Oil cylinder temperature control method and system for mine vehicle

Abstract

The invention relates to the technical field of mining equipment, and discloses an oil cylinder temperature control method and system for a mine vehicle, and the system is characterized in that a first radiator is arranged between a lifting reversing valve and an oil tank; one end of the second radiator is communicated with the first radiator oil outlet, and the other end is communicated with the oil tank oil return port; the sensor module comprises a temperature sensor and a wind speed sensor; the control module comprises an acquisition unit for judging whether to start pre-cooling heat dissipation or not; when it is judged that pre-cooling heat dissipation is started, the processing unit obtains a predicted temperature data set to determine the operation power of the second heat dissipation device during pre-cooling heat dissipation, and pre-cooling heat dissipation is conducted; the judgment unit judges whether the operation power of the second radiator is adjusted or not; and the adjusting unit determines the influence factor and the adjusting coefficient to adjust the operating power, and controls the second radiator to operate at the adjusted operating power. The temperature control capability of the hydraulic system of the mine vehicle is improved, and the aging and fault risks of the hydraulic element caused by high temperature are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of mining equipment, and in particular to a method and system for controlling the temperature of an oil cylinder of a mining vehicle. Background Art

[0002] Mining vehicles are heavy-duty engineering machinery used in mines to complete rock and earth stripping and ore transportation tasks. Their working characteristics are short distance and heavy load. They are usually loaded by large loaders and travel back and forth between mining sites and unloading sites. Traditional mining dump trucks are not equipped with hydraulic oil circuit radiators. In low-temperature solar terms, the impact is not great, but in high-temperature solar terms, the hydraulic oil has been in working condition since the vehicle was started. Due to the increase in ambient temperature and its own heat dissipation capacity, the oil temperature will remain high.

[0003] At present, some mining vehicles are equipped with radiators and temperature sensors, but the hydraulic oil cooling method mainly relies on a single radiator to dissipate the return oil, or the cooling system is started to cool down only when the hydraulic oil temperature reaches a certain threshold. The hydraulic oil temperature will not start to cool down until it reaches the set value, and the temperature change trend cannot be predicted, which leads to heat dissipation lag in high temperature environments, affecting the stability of the hydraulic oil; secondly, the heat dissipation capacity of a single radiator is limited. When faced with long-term high-intensity operations, the heat dissipation efficiency is difficult to meet the needs, resulting in excessively high temperatures in the hydraulic system, accelerating the aging and failure rate of hydraulic components; and the traditional control method does not fully consider external environmental factors, such as the impact of wind speed on the heat dissipation effect, resulting in a relatively passive operation mode of the heat dissipation system, high energy consumption, and lack of intelligent adjustment mechanism.

[0004] Therefore, it is necessary to design a cylinder temperature control method and system for mining vehicles to solve the problems existing in the current technology. Summary of the invention

[0005] In view of this, the present invention proposes a cylinder temperature control method and system for mining vehicles, aiming to solve the problem that the current hydraulic oil heat dissipation is difficult to meet the demand, resulting in excessively high temperature of the hydraulic system.

[0006] In one aspect, the present invention provides a cylinder temperature control system for a mining vehicle, comprising: A first radiator is arranged between the lifting reversing valve and the oil tank, and is used to dissipate the heat of the hydraulic oil in the oil return pipe of the lifting cylinder; A second radiator, wherein the oil inlet of the second radiator is connected to the oil outlet of the first radiator, and the oil outlet of the second radiator is connected to the oil return port of the oil tank; The sensor module includes a temperature sensor and a wind speed sensor, wherein the temperature sensor and the wind speed sensor are both arranged on the mining vehicle, and a plurality of the temperature sensor and the wind speed sensor are arranged; A control module connected to the first radiator, the second radiator and the sensor module, the control module comprising a collection unit, a processing unit, a judgment unit and an adjustment unit; The acquisition unit is configured to acquire temperature data of all the temperature sensors to establish a temperature data set, and to acquire a hydraulic oil temperature interval and a historical actual temperature interval of the temperature sensor when the first radiator is running at rated power, determine a temperature judgment range according to the hydraulic oil temperature interval and the historical actual temperature interval, obtain a current mean temperature according to the temperature data set, compare the mean temperature with the right boundary of the temperature judgment range, and determine whether to start pre-cooling and heat dissipation according to the comparison result; When the acquisition unit determines to turn on the pre-cooling and heat dissipation, the processing unit records the temperature data of all the temperature sensors within a preset period of time to establish a first observation data set, inputs the observation data set into the LSTM model, obtains a predicted temperature data set, determines the operating power of the second radiator during pre-cooling and heat dissipation according to the predicted temperature data set, and performs pre-cooling and heat dissipation; After the pre-cooling and heat dissipation is turned on, the judgment unit collects a second observation data set after the preset period of time, and judges whether to adjust the operating power of the second radiator according to the second observation data set; When the judgment unit determines to adjust the operating power of the second radiator, the adjustment unit determines the influencing factor according to the second observation data set and the wind speed data of all the wind speed sensors, determines the adjustment coefficient according to the influencing factor to adjust the operating power, and controls the second radiator to operate at the adjusted operating power.

[0007] Furthermore, when the acquisition unit determines the temperature judgment range according to the hydraulic oil temperature range and the historical actual temperature range, it includes: The acquisition unit compares the left boundary of the hydraulic oil temperature interval with the left boundary of the historical actual temperature interval, and selects the data with a smaller value as the left boundary of the temperature judgment range; Compare the right boundary of the hydraulic oil temperature interval with the right boundary of the historical actual temperature interval, and select the data with a larger value as the right boundary of the temperature judgment range; The left boundary and the right boundary of the temperature judgment range are combined to form the temperature judgment range.

