A laser radar intelligent temperature control and cooling system

Abstract

The present invention relates to the field of laser radar technology, and discloses a laser radar intelligent temperature control and heat dissipation system, which includes: a laser radar body, a heat dissipation module and a control module; the control module is connected to the heat dissipation module; the acquisition unit is configured to determine the basic heat dissipation parameters of the heat dissipation module based on the analysis result; the first judgment unit is configured to determine whether to optimize the basic heat dissipation parameters according to the historical operation deviation index; the optimization unit is configured to determine the optimization coefficient of the basic heat dissipation parameters according to the historical operation deviation index, and obtain the initial heat dissipation parameters; the second judgment unit is configured to determine whether to adjust the initial heat dissipation parameters according to the temperature data group; the adjustment unit is configured to determine the adjustment coefficient according to the comparison result and adjust the initial heat dissipation parameters to obtain the final heat dissipation parameters. The present invention improves the working efficiency and stability of the laser radar.

Description

Technical Field

[0001] The present invention relates to the field of laser radar technology, and in particular to an intelligent temperature control and heat dissipation system for a laser radar. Background Art

[0002] With the rapid development of autonomous driving, robot navigation, terrain mapping and other fields, LiDAR technology has become an indispensable core sensor in these technologies. With the continuous advancement of these technologies, the performance stability and reliability of LiDAR have become increasingly important. In the face of various working environments, such as extreme high temperature, low temperature, humidity and other conditions, the heat dissipation requirements of LiDAR are also different. The traditional constant power heat dissipation method is not flexible enough to deal with these changes, which may lead to insufficient heat dissipation, thus affecting the performance of LiDAR, or excessive heat dissipation, resulting in unnecessary energy waste.

[0003] Therefore, it is necessary to design a lidar intelligent temperature control and heat dissipation system to solve the problems existing in current technology. Summary of the invention

[0004] In view of this, the present invention proposes a laser radar intelligent temperature control and heat dissipation system, aiming to solve the problem that it is difficult to accurately control the operating temperature of the laser radar in current technology.

[0005] The present invention proposes a laser radar intelligent temperature control and heat dissipation system, comprising:

[0006] A laser radar body, a heat dissipation module and a control module; the laser radar body includes a front shell and a rear shell, the front shell and the rear shell are connected, and a plurality of temperature sensors are arranged inside the laser radar body; the heat dissipation module is arranged inside the laser radar body and close to a side of the rear shell, and the heat dissipation module includes a graphene heat conductive layer and a heat dissipation fan; the control module is connected to the heat dissipation module, and the control module includes a collection unit, a first judgment unit, an optimization unit, a second judgment unit and an adjustment unit, wherein,

[0007] The acquisition unit is configured to acquire operation stage information of the laser radar body, analyze the operation stage information, and determine basic heat dissipation parameters of the heat dissipation module based on the analysis result;

[0008] The first judgment unit is configured to extract corresponding historical operation records from a historical operation database based on the operation stage information, parse the historical operation records, and calculate a historical operation deviation index of the heat dissipation module based on the parsing result; and judge whether to optimize the basic heat dissipation parameters according to the historical operation deviation index;

[0009] The optimization unit is configured to determine an optimization coefficient of the basic heat dissipation parameter according to the historical operation deviation index and obtain an initial heat dissipation parameter when the first judgment unit determines to optimize the basic heat dissipation parameter;

[0010] The second judgment unit is configured to control the acquisition unit to acquire temperature data of each temperature sensor, and to establish a temperature data group, and to determine whether to adjust the initial heat dissipation parameter according to the temperature data group;

[0011] The adjustment unit is configured to calculate the temperature influence factor according to the temperature data group when the second judgment unit determines to adjust the initial heat dissipation parameters, compare the temperature influence factor with the historical data, determine the adjustment coefficient according to the comparison result, and adjust the initial heat dissipation parameters to obtain the final heat dissipation parameters.

[0012] Furthermore, the acquisition unit analyzes the operation stage information and determines the basic heat dissipation parameters of the heat dissipation module based on the analysis result, including:

[0013] The operation stage information includes the laser radar startup stage, the laser radar operation stage and the laser radar standby stage;

[0014] During the startup phase of the laser radar, determining the basic heat dissipation parameter of the heat dissipation module as the first heat dissipation parameter;

[0015] During the operation phase of the laser radar, determining the basic heat dissipation parameter of the heat dissipation module as the second heat dissipation parameter;

[0016] In the laser radar standby stage, determining the basic heat dissipation parameter of the heat dissipation module as a third heat dissipation parameter;

[0017] The third heat dissipation parameter is smaller than the first heat dissipation parameter, and the first heat dissipation parameter is smaller than the second heat dissipation parameter.

