A work range pre-evaluation system of a laser bomb disposal vehicle with heat management function

Abstract

The application discloses a kind of operation range pre-evaluation systems of laser explosive-removing vehicle with heat management function, belong to public safety technical field, including environmental parameter acquisition module, heat management state monitoring module, laser performance monitoring module, data processing and evaluation module and result output module, the present application is not combined heat management system state and environmental dynamic factor by to existing laser explosive-removing vehicle operation range evaluation, accuracy is insufficient, provide a kind of system that can real-time fusion environmental parameter, heat management system state and laser performance parameter, accurately pre-evaluation operation range;By including heat management system state in operation range evaluation, it solves the problem of only relying on experience or static parameter estimation, experimental verification shows that evaluation error is reduced to within ±5% from ±20% of prior art;By real-time dynamic correction operation range, when environment deteriorates or heat management system is abnormal, safety distance can be immediately warned and updated, to avoid operator misjudgment.

Description

Technical Field

[0001] This invention belongs to the field of public safety technology, specifically referring to a pre-assessment system for the operational range of a laser bomb disposal vehicle with thermal management function. Background Technology

[0002] In fields such as public safety, laser bomb disposal vehicles have become core equipment for reducing the risk of injury or death to bomb disposal personnel due to their advantages of remote operation and contactless disposal. Their operating range directly determines the safety and effectiveness of bomb disposal operations, and accurate assessment of this range is a key prerequisite for ensuring the smooth progress of the operation.

[0003] However, existing thermal management-enabled laser bomb disposal vehicles still have certain shortcomings in their operational range pre-assessment systems. Current technologies only monitor a few key indicators related to laser output, and existing data processing involves simple data aggregation or preliminary analysis. They lack precise quantitative models and rely heavily on experience or simple theoretical formulas for operational range estimation, lacking a real-time dynamic adjustment mechanism. This makes it difficult to respond promptly to changes in the environment and equipment status. The operational range of laser bomb disposal vehicles is affected by multiple factors: environmental factors such as atmospheric temperature, humidity, and wind speed can cause laser energy attenuation; the laser system's own status: lasers generate a large amount of heat during operation, and if the thermal management system is inefficient, the laser temperature will be too high, leading to a decrease in output power and a deterioration in beam quality, directly reducing the effective operational range. The operational range of bomb disposal vehicles typically relies on empirical estimations or static parameters, without considering dynamic environmental changes and the real-time status of the thermal management system. This can easily lead to insufficient range or blindly approaching the target during actual operations, posing safety hazards or low efficiency. Therefore, this paper proposes an operational range pre-assessment system for laser bomb disposal vehicles with thermal management capabilities. Summary of the Invention

[0004] The purpose of this invention is to provide a pre-assessment system for the operating range of a laser bomb disposal vehicle with thermal management function, so as to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a pre-assessment system for the operating range of a laser bomb disposal vehicle with thermal management function, comprising an environmental parameter acquisition module, a thermal management status monitoring module, a laser performance monitoring module, a data processing and evaluation module, and a result output module;

[0006] The environmental parameter acquisition module is used to collect dynamic parameters of the working environment in real time, such as temperature, humidity, and wind speed.

[0007] The thermal management status monitoring module is used to monitor the full-link parameters of the thermal management system of the laser bomb disposal vehicle, including heat generation, heat transfer, and heat dissipation.

[0008] The laser performance monitoring module is used to collect the output performance parameters of the laser in real time.

[0009] The data processing and evaluation module is used to integrate the data from the above modules and calculate the work scope through a preset model;

[0010] The result output module is used to feed back the pre-evaluation results to the operator.

[0011] Preferably, the environmental parameter acquisition module includes a temperature sensor, a humidity sensor, and a wind speed sensor. The temperature sensor is used to accurately acquire ambient temperature data; the humidity sensor can be adapted to different humidity conditions in different operating scenarios; and the wind speed sensor's range meets the wind speed monitoring needs in both conventional and complex wind field environments. The three types of sensors work together to acquire dynamic environmental parameters.