[0008] Furthermore, when the acquisition unit determines whether to start pre-cooling and heat dissipation according to the comparison result, it includes: When the mean temperature is greater than the right boundary of the temperature judgment range, the acquisition unit determines to start the pre-cooling and heat dissipation, and the pre-cooling and heat dissipation includes running the first radiator at rated power and starting the second radiator; When the mean temperature is less than or equal to the right boundary of the temperature judgment range, the acquisition unit determines not to start the pre-cooling heat dissipation, and compares the mean temperature with the left boundary of the temperature judgment range, and determines the operating power of the first radiator during basic heat dissipation according to the comparison result.

[0009] Further, when determining the operating power of the first radiator during basic heat dissipation according to the comparison result, it includes: When the mean temperature is less than the left boundary of the temperature judgment range, the acquisition unit controls the first radiator to operate at a first power; when the mean temperature is greater than or equal to the left boundary of the temperature judgment range and less than or equal to the right boundary of the temperature judgment range, the acquisition unit controls the first radiator to operate at a rated power, and the first power is less than the rated power.

[0010] Furthermore, when the processing unit inputs the observed data set into the LSTM model to obtain the predicted temperature data set, it includes: The processing unit pre-builds the forget gate of the LSTM model: ; Input Gate: ; ; Cell status update: ; Output Gate: ; ; in, represents the output of the forget gate, Represents the weight matrix of the forget gate, with a value range of [-1, 1], Indicates the hidden state at the previous moment, Represents input data, represents the bias term of the forget gate, σ is the sigmoid function, represents the input gate output, Represents the candidate cell state, with a value range of (-1, 1). Represents the weight matrix of the input gate, with a value range of [-1, 1], The weight matrix representing the candidate cell state has a value range of [-1, 1], , Represent the bias terms of the input gate and candidate cell state, respectively. Indicates the cell state at the current moment, Indicates the cell state at the previous moment, represents the output gate output, Represents the forecast data, Represents the weight matrix of the output gate, with a value range of [-1, 1], represents the bias term of the output gate; The processing unit divides the temperature data of each temperature sensor in the first observation data set into windows according to time series as input data, obtains predicted data of the temperature sensor, and integrates all the predicted data to obtain the predicted temperature data set.

[0011] Further, when the processing unit determines the operating power of the second radiator during pre-cooling and heat dissipation according to the predicted temperature data set, it includes: The processing unit obtains a predicted temperature mean value according to the predicted temperature data set, compares the predicted temperature mean value with a first preset temperature value and a second preset temperature value respectively, and determines the operating power of the second radiator according to the comparison result; the first preset temperature value is less than the second preset temperature value; When the predicted temperature average is less than or equal to the first preset temperature value, the operating power of the second radiator is determined to be the first power of the second radiator; when the predicted temperature average is greater than the first preset temperature value and less than or equal to the second preset temperature, the operating power of the second radiator is determined to be the second power of the second radiator; when the predicted temperature average is greater than the second preset temperature value, the operating power of the second radiator is determined to be the third power of the second radiator; the first power of the second radiator is less than the second power of the second radiator, and the second power of the second radiator is less than the third power of the second radiator.

[0012] Further, when the judgment unit judges whether to adjust the operating power of the second radiator according to the second observation data set, it includes: The judgment unit obtains a second mean temperature according to the second observation data set, compares the second mean temperature with a right boundary of the temperature judgment range, and judges whether to adjust the operating power of the second radiator according to the comparison result; When the second average temperature is less than or equal to the right boundary of the temperature judgment range, determining not to adjust the operating power of the second radiator; When the second average temperature is greater than the right boundary of the temperature judgment range, it is determined that the operating power of the second radiator is to be adjusted.

[0013] Further, the adjustment unit determines the influence factor according to the second observation data set and the wind speed data of all the wind speed sensors, and determines the adjustment coefficient according to the influence factor to adjust the operating power, including: The adjustment unit obtains the temperature change rate of each temperature sensor according to the second observation data set, and determines the wind speed average according to the wind speed data of all the wind speed sensors; obtains the distance between each temperature sensor and the second radiator, and determines the weight coefficient of each temperature change rate according to the distance:

[0014] Wherein, Zi represents the weight coefficient of the temperature change rate of the i-th temperature sensor, w is the standard deviation of all distances; Li represents the distance between the i-th temperature sensor and the second radiator; Calculate the overall temperature change data:

[0015] Wherein, n represents the total number of temperature change rates in the second observation data set, and Si represents the i-th temperature change rate in the second observation data set; Determine the influencing factor according to the overall temperature change data and the wind speed mean;

[0016] Among them, Y represents the influencing factor, W0 represents the normalized result of the overall temperature change data, α and β are weights, and α+β=1, and F0 represents the normalized result of the mean wind speed; The impact factor is compared with the historical impact factor in the historical adjustment record, and the adjustment coefficient is determined according to the comparison result to adjust the operating power of the second radiator. The historical adjustment record includes several historical impact factors and several historical adjustment coefficients, and each of the historical impact factors corresponds to a historical adjustment coefficient.

[0017] Furthermore, when the adjustment unit determines the adjustment coefficient according to the comparison result to adjust the operating power of the second radiator, it includes: When there is data in the historical adjustment record where the historical impact factor is the same as the impact factor, the adjustment unit uses the historical adjustment coefficient corresponding to the historical impact factor as the adjustment coefficient to adjust the operating power of the second radiator; When all historical impact factors in the historical adjustment record are different from the impact factor, the historical adjustment coefficient corresponding to the historical impact factor closest to the impact factor is selected as the basic adjustment coefficient, and the historical adjustment coefficient corresponding to the historical impact factor with a difference of 10% from the impact factor is selected to calibrate the basic adjustment coefficient, and the adjustment coefficient is obtained to adjust the operating power of the second radiator; The adjusted operating power is the product of the operating power of the second radiator and the adjustment coefficient.

