Vehicle front axle detection method, device, equipment and medium

Abstract

The invention discloses a vehicle front axle detection method, device and equipment and a medium. The method comprises the following steps: inputting a detection current into a bridge circuit configured on a front axle of a to-be-detected vehicle; the bridge circuit comprises a first parallel branch and a second parallel branch, the first parallel branch comprises a strain gauge and a resistor element, and the second parallel branch comprises a resistor element; acquiring the potential of the first sampling point and the potential of the second sampling point; determining a voltage value of the bridge circuit according to the potential of the first sampling point and the potential of the second sampling point; calculating a pressure value of the front axle according to the voltage value; comparing the pressure value with a front axle fault threshold value to obtain a pressure comparison result; and determining a front axle fault detection result of the to-be-detected vehicle according to the pressure comparison result. According to the embodiment of the invention, the accuracy of detecting the health state of the vehicle front axle can be improved.

Description

Technical Field

[0001] The present invention relates to the field of vehicle detection technology, and in particular to a vehicle front axle detection method, device, equipment and medium. Background Art

[0002] With the development of intelligent manufacturing and autonomous driving technologies, autonomous vehicles are increasingly handling factory logistics and transportation tasks. In particular, in large industrial parks, ports, or warehousing and logistics centers, autonomous logistics vehicles with automatic navigation and path planning capabilities have been deployed to improve transportation efficiency and reduce labor costs. However, in actual operation, due to the varying quality of factory road pavement, undetected potholes or rain-filled flooded sections often exist. Ground defects typically lack visual characteristics, making it difficult for sensors such as lidar and cameras in autonomous driving systems to detect these potholes or flooded sections. This can cause vehicles to enter potholes at normal speeds, causing severe vibrations in the vehicle body structure. The front axle, in particular, is more susceptible to fracture or structural fatigue under high-frequency impacts, posing a significant safety hazard. Therefore, it is necessary to monitor the health of the vehicle's front axle.

[0003] Currently, the existing detection method is to monitor the vibration frequency or acceleration change trend of the front axle by installing an acceleration sensor on the vehicle chassis to detect the health status of the front axle.

[0004] However, the above method is susceptible to external interference, such as loose equipment, temperature changes, or mud and sand obstruction, which may lead to misjudgment or missed judgment. The warning is triggered only after the front axle undergoes structural deformation or failure, and lacks the ability to continuously monitor and predict the stress trend of the front axle structure in advance. Summary of the Invention

[0005] The present invention provides a vehicle front axle detection method, device, equipment and medium. The embodiments of the present invention can improve the accuracy of health status detection of the vehicle front axle.

[0006] In a first aspect, an embodiment of the present invention provides a vehicle front axle detection method, the method comprising:

[0007] Inputting a detection current into a bridge circuit configured for the front axle of the vehicle to be detected; the bridge circuit includes a first parallel branch and a second parallel branch, the first parallel branch includes a strain gauge and a resistance element, and the second parallel branch includes a resistance element;

[0008] Acquire the potential of the first sampling point and the potential of the second sampling point;

[0009] determining a voltage value of the bridge circuit according to the potential of the first sampling point and the potential of the second sampling point;

[0010] Calculate the pressure value of the front axle according to the voltage value;

[0011] Comparing the pressure value with the front axle fault threshold to obtain a pressure comparison result;

[0012] The front axle fault detection result of the vehicle to be detected is determined based on the pressure comparison result.

[0013] In a second aspect, an embodiment of the present invention further provides a vehicle front axle detection device, the device comprising:

[0014] A detection current input module is used to input a detection current into a bridge circuit configured for the front axle of the vehicle to be detected; the bridge circuit includes a first parallel branch and a second parallel branch, the first parallel branch includes a strain gauge and a resistance element, and the second parallel branch includes a resistance element;

[0015] A potential acquisition module, configured to acquire the potential of a first sampling point and the potential of a second sampling point;

[0016] a voltage value determining module, configured to determine a voltage value of the bridge circuit according to the potential of the first sampling point and the potential of the second sampling point;

[0017] A pressure value calculation module is used to calculate the pressure value of the front axle according to the voltage value;

[0018] A pressure comparison result determination module is used to compare the pressure value with the front axle fault threshold to obtain a pressure comparison result;

[0019] The front axle fault detection module is used to determine the front axle fault detection result of the vehicle to be detected based on the pressure comparison result.

