A method for evaluating man-machine matching degree of individual soldier tractor based on multi-element sensor

Abstract

This disclosure relates to a method, device, electronic device, and storage medium for evaluating the human-machine compatibility of a single-soldier towing vehicle based on multiple sensors. The method includes: a pre-set test personnel wearing the single-soldier towing vehicle human-machine compatibility evaluation device completing a pre-set number of pre-set test actions, and collecting pre-set indicators based on the sensors used for evaluating the human-machine compatibility of the single-soldier towing vehicle; using the pre-set indicators as input, generating multiple sets of evaluation standards based on pre-set evaluation standard calculation rules; and calculating and generating a human-machine compatibility evaluation result based on the evaluation standards and their corresponding pre-set weight coefficients, thus completing the human-machine compatibility evaluation of the single-soldier towing vehicle based on multiple sensors. This disclosure establishes an objective and reliable evaluation standard for the human-machine compatibility of single-soldier towing vehicles, which is beneficial for accurately evaluating the role and impact of single-soldier towing vehicles on personnel and facilitates guidance for the design of such equipment.

Description

Technical Field

[0001] This disclosure relates to the field of human-machine compatibility evaluation for individual soldier tractor vehicles. Specifically, it relates to a method, device, electronic device, and computer-readable storage medium for evaluating human-machine compatibility of individual soldier tractor vehicles based on multiple sensors. Background Technology

[0002] In fields such as individual combat and fire rescue, individual soldiers need to carry heavy loads. Individual soldier towing vehicles are a new type of load-lifting equipment that can increase load weight and conserve physical energy. However, as a human-machine hybrid intelligent equipment, the equipment automatically follows and assists the personnel after they perform actions. Due to design flaws, the machine's response may lag behind the personnel's actions or produce erroneous movements, causing discomfort for the personnel. Currently, there is no objective and effective method for evaluating human-machine compatibility, making the automated design of towing vehicles lack a scientific basis.

[0003] In existing technologies, a multi-sensor exoskeleton comfort evaluation device and method describes an exoskeleton comfort evaluation device and method composed of a single-dimensional pressure sensor and an electromyography (EMG) signal sensor. However, this method is only applicable to exoskeleton systems and is used for comfort evaluation, not for guiding the human-machine interface evaluation of individual soldier towing vehicles. A steering comfort evaluation method that correlates EMG and subjective assessment describes a comfort evaluation method that combines objective scores calculated by an EMG signal sensor 204 with subjective questionnaire scores. This method is used to evaluate driver comfort in automotive driving systems, but it is insufficient for evaluating human-machine interface and only uses one sensor for objective state assessment, resulting in incomplete state data collection. A patent for an exoskeleton evaluation system and its usage method describes an exoskeleton evaluation system composed of an image unit and a pressure sensor unit for evaluating the design performance of the exoskeleton. However, the sensor arrangement of this system can only be used for measuring plantar pressure, resulting in a limited measurement range and preventing a comprehensive evaluation of the system.

[0004] The individual soldier towing vehicle is a new type of individual soldier assistance equipment. Currently, there is no human-machine compatibility evaluation method for this type of equipment, which leads to a lack of basis for the design of the equipment.

[0005] Therefore, one or more methods are needed to solve the above problems.

[0006] It should be noted that the information disclosed in the background section above is only used to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0007] The purpose of this disclosure is to provide a method, device, electronic device, and computer-readable storage medium for evaluating the human-machine compatibility of a single-soldier tractor based on multiple sensors, thereby overcoming, to at least to some extent, one or more problems caused by the limitations and defects of related technologies.

[0008] According to one aspect of this disclosure, a method for evaluating the human-machine compatibility of a single-soldier tractor vehicle based on multiple sensors is provided, comprising:

[0009] Based on the preset test personnel wearing the human-machine matching degree evaluation device for the individual soldier towing vehicle, a preset number of preset test actions are completed, and preset indicators are collected based on the sensors of the human-machine matching degree evaluation device for the individual soldier towing vehicle.