[0018] Compared with the prior art, the beneficial effects of the present invention are as follows: by setting a series heat dissipation structure of the first radiator and the second radiator, the hydraulic oil is efficiently dissipated in stages. Compared with the heat dissipation mode of a single radiator, the hydraulic oil temperature can be reduced more evenly and the heat dissipation efficiency can be improved. Multi-point data collection of temperature sensors and wind speed sensors is introduced, and temperature prediction analysis is performed in combination with the LSTM (Long Short-Term Memory) model, so that pre-cooling and heat dissipation can be started in advance before the hydraulic oil temperature reaches a high temperature, thereby avoiding the risk of excessive oil temperature due to delayed response in the traditional heat dissipation system. By analyzing historical data and determining a reasonable temperature judgment range, the accuracy of pre-cooling and heat dissipation is improved; after the pre-cooling and heat dissipation is turned on, the second observation data set is collected in real time, and the influence factor is calculated in combination with the data of the wind speed sensor, and the operating power of the second radiator is dynamically adjusted, so that it can adaptively adjust the heat dissipation intensity according to environmental conditions and oil temperature change trends, which not only ensures the heat dissipation effect, but also avoids unnecessary energy consumption, and improves the intelligence level and energy utilization efficiency of the system. The temperature control ability of the hydraulic system of mining vehicles is improved, and the risk of aging and failure of hydraulic components caused by high temperature is reduced.

[0019] On the other hand, the present application also provides a method for controlling the temperature of an oil cylinder for a mining vehicle, which is applied to the above-mentioned oil cylinder temperature control system for a mining vehicle, comprising: Collect temperature data of all temperature sensors to establish a temperature data set, and collect the hydraulic oil temperature range and the historical actual temperature range of the temperature sensor when the first radiator is running at rated power, determine the temperature judgment range according to the hydraulic oil temperature range and the historical actual temperature range, obtain the current mean temperature according to the temperature data set, compare the mean temperature with the right boundary of the temperature judgment range, and judge whether to start pre-cooling and heat dissipation according to the comparison result; When it is determined that the pre-cooling and heat dissipation is turned on, the temperature data of all the temperature sensors within a preset period are recorded to establish a first observation data set, the observation data set is input into the LSTM model to obtain a predicted temperature data set, the operating power of the second radiator during pre-cooling and heat dissipation is determined according to the predicted temperature data set, and pre-cooling and heat dissipation is performed; After the pre-cooling and heat dissipation is started, a second observation data set is collected after the preset period of time, and it is determined whether to adjust the operating power of the second radiator according to the second observation data set; When it is determined to adjust the operating power of the second radiator, an influencing factor is determined based on the second observation data set and the wind speed data of all the wind speed sensors, an adjustment coefficient is determined based on the influencing factor to adjust the operating power, and the second radiator is controlled to operate at the adjusted operating power.

[0020] It is understandable that the above-mentioned oil cylinder temperature control method and system for mining vehicles have the same beneficial effects, which will not be described in detail here. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings: Figure 1 A structural block diagram of a cylinder temperature control system for a mining vehicle provided by an embodiment of the present invention; Figure 2 A flow chart of a method for controlling the oil cylinder temperature of a mining vehicle provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0022] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, in the absence of conflict, the embodiments of the present invention and the features described in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0023] In some embodiments of the present application, see Figure 1 As shown, a cylinder temperature control system for a mining vehicle comprises: The first radiator is arranged between the lifting reversing valve and the oil tank, and is used for dissipating the heat of the hydraulic oil in the oil return pipe of the lifting cylinder.

[0024] The second radiator, the oil inlet of the second radiator is communicated with the oil outlet of the first radiator, and the oil outlet of the second radiator is communicated with the oil return port of the oil tank.

[0025] The sensor module includes a temperature sensor and a wind speed sensor. Both the temperature sensor and the wind speed sensor are arranged on the mining vehicle, and a plurality of both are arranged.

[0026] The control module is connected with the first radiator, the second radiator and the sensor module, and the control module includes a collection unit, a processing unit, a judgment unit and an adjustment unit.

[0027] The acquisition unit is configured to collect temperature data from all temperature sensors to establish a temperature data set, and to collect the hydraulic oil temperature range and the historical actual temperature range of the temperature sensor when the first radiator is operating at rated power, determine the temperature judgment range based on the hydraulic oil temperature range and the historical actual temperature range, obtain the current mean temperature based on the temperature data set, compare the mean temperature with the right boundary of the temperature judgment range, and determine whether to start pre-cooling and heat dissipation based on the comparison result.

[0028] When the acquisition unit determines to turn on pre-cooling and heat dissipation, the processing unit records the temperature data of all temperature sensors within a preset time period to establish a first observation data set, inputs the observation data set into the LSTM model, obtains a predicted temperature data set, determines the operating power of the second radiator during pre-cooling and heat dissipation according to the predicted temperature data set, and performs pre-cooling and heat dissipation.

[0029] After the pre-cooling and heat dissipation is turned on, the judgment unit collects a second observation data set after a preset period of time, and judges whether to adjust the operating power of the second radiator according to the second observation data set.

[0030] When the judgment unit determines to adjust the operating power of the second radiator, the adjustment unit determines the influencing factor based on the second observation data set and the wind speed data of all wind speed sensors, determines the adjustment coefficient based on the influencing factor to adjust the operating power, and controls the second radiator to operate at the adjusted operating power.

