A locomotive traction motor shaft temperature control method, medium and device

Abstract

The present application relates to traction motor shaft temperature control technical field, disclose a kind of locomotive traction motor shaft temperature control method, medium and equipment, method includes: obtaining bearing parameter judges whether bearing is abnormal, if abnormal then send warning prompt, if normal then enter next step;Through shaft temperature prediction method calculates whether it will occur shaft temperature alarm in the nearest climbing process at current operating state, if it will not occur alarm, then continue to run according to current state, if it will occur alarm then enter next step;Calculate the variable condition that does not occur shaft temperature alarm, adjust fan operation strategy so that subsequent traction motor does not occur shaft temperature alarm.The present application method can optimize fan operation strategy according to environment and line parameters, reduce bearing and motor temperature under various severe conditions, simultaneously intelligently judge whether louver screen is blocked and bearing is faulted, through various means and ways, early warning and solve the shaft temperature alarm problem caused by various reasons, reduce locomotive running traction motor temperature, prolong motor life.

Description

Technical Field

[0001] This invention relates to the field of traction motor shaft temperature control technology, and in particular to a method, medium, and equipment for controlling the shaft temperature of a locomotive traction motor. Background Technology

[0002] Freight locomotives such as HXD1 and HXD2 often experience traction motor bearing over-temperature alarms under the combined effects of heavy loads, long gradients, multiple tunnels, high-temperature environments, and bearing wear, seriously affecting the safe and stable operation of railway locomotives. Furthermore, bearing over-temperature alarms also indicate high temperatures in the traction motor core. Prolonged operation at high temperatures can easily cause degradation of the traction motor's insulation materials, leading to motor burnout and ultimately, locomotive failure, severely impacting the motor's lifespan and the safe operation of the locomotive.

[0003] The main methods currently used to solve the above problems are as follows:

[0004] 1) Increasing the alarm temperature limit, such as adjusting the maximum temperature threshold of the non-drive end bearing of the traction motor from 90°C to 100°C while keeping the temperature rise of 55K unchanged. This method only superficially eliminates the alarm problem and does not improve the actual bearing temperature and motor core temperature, thus not fundamentally solving the problem.

[0005] 2) Adjust the ambient reference temperature specified in the standard for temperature rise, such as temperature compensation for the ambient temperature used for the non-drive end bearing of the traction motor, increasing the ambient temperature value by 15°C as the cooling medium temperature. However, this method is only effective for temperature rise alarms and has no effect on over-temperature alarms, thus only superficially solving part of the alarm problem.

[0006] 3) Improve the temperature measurement conditions of the composite sensor, such as adding an outer cover to the temperature sensing probe of the bearing at the non-drive end to block or reduce the influence of hot air from the traction motor outlet on the sensor probe. This solution changes the temperature measured by the temperature sensor, but the effect is very limited and does not help reduce the actual shaft temperature and the operating temperature of the motor core.

[0007] 4) The traction motor control logic is adjusted based on axle temperature. For example, when the temperature at the drive end of a motor on a certain axle of the locomotive exceeds 105°C, the traction command decreases linearly. When the temperature reaches 115°C, the command value drops to 0. After the temperature drops below the limit, the motor torque command is reapplied to restore train traction. This solution is prone to causing locomotive safety problems. For example, alarms usually occur on long, steep slopes, and reduced power operation can easily cause the train to stop, leading to safety accidents.

[0008] In summary, the current methods for solving shaft temperature alarm problems have the following drawbacks: (1) The solutions are limited and can only improve or solve some alarm problems. (2) They cannot actually improve the bearing temperature and motor core temperature; they are only useful for handling the alarm fault. (3) They still face the risk of excessively high actual operating temperatures, deterioration of the working environment of the motor and bearings, and reduced service life.

