Tire monitoring method and device of loading machine and loading machine

Abstract

The invention provides a tire monitoring method and device of a loader and the loader, and relates to the technical field of loaders. The tire monitoring method of the loading machine comprises the steps that the temperature, the tire pressure, the deformation quantity and the load of a tire of the loading machine under various working conditions are obtained; establishing a tire load model according to the temperature, the tire pressure, the deformation quantity and the load; determining the actual load of the tire according to the tire load model; and according to the actual load, tipping information is generated. According to the tire monitoring method of the loading machine, the tire state is comprehensively evaluated by monitoring the temperature, the tire pressure, the deformation quantity, the load and the rollover of the tire of the loading machine, so that the tire failure risk is accurately predicted under the complex working condition, and active protection is provided for safe operation of equipment.

Description

Technical Field

[0001] This application relates to the field of loader technology, and more particularly to a tire monitoring method, device, and loader for a loader. Background Technology

[0002] Loaders operate under more severe conditions than ordinary vehicles. On the one hand, loaders frequently experience dynamic impact loads (such as the instantaneous impact when shoveling materials), uneven loading (force on one side of the bucket), and overloads, leading to localized stress concentration in the tires. On the other hand, loaders mainly operate on unpaved roads (such as mines, construction sites, and muddy areas), facing gravel, potholes, and slippery surfaces, making the tires susceptible to damage such as cutting, punctures, and slipping. Furthermore, the longitudinal impact force generated when the loader bucket inserts into the material pile causes instantaneous tire overload, and the shift in the center of gravity when lifting the bucket causes lateral tire displacement.

[0003] Loader tires are industrial tires specifically designed for loaders, and their condition directly affects the safety of loader operations. However, existing tire monitoring systems mostly focus on monitoring single parameters such as tire pressure and temperature, and cannot monitor loader tires for rollover. Summary of the Invention

[0004] In view of the above problems, this application provides a tire monitoring method, device and loader for a loader, so as to solve the problem that the existing tire monitoring system cannot monitor the overturning of the loader tires.

[0005] To achieve the above objectives, the embodiments of this application provide the following technical solutions:

[0006] The first aspect of this application provides a tire monitoring method for a loader, comprising:

[0007] Obtain tire temperature, tire pressure, deformation, and load under various operating conditions of the loader;

[0008] A tire load model is established based on temperature, tire pressure, deformation, and load.

[0009] Determine the actual load on the tire based on the tire load model;

[0010] Based on the actual load, rollover information is generated.

[0011] In one possible implementation, the operating conditions include the loader's travel speed, steering angle, acceleration, and braking pressure;

[0012] A tire load model is established based on temperature, tire pressure, and deformation, specifically including:

[0013] Establish a dataset for driving speed, steering angle, acceleration, braking pressure, temperature, tire pressure, deformation, and load;

[0014] The dataset is divided into a training subset and a validation subset;

[0015] Using driving speed, steering angle, braking pressure, acceleration, temperature, tire pressure and deformation in the training subset as input variables and load in the training subset as output variables, an initial tire load model is established.

[0016] The initial tire load model is trained by validating a subset of samples to generate a tire load model.

[0017] In one possible implementation, the actual load on the tire is determined based on a tire load model, specifically including:

[0018] Under the conditions of actual driving speed and actual steering angle of the loader, the actual temperature, actual tire pressure and actual deformation of the tires are obtained;

[0019] Input the actual driving speed, actual steering angle, actual acceleration, actual braking pressure, actual temperature, actual tire pressure, and actual deformation into the tire load model to generate the actual load.

[0020] In one possible implementation, rollover information is generated based on the actual load, specifically including:

[0021] Determine whether the actual load is within the preset load range;

[0022] If not, confirm the generation of overturning information and issue an alarm based on the overturning information.

[0023] In one possible implementation, rollover information is generated based on the actual load, specifically including:

[0024] Obtain the actual load on multiple tires of the loader;

[0025] Determine the difference in actual load between multiple tires based on their actual loads.

[0026] Determine whether the actual load difference is within the preset load difference range;

[0027] If not, confirm the generation of overturning information and issue an alarm based on the overturning information.