[0018] Furthermore, the first judgment unit analyzes the historical operation record, and calculates the historical operation deviation index of the heat dissipation module based on the analysis result, including:

[0019] Parsing the historical operation records to obtain historical normal operation behaviors and historical abnormal operation behaviors associated with temperature;

[0020] Determine the operation impact factor corresponding to each temperature-related historical abnormal operation behavior, and construct an operation impact factor sequence;

[0021] Counting the frequencies of all the historical normal operating behaviors, which are recorded as the first frequency; counting the frequencies of all the historical abnormal operating behaviors associated with the temperature, which are recorded as the second frequency;

[0022] Determine the historical operation deviation index according to the operation influencing factor sequence, the first frequency and the second frequency;

[0023] The historical operation deviation coefficient is obtained by the following formula:

[0024] ;

[0025] Among them, HRI represents the historical operation deviation coefficient; n represents the number of temperature-related historical abnormal operation behaviors; Ri represents the operation influencing factor of the i-th temperature-related historical abnormal operation behavior; fabi represents the frequency of the i-th temperature-related historical abnormal operation behavior; Fcb represents the first frequency; Fnb represents the second frequency; β represents the weight coefficient.

[0026] Furthermore, when the first judgment unit determines the operation influencing factor corresponding to each temperature-related historical abnormal operation behavior, it includes:

[0027] Extracting an actual operating temperature corresponding to a historical abnormal operating behavior associated with the temperature, obtaining a preset ideal operating temperature, and calculating a first temperature difference value according to the actual operating temperature and the ideal operating temperature;

[0028] Analyze all historical normal operating behaviors, determine the operating temperature of each normal operating behavior, and extract the minimum operating temperature; calculate a second temperature difference value according to the actual operating temperature and the minimum operating temperature;

[0029] An operation impact factor corresponding to each temperature-related historical abnormal operation behavior is calculated based on the first temperature difference and the second temperature difference.

[0030] Furthermore, when the first judgment unit judges whether to optimize the basic heat dissipation parameters according to the historical operation deviation index, it includes:

[0031] Comparing the historical operation deviation index with the historical deviation index threshold, and determining whether to optimize the basic heat dissipation parameters according to the comparison result;

[0032] When the historical operation deviation index is greater than the historical deviation index threshold, determining to optimize the basic heat dissipation parameters;

[0033] When the historical operation deviation index is less than or equal to the historical deviation index threshold, it is determined that the basic heat dissipation parameters are not optimized, and the basic heat dissipation parameters are used as the initial heat dissipation parameters.

[0034] Furthermore, when the optimization unit determines the optimization coefficient of the basic heat dissipation parameter according to the historical operation deviation index and obtains the initial heat dissipation parameter, it includes:

[0035] Comparing the historical operation deviation index with a first historical operation deviation index and a second historical operation deviation index, and determining the optimization coefficient according to the comparison result; wherein the first historical operation deviation index is less than the second historical operation deviation index;

[0036] When the historical operation deviation index is less than or equal to the first historical operation deviation index, determining the optimization coefficient to be a first optimization coefficient, and taking the product value of the first optimization coefficient and the basic heat dissipation parameter as the initial heat dissipation parameter;

[0037] When the historical operation deviation index is greater than the first historical operation deviation index and less than or equal to the second historical operation deviation index, determining that the optimization coefficient is a second optimization coefficient, and taking the product value of the second optimization coefficient and the basic heat dissipation parameter as the initial heat dissipation parameter;

[0038] When the historical operation deviation index is greater than the second historical operation deviation index, the optimization coefficient is determined to be a third optimization coefficient, and a product value of the third optimization coefficient and the basic heat dissipation parameter is used as the initial heat dissipation parameter.

[0039] Furthermore, when the second judgment unit judges whether to adjust the initial heat dissipation parameter according to the temperature data group, it includes:

[0040] Calculating the temperature change rate corresponding to each of the temperature sensors within a preset time period according to the temperature data group, and extracting the maximum temperature change rate;

[0041] Calculate the ratio of the maximum temperature change rate to the maximum temperature change rate threshold, and record it as the temperature ratio;

[0042] Comparing the temperature ratio with a temperature ratio threshold, and determining whether to adjust the initial heat dissipation parameter according to the comparison result;

[0043] When the temperature ratio is within the temperature ratio threshold, determining not to adjust the initial heat dissipation parameter;

[0044] When the temperature ratio is outside the temperature ratio threshold, it is determined to adjust the initial heat dissipation parameter.

[0045] Further, when the adjustment unit calculates the temperature influence factor according to the temperature data group, it includes:

[0046] Extracting the maximum temperature, the minimum temperature and the average temperature in the temperature data group;

[0047] Obtaining the ideal operating temperature;

[0048] Calculate the temperature impact factor according to the maximum temperature, minimum temperature, average temperature and ideal operating temperature;

[0049] The temperature influence factor is obtained by the following formula:

[0050] ;

[0051] Among them, TI represents the temperature influence factor; Tmax represents the maximum temperature; Tmin represents the minimum temperature; Tavg represents the average temperature; and Tideal represents the ideal operating temperature.