[0009] In summary, there is an urgent need for a method, medium, and equipment for controlling the shaft temperature of locomotive traction motors, which can fundamentally improve the core temperature of traction motors, completely solve the bearing temperature alarm problem, improve bearing operating conditions, extend the service life of bearings and motors, and effectively ensure the safe operation of locomotives. Summary of the Invention

[0010] The purpose of this invention is to provide a method, medium, and equipment for controlling the shaft temperature of a locomotive traction motor, the specific technical solution of which is as follows:

[0011] A method for controlling the axle temperature of a locomotive traction motor includes:

[0012] Step 1: Obtain the bearing parameters of the locomotive traction motor, determine if there is any abnormality in the bearing, and issue an alarm if there is an abnormality; otherwise, proceed to the next step.

[0013] Step 2: Obtain current locomotive information, cooling fan operating information, environmental information, and track information. Calculate whether an axle temperature alarm will occur during the nearest climb using the axle temperature prediction method. If no alarm occurs, continue operating as is. If an alarm occurs, proceed to the next step.

[0014] Step 3: Calculate the variable conditions that prevent shaft temperature alarms from occurring, and adjust the fan operation strategy to prevent subsequent traction motors from triggering shaft temperature alarms.

[0015] Preferably, the method for determining whether the bearing is malfunctioning in step one includes:

[0016] Obtain vibration acceleration and temperature data of the bearings of the locomotive traction motor;

[0017] By using data preprocessing and feature extraction algorithms, bearing vibration characteristic state indicators are constructed to preliminarily determine the bearing vibration status. If the characteristic state indicator H < 0.5, the bearing is judged to be normal.

[0018] If the characteristic state index H ≥ 0.5, then perform a Fourier transform on the vibration acceleration data to calculate the characteristic frequency and obtain a spectrum based on vibration acceleration.

[0019] Compare the spectrum diagram with the bearing failure frequency to determine the bearing failure type;

[0020] The construction process of the characteristic state index is as follows: First, based on the acceleration sensor data, characteristic values ​​including effective value, peak-to-peak value, high-low frequency energy ratio, kurtosis, impact decibels, and margin factor are calculated. Then, one or more key characteristics that best reflect the bearing condition are selected. Finally, the characteristic state index is constructed using the following formula:

[0021] ;

[0022] Where H is the constructed characteristic state index. x For the selected key feature values, n The maximum number of eigenvalues ​​is 13. w Weights for each feature value, index i =1,2,3 … n .

[0023] Preferably, step two specifically includes:

[0024] Obtain the current locomotive gross weight m, speed v, ambient temperature t, cooling fan operating frequency f, traction motor temperature t1, slope length L1, slope a, and distance from the slope L2;

[0025] The axle temperature prediction method is used to calculate whether an axle temperature alarm will occur during the current uphill climb. The axle temperature prediction method includes:

[0026] Based on the locomotive's total weight m, speed v, and gradient a, the locomotive's climbing power P is calculated using the following expression:

[0027] P=m g v sina;

[0028] The required output power P1 of the traction motor is calculated based on the required locomotive climbing power P and the motor efficiency η, as shown in the following expression:

[0029] P1 = P / η;

[0030] By combining the traction motor airflow-power-shaft temperature relationship curves under tunnel and non-tunnel conditions, the expected bearing temperature T under the current airflow and the required locomotive climbing power P is calculated. q The specific calculations are as follows:

[0031] The temperature rise at the top of the slope is calculated based on the following formula:

[0032] T=k1 P1 L1 / v-k2 Q d +k3 t;

[0033] Where T is the temperature rise at the top of the slope, k1, k2, and k3 are empirical coefficients related to the vehicle model, and Q... d Current airflow;

[0034] Expected bearing temperature T under current airflow and required locomotive climbing power P q The following formula is used to calculate:

[0035] T q =T0+T;

[0036] Where T0 is the temperature at the bottom of the slope;

[0037] Determine the T q Has the preset alarm temperature been reached, i.e., has T been met? q <120℃ and T q If -t < 80℃, the shaft temperature alarm will not occur;

[0038] If T q ≥120℃ or T q If -t≥80℃, a shaft temperature alarm will be triggered.