[0020] In a third aspect, an embodiment of the present invention further provides a vehicle front axle detection device, the vehicle front axle detection device comprising:

[0021] at least one processor; and

[0022] a memory communicatively connected to at least one processor; wherein,

[0023] The memory stores a computer program that can be executed by at least one processor. The computer program is executed by the at least one processor so that the at least one processor can execute the vehicle front axle detection method according to any embodiment of the present invention.

[0024] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the vehicle front axle detection method of any embodiment of the present invention when executed.

[0025] The technical solution of the embodiment of the present invention obtains the voltage response related to the strain gauge on the front axle by inputting a detection current into the bridge circuit configured for the front axle. By providing a first parallel branch and a second parallel branch, where the first branch contains the strain gauge, the resistance changes under the action of stress, thereby causing a change in the potential difference output by the bridge circuit, which helps to indirectly reflect the change in the pressure on the front axle. By obtaining the potential at the first sampling point and the second sampling point and determining the voltage value, the voltage value of the bridge circuit can be accurately measured. By calculating the front axle pressure value based on the voltage value, the weak electrical signal can be converted into a pressure value, thereby quantifying the stress condition of the front axle. By comparing the front axle pressure value with a preset front axle fault threshold, the front axle status can be determined, which helps to promptly detect abnormal stress conditions. Ultimately, the front axle fault detection result is determined based on the pressure comparison result, which can improve the safety and reliability of the vehicle during operation to a certain extent. The technical problem of the difficulty in timely and accurate detection of the stress condition of the front axle and identification of whether the front axle structure has faults in unmanned vehicles is solved, thereby improving the accuracy of the health status detection of the vehicle's front axle.

[0026] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0028] Figure 1 A flow chart of a vehicle front axle detection method provided by an embodiment of the present invention;

[0029] Figure 2 A flow chart of a vehicle front axle detection method provided by an embodiment of the present invention;

[0030] Figure 3 A schematic diagram of a vehicle front axle detection method provided by an embodiment of the present invention;

[0031] Figure 4 A layout diagram of a printed circuit board in a vehicle front axle detection method provided by an embodiment of the present invention;

[0032] Figure 5 A schematic structural diagram of a vehicle front axle detection device provided by an embodiment of the present invention;

[0033] Figure 6 A schematic structural diagram of a vehicle front axle detection device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0034] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0035] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0036] In the technical solutions of the embodiments of the present invention, the acquisition, storage and application of the electric potential, voltage values ​​and pressure values ​​involved all comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0037] Figure 1 This is a flow chart of a vehicle front axle detection method provided by an embodiment of the present invention. This embodiment of the present invention is applicable to detecting the health status of the front axle of an unmanned factory logistics vehicle. This method can be performed by a vehicle front axle detection device, which can be implemented in hardware and / or software.

[0038] See also Figure 1 The vehicle front axle detection method shown includes:

[0039] S101. Input a detection current to a bridge circuit configured for a front axle of a vehicle to be detected; the bridge circuit includes a first parallel branch and a second parallel branch, the first parallel branch includes a strain gauge and a resistance element, and the second parallel branch includes a resistance element.

[0040] The vehicle to be tested may refer to a vehicle whose front axle health status needs to be monitored. The vehicle to be tested may include: unmanned vehicles, especially unmanned logistics vehicles operating in closed environments such as factories and parks. For example, assuming that the vehicle to be tested is an unmanned logistics vehicle traveling within a factory, and its front axle passes through a pothole section or a flooded section filled with rainwater without slowing down, it is necessary to detect whether the front axle of the vehicle to be tested has a tendency to break, leading to the risk of a safety accident.

[0041] The front axle refers to a structural member in the vehicle chassis system that supports the front wheels and bears the front load of the vehicle. During driving, the front axle experiences stress changes due to uneven roads, braking, steering, and other operations. When the vehicle passes through an abnormal road condition, the front axle will be the first to pass through the abnormal road condition. For example, when the vehicle to be tested passes through a puddle of water while driving, the front axle is instantly subjected to a large impact, which may cause the strain gauges arranged on the front axle to undergo significant deformation, resulting in changes in the resistance of the strain gauges.