[0012] Preferably, the environmental parameter acquisition module collects environmental temperature, humidity, and wind speed data, which are then transmitted in real time to the data processing and evaluation module via a data bus. The humidity parameter directly participates in the laser energy attenuation calculation. The system synchronously calculates the change in laser energy attenuation rate at different distances based on the data, providing a quantitative basis for adjusting the operating range.

[0013] Preferably, the thermal management status monitoring module includes a temperature sensor, a flow sensor, a pressure sensor, and a thermal management system controller. The temperature sensor is used to measure the temperature of the laser body and the inlet and outlet temperatures of the cooling medium, the flow sensor is used to measure the flow rate of the cooling medium, the pressure sensor is used to measure the pressure of the cooling system, and the thermal management system controller is used to read the start / stop status and power output data of the cooling device, comprehensively covering the core operating parameters of the thermal management system.

[0014] Preferably, the thermal management status monitoring module integrates parameters such as laser body temperature, cooling medium flow rate, and cooling system pressure to determine the heat dissipation capacity of the thermal management system for the laser. When the laser temperature exceeds a preset threshold, the system automatically determines that the heat dissipation efficiency has decreased and transmits the determination result to the data processing and evaluation module.

[0015] Preferably, the laser performance monitoring module includes a power meter, a beam quality analyzer, and a wavelength meter. The power meter is used to collect the laser output power in real time; the beam quality analyzer is used to measure the laser beam divergence angle and beam quality factor; and the wavelength meter is used to monitor the laser wavelength in real time. The three types of devices work synchronously to comprehensively capture the dynamic changes in the laser output performance.

[0016] Preferably, the laser output power data collected by the laser performance monitoring module directly reflects the laser's ablation capability against unexploded ordnance. When a decrease in output power is detected, the data processing and evaluation module automatically associates it with the working distance adjustment logic and shortens the effective working distance through quantitative calculation to ensure the effectiveness of the bomb disposal operation.

[0017] Preferably, the workflow of the data processing and evaluation module includes data preprocessing, correlation model establishment and dynamic correction. In the data preprocessing stage, the collected environmental parameters, thermal management status parameters and laser performance parameters are filtered, denoised and normalized to eliminate data interference and ensure data quality.

[0018] Preferably, the correlation model of the data processing and evaluation module takes ambient temperature, humidity, wind speed, laser temperature, cooling medium flow rate, laser output power and beam divergence angle as input parameters, and the maximum effective working distance and working angle range of different types of targets as output parameters. The model is established based on experimentally fitted environmental parameters-laser energy attenuation curve, laser temperature-output power attenuation curve and beam divergence angle-energy focusing efficiency curve to ensure the accuracy of the calculation results.

[0019] Preferably, the result output module includes a vehicle-mounted display screen and an audible and visual alarm. The vehicle-mounted display screen is used to simultaneously display real-time operating range values ​​and a visual range diagram, providing intuitive feedback on the pre-assessment results. The audible and visual alarm automatically activates when the operating range is detected to be below a safety threshold, issuing a warning to the operator through audible and visual prompts.

[0020] Compared with the prior art, the beneficial effects of the present invention are:

[0021] 1. This invention addresses the problem that existing laser bomb disposal vehicle operation range assessments do not incorporate the status of the thermal management system and dynamic environmental factors, resulting in insufficient accuracy. It provides a system that can accurately predict the operation range by integrating environmental parameters, thermal management system status, and laser performance parameters in real time.

[0022] 2. This invention solves the problem of relying solely on experience or static parameters for estimation by incorporating the status of the thermal management system into the operational scope assessment. Experimental verification shows that the assessment error is reduced.

[0023] 3. This invention dynamically corrects the operating range in real time. When the environment deteriorates or the thermal management system malfunctions, it can immediately issue an early warning and update the safe distance, thus avoiding misjudgment by operators.