[0039] Preferably, step three specifically includes:

[0040] When the calculation result is T q ≥120℃ or T q When -t≥80℃, the maximum airflow Q of the cooling fan is used. max Recalculate T q And determine the climbing process T. q If the alarm threshold is exceeded, and if not, then based on the current location and the distance of the climb, when the distance L2=0, adjust the operating frequency of the cooling fan to the maximum frequency.

[0041] If the alarm condition is still triggered even when the cooling fan is running at maximum airflow or full frequency, then the maximum airflow Q will be used. max =1.45m 3 / s and preset alarm temperature T q Using the two parameters =120℃ as boundaries, the highest slope bottom temperature T0 that will not trigger an alarm is calculated by back-calculating the relationship curve of the traction motor air volume-power-shaft temperature.

[0042] Based on the current traction motor temperature T d The fan air volume or frequency, and the distance L2 from the slope, are expressed as follows, based on the balance between heat generation and heat dissipation of the traction motor on flat or downhill roads:

[0043] δT=k5 P1 L2 / v-k6 Q d ;

[0044] Among them, k5 and k6 are empirical coefficients related to vehicle models;

[0045] Let T d -T0=δT, calculate the shortest distance L from the bottom of the slope under maximum wind speed. 2min ;

[0046] Based on the current location and the distance of the climb, when the distance L2 = L 2min At that time, adjust the frequency of the fan to the maximum frequency to prevent shaft temperature alarms from occurring subsequently;

[0047] When the calculated L 2min When the distance from the locomotive to the bottom of the slope is L2, let L2 = L 2min According to δT=k5 P1 L2 / v-k6 Q d The computer shows the car's speed v, if v > v min v min If the minimum speed of the locomotive is given, then the locomotive speed should be immediately reduced to v. min And adjust the fan frequency to 60Hz to ensure that no shaft temperature alarm will occur subsequently;

[0048] When v <v min Even if the locomotive reduces its speed in time and operates under maximum ventilation conditions, an alarm may still occur during subsequent climbing. In this case, the locomotive must be stopped and restarted only after the traction motor temperature has dropped to the minimum temperature at which no alarm will occur, to ensure that the locomotive does not trigger an axle temperature alarm.

[0049] Preferably, step three further includes:

[0050] Obtain normal airflow data at the same frequency to determine the clogging status of the low-resistance louver filter.

[0051] Based on the blockage status and the variable condition that no axle temperature alarm will occur, determine whether an axle temperature alarm will occur if the fan at the bottom of the ramp is running at maximum wind speed. If an axle temperature alarm will occur, it is recommended to clean the low-resistance louver filter after the locomotive returns to the depot and set the current blockage status as a critical state.

[0052] Preferably, the method further includes a fourth step, which includes:

[0053] The parameters recorded in steps one through three are automatically generated into a database.

[0054] The present invention also provides a readable storage medium having computer program instructions stored thereon, which, when executed by a processor, implement the locomotive traction motor axle temperature control method as described above.

[0055] The present invention also provides an electronic device, comprising: at least one processor, at least one memory, and computer program instructions stored in the memory, wherein the computer program instructions are executed by the processor to perform the locomotive traction motor axle temperature control method as described above.