[0010] Using the preset indicators as input, and based on the preset evaluation standard calculation rules, multiple sets of evaluation standards are generated;

[0011] Based on the evaluation criteria and the preset weight coefficients corresponding to the evaluation criteria, the human-machine matching degree evaluation result is calculated and generated, and the human-machine matching degree evaluation of the single soldier tractor based on multiple sensors is completed.

[0012] In one exemplary embodiment of this disclosure, the method further includes:

[0013] Based on the pre-set test personnel wearing the human-machine matching evaluation device and load of the single soldier towing vehicle, three sets of pre-set test actions were completed. The pre-set test actions included standing still, moving forward at a constant speed, turning left, and turning right.

[0014] The preset test action group has a preset rest time for the test personnel.

[0015] In one exemplary embodiment of this disclosure, the method further includes:

[0016] The proportion of the pulling force of the traction workshop of the pre-set test personnel and the human-machine matching degree evaluation device of the single soldier tractor vehicle that is greater than the first pre-set pulling force F1 or less than the second pre-set pulling force F2 is η;

[0017] Based on the preset evaluation criteria calculation rules, the first evaluation criterion P1 = 40 + (1 - η) is generated. 2 ×60.

[0018] In one exemplary embodiment of this disclosure, the method further includes:

[0019] The force F in the X-axis direction of the traction workshop of the pre-set test personnel and the human-machine matching evaluation device of the single-soldier tractor vehicle is collected. xT At time T+1, the force F between the test personnel and the tractor of the single-soldier tractor vehicle human-machine matching evaluation device is preset. xT+1 The difference between them;

[0020] Based on the preset evaluation criteria calculation rules, a second evaluation criterion is generated.

[0021] Where N is the preset number of groups.

[0022] In one exemplary embodiment of this disclosure, the method further includes:

[0023] The maximum pulling force of the traction workshop of the preset test personnel and the human-machine matching evaluation device of the single soldier tractor is F. pull The maximum thrust is F pus ;

[0024] A third evaluation standard is generated based on the preset evaluation standard calculation rules.

[0025]

[0026] In one exemplary embodiment of this disclosure, the method further includes:

[0027] The torque M1 of the YOZ plane of the traction workshop of the preset test personnel and the human-machine matching degree evaluation device of the single soldier tractor is collected;

[0028] Based on the preset evaluation criteria calculation rules, a fourth evaluation criterion is generated. in, This is a preset reference torque.

[0029] In one exemplary embodiment of this disclosure, the method further includes:

[0030] The torque M2 of the XOZ plane of the traction workshop of the preset test personnel and the human-machine matching degree evaluation device of the single soldier tractor is collected;

[0031] The fifth evaluation standard is generated based on the preset evaluation standard calculation rules.

[0032] in, This is the initial torque.

[0033] In one exemplary embodiment of this disclosure, the method further includes:

[0034] The electromyography (EMG) signals (RMS(t) of the preset test personnel were collected by the human-machine matching evaluation device for a single-soldier tractor vehicle. m ;

[0035] Based on the preset evaluation criteria calculation rules, a sixth evaluation criterion is generated.

[0036] Where E i The weights are the root mean square values ​​of the electromyography (EMG) signal sensor signals.

[0037] In one exemplary embodiment of this disclosure, the method further includes:

[0038] Based on the evaluation criteria and the preset weight coefficients corresponding to the evaluation criteria, the human-machine matching degree evaluation result is calculated and generated. Where E i These are preset weighting coefficients.

[0039] In one aspect of this disclosure, a human-machine matching evaluation device for a single-soldier tractor vehicle based on multiple sensors is provided, including a host computer, tension / compression sensors, torque sensors, electromyography (EMG) signal sensors, a Bluetooth data acquisition device, and a tractor vehicle, wherein:

[0040] The tractor is connected to a pre-set tester's clothing and is used to collect pre-set indicators based on tension and compression sensors, torque sensors, electromyography signal sensors, and Bluetooth data acquisition devices when the pre-set tester completes a pre-set test action.