[0024] 4. This invention can be directly integrated into existing laser bomb disposal vehicles with thermal management functions without major modifications, resulting in low cost. Attached Figure Description

[0025] Figure 1 This is a schematic diagram of the system structure of a pre-assessment system for the operating range of a laser bomb disposal vehicle with thermal management function according to the present invention;

[0026] Figure 2 This is a flowchart illustrating the operation range pre-assessment system for a laser bomb disposal vehicle with thermal management function according to the present invention.

[0027] Figure 3 This is a schematic diagram of the system interface of the pre-assessment system for the operating range of a laser bomb disposal vehicle with thermal management function according to the present invention. Detailed Implementation

[0028] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0029] Example

[0030] Please see Figures 1-3 As shown, the present invention provides a technical solution including an environmental parameter acquisition module, a thermal management status monitoring module, a laser performance monitoring module, a data processing and evaluation module, and a result output module;

[0031] The environmental parameter acquisition module is used to collect dynamic parameters of the working environment in real time, such as temperature, humidity, and wind speed.

[0032] The thermal management status monitoring module is used to monitor the full-link parameters of the thermal management system of the laser bomb disposal vehicle, including heat generation, heat transfer, and heat dissipation.

[0033] The laser performance monitoring module is used to collect the output performance parameters of the laser in real time.

[0034] The data processing and evaluation module is used to integrate the data from the above modules and calculate the work scope through a preset model;

[0035] The result output module is used to feed back the pre-evaluation results to the operator.

[0036] In this embodiment, the environmental parameter acquisition module includes a temperature sensor, a humidity sensor, and a wind speed sensor. The temperature sensor has a measurement accuracy of ±0.5℃ and is used to accurately acquire ambient temperature data. The humidity sensor has a range covering 0-100%RH, which can adapt to different humidity conditions in operating scenarios. The wind speed sensor has a range of 0-20m / s, which meets the wind speed monitoring needs in conventional and complex wind field environments. The three types of sensors work together to acquire dynamic environmental parameters.

[0037] In this embodiment, the environmental temperature, humidity, and wind speed data collected by the environmental parameter acquisition module are transmitted to the data processing and evaluation module in real time via the data bus. The humidity parameter directly participates in the laser energy attenuation calculation. When the ambient humidity increases from 30% to 80%, the system calculates the change in the laser energy attenuation rate at different distances based on the data, providing a quantitative basis for adjusting the operating range.

[0038] In this embodiment, the thermal management status monitoring module includes a temperature sensor, a flow sensor, a pressure sensor, and a thermal management system controller. The temperature sensor is used to measure the temperature of the laser body and the inlet and outlet temperatures of the cooling medium, the flow sensor is used to measure the flow rate of the cooling medium, the pressure sensor is used to measure the pressure of the cooling system, and the thermal management system controller is used to read the start / stop status and power output data of the cooling device, comprehensively covering the core operating parameters of the thermal management system.

[0039] In this embodiment, the thermal management status monitoring module integrates parameters such as laser body temperature, cooling medium flow rate, and cooling system pressure to determine the heat dissipation capacity of the thermal management system for the laser. When the laser temperature exceeds a preset threshold, the system automatically determines that the heat dissipation efficiency has decreased and transmits the determination result to the data processing and evaluation module as a key basis for correcting the operating range.

[0040] In this embodiment, the laser performance monitoring module includes a power meter, a beam quality analyzer, and a wavelength meter. The power meter has a measurement accuracy of ±2% and is used to collect laser output power in real time. The beam quality analyzer is used to measure the laser beam divergence angle and beam quality factor. The wavelength meter is used to monitor the laser wavelength in real time. The three types of devices work synchronously to comprehensively capture the dynamic changes in the laser output performance.