[0042] A bridge circuit refers to a circuit structure composed of multiple resistor elements. By comparing the voltage differences between different parallel branches, the bridge circuit amplifies the tiny resistance changes caused by the strain gauge under load and converts them into a measurable electrical signal. As the core detection module, the bridge circuit is used to convert the stress of the front axle structure into a voltage value.

[0043] The sense current is a stable current input into the bridge circuit for excitation. This current is used to create a potential difference between the branches of the bridge circuit, thereby measuring the voltage change. The sense current serves as a basic measurement condition, ensuring the bridge circuit is functioning properly.

[0044] The first parallel branch can be one of the two parallel paths in the bridge circuit, connecting a strain gauge and a resistor in series. The change in the strain gauge's resistance affects the total resistance of the branch, indirectly affecting the bridge's output voltage. For example, under stress, the strain gauge's resistance changes from x ohms to y ohms, thus affecting the voltage distribution in the branch.

[0045] The second parallel branch may be another branch in the bridge circuit corresponding to the first branch, consisting solely of two resistors connected in series. The second parallel branch serves as a reference branch, unchanged by stress, and serves as a comparison benchmark. For example, the second branch may be fixedly comprised of two resistors of x ohms, resulting in a constant overall resistance, for use in bridge comparison.

[0046] Among them, the strain gauge can refer to a sensor element that measures tiny deformations. The strain gauge is usually made of metal wire or metal foil and is attached to the structural surface of the front axle. When the structure of the front axle is deformed, the strain gauge is stretched or compressed, and the resistance of the strain gauge also changes accordingly.

[0047] A resistor is an electronic component with a fixed resistance value. It is used in circuits to regulate voltage or current or act as a load. In bridge circuits, resistors act as fixed resistance references, forming bridge arms and participating in voltage division.

[0048] S102 : Acquire the potential of the first sampling point and the potential of the second sampling point.

[0049] The first sampling point can be the location in the bridge circuit used to collect the first measured potential. The first sampling point is typically located between the strain gauge and the resistor in the first parallel branch. The first sampling point is used to obtain the potential at a node in a bridge branch, providing a basis for subsequent voltage difference calculations.

[0050] The second sampling point may be another measurement node opposite to the first sampling point, also located in the bridge circuit, for obtaining the potential value on the second parallel branch. The first sampling point is typically located between the two resistor elements in the second parallel branch.

[0051] Potential refers to the electrical potential at a point in a circuit relative to a reference point. The difference in potential is the voltage, the core of bridge measurement.

[0052] S103 : Determine a voltage value of the bridge circuit according to the potential at the first sampling point and the potential at the second sampling point.

[0053] The voltage value may refer to the difference in potential between the first sampling point and the second sampling point, reflecting the output caused by the change in resistance of the bridge branch.

[0054] S104: Calculate the pressure value of the front axle according to the voltage value.

[0055] The pressure value refers to the force per unit area of ​​the front axle structure when it is subjected to stress. The pressure value can be converted from the voltage value. The pressure value is used to quantify the stress strength of the front axle structure and provide a basis for fault diagnosis.

[0056] S105 : Compare the pressure value with the front axle fault threshold to obtain a pressure comparison result.

[0057] The front axle fault threshold can refer to a set upper limit for front axle pressure. Exceeding this threshold is considered a potential or actual fault. The front axle fault threshold serves as a reference for determining whether a front axle is abnormal. For example, if the threshold is set to 4.0 MPa, then if the measured pressure exceeds this threshold multiple times within a time window, a front axle abnormality is considered.

[0058] The pressure comparison result may refer to a result obtained by comparing the actually measured front axle pressure value with the front axle fault threshold.

[0059] S106 : Determine a front axle fault detection result of the vehicle to be detected based on the pressure comparison result.

[0060] The front axle fault detection result can refer to the final determination based on the pressure comparison results, indicating whether the front axle is currently at risk of structural failure. The front axle fault detection result is used to output the conclusion of the detection process and can be used by the vehicle control system or maintenance system.