[0056] The application of the technical solution of the present invention has the following beneficial effects:

[0057] A method for controlling the axle temperature of a locomotive traction motor includes: acquiring bearing parameters of the locomotive traction motor; determining whether the bearing is abnormal; issuing an alarm if abnormal; and proceeding to the next step if normal. The method also includes acquiring current locomotive information, cooling fan operating information, environmental information, and track information; calculating whether an axle temperature alarm will occur during the nearest uphill climb using an axle temperature prediction method; continuing operation as before if no alarm occurs; and calculating the variable conditions that prevent an axle temperature alarm, adjusting the fan operating strategy to prevent subsequent traction motor axle temperature alarms. This method optimizes the fan operating strategy based on environmental and track conditions, axle temperature data, and current fan status, significantly increasing airflow or the duration of high airflow, and increasing heat dissipation. This reduces bearing and motor temperatures under various harsh conditions, enabling early warning and resolution of axle temperature alarms caused by multiple factors. It also intelligently determines whether the low-resistance louvered filter is clogged and whether the bearing is faulty. By employing various methods and approaches, it addresses bearing temperature alarms caused by various reasons, exhibiting automation, intelligence, and broad applicability.

[0058] In addition to the objectives, features, and advantages described above, the present invention has other objectives, features, and advantages. The invention will now be described in further detail with reference to the figures. Attached Figure Description

[0059] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings:

[0060] Figure 1 This is a flowchart illustrating a locomotive traction motor shaft temperature control method according to an embodiment of the present invention. Detailed Implementation

[0061] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings. However, the present invention can be implemented in many different ways as defined and covered by the claims.

[0062] The locomotive in this embodiment is a freight locomotive, which includes at least three parts: a low-resistance louver, a high-performance fan, and a fan energy efficiency monitoring system. The low-resistance louver includes air guides, dust collection grilles, sealing strips, frames, filters, and mounting holes. The high-performance fan is an axial-flow centrifugal fan, composed of an air inlet duct, impeller, fan casing, and motor. The fan energy efficiency monitoring system mainly consists of sensors arranged on the air duct and fan, a data acquisition box, a data processing host, an online bearing monitoring system, a positioning system, and a control system.

[0063] This embodiment of a locomotive traction motor shaft temperature control method further increases the ventilation volume of the traction motor by adjusting the structural parameters of the existing traction fan. The fan impeller diameter is increased by 5mm, the blade inlet angle is reduced by 4°, and the guide vanes of the air duct are adjusted by 3°. This significantly increases the ventilation volume of the traction motor while maintaining essentially the same power and noise levels. This reduces the temperature of the motor core, thereby reducing the heat transferred from the core to the traction motor bearings and lowering the bearing temperature. Optimizing the louver spacing reduces louver resistance. This, in turn, reduces the resistance of the ventilation and heat dissipation system composed of the louvers, air inlet duct, fan, and motor. The reduced system resistance causes the fan to operate at a higher flow rate, effectively increasing the ventilation volume even further.

[0064] Compared to the existing air intake louvers on the side roof of the locomotive, the low-resistance louvers can reduce flow resistance by about 5%; compared to the existing traction fans on the locomotive, the high-performance fans designed through parametric optimization can increase air volume by 8% to 15%.

[0065] refer to Figure 1 A method for controlling the axle temperature of a locomotive traction motor, comprising:

[0066] Step 1: Obtain the bearing parameters of the locomotive traction motor through the wind turbine energy efficiency monitoring system to determine if the bearing is abnormal. If abnormal, issue an alarm; if normal, proceed to the next step.

[0067] Methods for determining whether a bearing is malfunctioning include:

[0068] Obtain vibration acceleration and temperature data of the bearings of the locomotive traction motor;

[0069] Through data preprocessing, feature extraction algorithms, or bearing vibration characteristic indicators, the bearing vibration acceleration data, after data cleaning, calculation, and Fourier transform, yields vibration characteristic values. In this embodiment, the main characteristic values ​​are RMS value, peak-to-peak value, high-to-low frequency energy ratio, and kurtosis. The bearing vibration condition is initially judged based on the RMS value and peak-to-peak value; if the characteristic values ​​are small, the bearing is considered normal.

[0070] Depending on the specific circumstances, some or a combination of these characteristic values ​​are selected as diagnostic indicators. In this embodiment, peak value and impact DB are selected as characteristic indicators to determine whether the bearing is normal. If the characteristic state indicator H ≥ 0.5, the characteristic frequency is calculated by performing a Fourier transform on the vibration acceleration data to obtain a spectrum based on vibration acceleration.