[0031] Specifically, a heat dissipation method in which the first radiator and the second radiator are connected in series is adopted. The first radiator can adopt air cooling and the second radiator adopts liquid cooling. The first radiator is arranged between the lifting reversing valve and the oil tank, and is mainly responsible for initially reducing the temperature of the hydraulic oil in the return oil pipe of the lifting cylinder; the oil inlet of the second radiator is connected to the oil outlet of the first radiator. When only the first radiator is turned on, the second radiator does not work, and the hydraulic oil flows out of the first radiator and directly flows into the oil tank. When both the first radiator and the second radiator are working, the hydraulic oil flows out of the first radiator into the second radiator and then flows into the oil tank. Compared with the traditional single radiator structure, the dual radiator design can improve the heat dissipation efficiency and delay the rapid rise of the hydraulic oil temperature. The sensor module includes multiple temperature sensors and wind speed sensors, which are distributed at different positions of the mining vehicle to continuously collect the temperature and ambient wind speed data of the hydraulic system. The control module is responsible for data acquisition, processing, judgment and adjustment. The acquisition unit collects data from all temperature sensors, establishes a temperature data set, and calculates the temperature judgment range in combination with the temperature range of the hydraulic oil and the historical temperature changes of the first radiator. If the current mean temperature is close to the upper limit of the range, determine whether to start pre-cooling and heat dissipation in advance to avoid the lag problem of starting cooling after the temperature is too high. After the pre-cooling and heat dissipation is turned on, the LSTM (long short-term memory) model is further used to analyze the temperature change trend over the past period of time, predict the future changes in the hydraulic oil temperature, and calculate the optimal operating power of the second radiator accordingly. This method based on predictive control enables the system to actively adjust the heat dissipation intensity before the temperature reaches the critical value, thereby improving the accuracy of temperature control. After the pre-cooling and heat dissipation is started, the judgment unit will collect the second observation data set after a preset period of time, analyze the current temperature control effect, and decide whether the power of the second radiator needs to be adjusted. When it is determined that adjustment is required, the adjustment unit will calculate the influencing factor based on the data of the wind speed sensor, determine the adjustment coefficient according to the actual environmental conditions, and then optimize the operating power of the second radiator.

[0032] It is understandable that on the basis of the traditional mining vehicle hydraulic oil cooling system, a multi-level cooling structure is adopted to improve the heat dissipation capacity, and the temperature and ambient wind speed are monitored in real time through the sensor network to provide accurate data support for heat dissipation control. The introduction of the LSTM model for temperature trend prediction can intervene in advance to avoid the risk of excessive oil temperature caused by temperature control lag. By adaptively adjusting the operating power of the second radiator, intelligent and energy-saving temperature control management is realized, which effectively reduces the operating temperature of the hydraulic system and reduces equipment loss caused by high temperature.

[0033] In some embodiments of the present application, when the acquisition unit determines the temperature judgment range according to the hydraulic oil temperature range and the historical actual temperature range, it includes: The acquisition unit compares the left boundary of the hydraulic oil temperature range with the left boundary of the historical actual temperature range, and selects the data with the smaller value as the left boundary of the temperature judgment range.

[0034] The right boundary of the hydraulic oil temperature range is compared with the right boundary of the historical actual temperature range, and the data with the larger value is selected as the right boundary of the temperature judgment range.

[0035] The left boundary and the right boundary of the temperature judgment range are combined to form the temperature judgment range.

[0036] In some embodiments of the present application, when the acquisition unit determines whether to start pre-cooling and heat dissipation according to the comparison result, it includes: When the mean temperature is greater than the right boundary of the temperature judgment range, the acquisition unit determines to start pre-cooling and heat dissipation, and the pre-cooling and heat dissipation includes running the first radiator at rated power and starting the second radiator.

[0037] When the mean temperature is less than or equal to the right boundary of the temperature judgment range, the acquisition unit determines not to start pre-cooling and heat dissipation, and compares the mean temperature with the left boundary of the temperature judgment range, and determines the operating power of the first radiator during basic heat dissipation according to the comparison result.

[0038] In some embodiments of the present application, when determining the operating power of the first radiator during basic heat dissipation according to the comparison result, it includes: when the mean temperature is less than the left boundary of the temperature judgment range, the acquisition unit controls the first radiator to operate at the first power. When the mean temperature is greater than or equal to the left boundary of the temperature judgment range and less than or equal to the right boundary of the temperature judgment range, the acquisition unit controls the first radiator to operate at the rated power, and the first power is less than the rated power.

[0039] It is understandable that by optimizing the method for determining the temperature judgment range, it can dynamically adapt to different working conditions, ensuring that the cooling system can accurately control the hydraulic oil temperature under various environmental conditions. According to the comparison between the temperature judgment range and the current mean temperature, it is decided whether to turn on pre-cooling and cooling to avoid excessive oil temperature due to delayed response and improve cooling efficiency. The power adjustment strategy of basic cooling is further refined, so that the first radiator can flexibly adjust the operating power according to the actual temperature requirements, which not only ensures the cooling effect, but also reduces unnecessary energy consumption.

[0040] In some embodiments of the present application, when the processing unit inputs the observation data set into the LSTM model to obtain the predicted temperature data set, it includes: The processing unit pre-builds the forget gate of the LSTM model: .

[0041] Input Gate: .

[0042] .

[0043] Cell status update: .

[0044] Output Gate: .

[0045] .

[0046] in, represents the output of the forget gate, Represents the weight matrix of the forget gate, with a value range of [-1, 1], Indicates the hidden state at the previous moment, Represents input data, represents the bias term of the forget gate, σ is the sigmoid function, represents the input gate output, Represents the candidate cell state, with a value range of (-1, 1). Represents the weight matrix of the input gate, with a value range of [-1, 1], The weight matrix representing the candidate cell state has a value range of [-1, 1], , Represent the bias terms of the input gate and candidate cell state, respectively. Indicates the cell state at the current moment, Indicates the cell state at the previous moment, represents the output gate output, Represents the forecast data, Represents the weight matrix of the output gate, with a value range of [-1, 1], Represents the bias term of the output gate.