[0028] In one possible implementation, after obtaining the tire temperature, tire pressure, deformation, and load under various operating conditions of the loader, the method further includes:

[0029] Tire wear is generated based on temperature, tire pressure, deformation, and load.

[0030] Determine if the tire wear is within the preset wear range;

[0031] If not, confirm the generation of tire wear information and issue a prompt action based on the tire wear information.

[0032] A second aspect of this application provides a tire monitoring device for a loader, comprising:

[0033] The acquisition module is used to acquire the temperature, tire pressure, deformation, and load of the tires of the loader under various working conditions.

[0034] The processing module is used to establish a tire load model based on temperature, tire pressure, deformation, and load; determine the actual load on the tire based on the tire load model; and generate rollover information based on the actual load.

[0035] In one possible implementation, the acquisition module includes:

[0036] Temperature sensor used to monitor tire temperature;

[0037] Pressure sensors are used to monitor tire pressure.

[0038] Infrared sensors are used to monitor tire deformation.

[0039] The loader's tire monitoring device also includes a wireless transmission component, which is electrically and / or communicatively connected to temperature sensors, pressure sensors, and infrared sensors; the wireless transmission component is also communicatively connected to the vehicle-side control center.

[0040] The loader's tire monitoring device also includes a mounting base, which is built into the tire's inner cavity; the mounting base includes a housing; the housing has a first recess, a second recess, a third recess, and a fourth recess; a temperature sensor is built into the first recess; a pressure sensor is built into the second recess; an infrared sensor is built into the third recess; and a wireless transmission component is built into the fourth recess.

[0041] In one possible implementation, the mounting base and the tire body are independently disposed; the mounting base is movably disposed within the inner cavity of the tire; the mounting base also includes a base, which is disposed at the bottom of the housing, and the base and the housing together form a self-righting structure, the base being used to maintain the balance of the mounting base.

[0042] The third and fourth recesses are located on the vertical line of the center of gravity of the mounting base; the fourth recess is located at the center of gravity of the mounting base.

[0043] A third aspect of this application provides a loader, including: a memory and a processor;

[0044] The memory is used to store computer programs / instructions; the processor is used to implement the methods described above based on the computer programs / instructions stored in the memory.

[0045] The tire monitoring method for loaders provided in this application provides a comprehensive assessment of tire condition by monitoring the temperature, tire pressure, deformation, load, and rollover of the loader's tires. This enables accurate prediction of tire failure risks under complex working conditions and provides proactive protection for the safe operation of the equipment.

[0046] In addition to the technical problems solved by the embodiments of this application, the technical features constituting the technical solutions, and the beneficial effects brought about by the technical features of these technical solutions described above, other technical problems that can be solved by the tire monitoring method and tire monitoring device for loaders provided by the embodiments of this application, other technical features included in the technical solutions, and the beneficial effects brought about by these technical features will be further explained in detail in the specific implementation. Attached Figure Description

[0047] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0048] Figure 1 This is a first flowchart of a tire monitoring method for a loader provided in an embodiment of this application;

[0049] Figure 2 This is a second flowchart of a tire monitoring method for a loader provided in an embodiment of this application;

[0050] Figure 3 A third flowchart illustrating the tire monitoring method for a loader provided in an embodiment of this application;

[0051] Figure 4 A fourth flowchart of the tire monitoring method for a loader provided in an embodiment of this application;

[0052] Figure 5 A fifth flowchart illustrating the tire monitoring method for a loader provided in an embodiment of this application;

[0053] Figure 6 A sixth flowchart of the tire monitoring method for a loader provided in an embodiment of this application;

[0054] Figure 7 This is a schematic diagram of the mounting base for the tire monitoring device of a loader provided in an embodiment of this application;

[0055] Figure 8An assembly diagram of the temperature sensor, pressure sensor, infrared sensor, wireless transmission component, and mounting base of the tire monitoring device for a loader provided in this application embodiment;

[0056] Figure 9 A structural diagram showing the mounting base of the tire monitoring device for a loader provided in this application embodiment is built into the inner cavity of the tire.