[0071] The construction process of the characteristic state index is as follows: First, based on the acceleration sensor data, characteristic values ​​including effective value, peak-to-peak value, high-low frequency energy ratio, kurtosis, impact decibels, and margin factor are calculated. Then, one or more key characteristics that best reflect the bearing condition are selected. Finally, the characteristic state index is constructed using the following formula:

[0072] ;

[0073] Where H is the constructed characteristic state index. x For the selected key feature values, n The maximum number of eigenvalues ​​is 13. w Weights for each feature value, index i =1,2,3 … n .

[0074] The bearing fault type is determined by comparing the spectrum diagram with the bearing fault frequencies provided by the bearing manufacturer. For bearings that may be faulty, the characteristic frequency is further compared with the fault characteristic frequencies of the bearing's inner and outer rings and rolling elements to determine the final condition of the bearing. This process is performed and updated daily to help the locomotive ensure that the bearing is in normal condition before operation. If the characteristic frequency is consistent with the fault frequency of the bearing's inner and outer rings or rolling elements, and the temperature rise is high, the bearing is determined to be faulty. When the bearing is damaged, it will also trigger a shaft temperature alarm.

[0075] Step 2: Obtain current locomotive information, cooling fan operation information, environmental information, and line information through on-board sensors, and load them into the system in advance. The collected data is transmitted to each data acquisition box and a data processing host via a 485 communication line. In this embodiment, the calculation and control are all performed in the data processing host.

[0076] The axle temperature prediction method is used to calculate whether an axle temperature alarm will occur during the nearest uphill climb under the current operating condition. If no alarm occurs, operation continues under the current condition. If an alarm occurs, proceed to the next step, which specifically includes:

[0077] Obtain the current locomotive gross weight m, speed v, ambient temperature t, cooling fan operating frequency f, traction motor temperature t1, slope length L1, slope a, and distance from the slope L2;

[0078] The axle temperature prediction method is used to calculate whether an axle temperature alarm will occur during the current uphill climb. This method is a comprehensive judgment method combining theoretical approaches and historical data. The theoretical component includes:

[0079] Based on the locomotive's total weight m, speed v, and gradient a, the locomotive's climbing power P is calculated using the following expression:

[0080] P=m g v sina;

[0081] The required output power P1 of the traction motor is calculated based on the required locomotive climbing power P and the motor efficiency η, as shown in the following expression:

[0082] P1 = P / η;

[0083] By combining the traction motor airflow-power-shaft temperature relationship curves under tunnel and non-tunnel conditions, the expected bearing temperature T under the current airflow and the required locomotive climbing power P is calculated. q The specific calculations are as follows:

[0084] The temperature rise at the top of the slope is calculated based on the following formula:

[0085] T=k1 P1 L1 / v-k2 Q d +k3 t;

[0086] Where T is the temperature rise at the top of the slope, k1, k2, and k3 are empirical coefficients related to the vehicle model, and Q... d Given the current air volume, the only difference between tunnel and non-tunnel conditions is t;

[0087] Expected bearing temperature T under current airflow and required locomotive climbing power P q The following formula is used to calculate:

[0088] T q =T0+T;

[0089] Where T0 is the temperature at the bottom of the slope;

[0090] Determine the T q Has the preset alarm temperature been reached, i.e., has T been met? q <120℃ and T q If -t < 80℃, the shaft temperature alarm will not occur;

[0091] If T q ≥120℃ or T q If -t≥80℃, a shaft temperature alarm will be triggered.