[0047] The processing unit divides the temperature data of each temperature sensor in the first observation data set into windows according to the time series as input data, obtains the predicted data of the temperature sensor, and integrates all the predicted data to obtain the predicted temperature data set.

[0048] Specifically, the processing unit divides the temperature data of each temperature sensor in the first observation data set into windows according to the time series, that is, a fixed time step (such as the past 10 minutes or 30 minutes) is used as a data window to form the temperature time series input data. Ensure that the LSTM model can capture the trend of temperature changes over time, rather than analyzing the temperature at a certain time point alone. The processing unit inputs the time series data into the pre-trained LSTM model, and the model calculates the predicted temperature data for a period of time in the future (such as 5 minutes or 10 minutes) through the collaborative work of the forget gate, input gate, cell state update and output gate. Since the temperature sensors on the mining vehicle are distributed in different parts, the temperature prediction results of each sensor may be different, so the processing unit integrates the predicted data of all sensors to form the final predicted temperature data set.

[0049] It is understandable that the introduction of the LSTM deep learning model can predict trends based on historical temperature data, thereby dynamically adjusting the hydraulic oil temperature in advance and improving the intelligence and response speed of the cooling system. Compared with the traditional passive control method that relies on setting temperature thresholds, it can predict the temperature rise trend and actively adjust the cooling strategy before the temperature exceeds the limit, thereby avoiding the problem of hydraulic oil overheating caused by cooling lag. By utilizing the long-term dependent learning ability of LSTM, the temperature change pattern of mining vehicles under different working conditions can be comprehensively considered, making the cooling system more adaptable to complex mining operating environments, improving the stability and service life of the hydraulic system, while reducing energy consumption and improving overall operating efficiency.

[0050] In some embodiments of the present application, when the processing unit determines the operating power of the second radiator during pre-cooling and heat dissipation according to the predicted temperature data set, the processing unit obtains a predicted temperature mean value according to the predicted temperature data set, compares the predicted temperature mean value with the first preset temperature value and the second preset temperature value, and determines the operating power of the second radiator according to the comparison result. The first preset temperature value is less than the second preset temperature value.

[0051] Specifically, when the predicted temperature mean is less than or equal to the first preset temperature value, the operating power of the second radiator is determined to be the first power of the second radiator. When the predicted temperature mean is greater than the first preset temperature value and less than or equal to the second preset temperature, the operating power of the second radiator is determined to be the second power of the second radiator. When the predicted temperature mean is greater than the second preset temperature value, the operating power of the second radiator is determined to be the third power of the second radiator. The first power of the second radiator is less than the second power of the second radiator, and the second power of the second radiator is less than the third power of the second radiator.

[0052] It is understandable that the hierarchical control strategy based on the predicted temperature mean enables the operating power of the second radiator to be dynamically adjusted as the future temperature trend changes, avoiding the heat dissipation lag and energy waste caused by the traditional constant power or simple on / off control method. By setting different temperature thresholds, heat dissipation regulation is achieved, so that the hydraulic oil temperature can fluctuate within the optimal range, improving the stability and service life of the hydraulic system. At the same time, the hierarchical heat dissipation strategy effectively reduces energy consumption, reduces unnecessary heat dissipation power consumption, and improves the overall operating efficiency and economy of mining vehicles. Combined with the predictive ability of the LSTM model, adjustments can be made in advance instead of passively responding to temperature changes, enhancing the system's active regulation capabilities.

[0053] In some embodiments of the present application, when the judgment unit judges whether to adjust the operating power of the second radiator based on the second observation data set, it includes: the judgment unit obtains a second mean temperature based on the second observation data set, compares the second mean temperature with the right boundary of the temperature judgment range, and judges whether to adjust the operating power of the second radiator based on the comparison result.

[0054] Specifically, when the second mean temperature is less than or equal to the right boundary of the temperature judgment range, it is determined not to adjust the operating power of the second radiator. When the second mean temperature is greater than the right boundary of the temperature judgment range, it is determined to adjust the operating power of the second radiator.

[0055] In some embodiments of the present application, the adjustment unit determines the influence factor according to the second observation data set and the wind speed data of all wind speed sensors, and when the operating power is adjusted according to the influence factor, the adjustment unit obtains the temperature change rate of each temperature sensor according to the second observation data set, and determines the wind speed average according to the wind speed data of all wind speed sensors. Obtain the distance between each temperature sensor and the second radiator, and determine the weight coefficient of each temperature change rate according to the distance:

[0056] Wherein, Zi represents the weight coefficient of the temperature change rate of the i-th temperature sensor, w is the standard deviation of all distances, and Li represents the distance between the i-th temperature sensor and the second radiator.

[0057] Calculate the overall temperature change data:

[0058] Wherein, n represents the total number of temperature change rates in the second observation data set, and Si represents the i-th temperature change rate in the second observation data set.

[0059] The influencing factors are determined based on the overall temperature change data and the average wind speed.

[0060]

[0061] Among them, Y represents the influencing factor, W0 represents the normalized result of the overall temperature change data, α and β are weights, and α+β=1, and F0 represents the normalized result of the mean wind speed.

[0062] The impact factor is compared with the historical impact factor in the historical adjustment record, and the adjustment coefficient is determined according to the comparison result to adjust the operating power of the second radiator. The historical adjustment record includes several historical impact factors and several historical adjustment coefficients, and each historical impact factor corresponds to a historical adjustment coefficient.

[0063] Specifically, normalization is a way to simplify calculations, that is, to transform a dimensioned expression into a dimensionless expression, thus becoming a scalar. In this embodiment, the current value is subtracted from the minimum value, and then divided by the difference between the maximum value and the minimum value, and the quotient is taken as the normalization result.