[0057] Explanation of reference numerals in the attached figures:

[0058] 11. Temperature sensor; 12. Pressure sensor; 13. Infrared sensor; Wireless transmission component;

[0059] 20. Wireless transmission components;

[0060] 30. Mounting base; 31. Housing; 311. First recess; 312. Second recess; 313. Third recess; 314. Fourth recess; 32. Base;

[0061] 40. Tires. Detailed Implementation

[0062] First, those skilled in the art should understand that these embodiments are merely for explaining the technical principles of this application and are not intended to limit the scope of protection of this application. Those skilled in the art can make adjustments as needed to adapt to specific application scenarios.

[0063] Secondly, it should be noted that, in the description of the embodiments of this application, unless otherwise explicitly specified and limited, the terms "connected" and "linked" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in the embodiments of this application according to the specific circumstances.

[0064] As described in the background section, the extreme complexity of the loader's operating environment places far greater technical demands on tire health monitoring than on ordinary vehicles. The instantaneous bursts of dynamic loads in their operating scenarios (such as the instantaneous impact when loading materials), uneven loading (force on one side of the bucket), and excessive loads (loads in mining operations can reach several times the equipment's rated value) lead to localized stress concentration and abnormal deformation in the tires. The complex road conditions on unpaved surfaces (such as mine gravel or muddy construction sites) expose tires to multiple risks of damage, including cutting, punctures, and slippage. Existing tire monitoring systems mostly focus on monitoring single parameters such as tire pressure and temperature, making it difficult to capture key indicators such as deformation (reflecting the degree of wear / deformation) and load (determining the actual stress level), resulting in a severe deficiency in the ability to provide early warnings for high-risk conditions such as tire blowouts and rollovers.

[0065] To address the aforementioned technical problems, this application proposes a tire monitoring method for loaders, comprising: acquiring tire temperature, tire pressure, deformation, and load under various operating conditions of the loader; establishing a tire load model based on the temperature, tire pressure, deformation, and load; determining the actual load on the tire based on the tire load model; and generating rollover information based on the actual load. By monitoring the temperature, tire pressure, deformation, load, and rollover of the loader's tires, a comprehensive assessment of the tire condition can be achieved, thereby accurately predicting tire failure risks under complex operating conditions and providing proactive protection for the safe operation of the equipment.

[0066] The technical solutions of this application will be described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0067] In this application, an electronic device is used as the execution subject to perform the tire monitoring method for a loader according to the following embodiments. Specifically, the execution subject can be a hardware device of the electronic device, a software application implementing the following embodiments in the electronic device, a computer-readable storage medium on which the software application implementing the following embodiments is installed, or code implementing the software application of the following embodiments.

[0068] In some embodiments, the loader's tire monitoring system may include a tire monitoring unit and a control center of the loader, and a communication connection may be established between the tire monitoring unit and the control center.

[0069] In some embodiments, the tire monitoring unit may include a monitoring module, a processing module, a first communication module, and a power supply. The monitoring module is used to collect tire temperature, tire pressure, deformation, and load information. The processing module is used to convert the tire temperature, tire pressure, deformation, and load information into electrical signals. The processing module is electrically connected to the first communication module, which is used to communicate with the control center to transmit the temperature, tire pressure, deformation, and load information to the control center. The power supply is used to power the monitoring module, the processing module, and the first communication module.

[0070] In some embodiments, the control center may include a second communication module for establishing communication with the first communication module.

[0071] Furthermore, the second communication module and the first communication module can be wireless communication modules, and the second communication module is connected to the first communication module, enabling information to be transmitted between the tire monitoring system and the control center.

[0072] Figure 1 This paper illustrates a first flowchart of the tire monitoring method for a loader provided in an embodiment of this application. Please refer to the following: Figure 1 As shown, the tire monitoring methods for loaders include:

[0073] S101. Obtain the temperature, tire pressure, deformation, and load of the tires under various working conditions of the loader;

[0074] S102. Establish a tire load model based on temperature, tire pressure, deformation, and load;

[0075] S103. Determine the actual load on the tire based on the tire load model;

[0076] S104. Generate overturning information based on the actual load.