[0052] Furthermore, the adjustment unit compares the temperature influence factor with historical data, determines an adjustment coefficient according to the comparison result, and adjusts the initial heat dissipation parameter to obtain the final heat dissipation parameter, including:

[0053] When there is a historical temperature influence factor identical to the temperature influence factor in the historical data, adjusting the initial heat dissipation parameter according to a historical adjustment coefficient corresponding to the historical temperature influence factor, and taking the product value of the historical adjustment coefficient and the initial heat dissipation parameter as the final heat dissipation parameter;

[0054] When there is no historical temperature influence factor identical to the temperature influence factor in the historical data, the similarity between the temperature influence factor and the historical data is calculated one by one, and the maximum similarity is extracted, and the adjustment coefficient is determined according to the maximum similarity, and the initial heat dissipation parameter is adjusted to obtain the final heat dissipation parameter;

[0055] The similarity is obtained by the following formula:

[0056] ;

[0057] Among them, Sj represents the similarity between the j-th historical temperature influence factor and the temperature influence factor; TI represents the temperature influence factor; TIHj represents the j-th historical temperature influence factor.

[0058] Furthermore, the adjustment unit determines an adjustment coefficient according to the maximum similarity and adjusts the initial heat dissipation parameter to obtain a final heat dissipation parameter, including:

[0059] Comparing the maximum similarity with a first maximum similarity and a second maximum similarity, and determining the adjustment coefficient according to the comparison result; wherein the first maximum similarity is smaller than the second maximum similarity;

[0060] Setting an adjustment coefficient interval, wherein the adjustment coefficient interval includes a first adjustment coefficient, a second adjustment coefficient, and a third adjustment coefficient;

[0061] When the first condition is identified, determining the adjustment coefficient to be a first adjustment coefficient, and taking the product of the first adjustment coefficient and the initial heat dissipation parameter as the final heat dissipation parameter;

[0062] When the second condition is identified, determining the adjustment coefficient to be a second adjustment coefficient, and taking the product of the second adjustment coefficient and the initial heat dissipation parameter as the final heat dissipation parameter;

[0063] When the third condition is identified, determining the adjustment coefficient to be a third adjustment coefficient, and taking the product value of the third adjustment coefficient and the initial heat dissipation parameter as the final heat dissipation parameter;

[0064] Among them, the first condition is that the maximum similarity is less than or equal to the first maximum similarity; the second condition is that the maximum similarity is greater than the first maximum similarity and less than or equal to the second maximum similarity; the third condition is that the maximum similarity is greater than the second maximum similarity.

[0065] Compared with the prior art, the beneficial effect of the present invention is that the laser radar intelligent temperature control and heat dissipation system provided by the present invention can intelligently adjust the heat dissipation parameters of the heat dissipation module according to the temperature conditions of the laser radar body at different operating stages, ensuring that the laser radar body can operate within a suitable temperature range, thereby improving the working efficiency and stability of the laser radar. At the same time, by analyzing the historical operation records, calculating the historical operation deviation index of the heat dissipation module, and optimizing the basic heat dissipation parameters based on the index, the heat dissipation effect can be further improved and the service life of the laser radar can be extended. In addition, the system also collects the temperature data of the temperature sensor, calculates the temperature influence factor in real time, and compares the factor with the historical data to determine the adjustment coefficient, thereby realizing the precise adjustment of the initial heat dissipation parameters, ensuring that the laser radar can maintain good heat dissipation performance under various working conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] 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:

[0067] Figure 1 This is a structural block diagram of the laser radar intelligent temperature control and heat dissipation system provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0068] 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.

[0069] See also Figure 1 As shown, in some embodiments of the present application, this embodiment provides a laser radar intelligent temperature control and heat dissipation system, including:

[0070] A laser radar body, a heat dissipation module and a control module; the laser radar body includes a front shell and a rear shell, the front shell and the rear shell are connected, and a plurality of temperature sensors are arranged inside the laser radar body; the heat dissipation module is arranged inside the laser radar body and close to a side of the rear shell, and the heat dissipation module includes a graphene heat conductive layer and a heat dissipation fan; the control module is connected to the heat dissipation module, and the control module includes a collection unit, a first judgment unit, an optimization unit, a second judgment unit and an adjustment unit, wherein,

[0071] The acquisition unit is configured to acquire operation stage information of the laser radar body, analyze the operation stage information, and determine basic heat dissipation parameters of the heat dissipation module based on the analysis result;

[0072] The first judgment unit is configured to extract corresponding historical operation records from a historical operation database based on the operation stage information, parse the historical operation records, and calculate a historical operation deviation index of the heat dissipation module based on the parsing result; and judge whether to optimize the basic heat dissipation parameters according to the historical operation deviation index;

[0073] The optimization unit is configured to determine an optimization coefficient of the basic heat dissipation parameter according to the historical operation deviation index and obtain an initial heat dissipation parameter when the first judgment unit determines to optimize the basic heat dissipation parameter;

[0074] The second judgment unit is configured to control the acquisition unit to acquire temperature data of each temperature sensor, and to establish a temperature data group, and to determine whether to adjust the initial heat dissipation parameter according to the temperature data group;

[0075] The adjustment unit is configured to calculate the temperature influence factor according to the temperature data group when the second judgment unit determines to adjust the initial heat dissipation parameters, compare the temperature influence factor with the historical data, determine the adjustment coefficient according to the comparison result, and adjust the initial heat dissipation parameters to obtain the final heat dissipation parameters.

[0076] In some embodiments of the present invention, the basic heat dissipation parameter is the rotation speed of the heat dissipation fan.