[0092] Step 3: Calculate the variable conditions that prevent shaft temperature alarms, and adjust the fan operation strategy to ensure that subsequent traction motors do not trigger shaft temperature alarms. Step 3 specifically includes:

[0093] First, assume that the wind volume is greatest during uphill climbing, and the calculation result is T. q ≥120℃ or T q When -t≥80℃, the maximum airflow Q of the cooling fan is used. max (This embodiment is 1.45m) 3 / s (the maximum value varies depending on the fan) Recalculate T q And determine the climbing process T. q If the alarm threshold is exceeded, and if not, adjust the cooling fan's operating frequency to maximum when the distance L2 = 0, based on the current location and the distance climbed; if the alarm-free condition is met, appropriately reduce the airflow Q. d Repeat the above process until the alarm condition is just met, i.e., Tq=120 or Tq-T0=80℃. The air volume at this point is the minimum air volume Q that will not trigger an alarm. min The data processing host is based on the relationship between fan frequency and air volume (measured in advance in a laboratory or operating circuit, and built into the system; air volume Q=k7). f, between the maximum airflow Q max and minimum air volume Q min If a suitable airflow frequency is sent to the control system, the fan will operate at the appropriate frequency, and no alarm problem will occur.

[0094] Alternatively, the running speed can be increased appropriately until the calculated T is obtained. q If the axle temperature alarm condition is just reached, then the speed at this point is the locomotive's maximum permissible operating speed V. max The data processing host outputs information to control the traction fan to operate at a maximum frequency of 60Hz, and simultaneously sends data to the driver's console display, advising the driver to operate at a speed not exceeding the maximum V. max run.

[0095] If the alarm condition is still triggered even when the cooling fan is running at maximum airflow or full frequency, then the maximum airflow Q will be used. max =1.45m 3 / s and preset alarm temperature T q Using the two parameters =120℃ as boundaries, the highest slope bottom temperature T0 that will not trigger an alarm is calculated by back-calculating the relationship curve of the traction motor air volume-power-shaft temperature.

[0096] Based on the current traction motor temperature T dThe fan air volume or frequency, and the distance L2 from the hilltop location, are expressed as follows, based on the balance between heat generation and heat dissipation of the traction motor on flat roads or downhill slopes:

[0097] δT=k5 P1 L2 / v-k6 Q d ;

[0098] Among them, k5 and k6 are empirical coefficients related to vehicle model;

[0099] Let T d -T0=δT, calculate the shortest distance L from the bottom of the slope under maximum wind speed. 2min ;

[0100] Based on the current location and the distance of the climb, when the distance L2 = L 2min At that time, adjust the frequency of the fan to the maximum frequency to prevent shaft temperature alarms from occurring subsequently;

[0101] When the calculated L 2min When the distance from the locomotive to the bottom of the slope is L2, let L2 = L 2min According to δT=k5 P1 L2 / v-k6 Q d The computer shows the car's speed v, if v > v min v min If the minimum speed of the locomotive is given, then the locomotive speed should be immediately reduced to v. min And adjust the fan frequency to 60Hz to ensure that no shaft temperature alarm will occur subsequently;

[0102] When v <v min Even if the locomotive reduces its speed in time and operates under maximum ventilation conditions, an alarm may still occur during subsequent climbing. In this case, the locomotive must be stopped and restarted only after the traction motor temperature has dropped to the minimum temperature at which no alarm will occur, to ensure that the locomotive does not trigger an axle temperature alarm.

[0103] In addition, after the locomotive has been running for a period of time, the airflow often decreases due to the clogging of the low-resistance louver filter, affecting the heat dissipation of the motor bearings. In this embodiment, when the louvers are clogged, the system resistance increases. The monitoring system analyzes the airflow data at the same frequency to determine the clogging status. When the current fan airflow is only 90% of the original airflow under the same frequency in tunnel or non-tunnel conditions, it means that the louvers are about 10% clogged. Based on the airflow under the clogging condition, the shaft temperature is predicted. When the system predicts that an alarm will still occur even when the fan is running at maximum speed at the bottom of the ramp, the louvers must be cleaned, and the current clogging status is set as a critical state. Subsequently, the system will dynamically adjust the clogging status to achieve condition-based maintenance and cleaning of the louvers.