[0077] It should be noted that the condition of tires during loader operation is directly affected by various working conditions, including travel speed, steering angle, acceleration, and braking pressure. For example, tires experience instantaneous impact loads when loading materials, while the load distribution tends to stabilize during transportation. When the loader operates on a mining slope, the front tires experience increased tire pressure due to the weight of the bucket, and changes in steering angle cause load differences between the left and right wheels. During transportation, continuous travel speed raises tire temperature, accelerating rubber aging. Ignoring any of these parameters may lead to missed risks of tire blowouts or uneven wear. By acquiring tire temperature, tire pressure, deformation, and load data under various working conditions, abnormal conditions can be identified in advance, reducing the misjudgment rate.

[0078] In this embodiment, the temperature, tire pressure, deformation, and load of the tires under various working conditions of the loader are acquired; a tire load model is established based on the temperature, tire pressure, deformation, and load; the actual load of the tire is determined based on the tire load model; and rollover information is generated based on the actual load. This not only allows for simultaneous monitoring of the temperature, tire pressure, deformation, and load of the tires, but also enables rollover monitoring of the loader, thereby accurately predicting the risk of tire failure under complex working conditions.

[0079] Figure 2 This paper illustrates a second flowchart of the tire monitoring method for a loader provided in an embodiment of this application. Please refer to [link / reference]. Figure 2 As shown, in step S201, the operating conditions include the loader's travel speed, steering angle, acceleration, and braking pressure;

[0080] In step S202, a tire load model is established based on temperature, tire pressure, and deformation, specifically including:

[0081] S2021. Establish a dataset for driving speed, steering angle, acceleration, braking pressure, temperature, tire pressure, deformation, and load;

[0082] S2022. Divide the dataset into a training subset and a validation subset;

[0083] S2023. Using the driving speed, steering angle, braking pressure, acceleration, temperature, tire pressure and deformation in the training subset as input variables and the load in the training subset as output variables, establish an initial tire load model.

[0084] S2024. Train the initial tire load model using the validation subset to generate the tire load model.

[0085] It should be noted that tire load is affected by multiple dynamic factors coupled together. For example, changes in driving speed lead to uneven distribution of ground pressure, steering angle causes lateral force shift, and braking pressure directly affects tire slip ratio. By using operating parameters (driving speed, steering angle, acceleration, and braking pressure) and tire condition parameters (temperature, tire pressure, and deformation, etc.) as input variables, the response patterns under complex operating conditions can be captured.

[0086] For example, in mining slope operations, the front wheels of a loader experience increased tire pressure due to the weight of the bucket, while changes in steering angle cause load differences between the left and right wheels. In this situation, the model needs to incorporate acceleration data to correct load calculations; relying solely on a single parameter (such as tire pressure) will lead to inaccurate load estimations. By dividing the model into training and validation subsets, the model can learn parameter weights under different working conditions. For instance, on slippery surfaces, the weight of braking pressure's influence on load needs to be reduced. Dynamic modeling improves the real-time performance and accuracy of load calculations, providing reliable input for subsequent rollover warnings and thus reducing safety risks caused by model lag.

[0087] In some embodiments, considering that tire load is affected by multidimensional dynamic parameters (such as driving speed, steering angle, and braking pressure) and nonlinear coupling effects (such as the interaction between temperature and tire pressure), in order to capture the dynamic relationships under complex working conditions, this application adopts a Long Short-Term Memory (LSTM) network as the core model architecture. LSTM, through the synergistic effect of input gates, forget gates, and output gates, can learn temporal features such as sudden changes in steering angle and acceleration fluctuations, and adapt to parameter interactions under different working conditions. For example, in mine slope operations, the front wheels experience sudden load changes due to the weight of the bucket, while frequent adjustments to the steering angle cause load oscillations on the left and right wheels. By memorizing the working condition sequence within the previous 10 seconds (such as a sudden increase in speed from 5 km / h to 10 km / h and a sudden drop in braking pressure), LSTM can accurately predict the load fluctuation trend and reduce the error rate.

[0088] Furthermore, the dataset was divided into training, validation, and test sets in a 7:2:1 ratio; 5-fold cross-validation was used to optimize hyperparameters and avoid overfitting; and data with a timestamp deviation greater than 200ms were removed by sorting by operating condition timestamp.