[0064] It is understandable that by calculating the temperature change rate, the trend of temperature change can be identified, rather than just making decisions based on single-point temperature data. Combined with wind speed data, the accuracy of heat dissipation power calculation is improved, avoiding unnecessary high-power heat dissipation when the wind speed is high. By comparing historical influencing factors and adjustment coefficients, and using historical experience to optimize power adjustment strategies, the problem of over-adjustment or under-adjustment is avoided, and the stability and adaptability of the cooling system are improved. The heat dissipation power is dynamically adjusted according to the current temperature status, and the adjustment range is optimized through historical data.

[0065] In some embodiments of the present application, when the adjustment unit determines the adjustment coefficient based on the comparison result to adjust the operating power of the second radiator, it includes: when there is data in the historical adjustment record that the historical impact factor is the same as the impact factor, the adjustment unit uses the historical adjustment coefficient corresponding to the historical impact factor as the adjustment coefficient to adjust the operating power of the second radiator. When all historical impact factors in the historical adjustment record are different from the impact factor, the historical adjustment coefficient corresponding to the historical impact factor closest to the impact factor is selected as the basic adjustment coefficient, and the historical adjustment coefficient corresponding to the historical impact factor that is within 10% of the impact factor is selected to calibrate the basic adjustment coefficient to obtain the adjustment coefficient to adjust the operating power of the second radiator. The adjusted operating power is the product of the operating power of the second radiator and the adjustment coefficient. Specifically, Among them, t represents the adjustment coefficient, t0 represents the basic adjustment coefficient, M represents the number of historical impact factors that are within 10% of the impact factor, and tm represents the historical adjustment coefficient corresponding to the mth historical impact factor that is within 10% of the impact factor.

[0066] It is understandable that directly matching the same historical influencing factors ensures the accuracy of the adjustment coefficient and avoids unreasonable fluctuations in heat dissipation power due to error accumulation. When a completely matching influencing factor cannot be found, the nearest neighbor interpolation is not used, but multiple historical adjustment records are combined for fine correction to reduce errors and improve adjustment accuracy. Combined with historical adjustment records, the adjustment of heat dissipation power has memory and learning capabilities, can adapt to temperature changes in different environments and working conditions, and enhance the self-regulation ability of the system. By accumulating the adjustment coefficients of multiple similar influencing factors, the final calculated adjustment coefficient will not undergo mutations, thereby avoiding abrupt power fluctuations during power adjustment and improving the stability of the heat dissipation system.

[0067] In the above embodiment, by setting the series heat dissipation structure of the first radiator and the second radiator, the hydraulic oil is efficiently dissipated in stages. Compared with the heat dissipation method of a single radiator, the hydraulic oil temperature can be reduced more evenly and the heat dissipation efficiency can be improved. The multi-point data collection of the temperature sensor and the wind speed sensor is introduced, and the temperature prediction analysis is performed in combination with the LSTM model. The pre-cooling heat dissipation can be started in advance before the hydraulic oil temperature reaches a high temperature, avoiding the risk of excessive oil temperature due to the delayed response of the traditional heat dissipation system. By analyzing historical data, a reasonable temperature judgment range is determined, and the accuracy of pre-cooling heat dissipation is improved. After the pre-cooling heat dissipation is turned on, the second observation data set is collected in real time, and the influence factor is calculated in combination with the data of the wind speed sensor, and the operating power of the second radiator is dynamically adjusted, so that it can adaptively adjust the heat dissipation intensity according to the environmental conditions and the oil temperature change trend, which not only ensures the heat dissipation effect, but also avoids unnecessary energy consumption, and improves the intelligence level and energy utilization efficiency of the system. The temperature control ability of the hydraulic system of the mining vehicle is improved, and the aging and failure risks of hydraulic components caused by high temperature are reduced.

[0068] In another preferred embodiment based on the above embodiment, refer to Figure 2 As shown, this embodiment provides a method for controlling the temperature of a cylinder of a mining vehicle, which is applied to the above-mentioned cylinder temperature control system for a mining vehicle, and includes: S100: Collect temperature data from all temperature sensors to establish a temperature data set, and collect the hydraulic oil temperature range and the historical actual temperature range of the temperature sensor when the first radiator is running at rated power, determine the temperature judgment range according to the hydraulic oil temperature range and the historical actual temperature range, obtain the current mean temperature according to the temperature data set, compare the mean temperature with the right boundary of the temperature judgment range, and determine whether to start pre-cooling and heat dissipation according to the comparison result.

[0069] S200: When it is determined to turn on pre-cooling and heat dissipation, the temperature data of all temperature sensors within a preset time period are recorded to establish a first observation data set, the observation data set is input into the LSTM model to obtain a predicted temperature data set, the operating power of the second radiator during pre-cooling and heat dissipation is determined according to the predicted temperature data set, and pre-cooling and heat dissipation is performed.

[0070] S300: After the pre-cooling and heat dissipation is started, a second observation data set is collected after a preset period of time, and it is determined whether to adjust the operating power of the second radiator according to the second observation data set.

[0071] S400: When it is determined to adjust the operating power of the second radiator, an influencing factor is determined according to the second observation data set and the wind speed data of all wind speed sensors, an adjustment coefficient is determined according to the influencing factor to adjust the operating power, and the second radiator is controlled to operate at the adjusted operating power.