[0077] It is understandable that the laser radar intelligent temperature control and heat dissipation system provided in this embodiment can intelligently adjust the heat dissipation parameters of the heat dissipation module according to the temperature conditions of the laser radar body at different operating stages, ensuring that the laser radar body can operate within a suitable temperature range, thereby improving the working efficiency and stability of the laser radar. At the same time, by analyzing the historical operation records, calculating the historical operation deviation index of the heat dissipation module, and optimizing the basic heat dissipation parameters based on the index, the heat dissipation effect can be further improved and the service life of the laser radar can be extended. In addition, the system also collects temperature data from the temperature sensor, calculates the temperature influence factor in real time, and compares the factor with historical data to determine the adjustment coefficient, thereby achieving precise adjustment of the initial heat dissipation parameters and ensuring that the laser radar can maintain good heat dissipation performance under various working conditions.

[0078] Specifically, the acquisition unit analyzes the operation stage information and determines the basic heat dissipation parameters of the heat dissipation module based on the analysis result, including:

[0079] The operation stage information includes the laser radar startup stage, the laser radar operation stage and the laser radar standby stage;

[0080] During the startup phase of the laser radar, determining the basic heat dissipation parameter of the heat dissipation module as the first heat dissipation parameter;

[0081] During the operation phase of the laser radar, determining the basic heat dissipation parameter of the heat dissipation module as the second heat dissipation parameter;

[0082] In the laser radar standby stage, determining the basic heat dissipation parameter of the heat dissipation module as a third heat dissipation parameter;

[0083] The third heat dissipation parameter is smaller than the first heat dissipation parameter, and the first heat dissipation parameter is smaller than the second heat dissipation parameter.

[0084] It is understandable that by setting different basic cooling parameters for different cooling stages, the cooling effect of the cooling module can be controlled more accurately, avoiding energy waste caused by excessive cooling during the startup and standby stages of the LiDAR. At the same time, the cooling effect can be ensured during the operation stage of the LiDAR to prevent the performance of the LiDAR from being degraded due to excessive temperature.

[0085] Specifically, the first judgment unit analyzes the historical operation record, and calculates the historical operation deviation index of the heat dissipation module based on the analysis result, including:

[0086] Parsing the historical operation records to obtain historical normal operation behaviors and historical abnormal operation behaviors associated with temperature;

[0087] Determine the operation impact factor corresponding to each temperature-related historical abnormal operation behavior, and construct an operation impact factor sequence;

[0088] Counting the frequencies of all the historical normal operating behaviors, which are recorded as the first frequency; counting the frequencies of all the historical abnormal operating behaviors associated with the temperature, which are recorded as the second frequency;

[0089] Determine the historical operation deviation index according to the operation influencing factor sequence, the first frequency and the second frequency;

[0090] The historical operation deviation coefficient is obtained by the following formula:

[0091] ;

[0092] Among them, HRI represents the historical operation deviation coefficient; n represents the number of temperature-related historical abnormal operation behaviors; Ri represents the operation influencing factor of the i-th temperature-related historical abnormal operation behavior; fabi represents the frequency of the i-th temperature-related historical abnormal operation behavior; Fcb represents the first frequency; Fnb represents the second frequency; β represents the weight coefficient.

[0093] In some embodiments of the present invention, historical normal operating behavior means that the laser radar is in a normal working state, its internal components operate according to a predetermined workflow and parameters, and the temperature data of the temperature sensor is within a preset normal range.

[0094] In some embodiments of the present invention, the temperature-related historical abnormal operation behavior refers to the temperature data of the temperature sensor exceeding the preset normal range due to some external factors or internal failures when the laser radar is in normal working state. These abnormal operation behaviors include but are not limited to the rapid rise in temperature when the laser radar is working in a specific environment, false alarms caused by temperature sensor failures, poor heat dissipation due to heat dissipation module failures, etc.

[0095] It is understandable that by deeply analyzing the historical operation records, especially focusing on those historical operation behaviors related to temperature anomalies, the degree of deviation of the cooling module in the past operation can be more accurately evaluated. The quantification of this degree of deviation, namely the historical operation deviation index, provides an important reference for the subsequent optimization of cooling parameters. By comprehensively considering the operation influencing factors, the frequency of normal operation behavior, and the frequency of abnormal operation behavior, the calculation of the historical operation deviation index can be ensured to be both comprehensive and accurate.

[0096] Specifically, when the first judgment unit determines the operation influencing factor corresponding to each temperature-related historical abnormal operation behavior, it includes:

[0097] Extracting an actual operating temperature corresponding to a historical abnormal operating behavior associated with the temperature, obtaining a preset ideal operating temperature, and calculating a first temperature difference value according to the actual operating temperature and the ideal operating temperature;

[0098] Analyze all historical normal operating behaviors, determine the operating temperature of each normal operating behavior, and extract the minimum operating temperature; calculate a second temperature difference value according to the actual operating temperature and the minimum operating temperature;

[0099] An operation impact factor corresponding to each temperature-related historical abnormal operation behavior is calculated based on the first temperature difference and the second temperature difference.

[0100] In some embodiments of the present invention, the ideal operating temperature refers to the temperature value corresponding to when the internal components of the laser radar reach the optimal working state under standard operating conditions.