[0089] Furthermore, during training, the input variables include driving speed, steering angle, braking pressure, acceleration, temperature, tire pressure, and deformation, while the output variable is the single tire load. The model employs the Adam optimizer, with 3 LSTM layers and an initial learning rate of 0.001, combined with a learning rate decay strategy (the learning rate is multiplied by 0.5 when the validation loss does not improve for 5 consecutive rounds). To prevent overfitting, a Dropout layer (with a ratio of 0.3) is added after each LSTM layer to randomly mask some neuron connections. The number of training rounds is dynamically adjusted, and training is terminated early when the validation loss does not improve for 50 consecutive rounds to avoid overfitting the model to noisy data. The number of hidden units is set to 128 (per layer) to capture high-dimensional feature interactions.

[0090] Furthermore, considering the timing characteristics of loader operations, a sliding window technique is employed to convert discrete operating parameters (such as steering angle and acceleration) into continuous time-series features. For example, steering angle data collected every 0.1 seconds over the past 10 seconds is integrated into a time-series vector of length 100 to capture dynamic change patterns. Interaction terms (such as temperature × tire pressure, acceleration × brake pressure) are introduced in feature engineering to capture nonlinear coupling effects, and Z-score normalization is used to eliminate dimensional differences.

[0091] Furthermore, missing data is filled using the K-nearest neighbor interpolation method, and outliers are removed using the 3σ principle to ensure the integrity and consistency of the dataset.

[0092] Furthermore, the model employs a Long Short-Term Memory (LSTM) network as its core architecture, capturing the temporal dependence and nonlinear characteristics of tire load through a two-layer stacked structure. The model input consists of 10 time steps (corresponding to 0.1-second sampling of operating conditions within 1 second) and 7 feature dimensions (driving speed, steering angle, acceleration, braking pressure, temperature, tire pressure, and deformation), with the output being the predicted single-tire load value. The overall process follows a "feature extraction-feature compression-regression prediction" workflow, balancing dynamic modeling capabilities with computational efficiency.

[0093] Figure 3 This paper illustrates a third flowchart of the tire monitoring method for a loader provided in an embodiment of this application. Please refer to [link / reference]. Figure 3 As shown, in step S303, the actual load of the tire is determined according to the tire load model, specifically including:

[0094] S3031. Under the condition of actual driving speed and actual steering angle of the loader, obtain the actual temperature, actual tire pressure and actual deformation of the tires;

[0095] S3032. Input the actual driving speed, actual steering angle, actual acceleration, actual braking pressure, actual temperature, actual tire pressure and actual deformation into the tire load model to generate the actual load.

[0096] It should be noted that the actual load needs to be dynamically calculated in conjunction with real-time operating conditions. For example, when a loader lifts the bucket, the shift in the center of gravity causes an increase in the load on one side of the tires. In this case, the steering angle and acceleration data need to be included in the model input. Relying solely on historical data cannot reflect instantaneous changes in conditions and may miss potential problems such as tire blowouts or uneven wear.

[0097] For example, when a loader makes a sharp turn on a gravel road, the outer tire bears additional lateral force, and the model needs to adjust the load distribution weights according to the steering angle and braking pressure. If the tire temperature rises due to friction at this time, it is also necessary to compensate for the impact of changes in rubber stiffness on deformation, so as to avoid load calculation errors caused by insufficient temperature compensation. Real-time data-driven load calculation can accurately reflect the actual load state of the tire, avoid warning delays caused by sudden changes in working conditions, and improve the system response speed.

[0098] Figure 4 This paper illustrates the fourth flowchart of the tire monitoring method for a loader provided in an embodiment of this application. Please refer to [link / reference]. Figure 4 As shown, in step S404, overturning information is generated based on the actual load, specifically including:

[0099] S4041. Determine whether the actual load is within the preset load range;

[0100] S4042. If not, confirm the generation of overturning information and issue an alarm action based on the overturning information.

[0101] It should be noted that rollover risk arises from a single tire load exceeding the safety threshold or an overall imbalance in load distribution. Abnormal overload conditions can be identified by setting a load range (such as ±20% of the rated load).

[0102] For example, when the load on the right tire of the loader suddenly increases due to road subsidence, the model calculates that the actual load on a single tire exceeds the preset range, triggering a warning and limiting the vehicle speed. If the difference continues to widen, the system can automatically activate the hydraulic brakes to prevent rollover, avoiding accidents caused by delays in manual intervention.