[0072] It is understandable that by setting up the series heat dissipation structure of the first radiator and the second radiator, the hydraulic oil can be efficiently dissipated in stages. Compared with the heat dissipation method of a single radiator, the hydraulic oil temperature can be reduced more evenly and the heat dissipation efficiency can be improved. Multi-point data collection of temperature sensors and wind speed sensors is introduced, and the temperature prediction analysis is performed in combination with the LSTM (Long Short-Term Memory) model, so that pre-cooling and heat dissipation can be started in advance before the hydraulic oil temperature reaches a high temperature, avoiding the risk of excessive oil temperature due to delayed response of the traditional heat dissipation system. By analyzing historical data, a reasonable temperature judgment range is determined, and the accuracy of pre-cooling and heat dissipation is improved. After the pre-cooling and heat dissipation is turned on, the second observation data set is collected in real time, and the influencing factor is calculated in combination with the data of the wind speed sensor, and the operating power of the second radiator is dynamically adjusted, so that it can adaptively adjust the heat dissipation intensity according to the environmental conditions and the trend of oil temperature changes, which not only ensures the heat dissipation effect, but also avoids unnecessary energy consumption, and improves the intelligence and energy utilization efficiency of the system. The temperature control ability of the hydraulic system of mining vehicles is improved, and the aging and failure risks of hydraulic components caused by high temperature are reduced.

[0073] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0074] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0075] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0076] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0077] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A cylinder temperature control system for a mining vehicle, characterized in that: include: A first radiator is arranged between the lifting reversing valve and the oil tank, and is used to dissipate the heat of the hydraulic oil in the oil return pipe of the lifting cylinder; A second radiator, wherein the oil inlet of the second radiator is connected to the oil outlet of the first radiator, and the oil outlet of the second radiator is connected to the oil return port of the oil tank; The sensor module includes a temperature sensor and a wind speed sensor, wherein the temperature sensor and the wind speed sensor are both arranged on the mining vehicle, and a plurality of the temperature sensor and the wind speed sensor are arranged; A control module connected to the first radiator, the second radiator and the sensor module, the control module comprising a collection unit, a processing unit, a judgment unit and an adjustment unit; The acquisition unit is configured to acquire temperature data of all the temperature sensors to establish a temperature data set, and to acquire a hydraulic oil temperature interval and a historical actual temperature interval of the temperature sensor when the first radiator is running at rated power, determine a temperature judgment range according to the hydraulic oil temperature interval and the historical actual temperature interval, obtain a current mean temperature according to the temperature data set, compare the mean temperature with the right boundary of the temperature judgment range, and determine whether to start pre-cooling and heat dissipation according to the comparison result; When the acquisition unit determines to turn on the pre-cooling and heat dissipation, the processing unit records the temperature data of all the temperature sensors within a preset period of time to establish a first observation data set, inputs the observation data set into the LSTM model, obtains a predicted temperature data set, determines the operating power of the second radiator during pre-cooling and heat dissipation according to the predicted temperature data set, and performs pre-cooling and heat dissipation; After the pre-cooling and heat dissipation is turned on, the judgment unit collects a second observation data set after the preset period of time, and judges whether to adjust the operating power of the second radiator according to the second observation data set; When the judgment unit determines to adjust the operating power of the second radiator, the adjustment unit determines the influencing factor according to the second observation data set and the wind speed data of all the wind speed sensors, determines the adjustment coefficient according to the influencing factor to adjust the operating power, and controls the second radiator to operate at the adjusted operating power.

2. The oil cylinder temperature control system for mining vehicles according to claim 1, characterized in that: When the acquisition unit determines the temperature judgment range according to the hydraulic oil temperature range and the historical actual temperature range, it includes: The acquisition unit compares the left boundary of the hydraulic oil temperature interval with the left boundary of the historical actual temperature interval, and selects the data with a smaller value as the left boundary of the temperature judgment range; Compare the right boundary of the hydraulic oil temperature interval with the right boundary of the historical actual temperature interval, and select the data with a larger value as the right boundary of the temperature judgment range; The left boundary and the right boundary of the temperature judgment range are combined to form the temperature judgment range.

3. The oil cylinder temperature control system for mining vehicles according to claim 2, characterized in that: When the acquisition unit determines whether to start pre-cooling and heat dissipation according to the comparison result, it includes: When the mean temperature is greater than the right boundary of the temperature judgment range, the acquisition unit determines to start the pre-cooling and heat dissipation, and the pre-cooling and heat dissipation includes running the first radiator at rated power and starting the second radiator; When the mean temperature is less than or equal to the right boundary of the temperature judgment range, the acquisition unit determines not to start the pre-cooling heat dissipation, and compares the mean temperature with the left boundary of the temperature judgment range, and determines the operating power of the first radiator during basic heat dissipation according to the comparison result.

4. The oil cylinder temperature control system for mining vehicles according to claim 3, characterized in that: Determining the operating power of the first radiator during basic heat dissipation according to the comparison result includes: When the mean temperature is less than the left boundary of the temperature judgment range, the acquisition unit controls the first radiator to operate at a first power; when the mean temperature is greater than or equal to the left boundary of the temperature judgment range and less than or equal to the right boundary of the temperature judgment range, the acquisition unit controls the first radiator to operate at a rated power, and the first power is less than the rated power.

5. The oil cylinder temperature control system for mining vehicles according to claim 4, characterized in that: When the processing unit inputs the observed data set into the LSTM model to obtain the predicted temperature data set, it includes: The processing unit pre-builds the forget gate of the LSTM model: ； Input Gate: ； ； Cell status update: ； Output Gate: ； ； in, represents the output of the forget gate, Represents the weight matrix of the forget gate, with a value range of [-1, 1], Indicates the hidden state at the previous moment, Represents input data, represents the bias term of the forget gate, σ is the sigmoid function, represents the input gate output, Represents the candidate cell state, with a value range of (-1, 1). Represents the weight matrix of the input gate, with a value range of [-1, 1], The weight matrix representing the candidate cell state has a value range of [-1, 1], , Represent the bias terms of the input gate and candidate cell state, respectively. Indicates the cell state at the current moment, Indicates the cell state at the previous moment, represents the output gate output, Represents the forecast data, Represents the weight matrix of the output gate, with a value range of [-1, 1], Represents the bias term of the output gate; The processing unit divides the temperature data of each temperature sensor in the first observation data set into windows according to time series as input data, obtains predicted data of the temperature sensor, and integrates all the predicted data to obtain the predicted temperature data set.