[0061] As can be seen, in the embodiments of the present application, by inputting a detection current into the bridge circuit configured for the front axle, a voltage response related to the strain gauge on the front axle can be obtained. By providing a first parallel branch and a second parallel branch, where the first branch includes a strain gauge, a resistance change can be generated under the action of stress, thereby causing a change in the potential difference output by the bridge circuit, which helps to indirectly reflect the change in pressure on the front axle. By obtaining the potential at the first sampling point and the second sampling point and determining the voltage value, the voltage value of the bridge circuit can be accurately measured. By calculating the front axle pressure value based on the voltage value, a weak electrical signal can be converted into a pressure value, thereby quantifying the stress condition of the front axle. By comparing the front axle pressure value with a preset front axle fault threshold, the front axle state can be determined, which helps to promptly detect abnormal stress conditions. Ultimately, the front axle fault detection result is determined based on the pressure comparison result, which can improve the safety and reliability of the vehicle during operation to a certain extent. The technical problem of difficulty in timely and accurate detection of the stress condition of the front axle and identification of whether the front axle structure has a fault in unmanned vehicles is solved, thereby improving the accuracy of the health status detection of the vehicle's front axle.

[0062] In an optional embodiment, Figure 2 A flowchart of a vehicle front axle detection method provided in an embodiment of the present invention refines "calculating the pressure value of the front axle based on the voltage value" into "determining the voltage interval to which the voltage value belongs based on the voltage value; calculating the pressure value of the front axle based on the voltage interval and the segmented voltage-pressure relationship corresponding to the voltage interval" to improve the operation of vehicle front axle detection.

[0063] It should be noted that for parts not described in detail in the embodiments of the present invention, reference may be made to the descriptions of other embodiments.

[0064] See also Figure 2 The vehicle front axle detection method shown includes:

[0065] S201. Input a detection current to a bridge circuit configured for a front axle of a vehicle to be detected; the bridge circuit includes a first parallel branch and a second parallel branch, the first parallel branch includes a strain gauge and a resistance element, and the second parallel branch includes a resistance element.

[0066] S202 , obtaining the potential of a first sampling point and the potential of a second sampling point; the first sampling point is located between the strain gauge and the resistance element in the first parallel branch, and the second sampling point is located between the two resistance elements in the second parallel branch.

[0067] S203 : Determine a voltage value of the bridge circuit according to the potential at the first sampling point and the potential at the second sampling point.

[0068] S204: Determine the voltage range to which the voltage value belongs according to the voltage value.

[0069] The voltage interval may refer to dividing the entire possible voltage value range into several continuous and non-overlapping sub-ranges according to the variation range of the voltage value, and each interval corresponds to a section of an approximately linear or modeled voltage and pressure conversion relationship.

[0070] Specifically, because the correspondence between voltage and pressure values ​​typically follows a nonlinear curve distribution, it is difficult to accurately represent it using a single analytical function. Therefore, to facilitate calculation and implementation, this correspondence is divided into several small voltage intervals. Within each voltage interval, the relationship between voltage and pressure can be approximated using a relatively simplified mathematical model, forming a set of segmented voltage-pressure equations. By determining the voltage interval in which the current voltage value falls and applying the corresponding equation, the pressure value corresponding to that voltage value can be calculated.

[0071] S205 : Calculate the pressure value of the front axle according to the voltage interval and the segmented voltage-pressure relationship corresponding to the voltage interval.

[0072] The segmented voltage-pressure relationship refers to a mathematical function expression established for each voltage interval to express the corresponding relationship between voltage and pressure within that interval. The original relationship between voltage and pressure is a continuous but difficult-to-express nonlinear curve. This curve is approximated as a local expression within a small interval to simplify overall function modeling. The segmented functions can be continuous or discontinuous at the interval boundaries, depending on the actual modeling strategy. The segmented voltage-pressure relationship approximates the nonlinear strain response, enabling rapid calculation of the front axle pressure value.

[0073] S206 : Compare the pressure value with the front axle fault threshold to obtain a pressure comparison result.

[0074] S207: Determine a front axle fault detection result of the vehicle to be detected based on the pressure comparison result.