[0103] Figure 5 This paper illustrates the fifth flowchart of the tire monitoring method for a loader provided in an embodiment of this application. Please refer to [link / reference]. Figure 5 As shown, in step S504, overturning information is generated based on the actual load, specifically including:

[0104] S5041. Obtain the actual load on multiple tires of the loader;

[0105] S5042. Determine the difference in actual load between multiple tires based on their actual loads.

[0106] S5043. Determine whether the actual load difference is within the preset load difference range;

[0107] S5044. If not, confirm the generation of overturning information and issue an alarm action based on the overturning information.

[0108] It should be noted that the load difference between the left and right wheels during loader operation is a hidden cause of rollover. For example, in mining slope operations, the front wheels experience concentrated load due to the weight of the bucket. If the load difference between the left and right wheels exceeds the safety threshold, it may cause skidding or rollover.

[0109] For example, when the load on the right tire of the loader suddenly increases due to road subsidence, the model calculates that the difference in load between the left and right tires exceeds the safe range, triggering a warning and limiting the vehicle speed. If the difference continues to increase, the system can automatically activate the hydraulic brakes to prevent rollover. Multi-tire load collaborative analysis enables proactive warning of rollover risk. Compared to traditional single-parameter alarms, it can intervene in dangerous operations in advance, thereby reducing the probability of accidents.

[0110] Figure 6 The sixth flowchart of the tire monitoring method for a loader provided in this application embodiment is shown below. Please refer to [link / reference]. Figure 6 As shown, after step 601, which involves obtaining the temperature, tire pressure, deformation, and load of the tires under various operating conditions of the loader, the following steps are also included:

[0111] S602. Generate tire wear data based on temperature, tire pressure, deformation, and load.

[0112] S603. Determine whether the tire wear is within the preset wear range;

[0113] S604. If not, confirm the generation of tire wear information and issue a prompt action based on the tire wear information.

[0114] It should be noted that tire wear is closely related to load, temperature, and deformation. For example, prolonged uneven loading leads to abnormal wear on the tire shoulder, and high temperatures accelerate tread aging. By analyzing the correlation between multiple parameters such as temperature, tire pressure, deformation, and load, the wear rate can be quantified and the remaining life can be predicted, thus avoiding tire blowouts caused by excessive wear and enabling more comprehensive monitoring of tire health.

[0115] For example, in mining operations, frequent impact loads cause blocky wear on the tire tread. The model, combining deformation and temperature data, determines that the wear rate exceeds a threshold, prompting tire replacement. Monitoring only tire pressure might misjudge it as normal wear. Wear monitoring enables preventative maintenance, reduces unplanned downtime, and extends tire life.

[0116] A second aspect of this application provides a tire monitoring device for a loader, comprising:

[0117] The acquisition module is used to acquire the temperature, tire pressure, deformation, and load of the tires of the loader under various working conditions.

[0118] The processing module is used to establish a tire load model based on temperature, tire pressure, deformation, and load; determine the actual load on the tire based on the tire load model; and generate rollover information based on the actual load.

[0119] The tire monitoring device for the loader provided in this application embodiment can execute the above method embodiment. Its specific implementation principle and technical effect can be found in the above method embodiment, and will not be repeated here.

[0120] In one possible implementation, please combine... Figure 7 , Figure 8 and Figure 9 As shown, the acquisition module includes:

[0121] Temperature sensor 11 is used to monitor the temperature of the tire;

[0122] Pressure sensor 12 is used to monitor tire pressure;

[0123] Infrared sensor 13 is used to monitor tire deformation;

[0124] The loader's tire monitoring device also includes a wireless transmission component 20, which is electrically and / or communicatively connected to a temperature sensor 11, a pressure sensor 12, and an infrared sensor 13; the wireless transmission component 20 is also communicatively connected to the vehicle-side control center.

[0125] The loader's tire monitoring device also includes a mounting base 30, which is built into the inner cavity of the tire 40. The mounting base 30 includes a housing 31. The housing 31 is provided with a first recess 311, a second recess 312, a third recess 313, and a fourth recess 314. A temperature sensor 11 is built into the first recess 311. A pressure sensor 12 is built into the second recess 312. An infrared sensor 13 is built into the third recess 313. A wireless transmission component 20 is built into the fourth recess 314.