[0104] Step 4: When there are many similar routes and operating conditions, the parameters from Steps 1 to 3 are automatically recorded to form a database. When running on the same routes and under the same conditions, the system automatically controls axle temperature alarms according to the database, eliminating the need for recalculation. This improves system decision-making time, ensures decision accuracy, and reduces decision-making time.

[0105] This embodiment also includes a readable storage medium storing computer program instructions, which, when executed by a processor, implement the locomotive traction motor shaft temperature control method as described above.

[0106] For example, the computer program may be divided into one or more modules / units, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules / units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in the electronic device.

[0107] This embodiment also includes an electronic device, comprising: at least one processor, at least one memory, and computer program instructions stored in the memory, wherein the computer program instructions are executed by the processor to perform the locomotive traction motor shaft temperature control method as described above.

[0108] The electronic device can be a mobile phone, desktop computer, laptop, handheld computer, cloud server, or other computing device. The electronic device may include, but is not limited to, processors and memory. For example, the electronic device may also include input / output devices, network access devices, buses, etc.

[0109] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for controlling the shaft temperature of a locomotive traction motor, characterized in that, include: Step 1: Obtain the bearing parameters of the locomotive traction motor, determine if there is any abnormality in the bearing, and issue an alarm if there is an abnormality; otherwise, proceed to the next step. Step 2: Obtain current locomotive information, cooling fan operating information, environmental information, and track information. Calculate whether an axle temperature alarm will occur during the nearest climb using the axle temperature prediction method. If no alarm occurs, continue operating as is. If an alarm occurs, proceed to the next step. Step two specifically includes: Obtain the current locomotive gross weight m, speed v, ambient temperature t, cooling fan operating frequency f, traction motor temperature t1, slope length L1, slope a, and distance from the slope L2; The axle temperature prediction method is used to calculate whether an axle temperature alarm will occur during the current uphill climb. The axle temperature prediction method includes: Based on the locomotive's total weight m, speed v, and gradient a, the locomotive's climbing power P is calculated using the following expression: P=m g v sina; The required output power P1 of the traction motor is calculated based on the required locomotive climbing power P and the motor efficiency η, as shown in the following expression: P1 = P / η; By combining the traction motor airflow-power-shaft temperature relationship curves under tunnel and non-tunnel conditions, the expected bearing temperature T under the current airflow and the required locomotive climbing power P is calculated. q The specific calculations are as follows: The temperature rise at the top of the slope is calculated based on the following formula: T=k1 P1 L1 / v-k2 Q d +k3 t; Where T is the temperature rise at the top of the slope, k1, k2, and k3 are empirical coefficients related to the vehicle model, and Q... d Current airflow; Expected bearing temperature T under current airflow and required locomotive climbing power P q The following formula is used to calculate: T q =T0+T; Where T0 is the temperature at the bottom of the slope; Determine the T q Has the preset alarm temperature been reached, i.e., has T been met? q <120℃ and T q If -t < 80℃, the shaft temperature alarm will not occur; If T q ≥120℃ or T q If -t≥80℃, a shaft temperature alarm will be triggered; Step 3: Calculate the variable conditions under which the shaft temperature alarm will not occur, and adjust the fan operation strategy so that the subsequent traction motor will not trigger the shaft temperature alarm; Step three specifically includes: When the calculation result is T q ≥120℃ or T q When -t≥80℃, the maximum airflow Q of the cooling fan is used. max Recalculate T q And determine the climbing process T. q If the alarm threshold is exceeded, and if not, then based on the current location and the distance of the climb, when the distance L2=0, adjust the operating frequency of the cooling fan to the maximum frequency. If the alarm condition is still triggered even when the cooling fan is running at maximum airflow or full frequency, then the maximum airflow Q will be used. max =1.45m 3 / s and preset alarm temperature T q Using the two parameters =120℃ as boundaries, the highest slope bottom temperature T0 that will not trigger an alarm is calculated by back-calculating the relationship curve of the traction motor air volume-power-shaft temperature. Based on the current traction motor temperature T d The fan air volume or frequency, and the distance L2 from the slope, are expressed as follows, based on the balance between heat generation and heat dissipation of the traction motor on flat or downhill roads: δT=k5 P1 L2 / v-k6 Q d ; Among them, k5 and k6 are empirical coefficients related to vehicle models; Let T d -T0=δT, calculate the shortest distance L from the bottom of the slope under maximum wind speed. 2min ; Based on the current location and the distance of the climb, when the distance L2 = L 2min At that time, adjust the frequency of the fan to the maximum frequency to prevent shaft temperature alarms from occurring subsequently; When the calculated L 2min When the distance from the locomotive to the bottom of the slope is L2, let L2 = L 2min According to δT=k5 P1 L2 / v-k6 Q d The computer shows the car's speed v, if v > v min v min If the minimum speed of the locomotive is given, then the locomotive speed should be immediately reduced to v. min And adjust the fan frequency to 60Hz to ensure that no shaft temperature alarm will occur subsequently; When v <v min Even if the locomotive reduces its speed in time and operates under maximum ventilation conditions, an alarm may still occur during subsequent climbing. In this case, the locomotive must be stopped and restarted only after the traction motor temperature has dropped to the minimum temperature at which no alarm will occur, to ensure that the locomotive does not trigger an axle temperature alarm.