[0101] In some embodiments of the present invention, the operation influencing factor is obtained by weighted calculation of the first temperature difference and the second temperature difference.

[0102] It is understandable that the operation impact factor can reflect the degree of influence of temperature-related historical abnormal operation behavior on the overall operation status of the lidar. By comprehensively considering the deviation between the actual operating temperature and the ideal operating temperature and the deviation between the actual operating temperature and the minimum operating temperature, the impact of temperature anomalies on the performance of the lidar can be more comprehensively evaluated. The quantification of this impact factor provides more precise guidance for subsequent optimization adjustments.

[0103] Specifically, when the first judgment unit judges whether to optimize the basic heat dissipation parameters according to the historical operation deviation index, it includes:

[0104] Comparing the historical operation deviation index with the historical deviation index threshold, and determining whether to optimize the basic heat dissipation parameters according to the comparison result;

[0105] When the historical operation deviation index is greater than the historical deviation index threshold, determining to optimize the basic heat dissipation parameters;

[0106] When the historical operation deviation index is less than or equal to the historical deviation index threshold, it is determined that the basic heat dissipation parameters are not optimized, and the basic heat dissipation parameters are used as the initial heat dissipation parameters.

[0107] It is understandable that by setting the historical deviation index threshold, the system can automatically determine whether the historical operating status of the cooling module deviates from the normal range. When the historical operation deviation index exceeds the threshold, it means that there may be some problems in the past operation of the cooling module, and the basic cooling parameters need to be optimized and adjusted to improve the cooling effect. When the historical operation deviation index is within the threshold range, it means that the cooling module is in good operating condition, and there is no need to optimize the basic cooling parameters, which can be directly used as the initial cooling parameters. It can ensure that the cooling system can maintain the best cooling performance under different working conditions.

[0108] Specifically, when the optimization unit determines the optimization coefficient of the basic heat dissipation parameter according to the historical operation deviation index and obtains the initial heat dissipation parameter, it includes:

[0109] Comparing the historical operation deviation index with a first historical operation deviation index and a second historical operation deviation index, and determining the optimization coefficient according to the comparison result; wherein the first historical operation deviation index is less than the second historical operation deviation index;

[0110] When the historical operation deviation index is less than or equal to the first historical operation deviation index, determining the optimization coefficient to be a first optimization coefficient, and taking the product value of the first optimization coefficient and the basic heat dissipation parameter as the initial heat dissipation parameter;

[0111] When the historical operation deviation index is greater than the first historical operation deviation index and less than or equal to the second historical operation deviation index, determining that the optimization coefficient is a second optimization coefficient, and taking the product value of the second optimization coefficient and the basic heat dissipation parameter as the initial heat dissipation parameter;

[0112] When the historical operation deviation index is greater than the second historical operation deviation index, the optimization coefficient is determined to be a third optimization coefficient, and a product value of the third optimization coefficient and the basic heat dissipation parameter is used as the initial heat dissipation parameter.

[0113] In some embodiments of the present invention, the first optimization coefficient is less than the second optimization coefficient and less than the third optimization coefficient.

[0114] It is understandable that by comparing the historical operation deviation index in sections, different optimization strategies can be provided for heat dissipation modules with different degrees of deviation. When the historical operation deviation index is low, it means that the operation of the heat dissipation module is relatively good. At this time, a smaller optimization coefficient can be used to fine-tune the basic heat dissipation parameters. When the historical operation deviation index is high, it means that there may be major problems with the operation of the heat dissipation module, and a larger optimization coefficient is required to make larger adjustments to the basic heat dissipation parameters to improve the heat dissipation effect. This segmented optimization method can ensure that the heat dissipation system can obtain the most appropriate optimization adjustment at different degrees of deviation, thereby further improving its heat dissipation performance and stability.

[0115] Specifically, when the second judgment unit judges whether to adjust the initial heat dissipation parameter according to the temperature data group, it includes:

[0116] Calculating the temperature change rate corresponding to each of the temperature sensors within a preset time period according to the temperature data group, and extracting the maximum temperature change rate;

[0117] Calculate the ratio of the maximum temperature change rate to the maximum temperature change rate threshold, and record it as the temperature ratio;

[0118] Comparing the temperature ratio with a temperature ratio threshold, and determining whether to adjust the initial heat dissipation parameter according to the comparison result;

[0119] When the temperature ratio is within the temperature ratio threshold, determining not to adjust the initial heat dissipation parameter;

[0120] When the temperature ratio is outside the temperature ratio threshold, it is determined to adjust the initial heat dissipation parameter.

[0121] It is understandable that by calculating the temperature change rate and comparing it with the preset temperature change rate threshold, the system can sensitively capture the trend of the temperature change of the lidar body. If the temperature change rate exceeds the preset threshold, that is, the temperature ratio exceeds the temperature ratio threshold range, this means that the lidar body is experiencing abnormal temperature changes, which may be caused by changes in the external environment, internal component failure, or reduced performance of the heat dissipation module.