[0041] In this embodiment, the laser output power data collected by the laser performance monitoring module directly reflects the laser's ablation capability against unexploded ordnance. When a decrease in output power is detected, the data processing and evaluation module automatically associates it with the working distance adjustment logic and shortens the effective working distance through quantitative calculation to ensure the effectiveness of the bomb disposal operation.

[0042] In this embodiment, the workflow of the data processing and evaluation module includes data preprocessing, correlation model establishment and dynamic correction. In the data preprocessing stage, the collected environmental parameters, thermal management status parameters and laser performance parameters are filtered, denoised and normalized to eliminate data interference and ensure data quality.

[0043] In this embodiment, the correlation model of the data processing and evaluation module takes ambient temperature, humidity, wind speed, laser temperature, cooling medium flow rate, laser output power and beam divergence angle as input parameters, and the maximum effective working distance and working angle range of different types of targets as output parameters. The model is established based on experimentally fitted environmental parameters-laser energy attenuation curve, laser temperature-output power attenuation curve and beam divergence angle-energy focusing efficiency curve to ensure the accuracy of the calculation results.

[0044] In this embodiment, the result output module includes a vehicle-mounted display screen and an audible and visual alarm. The vehicle-mounted display screen is used to simultaneously display real-time operating range values ​​and a visual range diagram, providing intuitive feedback on the pre-assessment results. The audible and visual alarm automatically activates when it detects that the operating range is below the safety threshold, issuing a warning to the operator through audible and visual prompts to avoid operational risks.

[0045] In this embodiment, multiple parameters are monitored in real time:

[0046] Expanding the dimensions of monitoring parameters:

[0047] Breaking through the limitations of traditional methods that only monitor the temperature of the laser module, this system covers the entire heat management system chain from heat generation to heat transfer to heat dissipation, adding three new key parameters:

[0048] Refined monitoring of heat generation: In addition to the surface temperature of the laser module, the junction temperature of the laser diode and the power loss of the pump source are added to directly capture the core source of heat generation;

[0049] Dynamic monitoring of heat transfer end: Temperature sensors are installed at key nodes of the coolant pipeline to monitor the coolant temperature difference simultaneously; coolant viscosity sensor and pipeline pressure sensor are added.

[0050] Heat dissipation performance monitoring: In addition to fan speed and heat exchanger efficiency, a new cooling fan air pressure sensor, a heat flux density sensor on the heat sink surface, and an ambient wind speed sensor have been added.

[0051] Monitoring accuracy and reliability assurance:

[0052] Sensor redundancy design: Core parameters (such as laser junction temperature and coolant flow rate) are cross-validated using dual sensors. When the deviation between the two data streams is greater than 5%, the backup sensor is automatically switched and a data anomaly warning is triggered.

[0053] Anti-interference measures: To address electromagnetic interference at the bomb disposal site, sensor signals utilize differential transmission with shielded cables, and the data acquisition module incorporates an EMC electromagnetic compatibility filter circuit to ensure a data transmission error rate of <10⁻⁻⁴. 6 ;

[0054] Sampling frequency hierarchical control: basic parameters are sampled at 1Hz, core parameters at 10Hz, and sudden operating conditions are automatically switched to 100Hz high-frequency sampling, taking into account both real-time performance and power consumption.

[0055] In this embodiment, data fusion and processing are as follows:

[0056] Spatiotemporal alignment and noise reduction of multi-source data:

[0057] Spatiotemporal alignment mechanism: GPS timestamp modules are added to all sensors to ensure that data from sensors of different locations and types are synchronized in the time dimension; the spatial coordinates of the data are matched with the positioning information of the bomb disposal vehicle through dual-link transmission of vehicle CAN bus + Ethernet;