[0041] The tension / compression sensor and torque sensor are arranged at the connection point between the pre-set test personnel and the tractor, and are used to collect torque in the pre-set coordinate direction, respectively.

[0042] The electromyography (EMG) signal sensors are arranged on the left and right psoas major muscles of the preset test subject to collect EMG signals from the preset test subject.

[0043] The host computer establishes a communication connection with the tension / compression sensor, torque sensor, and electromyography signal sensor based on the Bluetooth data acquisition device.

[0044] In one aspect of this disclosure, an electronic device is provided, comprising:

[0045] Processor; and

[0046] A memory storing computer-readable instructions that, when executed by the processor, implement the method according to any one of the preceding claims.

[0047] In one aspect of this disclosure, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the method according to any one of the preceding claims.

[0048] An exemplary embodiment of this disclosure discloses a method for evaluating the human-machine compatibility of a single-soldier towing vehicle based on multiple sensors. The method includes: a preset number of preset test actions performed by a pre-set test personnel wearing a human-machine compatibility evaluation device for the single-soldier towing vehicle; collecting preset indicators based on the sensors used for human-machine compatibility evaluation; generating multiple sets of evaluation standards based on preset evaluation standard calculation rules using the preset indicators as input; and calculating and generating a human-machine compatibility evaluation result based on the evaluation standards and their corresponding preset weight coefficients, thus completing the human-machine compatibility evaluation of the single-soldier towing vehicle based on multiple sensors. This disclosure establishes an objective and reliable evaluation standard for the human-machine compatibility of single-soldier towing vehicles, which is beneficial for accurately evaluating the role and impact of single-soldier towing vehicles on personnel and facilitates guidance for the design of such equipment.

[0049] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0050] The above and other features and advantages of this disclosure will become more apparent from the detailed description of exemplary embodiments thereof with reference to the accompanying drawings.

[0051] Figure 1 A flowchart is shown below for an exemplary embodiment of the present disclosure of a human-machine matching evaluation method for a single-soldier tractor vehicle based on multiple sensors;

[0052] Figure 2 A schematic diagram of a human-machine matching evaluation device for a single-soldier tractor vehicle based on multiple sensors is shown according to an exemplary embodiment of the present disclosure;

[0053] Figure 3 A block diagram of an electronic device according to an exemplary embodiment of the present disclosure is schematically shown; and

[0054] Figure 4 The illustration shows a schematic diagram of a computer-readable storage medium according to an exemplary embodiment of the present disclosure. Detailed Implementation

[0055] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the embodiments set forth herein; rather, they are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the exemplary embodiments to those skilled in the art. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted.

[0056] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough understanding of embodiments of this disclosure. However, those skilled in the art will recognize that the technical solutions of this disclosure can be practiced without one or more of the specific details described, or other methods, components, materials, apparatuses, steps, etc., can be employed. In other instances, well-known structures, methods, apparatuses, implementations, materials, or operations are not shown or described in detail to avoid obscuring various aspects of this disclosure.

[0057] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, or in one or more software-hardened modules, or in different network and / or processor devices and / or microcontroller devices.

[0058] In this example embodiment, a method for evaluating the human-machine compatibility of a single-soldier tractor vehicle based on multiple sensors is first provided; refer to Figure 1 As shown, the human-machine matching evaluation method for a single-soldier tractor based on multiple sensors may include the following steps:

[0059] Step S110: Based on the preset test personnel wearing the human-machine matching degree evaluation device of the individual soldier towing vehicle, a preset number of preset test actions are completed, and preset indicators are collected based on the sensor of the human-machine matching degree evaluation of the individual soldier towing vehicle.