[0126] It should be noted that in related technologies, tire monitoring usually uses single-sensor measurement, and each sensor needs to be installed separately, which is complicated to operate and requires a lot of space. If the internal installation method is used, the sensor needs to be accurately fixed, and there needs to be a matching device on the rim or tire. If the external installation method is used, it may be damaged by harsh external environments, resulting in low measurement accuracy and sometimes uncontrollable parameters.

[0127] In this embodiment, by providing a first recess 311, a second recess 312, a third recess 313, and a fourth recess 314 on the housing 31, and installing a temperature sensor 11 in the first recess 311, a pressure sensor 12 in the second recess 312, an infrared sensor 13 in the third recess 313, and a wireless transmission component 20 in the fourth recess 314, multiple sensors and the wireless transmission component 20 are integrated into a single module and built into the inner cavity of the tire 40. This not only reduces the complexity of the installation operation but also saves installation space and avoids damage caused by harsh external environments.

[0128] In one possible implementation, please combine... Figure 7 , Figure 8 and Figure 9 As shown, the mounting base 30 is independently set with respect to the tire body; the mounting base 30 is movably set inside the tire cavity; the mounting base 30 also includes a base 32, which is located at the bottom of the housing 31. The base 32 and the housing 31 together form a self-righting structure, and the base 32 is used to maintain the balance of the mounting base 30.

[0129] The third recess 313 and the fourth recess 314 are located on the vertical line of the center of gravity of the mounting base 30; the fourth recess 314 is located at the center of gravity of the mounting base 30.

[0130] In this embodiment, the mounting base 30 is not rigidly connected to the tire 40, and free displacement is achieved through the movable space inside the tire 40. By forming a self-righting structure together with the base 32 and the housing 31, the mounting base 30 can always be located near the lowest point inside the tire 40 and maintain a balanced state during vehicle operation. Regardless of whether the tire 40 deforms due to load or tire pressure changes, the mounting base 30 can automatically adapt to the changes in the geometric shape of the tire 40's inner cavity. For example, when the tire is underinflated, the tire body collapses, causing the tire 40's space to deform. The mounting base 30 sinks to a new lowest point under the action of gravity, ensuring a tight fit with the contact surface and avoiding signal distortion caused by gaps.

[0131] By placing the third recess 313 on the vertical line of the center of gravity of the mounting base 30, the measurement axis of the infrared sensor 13 is aligned with the center line of the tire, thereby reducing measurement deviation. By placing the fourth recess 314 on the vertical line of the center of gravity of the mounting base 30, and placing the fourth recess 314 at the center of gravity of the mounting base 30, the transmission angle of the wireless transmission component 20 remains unchanged, which helps to ensure signal strength and stability.

[0132] A third aspect of this application provides a loader, including: a memory and a processor;

[0133] The memory is used to store computer programs / instructions; the processor is used to implement the methods of the various embodiments described above according to the computer programs / instructions stored in the memory.

[0134] The loader also includes a communication interface. The processor provides computing and control capabilities and can be a GPU, CPU, NPU, MCU, FPGA, etc. Storage devices include internal memory and non-volatile memory. The non-volatile memory stores the computer programs implementing the above methods. Internal memory provides the environment for program startup and execution. The communication interface is used for wired or wireless communication with external terminals.

[0135] A fourth aspect of this application provides a computer-readable storage medium / computer program product, wherein the computer-readable storage medium stores a computer program / computer program product including a computer program, which, when executed by a processor, is used to implement the method as described above.

[0136] The various embodiments or implementation methods described in this specification are presented in a progressive manner. Each embodiment focuses on the differences from other embodiments, and the same or similar parts between the embodiments can be referred to each other.

[0137] It should be noted that the terms "one embodiment," "embodiment," "exemplary embodiment," "some embodiments," etc., mentioned in the specification indicate that the described embodiment may include a specific feature, structure, or characteristic, but not every embodiment necessarily includes that specific feature, structure, or characteristic. Furthermore, such phrases do not necessarily refer to the same embodiment. Moreover, when a specific feature, structure, or characteristic is described in connection with an embodiment, implementing such a feature, structure, or characteristic in conjunction with other embodiments, whether explicitly described or not, is within the knowledge scope of those skilled in the art.