[0058] The hierarchical noise reduction algorithm consists of three layers: the first layer uses a sliding window mean filter to process high-frequency fluctuating data, with the window size dynamically adjusted according to the sampling frequency; the second layer uses a Kalman filter to fuse redundant sensor data and eliminate random errors; and the third layer uses an outlier identification algorithm to remove invalid data caused by sudden changes due to explosions or electromagnetic interference. Taking into account the characteristics of sudden changes caused by explosions or electromagnetic interference, the specific outlier identification algorithm uses a combination of the 3σ principle and the sliding window threshold method. This approach can quickly identify sudden, large fluctuations while also setting reasonable boundaries based on actual working conditions. The 3σ principle (Laida criterion) assumes that the data follows a normal distribution, and data exceeding the mean ± 3 standard deviations are considered outliers, suitable for quickly screening obvious sudden changes. The sliding window threshold method involves setting a reasonable threshold range based on engineering experience (such as the normal fluctuation range of laser power / temperature), and data exceeding the threshold for a certain period is considered an anomaly.

[0059] The coupling relationship between thermal management data and laser performance data:

[0060] Construct a data correlation matrix to quantify the correlation between thermal management parameters and laser performance parameters, and screen core influencing factors:

[0061] The correlation between each parameter and the actual laser power attenuation rate was calculated using the Pearson correlation coefficient. Parameters with a correlation coefficient > 0.7 were retained, while weakly correlated parameters were removed. The formula for calculating the Pearson correlation coefficient is as follows, where the coefficient r is used to measure the degree of linear correlation between the two variables, denoted as thermal management parameter X and actual laser power attenuation rate Y:

[0062]

[0063] in:

[0064] n: The total number of samples collected (the sample size must be ≥30 to avoid randomness);

[0065] Xi: The i-th sample value of the thermal management parameter (such as laser module temperature, coolant flow rate, etc.);

[0066] Xˉ: Sample mean of thermal management parameters;

[0067] Yi: The observed value of the actual laser power attenuation rate in the i-th sample;

[0068] Yˉ: Sample mean of actual laser power attenuation rate.

[0069] Establish a data priority mechanism: When multiple parameters conflict, data fusion is performed according to the priority weight of heat generation end > heat transfer end > heat dissipation end to avoid misjudgment of a single parameter.

[0070] In this embodiment, the thermal management-laser performance-operating range model is constructed as follows:

[0071] Three-order progressive model architecture:

[0072] First-order: Thermal management system heat loss sub-model:

[0073] Breaking through the limitations of traditional linear formulas, a nonlinear heat loss model is established, introducing three correction factors:

[0074] ,

[0075] Where K_1 is the junction temperature influence coefficient; K_2 is the coolant heat transfer coefficient; and K_3 is the heat dissipation efficiency coefficient.

[0076] Model calibration: Through 100 sets of real vehicle tests under different operating conditions (temperature-flow-power), the dynamic value curves of K1, K2, and K3 were fitted using the least squares method to ensure that the model error is less than 3%.

[0077] Second-order: Laser performance attenuation sub-model:

[0078] A new assessment of thermally induced beam quality degradation has been added, addressing the shortcomings of traditional methods that only consider power attenuation:

[0079] Introducing the beam quality factor M², and measuring it in real time using a laser spot analyzer, the relationship between M² and thermal management parameters is established: when the laser junction temperature increases by 10℃, M² increases from 1.2 to 1.8, causing the growth rate of the spot area S with distance L to change from L² to (1.5L)².

[0080] Corrected laser power density formula:

[0081] (α is an environmental correction factor) to ensure more accurate calculation of the actual power density of the laser at long distances.

[0082] 3.1.3 Third-order: Operation range mapping sub-model.

[0083] Maximum effective operating distance correction: Combining the power density ρ of the second-order model, a dynamic table of the damage threshold β is established for each target type, and the correction formula is as follows:

[0084] (r is the laser spot radius at the laser emitter);

[0085] Working angle correction: When the thermal management health level is less than 70%, the laser module will deviate from the emission angle by ±1° due to thermal deformation. The working angle will be automatically reduced by 2° to avoid missing the target due to beam deviation.

[0086] In this embodiment, model self-learning and iterative optimization are performed.