[0075] It can be seen that in this embodiment, by determining the voltage interval to which the voltage value belongs, the nonlinear voltage-pressure relationship can be processed in segments, which simplifies the expression and calculation of complex curve relationships; by applying the corresponding segmented voltage-pressure relationship formula to calculate the pressure value in each voltage interval, the accuracy and speed of pressure calculation can be improved.

[0076] In some embodiments, calculating the pressure value of the front axle according to the voltage interval and the segmented voltage-pressure relationship corresponding to the voltage interval includes:

[0077] Determine the pressure value of the strain gauge in the bridge circuit based on the voltage interval and the segmented voltage-pressure relationship corresponding to the voltage interval;

[0078] Calculate the pressure value of the front axle based on the pressure value of the strain gauge.

[0079] Specifically, based on the pressure value of the strain gauge, the pressure value of the front axle can be calculated in the following way: the local pressure value at the location is obtained through strain gauge detection; based on the pressure value and the force area of ​​the strain gauge attachment position, the force value at the location is determined; the force values ​​of multiple strain gauges are substituted into the mechanical model to calculate the pressure value of the entire front axle; in the case of symmetrical structure, the total pressure value of the front axle is the sum of the force values ​​at the left and right ends; if the structure is asymmetrical, the torque balance correction is further performed in combination with the strain gauge position and the vehicle geometry to accurately obtain the pressure value of the front axle.

[0080] It can be seen that in this embodiment, by calculating the pressure value of the strain gauge based on the voltage interval and the segmented voltage-pressure relationship, the electrical signal can be more accurately converted into the corresponding physical pressure value, which helps to improve the accuracy of pressure measurement; due to the use of the segmented voltage-pressure relationship, the nonlinear response characteristics of the strain gauge in different voltage intervals can be adapted, thereby improving the accuracy problem of the traditional linear model in high strain or low strain sections; by first calculating the pressure value of the strain gauge and then further calculating the pressure value of the front axle, the measurement process has a stronger physical hierarchical structure, which is conducive to modular modeling and error analysis.

[0081] In some embodiments, the vehicle to be detected includes a long-wheelbase unmanned vehicle.

[0082] Specifically, long-wheelbase vehicles have a greater distance between the front and rear axles, resulting in higher structural rigidity. However, they also have slower steering response and more sensitive handling, placing higher demands on front axle load and road adaptability. Therefore, more accurate front axle pressure detection is required to ensure stable driving and the correct decision-making of the autonomous driving system. If an anomaly occurs in front axle detection, deceleration or braking can be applied to minimize damage to the rear axle. Since manual driving allows the driver to detect potholes or flooded roads through physical sensation and visual perception, damage to the front axle can be avoided. Therefore, the use of unmanned vehicles can reduce costs.

[0083] It can be seen that in this embodiment, by limiting the vehicle to be detected to a long-wheelbase unmanned vehicle, the detection method can be applied to unmanned vehicles with a long front-to-rear axle distance and high requirements for front axle pressure detection.

[0084] In some embodiments, after determining a front axle fault detection result of the vehicle to be detected based on the pressure comparison result, the method further includes:

[0085] When the front axle fault detection result of the vehicle to be detected is abnormal, the vehicle to be detected is controlled to brake.

[0086] It can be seen that in this embodiment, by controlling the vehicle to be detected to brake when the front axle fault is detected to be abnormal, a timely response to the front axle fault can be achieved, thereby preventing the vehicle from continuing to drive in an abnormal state, and reducing the risk of damage to the rear axle by braking; controlling the vehicle to brake helps to reduce the driving risks that may be caused by front axle failure and improves the safety of vehicle driving; automatically controlling the braking when the front axle fault detection result is abnormal can reduce human intervention and improve the system's automated processing capabilities.

[0087] In some embodiments, the bridge circuit comprises a Wheatstone bridge circuit.