[0060] Step S120: Using the preset indicators as input, generate multiple sets of evaluation standards based on the preset evaluation standard calculation rules;

[0061] Step S130: Based on the evaluation criteria and the preset weight coefficients corresponding to the evaluation criteria, calculate and generate the human-machine matching degree evaluation result, and complete the human-machine matching degree evaluation of the single soldier tractor based on multiple sensors.

[0062] An exemplary embodiment of this disclosure discloses a method for evaluating the human-machine compatibility of a single-soldier towing vehicle based on multiple sensors. The method includes: a preset number of preset test actions performed by a pre-set test personnel wearing a human-machine compatibility evaluation device for the single-soldier towing vehicle; collecting preset indicators based on the sensors used for human-machine compatibility evaluation; generating multiple sets of evaluation standards based on preset evaluation standard calculation rules using the preset indicators as input; and calculating and generating a human-machine compatibility evaluation result based on the evaluation standards and their corresponding preset weight coefficients, thus completing the human-machine compatibility evaluation of the single-soldier towing vehicle based on multiple sensors. This disclosure establishes an objective and reliable evaluation standard for the human-machine compatibility of single-soldier towing vehicles, which is beneficial for accurately evaluating the role and impact of single-soldier towing vehicles on personnel and facilitates guidance for the design of such equipment.

[0063] The following will further explain a human-machine matching evaluation method for a single-soldier tractor based on multiple sensors in this example embodiment.

[0064] Example 1:

[0065] In step S110, a preset number of preset test actions can be completed by a preset test personnel wearing the human-machine matching degree evaluation device for the individual soldier towing vehicle, and preset indicators can be collected based on the sensors of the human-machine matching degree evaluation device for the individual soldier towing vehicle.

[0066] In this example embodiment, the method further includes:

[0067] Based on the pre-set test personnel wearing the human-machine matching evaluation device and load of the single soldier towing vehicle, three sets of pre-set test actions were completed. The pre-set test actions included standing still, moving forward at a constant speed, turning left, and turning right.

[0068] The preset test action group has a preset rest time for the test personnel.

[0069] In step S120, multiple sets of evaluation criteria can be generated based on the preset indicators as input and the preset evaluation criteria calculation rules.

[0070] In this example embodiment, the method further includes:

[0071] The proportion of the tension between the test personnel and the tractor 201 of the single-soldier tractor vehicle human-machine matching evaluation device that is greater than the first preset tension F1 or less than the second preset tension F2 is collected as η;

[0072] Based on the preset evaluation criteria calculation rules, the first evaluation criterion P1 = 40 + (1 - η) is generated. 2 ×60.

[0073] In this example embodiment, the method further includes:

[0074] The force F along the X-axis between the pre-set test personnel and the tractor 201 of the single-soldier tractor vehicle human-machine matching evaluation device is collected. xT At time T+1, the force F between the test personnel and the tractor 201 of the single-soldier tractor vehicle human-machine matching evaluation device is preset. xT+1 The difference between them;

[0075] Based on the preset evaluation criteria calculation rules, a second evaluation criterion is generated.

[0076] Where N is the preset number of groups.

[0077] In this example embodiment, the method further includes:

[0078] The maximum pulling force F between the preset test personnel and the tractor 201 of the single-soldier tractor vehicle human-machine matching evaluation device is collected. pull The maximum thrust is F pus ;

[0079] A third evaluation standard is generated based on the preset evaluation standard calculation rules.

[0080]

[0081] In this example embodiment, the method further includes:

[0082] The torque M1 in the YOZ plane between the preset test personnel and the tractor 201 of the single-soldier tractor vehicle human-machine matching evaluation device is collected;

[0083] Based on the preset evaluation criteria calculation rules, a fourth evaluation criterion is generated. in, This is a preset reference torque.

[0084] In this example embodiment, the method further includes:

[0085] The torque M2 on the XOZ plane between the preset test personnel and the tractor 201 of the single soldier tractor vehicle human-machine matching evaluation device is collected.

[0086] The fifth evaluation standard is generated based on the preset evaluation standard calculation rules.