6. The oil cylinder temperature control system for mining vehicles according to claim 5, characterized in that: When the processing unit determines the operating power of the second radiator during pre-cooling and heat dissipation according to the predicted temperature data set, it includes: The processing unit obtains a predicted temperature mean value according to the predicted temperature data set, compares the predicted temperature mean value with a first preset temperature value and a second preset temperature value respectively, and determines the operating power of the second radiator according to the comparison result; the first preset temperature value is less than the second preset temperature value; When the predicted temperature average is less than or equal to the first preset temperature value, the operating power of the second radiator is determined to be the first power of the second radiator; when the predicted temperature average is greater than the first preset temperature value and less than or equal to the second preset temperature, the operating power of the second radiator is determined to be the second power of the second radiator; when the predicted temperature average is greater than the second preset temperature value, the operating power of the second radiator is determined to be the third power of the second radiator; the first power of the second radiator is less than the second power of the second radiator, and the second power of the second radiator is less than the third power of the second radiator.

7. The oil cylinder temperature control system for a mining vehicle according to claim 6, characterized in that: When the judging unit judges whether to adjust the operating power of the second radiator according to the second observation data set, it includes: The judgment unit obtains a second mean temperature according to the second observation data set, compares the second mean temperature with a right boundary of the temperature judgment range, and judges whether to adjust the operating power of the second radiator according to the comparison result; When the second average temperature is less than or equal to the right boundary of the temperature judgment range, determining not to adjust the operating power of the second radiator; When the second average temperature is greater than the right boundary of the temperature judgment range, it is determined that the operating power of the second radiator is to be adjusted.

8. The oil cylinder temperature control system for a mining vehicle according to claim 7, characterized in that: The adjusting unit determines the influence factor according to the second observation data set and the wind speed data of all the wind speed sensors, and determines the adjustment coefficient according to the influence factor to adjust the operating power, including: The adjustment unit obtains the temperature change rate of each temperature sensor according to the second observation data set, and determines the wind speed average according to the wind speed data of all the wind speed sensors; obtains the distance between each temperature sensor and the second radiator, and determines the weight coefficient of each temperature change rate according to the distance: ； Wherein, Zi represents the weight coefficient of the temperature change rate of the i-th temperature sensor, w is the standard deviation of all distances; Li represents the distance between the i-th temperature sensor and the second radiator; Calculate the overall temperature change data: ； Wherein, n represents the total number of temperature change rates in the second observation data set, and Si represents the i-th temperature change rate in the second observation data set; Determine the influencing factor according to the overall temperature change data and the wind speed mean; ； Among them, Y represents the influencing factor, W0 represents the normalized result of the overall temperature change data, α and β are weights, and α+β=1, and F0 represents the normalized result of the mean wind speed; The impact factor is compared with the historical impact factor in the historical adjustment record, and the adjustment coefficient is determined according to the comparison result to adjust the operating power of the second radiator. The historical adjustment record includes several historical impact factors and several historical adjustment coefficients, and each of the historical impact factors corresponds to a historical adjustment coefficient.

9. The oil cylinder temperature control system for a mining vehicle according to claim 8, characterized in that: When the adjustment unit determines the adjustment coefficient according to the comparison result to adjust the operating power of the second radiator, it includes: When there is data in the historical adjustment record where the historical impact factor is the same as the impact factor, the adjustment unit uses the historical adjustment coefficient corresponding to the historical impact factor as the adjustment coefficient to adjust the operating power of the second radiator; When all historical impact factors in the historical adjustment record are different from the impact factor, the historical adjustment coefficient corresponding to the historical impact factor closest to the impact factor is selected as the basic adjustment coefficient, and the historical adjustment coefficient corresponding to the historical impact factor with a difference of 10% from the impact factor is selected to calibrate the basic adjustment coefficient, and the adjustment coefficient is obtained to adjust the operating power of the second radiator; The adjusted operating power is the product of the operating power of the second radiator and the adjustment coefficient.

10. A method for controlling the temperature of a cylinder of a mining vehicle, applied to the cylinder temperature control system for a mining vehicle as claimed in any one of claims 1 to 9, characterized in that: include: Collect temperature data of all temperature sensors to establish a temperature data set, and collect the hydraulic oil temperature range and the historical actual temperature range of the temperature sensor when the first radiator is running at rated power, determine the temperature judgment range according to the hydraulic oil temperature range and the historical actual temperature range, obtain the current mean temperature according to the temperature data set, compare the mean temperature with the right boundary of the temperature judgment range, and judge whether to start pre-cooling and heat dissipation according to the comparison result; When it is determined that the pre-cooling and heat dissipation is turned on, the temperature data of all the temperature sensors within a preset period are recorded to establish a first observation data set, the observation data set is input into the LSTM model to obtain a predicted temperature data set, the operating power of the second radiator during pre-cooling and heat dissipation is determined according to the predicted temperature data set, and pre-cooling and heat dissipation is performed; After the pre-cooling and heat dissipation is started, a second observation data set is collected after the preset period of time, and it is determined whether to adjust the operating power of the second radiator according to the second observation data set; When it is determined to adjust the operating power of the second radiator, an influencing factor is determined based on the second observation data set and the wind speed data of all the wind speed sensors, an adjustment coefficient is determined based on the influencing factor to adjust the operating power, and the second radiator is controlled to operate at the adjusted operating power.

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