[0122] Specifically, when the adjustment unit calculates the temperature influence factor according to the temperature data group, it includes:

[0123] Extracting the maximum temperature, the minimum temperature and the average temperature in the temperature data group;

[0124] Obtaining the ideal operating temperature;

[0125] Calculate the temperature impact factor according to the maximum temperature, minimum temperature, average temperature and ideal operating temperature;

[0126] The temperature influence factor is obtained by the following formula:

[0127] ;

[0128] Among them, TI represents the temperature influence factor; Tmax represents the maximum temperature; Tmin represents the minimum temperature; Tavg represents the average temperature; and Tideal represents the ideal operating temperature.

[0129] It is understandable that the temperature impact factor is a composite indicator that comprehensively considers the maximum temperature, minimum temperature, average temperature and ideal operating temperature in the temperature data group. It reflects the degree of deviation between the current temperature state of the lidar body and the ideal state, as well as the range of temperature fluctuations. By introducing the temperature impact factor, the system can more carefully evaluate the demand for temperature data for heat dissipation parameter adjustment, ensuring that the heat dissipation adjustment strategy is neither excessive nor too conservative, thereby maximizing its working efficiency and service life while ensuring the stable operation of the lidar.

[0130] Specifically, the adjustment unit compares the temperature influence factor with the historical data, determines the adjustment coefficient according to the comparison result, and adjusts the initial heat dissipation parameter to obtain the final heat dissipation parameter, including:

[0131] When there is a historical temperature influence factor identical to the temperature influence factor in the historical data, adjusting the initial heat dissipation parameter according to a historical adjustment coefficient corresponding to the historical temperature influence factor, and taking the product value of the historical adjustment coefficient and the initial heat dissipation parameter as the final heat dissipation parameter;

[0132] When there is no historical temperature influence factor identical to the temperature influence factor in the historical data, the similarity between the temperature influence factor and the historical data is calculated one by one, and the maximum similarity is extracted, and the adjustment coefficient is determined according to the maximum similarity, and the initial heat dissipation parameter is adjusted to obtain the final heat dissipation parameter;

[0133] The similarity is obtained by the following formula:

[0134] ;

[0135] Among them, Sj represents the similarity between the j-th historical temperature influence factor and the temperature influence factor; TI represents the temperature influence factor; TIHj represents the j-th historical temperature influence factor.

[0136] It is understandable that by comparing the temperature impact factor with historical data, the system can make full use of historical experience to guide the current cooling parameter adjustment. When there is a historical record in the historical data that is exactly the same as the current temperature impact factor, the system can directly use the corresponding historical adjustment coefficient, so that the cooling parameter adjustment can be completed quickly and accurately. When there is no exactly the same temperature impact factor in the historical data, the system finds the closest historical record by calculating the similarity and makes appropriate adjustments based on its adjustment coefficient. This intelligent adjustment strategy based on historical data not only improves the accuracy and efficiency of cooling parameter adjustment, but also ensures that the cooling system can adapt to various complex working conditions, thereby effectively extending the service life of the lidar and improving its working performance.

[0137] Specifically, the adjustment unit determines the adjustment coefficient according to the maximum similarity and adjusts the initial heat dissipation parameter to obtain the final heat dissipation parameter, including:

[0138] Comparing the maximum similarity with a first maximum similarity and a second maximum similarity, and determining the adjustment coefficient according to the comparison result; wherein the first maximum similarity is smaller than the second maximum similarity;

[0139] Setting an adjustment coefficient interval, wherein the adjustment coefficient interval includes a first adjustment coefficient, a second adjustment coefficient, and a third adjustment coefficient;

[0140] When the first condition is identified, determining the adjustment coefficient to be a first adjustment coefficient, and taking the product of the first adjustment coefficient and the initial heat dissipation parameter as the final heat dissipation parameter;

[0141] When the second condition is identified, determining the adjustment coefficient to be a second adjustment coefficient, and taking the product of the second adjustment coefficient and the initial heat dissipation parameter as the final heat dissipation parameter;

[0142] When the third condition is identified, determining the adjustment coefficient to be a third adjustment coefficient, and taking the product value of the third adjustment coefficient and the initial heat dissipation parameter as the final heat dissipation parameter;

[0143] Among them, the first condition is that the maximum similarity is less than or equal to the first maximum similarity; the second condition is that the maximum similarity is greater than the first maximum similarity and less than or equal to the second maximum similarity; the third condition is that the maximum similarity is greater than the second maximum similarity.

[0144] It is understandable that by performing segmented comparison of the maximum similarity, the system can provide more refined control for the adjustment of the heat dissipation parameters according to different degrees of similarity. When the maximum similarity is low, it means that the current temperature influencing factor deviates greatly from the historical data. At this time, the system uses a smaller adjustment coefficient for fine-tuning to avoid instability caused by excessive adjustment. When the maximum similarity is high, it means that the current temperature influencing factor is closer to the historical data. At this time, the system can use a larger adjustment coefficient for larger adjustments to adapt to temperature changes more quickly and improve the heat dissipation effect. This segmented adjustment strategy based on maximum similarity not only improves the flexibility and accuracy of the heat dissipation parameter adjustment, but also ensures that the heat dissipation system can make timely and reasonable responses when faced with complex working conditions, thereby further improving the working performance and stability of the lidar.

[0145] 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 a combination of software and hardware embodiments. Furthermore, 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.

[0146] 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 collection 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.

[0147] 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.