[0088] It can be seen that in this embodiment, through the structural characteristics of the Wheatstone bridge circuit, tiny resistance changes in the bridge circuit can be sensitively detected, thereby improving the accuracy of pressure detection; the Wheatstone bridge has differential detection capabilities. When the resistance of the two branches changes, its output voltage reflects the resistance difference between the two branches, thereby reducing the impact of common-mode interference such as ambient temperature on the pressure detection results; using the Wheatstone bridge circuit, zero point adjustment and sensitivity adjustment can be achieved by adjusting the resistance value of each arm of the bridge, which is conducive to adapting to the parameter configuration requirements under different sensing applications; when combined with strain gauges to form the bridge arm resistance, the Wheatstone bridge can convert tiny mechanical deformations into obvious voltage signals, thereby facilitating subsequent voltage acquisition and processing.

[0089] In an optional embodiment, the strain gauge adopts a nominal resistance of 120 ohms, a maximum deformation of 2%, and an operating temperature of -40 degrees to 135 degrees; the bridge adopts a Wheatstone bridge mode, a bridge circuit composed of four resistors, and the four resistors are called bridge arms of the bridge. Changes in the resistance of the strain gauge will cause corresponding voltage changes. The voltage signal taken out by the bridge is input into the analog-to-digital converter and then sent to the microcontroller; nonlinear compensation is performed in the internal program of the microcontroller, and the compensated data is displayed on the LCD screen after algorithm processing and uploaded to the host computer through the serial port for further analysis and processing; the power supply voltage of the bridge is controlled by the microcontroller, and the voltage is adjustable from 0V to 10V.

[0090] Figure 3 This is a schematic diagram of a vehicle front axle detection method provided by an embodiment of the present invention. For micro-electric signal measurement, interference factors should be fully considered when designing the circuit. First, the size of the printed circuit board (PCB) should be considered. If the PCB is too large, the printed lines will be longer, the impedance will increase, the noise immunity will decrease, and the cost will increase. If the PCB is too small, the heat dissipation performance will be poor and adjacent lines will be susceptible to interference. Second, the positions of the various functional circuit units should be arranged according to the circuit flow, so that the layout facilitates signal flow and keeps the signals in the same direction as much as possible. To further eliminate power supply interference, the power supply for all components on the circuit board is provided by the same power supply. The digital power supply, analog power supply, and reference power supply are isolated and confined to specific areas. They are all decoupled with 10uF tantalum capacitors and 0.1uF ceramic capacitors, and the capacitors are placed as close to the power pins as possible. To accommodate a wide range of operating conditions, the power supply voltage is 220V AC. A transformer converts the 220V AC into 16V and 8V AC before supplying it to the PCB. After determining the device selection and power supply circuit design principles,

[0091] Figure 4 This is a layout diagram for a printed circuit board (PCB) used in a vehicle front axle detection method according to an embodiment of the present invention. When laying out the PCB, analog components and digital components are placed separately. During PCB routing, noise interference from power and ground wires is minimized to ensure product quality. After routing according to these principles, the PCB is fabricated after testing is complete.

[0092] Figure 5 A schematic diagram of the structure of a vehicle front axle detection device provided by an embodiment of the present invention. This embodiment of the present invention is applicable to detecting the health status of the front axle of an unmanned factory logistics vehicle. The device can execute a vehicle front axle detection method and can be implemented in hardware and / or software.

[0093] See also Figure 5The vehicle front axle detection device shown includes: a detection current input module 501, a potential acquisition module 502, a voltage value determination module 503, a pressure value calculation module 504, a pressure comparison result determination module 505 and a front axle fault detection module 506, wherein:

[0094] A detection current input module 501 is used to input a detection current into a bridge circuit configured for the front axle of the vehicle to be detected; the bridge circuit includes a first parallel branch and a second parallel branch, the first parallel branch includes a strain gauge and a resistor element, and the second parallel branch includes a resistor element;

[0095] A potential acquisition module 502 is used to acquire the potential of the first sampling point and the potential of the second sampling point;

[0096] A voltage value determination module 503 is configured to determine a voltage value of the bridge circuit according to the potential of the first sampling point and the potential of the second sampling point;

[0097] A pressure value calculation module 504 is used to calculate the pressure value of the front axle according to the voltage value;

[0098] A pressure comparison result determination module 505 is used to compare the pressure value with the front axle fault threshold to obtain a pressure comparison result;

[0099] The front axle fault detection module 506 is configured to determine a front axle fault detection result of the vehicle to be detected based on the pressure comparison result.