[0087] After each bomb disposal operation, the system automatically records the pre-assessment range → actual operation results and calculates the deviation value. Using the gradient descent algorithm, the K1, K2, and K3 coefficients of the heat loss model are iteratively optimized every 50 sets of data, so that the model accuracy continues to improve with the number of uses.

[0088] In this embodiment, the specific deviation calculation method is as follows:

[0089] Absolute deviation: Reflects the absolute difference between the actual result and the pre-assessment;

[0090] ;

[0091] A positive result indicates that the actual range is larger than the pre-evaluation, while a negative result indicates that the actual range is smaller.

[0092] Relative deviation: Reflects the degree of relative error in the pre-assessment (more intuitive);

[0093] ;

[0094] ③Comprehensive deviation of multiple indicators: If the working distance and coverage area are compared at the same time, the deviation can be calculated by weighting.

[0095] .

[0096] The specific implementation of the gradient descent algorithm (used to optimize the coefficients of the heat loss model) is as follows:

[0097] Assume the heat loss model is: P decay rate = K1×T + K2×V + K3×t, where T is the laser module temperature, V is the coolant flow rate, t is the operating time, and K1, K2, and K3 are coefficients to be optimized.

[0098] Derivation of the loss function (mean squared error):

[0099] The core of the loss function is to measure the difference between the predicted value and the actual value, and mean squared error is one of the most commonly used methods.

[0100] Error of a single sample: (Hreal, iHpreset, i)2 (squared to eliminate the cancellation of positive and negative errors, while amplifying larger errors);

[0101] The average error of all n samples: the average of the errors of a single sample, i.e.

[0102] The predicted heat loss Hprei here is obtained through a linear combination of features (Ti, Pi) and parameters (K1, K2, K3): Hprei = K1·Ti + K2·Pi + K3·Ti·Pi. The model assumes that heat loss is related to temperature, power, and the interaction term between the two. Therefore, the loss function is finally written as:

[0103] Define a loss function, using mean squared error, to measure the difference between predicted and actual heat loss:

[0104] ;

[0105] Where Loss is the loss function, which uses mean squared error to measure the difference between predicted and actual heat loss; n is the number of datasets involved in the calculation, calculated once every 50 datasets, so n=50; Hreal, i is the actual heat loss of the i-th dataset, the true observed value; Hpredict, i is the predicted heat loss of the i-th dataset, the result calculated by the model; Ti is the temperature feature in the i-th dataset, one of the input variables; Pi is the power feature in the i-th dataset, one of the input variables; K1, K2, K3 are the parameters to be optimized in the model, coefficients that need to be updated through gradient descent; α is the learning rate, which controls the step size of parameter updates, usually taken as 0.001~0.01.

[0106] In this embodiment, the gradient is calculated, and the partial derivatives of the loss function with respect to each coefficient are:

[0107] Gradient descent requires calculating the partial derivative of the loss function with respect to each parameter, i.e., the slope of the loss as the parameters change, to guide parameter updates.

[0108] by For example, let's derive it using the chain rule:

[0109] Given:

[0110]

[0111] Take the partial derivative with respect to K1:

[0112]

[0113] Similarly, the derivation :

[0114] Hpre, the partial derivative of i with respect to K2 is Pi, therefore:

[0115]

[0116] Derivation :

[0117] Hpre, the partial derivative of i with respect to K3 is Pi, therefore:

[0118] .

[0119] In this embodiment, the core logic of gradient descent is to update the parameters in the direction that reduces the loss, in the opposite direction of the partial derivatives.

[0120] The formula for parameter update is:

[0121] Knew = Kold - α· α is the learning rate, which controls the step size of the update. It avoids oscillations caused by a step size that is too large, and slow convergence caused by a step size that is too small. The minus sign means that if the partial derivative is positive, the parameter should be reduced; if the partial derivative is negative, the parameter should be increased, that is, the loss should eventually change in the direction of reduction.