[0148] 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 A step that specifies a function in one or more boxes.

[0149] 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 laser radar intelligent temperature control and heat dissipation system, characterized in that: include: A laser radar body, a heat dissipation module and a control module; the laser radar body includes a front shell and a rear shell, the front shell and the rear shell are connected, and a plurality of temperature sensors are arranged inside the laser radar body; the heat dissipation module is arranged inside the laser radar body and close to a side of the rear shell, and the heat dissipation module includes a graphene heat conductive layer and a heat dissipation fan; the control module is connected to the heat dissipation module, and the control module includes a collection unit, a first judgment unit, an optimization unit, a second judgment unit and an adjustment unit, wherein, The acquisition unit is configured to acquire operation stage information of the laser radar body, analyze the operation stage information, and determine basic heat dissipation parameters of the heat dissipation module based on the analysis result; The first judgment unit is configured to extract corresponding historical operation records from a historical operation database based on the operation stage information, parse the historical operation records, and calculate a historical operation deviation index of the heat dissipation module based on the parsing result; and judge whether to optimize the basic heat dissipation parameters according to the historical operation deviation index; The optimization unit is configured to determine an optimization coefficient of the basic heat dissipation parameter according to the historical operation deviation index and obtain an initial heat dissipation parameter when the first judgment unit determines to optimize the basic heat dissipation parameter; The second judgment unit is configured to control the acquisition unit to acquire temperature data of each temperature sensor, and to establish a temperature data group, and to determine whether to adjust the initial heat dissipation parameter according to the temperature data group; The adjustment unit is configured to calculate the temperature influence factor according to the temperature data group when the second judgment unit determines to adjust the initial heat dissipation parameters, compare the temperature influence factor with the historical data, determine the adjustment coefficient according to the comparison result, and adjust the initial heat dissipation parameters to obtain the final heat dissipation parameters.

2. The laser radar intelligent temperature control and heat dissipation system according to claim 1, characterized in that: The acquisition unit analyzes the operation stage information and determines the basic heat dissipation parameters of the heat dissipation module based on the analysis result, including: The operation stage information includes the laser radar startup stage, the laser radar operation stage and the laser radar standby stage; During the startup phase of the laser radar, determining the basic heat dissipation parameter of the heat dissipation module as the first heat dissipation parameter; During the operation phase of the laser radar, determining the basic heat dissipation parameter of the heat dissipation module as the second heat dissipation parameter; In the laser radar standby stage, determining the basic heat dissipation parameter of the heat dissipation module as a third heat dissipation parameter; The third heat dissipation parameter is smaller than the first heat dissipation parameter, and the first heat dissipation parameter is smaller than the second heat dissipation parameter.

3. The laser radar intelligent temperature control and heat dissipation system according to claim 1, characterized in that: The first judgment unit analyzes the historical operation record and calculates the historical operation deviation index of the heat dissipation module based on the analysis result, including: Parsing the historical operation records to obtain historical normal operation behaviors and historical abnormal operation behaviors associated with temperature; Determine the operation impact factor corresponding to each temperature-related historical abnormal operation behavior, and construct an operation impact factor sequence; Counting the frequencies of all the historical normal operating behaviors, which are recorded as the first frequency; counting the frequencies of all the historical abnormal operating behaviors associated with the temperature, which are recorded as the second frequency; Determine the historical operation deviation index according to the operation influencing factor sequence, the first frequency and the second frequency; The historical operation deviation coefficient is obtained by the following formula: ； Among them, HRI represents the historical operation deviation coefficient; n represents the number of temperature-related historical abnormal operation behaviors; Ri represents the operation influencing factor of the i-th temperature-related historical abnormal operation behavior; fabi represents the frequency of the i-th temperature-related historical abnormal operation behavior; Fcb represents the first frequency; Fnb represents the second frequency; β represents the weight coefficient.

4. The laser radar intelligent temperature control and heat dissipation system according to claim 3 is characterized in that: When the first judgment unit determines the operation influencing factor corresponding to each temperature-related historical abnormal operation behavior, it includes: Extracting an actual operating temperature corresponding to a historical abnormal operating behavior associated with the temperature, obtaining a preset ideal operating temperature, and calculating a first temperature difference value according to the actual operating temperature and the ideal operating temperature; Analyze all historical normal operating behaviors, determine the operating temperature of each normal operating behavior, and extract the minimum operating temperature; calculate a second temperature difference value according to the actual operating temperature and the minimum operating temperature; An operation impact factor corresponding to each temperature-related historical abnormal operation behavior is calculated based on the first temperature difference and the second temperature difference.

5. The laser radar intelligent temperature control and heat dissipation system according to claim 4, characterized in that: When the first judgment unit judges whether to optimize the basic heat dissipation parameters according to the historical operation deviation index, it includes: Comparing the historical operation deviation index with the historical deviation index threshold, and determining whether to optimize the basic heat dissipation parameters according to the comparison result; When the historical operation deviation index is greater than the historical deviation index threshold, determining to optimize the basic heat dissipation parameters; When the historical operation deviation index is less than or equal to the historical deviation index threshold, it is determined that the basic heat dissipation parameters are not optimized, and the basic heat dissipation parameters are used as the initial heat dissipation parameters.