[0100] The technical solution of the embodiment of the present invention obtains the voltage response related to the strain gauge on the front axle by inputting a detection current into the bridge circuit configured for the front axle. By providing a first parallel branch and a second parallel branch, where the first branch contains the strain gauge, the resistance changes under the action of stress, thereby causing a change in the potential difference output by the bridge circuit, which helps to indirectly reflect the change in the pressure on the front axle. By obtaining the potential at the first sampling point and the second sampling point and determining the voltage value, the voltage value of the bridge circuit can be accurately measured. By calculating the front axle pressure value based on the voltage value, the weak electrical signal can be converted into a pressure value, thereby quantifying the stress condition of the front axle. By comparing the front axle pressure value with a preset front axle fault threshold, the front axle status can be determined, which helps to promptly detect abnormal stress conditions. Ultimately, the front axle fault detection result is determined based on the pressure comparison result, which can improve the safety and reliability of the vehicle during operation to a certain extent. The technical problem of the difficulty in timely and accurate detection of the stress condition of the front axle and identification of whether the front axle structure has faults in unmanned vehicles is solved, thereby improving the accuracy of the health status detection of the vehicle's front axle.

[0101] In some embodiments, the first sampling point is located between the strain gauge and the resistor element in the first parallel branch, and the second sampling point is located between the two resistor elements in the second parallel branch.

[0102] In some embodiments, in calculating the pressure value of the front axle based on the voltage value, the pressure value calculation module 504 is specifically configured to:

[0103] According to the voltage value, determining the voltage interval to which the voltage value belongs;

[0104] The pressure value of the front axle is calculated based on the voltage interval and the segmented voltage-pressure relationship corresponding to the voltage interval.

[0105] In some embodiments, in calculating the pressure value of the front axle based on the voltage interval and the segmented voltage-pressure relationship corresponding to the voltage interval, the pressure value calculation module 504 is specifically configured to:

[0106] Determine the pressure value of the strain gauge in the bridge circuit based on the voltage interval and the segmented voltage-pressure relationship corresponding to the voltage interval;

[0107] Calculate the pressure value of the front axle based on the pressure value of the strain gauge.

[0108] In some embodiments, the vehicle to be detected includes a long-wheelbase unmanned vehicle.

[0109] In some embodiments, after determining the front axle fault detection result of the vehicle to be detected based on the pressure comparison result, the front axle fault detection module 506 is further specifically configured to:

[0110] When the front axle fault detection result of the vehicle to be detected is abnormal, the vehicle to be detected is controlled to brake.

[0111] In some embodiments, the bridge circuit comprises a Wheatstone bridge circuit.

[0112] The vehicle front axle detection device provided in the embodiment of the present invention can execute the vehicle front axle detection method provided in any embodiment of the present invention, and has corresponding functional modules and beneficial effects for executing the vehicle front axle detection method.

[0113] Figure 6 A schematic structural diagram of a vehicle front axle detection device provided in an embodiment of the present invention.

[0114] like Figure 6As shown, the vehicle front axle detection device 600 includes at least one processor 601 and a memory connected to the at least one processor 601, such as a read-only memory (ROM) 602, a random access memory (RAM) 603, etc., wherein the memory stores a computer program that can be executed by the at least one processor, and the processor 601 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 602 or the computer program loaded from the storage unit 608 to the random access memory (RAM) 603. Various programs and data required for the operation of the vehicle front axle detection device 600 can also be stored in the RAM 603. The processor 601, ROM 602 and RAM 603 are connected to each other via a bus 604. An input / output (I / O) interface 608 is also connected to the bus 604.

[0115] Multiple components in the vehicle front axle detection device 600 are connected to the I / O interface 605, including an input unit 606, such as a keyboard and mouse; an output unit 607, such as various types of displays and speakers; a storage unit 608, such as a magnetic disk and optical disk; and a communication unit 609, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 609 allows the vehicle front axle detection device 600 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0116] The processor 601 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of the processor 601 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 601 executes the various methods and processes described above, such as the vehicle front axle detection method.