2. The locomotive traction motor axle temperature control method according to claim 1, characterized in that, The method for determining whether the bearing is malfunctioning in step one includes: Obtain vibration acceleration and temperature data of the bearings of the locomotive traction motor; By using data preprocessing and feature extraction algorithms, bearing vibration characteristic state indicators are constructed to preliminarily determine the bearing vibration status. If the characteristic state indicator H < 0.5, the bearing is judged to be normal. If the characteristic state index H ≥ 0.5, then perform a Fourier transform on the vibration acceleration data to calculate the characteristic frequency and obtain a spectrum based on vibration acceleration. Compare the spectrum diagram with the bearing failure frequency to determine the bearing failure type; The construction process of the characteristic state index is as follows: First, based on the acceleration sensor data, characteristic values ​​including effective value, peak-to-peak value, high-low frequency energy ratio, kurtosis, impact decibels, and margin factor are calculated. Then, one or more key characteristics that best reflect the bearing condition are selected. Finally, the characteristic state index is constructed using the following formula: ； Where H is the constructed characteristic state index. x For the selected key feature values, n The maximum number of eigenvalues ​​is 13. w Weights for each feature value, index i =1,2,3 … n .

3. The locomotive traction motor axle temperature control method according to claim 2, characterized in that, Step three also includes: Obtain normal airflow data at the same frequency to determine the clogging status of the low-resistance louver filter. Based on the blockage status and the variable condition that no axle temperature alarm will occur, determine whether an axle temperature alarm will occur if the fan at the bottom of the ramp is running at maximum wind speed. If an axle temperature alarm will occur, it is recommended to clean the low-resistance louver filter after the locomotive returns to the depot and set the current blockage status as a critical state.

4. The locomotive traction motor axle temperature control method according to claim 3, characterized in that, It also includes step four, which includes: The parameters recorded in steps one through three are automatically generated into a database.

5. A readable storage medium, characterized in that, It stores computer program instructions, which, when executed by a processor, implement the locomotive traction motor axle temperature control method as described in any one of claims 1 to 4.

6. An electronic device, characterized in that, include: The locomotive traction motor axle temperature control method as described in any one of claims 1 to 4 includes at least one processor, at least one memory, and computer program instructions stored in the memory, which are executed by the processor when the computer program instructions are executed.

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