[0087] in, This is the initial torque.

[0088] In this example embodiment, the method further includes:

[0089] The electromyography (EMG) signals (RMS(t) of the preset test personnel were collected by the human-machine matching evaluation device for a single-soldier tractor vehicle. m ;

[0090] Based on the preset evaluation criteria calculation rules, a sixth evaluation criterion is generated.

[0091] Where E i The weights are the root mean square values ​​of the electromyography (EMG) signal sensor signals.

[0092] In this example embodiment, the method further includes:

[0093] Based on the evaluation criteria and the preset weight coefficients corresponding to the evaluation criteria, the human-machine matching degree evaluation result is calculated and generated. Where E i These are preset weighting coefficients.

[0094] In step S130, the human-machine matching degree evaluation result can be calculated and generated based on the evaluation criteria and the preset weight coefficients corresponding to the evaluation criteria, thereby completing the human-machine matching degree evaluation of the single-soldier tractor based on multiple sensors.

[0095] Example 2:

[0096] In this example embodiment, the usage procedure of the human-machine matching evaluation device for a single-soldier tractor based on multiple sensors is as follows: First, a test personnel is selected, correctly equipped with the tractor 201, and a load is placed as needed. The personnel performs a series of prescribed actions along the ground markings, including standing still, moving forward at a constant speed, turning left, and turning right. After completing the actions, the personnel rest for at least 0.5 hours before performing the prescribed actions again. Considering the inherent uncertainty of the personnel's actions, it is stipulated that after accumulating 3 sets of prescribed actions, the data during the action process is recorded and calculated.

[0097] The purpose of the tension / compression sensor 202 in the evaluation device is to measure the forces acting between the tractor 201 and the personnel along the direction of vehicle travel, denoted as F. x In the legend, the positive X-axis represents the pressure exerted by the vehicle on the person, and the negative X-axis represents the pulling force exerted by the vehicle on the person. The sampling period is set to 0.01s, and the number of samples recorded during the entire motion process is N.

[0098] If the towing vehicle 201 has a high degree of human-machine matching, the force between the operator and the towing vehicle 201 should be maintained within a certain range, so that the operator does not need to exert too much or too little force to drive the towing vehicle 201, that is, it satisfies...

[0099] F1≤F x ≤F2

[0100] When F is less than F1, a large pulling force is required to move the tractor 201, resulting in poor assist effect. When F is greater than F2, the personnel feel a noticeable pushing force, leading to low comfort and increased risk of danger. In practical use, F1 is set to -35N and F2 to 25N. The tension and compression data from the sensor 202 are recorded throughout the entire movement process. The proportion of force data exceeding the range is recorded as η. Based on this proportion, the formula for the evaluation standard P1 is set as follows:

[0101] P1 = 40 + (1 - η) 2 ×60

[0102] Furthermore, the degree of force change between the tractor 201 and the personnel is also an important evaluation indicator. If the force change is too rapid, the personnel will clearly feel this change, and in severe cases, they will feel a noticeable pushing or pulling sensation. Therefore, an index P2 is set to measure the fluctuation of the traction force between the tractor 201 and the personnel. The calculation method is to use the force F in the X-axis direction between the personnel and the tractor 201 at time T. xT The force F between the personnel and the tractor 201 at time T+1 xT+1 The difference between the values ​​reflects the degree of force fluctuation. The average of these differences reflects the degree of force fluctuation experienced by the person throughout the entire movement. The evaluation standard P2 formula is set as follows:

[0103]

[0104] During use, the maximum pulling force and maximum thrust between the towing vehicle 201 and the personnel are also important performance indicators. If the maximum pulling force used by the personnel to pull the towing vehicle 201 is too high, it will result in increased effort for the personnel. Because the towing vehicle 201 provides forward assistance, it will exert a thrust on the personnel at a certain stage; if this thrust is too great, it will lead to danger. The maximum pulling force during the entire movement is recorded as F. pull The maximum thrust is F push Calculating the difference between the maximum tension and the maximum thrust, and comparing it with the average force throughout the entire motion, reflects the extent to which the average force increases compared to the maximum tension. Therefore, the evaluation criterion P3 is set as follows:

[0105]

[0106] The torque sensor 203 in the evaluation device is used to measure the magnitude of the torque applied by the operator in the YOZ and XOZ planes when driving the tractor 201. The sampling period is set the same as that of the force sensor. The torque M1 in the YOZ plane is the steering torque applied by the operator to the tractor 201, used to measure the magnitude of the operator's movement during steering. A larger value of M1 means that the operator needs a larger range of motion to rotate the tractor 201. A reference torque M1 is set. r M1 is used to measure the magnitude of the average steering torque; in practice, it is set to... r =5Nm, and the evaluation criterion P4 based on the numerical value of M1 is:

[0107]

[0108] The torque M2 on the XOZ plane is used to measure the downward or upward lifting effect of the traction vehicle 201 on the person's waist. If M2 is too large, it means that the traction vehicle 201 applies too much downward torque to the person, making them feel heavy. If M2 is too small, it means that the traction vehicle 201 lifts the person upward, and this lifting sensation can easily cause instability or difficulty walking. Ideally, M2 should remain constant so that the person does not frequently feel changes in the force on their waist during movement. The initial torque is measured and recorded as M2 after the person wearing the traction vehicle 201 remains stationary. r Calculate the torque M2 at each moment. i With M2 r The difference is calculated, and the average value of the difference reflects the degree of torque change of the tractor 201. Based on this, the evaluation standard P5 is set as follows:

[0109]

[0110] The electromyography (EMG) signal sensors 204 in the evaluation device are positioned on the left and right psoas major muscles of the lower back. Their purpose is to detect the degree of muscle fatigue in the lower back during exercise based on the intensity of the EMG signals. First, electrode pads are attached to the muscles to be tested, and a control electrode is attached above the lower back muscles. EMG signals are acquired using a physiological signal acquisition device and transmitted to a host computer for processing via Bluetooth data acquisition. Considering the significant noise in the EMG signals and that their frequency is mostly concentrated between 20-500 Hz, a 20-500 Hz bandpass filter is used to process the signals, while a notch filter is used to filter out 50 Hz power frequency noise. The root mean square (RMS) value is used to calculate the filtered EMG signal data, as shown in the following formula:

[0111]

[0112] Here, e(t) is the electromyographic signal acquired at time T, with the sampling period T set to 0.05s.

[0113] The root mean square values ​​calculated by the two electromyography (EMG) signal sensors 204 in the lumbar muscles are summed, and the results are normalized to obtain the formula for the evaluation standard P6 based on EMG signals, as follows:

[0114]

[0115] Among them, E i The weights representing the root mean square values ​​of the electromyography (EMG) sensor signals are set to 0.5 and 0.5 for E1 and E2, respectively, when the person is standing still and moving forward at a constant speed. When the person turns left, the contraction amplitude of the left psoas major muscle is greater. To accurately measure the impact of the tractor 201 on muscle fatigue, the weight E1 of the left EMG sensor 204 is set to 0.8, and the weight E2 of the right EMG sensor 204 is set to 0.2. Correspondingly, when the person turns right, the weight E1 of the left EMG sensor 204 is set to 0.2, and the weight E2 of the right EMG sensor 204 is set to 0.8. Sensor data is collected after the person completes the movement, and the EMG data is processed and evaluation criteria are calculated according to the above method. The min-max normalization method is used to calculate each evaluation criterion as follows:

[0116]

[0117] After each action is completed, a comprehensive evaluation of the human-machine compatibility of the 201 single-soldier tractor is conducted. The evaluation formula is as follows:

[0118]