[0122] Taking K1 as an example, combining the previous partial derivative results, the updated formula is:

[0123]

[0124] The update logic for K2 and K3 is completely consistent, ultimately yielding the system of equations for parameter updates, namely:

[0125]

[0126] Perform the gradient calculation and parameter update once every 50 sets of data accumulated, until the loss converges.

[0127] In this embodiment, dynamic correction and real-time early warning technology solve the problems of lagging evaluation results and fixed early warning thresholds;

[0128] Dynamic correction: From static evaluation to real-time adaptive correction;

[0129] Correction of triggering mechanism: Set three types of triggering conditions to realize dynamic updates of evaluation results: timed correction; threshold-triggered correction; and working condition switching correction.

[0130] Visual update of the corrected range: The effective operating sector on the vehicle-mounted electronic map is dynamically updated with a gradient. When the range expands, it gradually changes from green to dark green, and when it shrinks, it gradually changes from green to yellow, so as to avoid misjudgment by operators due to sudden changes in the range.

[0131] Real-time alerts: From single threshold alerts to tiered alerts plus intelligent recommendations;

[0132] Warning levels and thresholds are dynamically adjusted;

[0133] The warning system is divided into three levels, with the thresholds dynamically changing according to the thermal management status and operating conditions: Level 1 warning (green, normal); Level 2 warning (yellow, attention); Level 3 warning (red, danger).

[0134] Early warning and associated intelligent handling suggestions;

[0135] Breaking away from the limitations of traditional methods that only issue alarms without providing guidance, this system matches response plans to different warning levels:

[0136] Level 2 warning: A pop-up message on the screen suggests reducing the laser power by 10% or increasing the cooling fan speed to 120%.

[0137] Level 3 warning: In addition to the audible and visual alarm, the laser emission permission is automatically locked. The operator needs to confirm and adjust the distance between the vehicles to Lmax+1m or stop the operation for 5 minutes to cool down before unlocking.

[0138] Historical data correlation: When an alert is issued, the handling effects of the last three similar operating conditions are displayed simultaneously to assist in rapid decision-making.

[0139] In this embodiment, before operation, environmental parameters are collected, and the status of the thermal management system can be automatically monitored to obtain laser temperature, cooling liquid flow rate data, and system pressure data. Based on data such as laser output power, operation time, and target distance, the system automatically calculates and matches the heat dissipation data of the thermal management system to ensure the system meets the operation requirements under different ambient temperatures.

[0140] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their likenesses.

[0141] The present invention and its embodiments have been described above. This description is not restrictive, and the accompanying drawings are only one embodiment of the present invention; the actual structure is not limited thereto. In conclusion, if those skilled in the art are inspired by this description and design similar structures and embodiments without departing from the spirit of the invention, such designs should fall within the protection scope of the present invention.

Claims

1. A pre-assessment system for the operational range of a laser bomb disposal vehicle with thermal management function, characterized in that: It includes an environmental parameter acquisition module, a thermal management status monitoring module, a laser performance monitoring module, a data processing and evaluation module, and a result output module; The environmental parameter acquisition module is used to collect dynamic parameters of the working environment, such as temperature, humidity, and wind speed, in real time. The thermal management status monitoring module is used to monitor the full-link parameters of the thermal management system of the laser bomb disposal vehicle, including heat generation, heat transfer, and heat dissipation. The laser performance monitoring module is used to collect the output performance parameters of the laser in real time. The data processing and evaluation module is used to integrate the data from the above modules and calculate the work scope through a preset model; The result output module is used to feed back the pre-evaluation results to the operator.

2. The operational range pre-assessment system for a laser bomb disposal vehicle with thermal management function according to claim 1, characterized in that: The environmental parameter acquisition module includes a temperature sensor, a humidity sensor, and a wind speed sensor. The temperature sensor is used to accurately collect ambient temperature data; the humidity sensor can be adapted to different humidity conditions in different operating scenarios; and the wind speed sensor's range meets the wind speed monitoring needs in both conventional and complex wind field environments. The three types of sensors work together to collect dynamic environmental parameters.