[0138] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A tire monitoring method for a loader, characterized in that, include: Obtain tire temperature, tire pressure, deformation, and load under various operating conditions of the loader; A tire load model is established based on the temperature, tire pressure, deformation, and load. The actual load on the tire is determined based on the tire load model. Based on the actual load, rollover information is generated.

2. The tire monitoring method for a loader according to claim 1, characterized in that, The operating conditions include the loader's travel speed, steering angle, acceleration, and braking pressure; Based on the temperature, tire pressure, and deformation, a tire load model is established, specifically including: Establish a dataset for the driving speed, steering angle, acceleration, braking pressure, temperature, tire pressure, deformation, and load; The dataset is divided into a training subset and a validation subset; Using the driving speed, steering angle, braking pressure, acceleration, temperature, tire pressure, and deformation in the training subset as input variables, and the load in the training subset as output variables, an initial tire load model is established. The initial tire load model is trained using the validation subset to generate the tire load model.

3. The tire monitoring method for a loader according to claim 1, characterized in that, Based on the tire load model, the actual load of the tire is determined, specifically including: Under the condition of obtaining the actual driving speed and actual steering angle of the loader, the actual temperature, actual tire pressure and actual deformation of the tires; The actual driving speed, actual steering angle, actual acceleration, actual braking pressure, actual temperature, actual tire pressure, and actual deformation are input into the tire load model to generate the actual load.

4. The tire monitoring method for a loader according to claim 1, characterized in that, Based on the actual load, rollover information is generated, specifically including: Determine whether the actual load is within the preset load range; If not, confirm the generation of the overturning information and issue an alarm action based on the overturning information.

5. The tire monitoring method for a loader according to claim 1, characterized in that, Based on the actual load, rollover information is generated, specifically including: Obtain the actual load on the plurality of tires of the loader; Based on the actual loads of the multiple tires, determine the actual load difference of the multiple tires; Determine whether the actual load difference is within the preset load difference range; If not, confirm the generation of the overturning information and issue an alarm action based on the overturning information.

6. The tire monitoring method for a loader according to any one of claims 1-5, characterized in that, After obtaining the tire temperature, tire pressure, deformation, and load under various operating conditions of the loader, the following is also included: The tire wear amount is generated based on the temperature, tire pressure, deformation, and load. Determine whether the tire wear is within a preset wear range; If not, confirm the generation of tire wear information and issue a prompt action based on the tire wear information.

7. A tire monitoring device for a loader, characterized in that, include: The acquisition module is used to acquire the temperature, tire pressure, deformation, and load of the tires of the loader under various working conditions. The processing module is used to establish a tire load model based on the temperature, tire pressure, deformation, and load; and to determine the actual load of the tire based on the tire load model. Based on the actual load, rollover information is generated.

8. The tire monitoring device for a loader according to claim 7, characterized in that, The acquisition module includes: Temperature sensor used to monitor tire temperature; Pressure sensors are used to monitor tire pressure. Infrared sensors are used to monitor tire deformation. The tire monitoring device of the loader also includes a wireless transmission component, which is electrically and / or communicatively connected to the temperature sensor, the pressure sensor and the infrared sensor; the wireless transmission component is communicatively connected to the vehicle control center. The tire monitoring device of the loader also includes a mounting base, which is built into the inner cavity of the tire; the mounting base includes a housing; the housing is provided with a first recess, a second recess, a third recess and a fourth recess; the temperature sensor is built into the first recess; the pressure sensor is built into the second recess; the infrared sensor is built into the third recess; and the wireless transmission component is built into the fourth recess.

9. The tire monitoring device for a loader according to claim 8, characterized in that, The mounting base is independently disposed from the tire body; the mounting base is movably disposed within the tire cavity; the mounting base also includes a base, which is disposed at the bottom of the housing, and the base and the housing together form a self-righting structure, the base being used to maintain the balance of the mounting base; The third and fourth recesses are located on the vertical line of the center of gravity of the mounting base; the fourth recess is located at the center of gravity of the mounting base.

10. A loader, characterized in that, include: Memory, processor; The memory is used to store computer programs / instructions; The processor is used to implement the tire monitoring method for a loader as described in any one of claims 1 to 6, according to the computer program / instructions stored in the memory.

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