6. The laser radar intelligent temperature control and heat dissipation system according to claim 5, characterized in that: When the optimization unit determines the optimization coefficient of the basic heat dissipation parameter according to the historical operation deviation index and obtains the initial heat dissipation parameter, it includes: Comparing the historical operation deviation index with a first historical operation deviation index and a second historical operation deviation index, and determining the optimization coefficient according to the comparison result; wherein the first historical operation deviation index is less than the second historical operation deviation index; When the historical operation deviation index is less than or equal to the first historical operation deviation index, determining the optimization coefficient to be a first optimization coefficient, and taking the product value of the first optimization coefficient and the basic heat dissipation parameter as the initial heat dissipation parameter; When the historical operation deviation index is greater than the first historical operation deviation index and less than or equal to the second historical operation deviation index, determining that the optimization coefficient is a second optimization coefficient, and taking the product value of the second optimization coefficient and the basic heat dissipation parameter as the initial heat dissipation parameter; When the historical operation deviation index is greater than the second historical operation deviation index, the optimization coefficient is determined to be a third optimization coefficient, and a product value of the third optimization coefficient and the basic heat dissipation parameter is used as the initial heat dissipation parameter.

7. The laser radar intelligent temperature control and heat dissipation system according to claim 6, characterized in that: When the second judgment unit judges whether to adjust the initial heat dissipation parameter according to the temperature data group, it includes: Calculating the temperature change rate corresponding to each of the temperature sensors within a preset time period according to the temperature data group, and extracting the maximum temperature change rate; Calculate the ratio of the maximum temperature change rate to the maximum temperature change rate threshold, and record it as the temperature ratio; Comparing the temperature ratio with a temperature ratio threshold, and determining whether to adjust the initial heat dissipation parameter according to the comparison result; When the temperature ratio is within the temperature ratio threshold, determining not to adjust the initial heat dissipation parameter; When the temperature ratio is outside the temperature ratio threshold, it is determined to adjust the initial heat dissipation parameter.

8. The laser radar intelligent temperature control and heat dissipation system according to claim 7, characterized in that: When the adjustment unit calculates the temperature influence factor according to the temperature data group, it includes: Extracting the maximum temperature, the minimum temperature and the average temperature in the temperature data group; Obtaining the ideal operating temperature; Calculate the temperature impact factor according to the maximum temperature, minimum temperature, average temperature and ideal operating temperature; The temperature influence factor is obtained by the following formula: ； Among them, TI represents the temperature influence factor; Tmax represents the maximum temperature; Tmin represents the minimum temperature; Tavg represents the average temperature; and Tideal represents the ideal operating temperature.

9. The laser radar intelligent temperature control and heat dissipation system according to claim 8, characterized in that: The adjustment unit compares the temperature influence factor with the historical data, determines the adjustment coefficient according to the comparison result, and adjusts the initial heat dissipation parameter to obtain the final heat dissipation parameter, including: When there is a historical temperature influence factor identical to the temperature influence factor in the historical data, adjusting the initial heat dissipation parameter according to a historical adjustment coefficient corresponding to the historical temperature influence factor, and taking the product value of the historical adjustment coefficient and the initial heat dissipation parameter as the final heat dissipation parameter; When there is no historical temperature influence factor identical to the temperature influence factor in the historical data, the similarity between the temperature influence factor and the historical data is calculated one by one, and the maximum similarity is extracted, and the adjustment coefficient is determined according to the maximum similarity, and the initial heat dissipation parameter is adjusted to obtain the final heat dissipation parameter; The similarity is obtained by the following formula: ； Among them, Sj represents the similarity between the j-th historical temperature influence factor and the temperature influence factor; TI represents the temperature influence factor; TIHj represents the j-th historical temperature influence factor.

10. The laser radar intelligent temperature control and heat dissipation system according to claim 9, characterized in that: The adjusting unit determines the adjustment coefficient according to the maximum similarity and adjusts the initial heat dissipation parameter to obtain the final heat dissipation parameter, including: Comparing the maximum similarity with a first maximum similarity and a second maximum similarity, and determining the adjustment coefficient according to the comparison result; wherein the first maximum similarity is smaller than the second maximum similarity; Setting an adjustment coefficient interval, wherein the adjustment coefficient interval includes a first adjustment coefficient, a second adjustment coefficient, and a third adjustment coefficient; When the first condition is identified, determining the adjustment coefficient to be a first adjustment coefficient, and taking the product of the first adjustment coefficient and the initial heat dissipation parameter as the final heat dissipation parameter; When the second condition is identified, determining the adjustment coefficient to be a second adjustment coefficient, and taking the product of the second adjustment coefficient and the initial heat dissipation parameter as the final heat dissipation parameter; When the third condition is identified, determining the adjustment coefficient to be a third adjustment coefficient, and taking the product value of the third adjustment coefficient and the initial heat dissipation parameter as the final heat dissipation parameter; Among them, the first condition is that the maximum similarity is less than or equal to the first maximum similarity; the second condition is that the maximum similarity is greater than the first maximum similarity and less than or equal to the second maximum similarity; the third condition is that the maximum similarity is greater than the second maximum similarity.

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