3. The operational range pre-assessment system for a laser bomb disposal vehicle with thermal management function according to claim 2, characterized in that: The environmental parameter acquisition module collects ambient temperature, humidity, and wind speed data, which are transmitted in real time to the data processing and evaluation module via a data bus. The humidity parameter directly participates in the laser energy attenuation calculation. The system calculates the change in laser energy attenuation rate at different distances based on the data, providing a quantitative basis for adjusting the operating range.

4. The operational range pre-assessment system for a laser bomb disposal vehicle with thermal management function according to claim 3, characterized in that: The thermal management status monitoring module includes a temperature sensor, a flow sensor, a pressure sensor, and a thermal management system controller. The temperature sensor is used to measure the temperature of the laser body and the inlet and outlet temperatures of the cooling medium. The flow sensor is used to measure the flow rate of the cooling medium. The pressure sensor is used to measure the pressure of the cooling system. The thermal management system controller is used to read the start / stop status and power output data of the cooling device, comprehensively covering the core operating parameters of the thermal management system.

5. The operational range pre-assessment system for a laser bomb disposal vehicle with thermal management function according to claim 4, characterized in that: The thermal management status monitoring module integrates parameters such as laser body temperature, cooling medium flow rate, and cooling system pressure to determine the heat dissipation capacity of the thermal management system for the laser. When the laser temperature exceeds a preset threshold, the system automatically determines that the heat dissipation efficiency has decreased and transmits the determination result to the data processing and evaluation module.

6. The operational range pre-assessment system for a laser bomb disposal vehicle with thermal management function according to claim 5, characterized in that: The laser performance monitoring module includes a power meter, a beam quality analyzer, and a wavelength meter. The power meter is used to collect laser output power in real time; the beam quality analyzer is used to measure the laser beam divergence angle and beam quality factor; and the wavelength meter is used to monitor the laser wavelength in real time. The three types of equipment work synchronously to comprehensively capture the dynamic changes in the laser output performance.

7. The operational range pre-assessment system for a laser bomb disposal vehicle with thermal management function according to claim 6, characterized in that: The laser output power data collected by the laser performance monitoring module directly reflects the laser's ablation capability against unexploded ordnance. When a decrease in output power is detected, the data processing and evaluation module automatically associates it with the working distance adjustment logic and shortens the effective working distance through quantitative calculation.

8. The operational range pre-assessment system for a laser bomb disposal vehicle with thermal management function according to claim 7, characterized in that: The workflow of the data processing and evaluation module includes data preprocessing, correlation model establishment and dynamic correction. In the data preprocessing stage, the collected environmental parameters, thermal management status parameters and laser performance parameters are filtered, denoised and normalized to eliminate data interference.

9. The operational range pre-assessment system for a laser bomb disposal vehicle with thermal management function according to claim 8, characterized in that: The correlation model of the data processing and evaluation module takes ambient temperature, humidity, wind speed, laser temperature, cooling medium flow rate, laser output power and beam divergence angle as input parameters, and the maximum effective working distance and working angle range of different types of targets as output parameters. The model is established based on experimentally fitted environmental parameters-laser energy attenuation curve, laser temperature-output power attenuation curve and beam divergence angle-energy focusing efficiency curve.

10. The operational range pre-assessment system for a laser bomb disposal vehicle with thermal management function according to claim 9, characterized in that: The result output module includes a vehicle-mounted display screen and an audible and visual alarm. The vehicle-mounted display screen is used to simultaneously display real-time operating range values ​​and a visual range diagram, providing intuitive feedback on the pre-assessment results. The audible and visual alarm automatically activates when it detects that the operating range is below the safety threshold, issuing a warning to the operator through audible and visual prompts.

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