core and the rotor bars, the definition is 4. The motor overload heating detection method according to claim 3 is characterized in that: The zero-pole cancellation method includes simplifying the model function based on the pull-type transformation, and the model simplification of the initial motor lumped parameter thermal network model by the zero-pole cancellation method includes: Solving the initial motor lumped parameter thermal network model, we get the motor temperature rise analytical formula, which is represented as: Based on the motor temperature rise analytical expression after the pull-type transformation, the transfer function of the motor state equation of the motor to be detected is obtained, which is characterized as: The transfer function of the motor state equation of the motor to be detected is simplified by reducing the order to obtain the target second-order simplified function, which is characterized as: Based on the above target second-order simplified function, a second-order thermal network model is obtained through Laplace inverse transformation, and the target thermal network model is determined according to the second-order thermal network model, which is characterized as: Among them, t is the time.

5. The motor overload heating detection method according to claim 4, characterized in that: Determining the target thermal network model according to the second-order thermal network model further includes: The second-order thermal network model is discretized to obtain the target thermal network model, which is characterized as: Among them, k is the current sampling point.

6. The motor overload heating detection method according to claim 1, characterized in that: Determining the thermal parameters of the motor to be detected based on the real-time operating parameters and the target thermal network model includes: Writing the target thermal network model into a target protector, wherein the target protector is used to provide protection against motor overload fault; The real-time operating parameters are input into the target protector, and the target protector solves the parameters to obtain the thermal parameters of the motor to be detected.

7. The motor overload heating detection method according to any one of claims 1 to 6, characterized in that: Determining the overload state of the motor to be detected according to the thermal parameters of the motor to be detected includes: If the thermal parameter of the motor to be detected is greater than or equal to a preset detection threshold, controlling the motor to be detected to perform a power-off operation; If the thermal parameter of the motor to be detected is less than a preset detection threshold, the motor to be detected is kept running.

8. A motor overload heating detection system, characterized in that: The motor overload heating detection system comprises: A detection parameter acquisition module is used to obtain specific heat capacity parameters, density parameters and volume parameters of the target node thermal element in the motor to be detected, as well as real-time operating parameters of the motor to be detected; A detection model building module is used to build a thermal network model based on the lumped parameter method according to the specific heat capacity parameter, density parameter and volume parameter of the target node thermal element to obtain an initial motor lumped parameter thermal network model; the initial motor lumped parameter thermal network model is simplified by the zero-pole cancellation method to obtain a target thermal network model; The motor overload detection module is used to determine the thermal parameters of the motor to be detected based on the real-time operating parameters and the target thermal network model, so as to determine the overload state of the motor to be detected according to the thermal parameters of the motor to be detected.

9. An electronic device, characterized in that: include: one or more processors; A storage device for storing one or more programs, when the one or more programs are executed by the one or more processors, enables the electronic device to implement the motor overload heating detection method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: Computer-readable instructions are stored thereon, and when the computer-readable instructions are executed by a processor of a computer, the computer is caused to execute the motor overload heating detection method as claimed in any one of claims 1 to 7.

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