[0117] In some embodiments, the vehicle front axle detection method can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 608. In some embodiments, part or all of the computer program can be loaded and / or installed on the vehicle front axle detection device 600 via the ROM 602 and / or the communication unit 609. When the computer program is loaded into the RAM 603 and executed by the processor 601, one or more steps of the vehicle front axle detection method described above can be performed. Alternatively, in other embodiments, the processor 601 can be configured to perform the vehicle front axle detection method in any other appropriate manner (for example, by means of firmware).

[0118] Various embodiments of the systems and techniques described above can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0119] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer program is executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer program may be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0120] In the context of the present invention, computer-readable storage media can be tangible media that can contain or store a computer program for use with an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. Computer-readable storage media can include but are not limited to electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, computer-readable storage media can be machine-readable signal media. More specific examples of machine-readable storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0121] To provide interaction with a user, the systems and techniques described herein can be implemented on an operational detection device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and pointing device (e.g., a mouse or trackball) through which a user can provide input to the vehicle front axle detection device. Other types of devices can also be used to provide interaction with a user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0122] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0123] A computing system may include clients and servers. The clients and servers are generally remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within a cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS (Virtual Private Server) services.

[0124] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved. This is not limited herein.

[0125] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A vehicle front axle detection method, characterized in that: The method comprises: Inputting a detection current into a bridge circuit configured for the front axle of the vehicle to be detected; the bridge circuit includes a first parallel branch and a second parallel branch, the first parallel branch includes a strain gauge and a resistance element, and the second parallel branch includes a resistance element; Acquire the potential of the first sampling point and the potential of the second sampling point; determining a voltage value of the bridge circuit according to the potential of the first sampling point and the potential of the second sampling point; Calculating a pressure value of the front axle according to the voltage value; comparing the pressure value with a front axle fault threshold to obtain a pressure comparison result; A front axle fault detection result of the vehicle to be detected is determined according to the pressure comparison result.

2. The method according to claim 1, characterized in that The first sampling point is located between the strain gauge and the resistance element in the first parallel branch, and the second sampling point is located between the two resistance elements in the second parallel branch.

3. The method according to claim 1, characterized in that Calculating the pressure value of the front axle according to the voltage value includes: determining, according to the voltage value, a voltage interval to which the voltage value belongs; The pressure value of the front axle is calculated according to the voltage interval and the segmented voltage-pressure relationship formula corresponding to the voltage interval.

4. The method according to claim 3, characterized in that Calculating the pressure value of the front axle according to the voltage interval and the segmented voltage-pressure relationship corresponding to the voltage interval includes: determining a pressure value of a strain gauge in the bridge circuit according to the voltage interval and a segmented voltage-pressure relationship corresponding to the voltage interval; The pressure value of the front axle is calculated according to the pressure value of the strain gauge.

5. The method according to claim 1, wherein The vehicle to be detected includes an unmanned vehicle with a long wheelbase.

6. The method according to claim 5, characterized in that After determining the front axle fault detection result of the vehicle to be detected according to the pressure comparison result, the method further includes: When the front axle fault detection result of the vehicle to be detected is abnormal, the vehicle to be detected is controlled to brake.

7. The method according to claim 1, characterized in that The bridge circuit includes a Wheatstone bridge circuit.

8. A vehicle front axle detection device, characterized in that: include: a detection current input module, configured to input a detection current into a bridge circuit configured for the front axle of the vehicle to be detected; the bridge circuit includes a first parallel branch and a second parallel branch, the first parallel branch includes a strain gauge and a resistance element, and the second parallel branch includes a resistance element; A potential acquisition module, configured to acquire the potential of a first sampling point and the potential of a second sampling point; a voltage value determining module, configured to determine a voltage value of the bridge circuit according to the potential of the first sampling point and the potential of the second sampling point; a pressure value calculation module, configured to calculate a pressure value of the front axle according to the voltage value; a pressure comparison result determination module, configured to compare the pressure value with a front axle fault threshold to obtain a pressure comparison result; The front axle fault detection module is used to determine a front axle fault detection result of the vehicle to be detected based on the pressure comparison result.

9. A vehicle front axle detection device, characterized in that: The vehicle front axle detection device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor. The computer program is executed by the at least one processor so as to enable the at least one processor to perform the vehicle front axle detection method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the vehicle front axle detection method according to any one of claims 1 to 7 when executed.

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