[0119] Among them, E i The weighting coefficients for each evaluation indicator are assigned when the person is performing different actions. When the person is standing still and moving at a constant speed, the turning torque has a relatively small impact on human-machine compatibility, and its weight should be low. However, when turning left or right, this weight should be relatively increased. The weighting coefficient set for the person standing still and moving at a constant speed is set as follows:

[0120] E = {0.2, 0.2, 0.2, 0.1, 0.2, 0.1}

[0121] When personnel turn left or right, the weighting coefficient group is set as follows:

[0122] E = {0.1, 0.1, 0.2, 0.3, 0.2, 0.1}

[0123] The human-machine matching evaluation result of the tractor 201 during use is calculated according to the formula. Generally speaking, a score higher than 85 points can be considered as a relatively good human-machine matching.

[0124] It should be noted that although the steps of the method in this disclosure are described in a specific order in the accompanying drawings, this does not require or imply that the steps must be performed in that specific order, or that all the steps shown must be performed to achieve the desired result. Additional or alternative steps may be omitted, multiple steps may be combined into one step, and / or a step may be broken down into multiple steps.

[0125] Furthermore, in this example embodiment, a human-machine matching evaluation device for a single-soldier tractor vehicle based on multiple sensors is also provided. (Refer to...) Figure 2 As shown, the human-machine matching evaluation device 200 for a single-soldier tractor based on multiple sensors may include a host computer, a tension / compression sensor 202, a torque sensor 203, an electromyography signal sensor 204, a Bluetooth data acquisition device, and a tractor 201, wherein:

[0126] The tractor 201 is connected to the preset test personnel's clothing and is used to collect preset indicators based on the tension and compression sensor 202, torque sensor 203, electromyography signal sensor 204, and Bluetooth data acquisition device when the preset test personnel complete the preset test action.

[0127] The tension / compression sensor 202 and torque sensor 203 are arranged at the connection between the preset test personnel and the tractor 201, and are used to collect torque in preset coordinate directions respectively;

[0128] The electromyography (EMG) signal sensor 204 is arranged at the left and right psoas major muscles of the preset test subject to collect the EMG signals of the preset test subject.

[0129] The host computer establishes a communication connection with the tension / compression sensor 202, torque sensor 203, and electromyography signal sensor 204 based on the Bluetooth data acquisition device.

[0130] In this example embodiment, tensile stress sensors and torque sensors 203 should be positioned at the connection point between the person and the tractor 201. Tensile / compression sensors 202 are used to measure the force between the person and the tractor 201 in the X direction of the diagram. In this example, it is assumed that the positive X direction is the direction of the thrust force exerted by the tractor 201 on the person. Two torque sensors 203 are used to measure the torque between the person and the tractor 201 along the Y and Z axes, respectively. In actual system setup, a triaxial force / torque sensor 203 with X-direction force and Y / Z-axis torque measurement functions can be selected. Electromyography (EMG) sensors 204 are sewn onto the fabric and positioned at the left and right psoas major muscles of the person to measure muscle fatigue during movement. The data from these sensors are received and processed by a host computer via wireless transmission.

[0131] The specific details of each of the above-mentioned human-machine matching degree evaluation device modules for individual soldier tractor vehicles based on multiple sensors have been described in detail in the corresponding human-machine matching degree evaluation method for individual soldier tractor vehicles based on multiple sensors, so they will not be repeated here.

[0132] It should be noted that although several modules or units of the meeting summary generation apparatus 200 have been mentioned in the detailed description above, this division is not mandatory. In fact, according to embodiments of this disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0133] Furthermore, in an exemplary embodiment of this disclosure, an electronic device capable of implementing the above-described method is also provided.

[0134] Those skilled in the art will understand that various aspects of the present invention can be implemented as systems, methods, or program products. Therefore, various aspects of the present invention can be specifically implemented as entirely hardware embodiments, entirely software embodiments (including firmware, microcode, etc.), or embodiments combining hardware and software aspects, collectively referred to herein as “circuit,” “module,” or “system.”

[0135] The following reference Figure 3 To describe an electronic device 300 according to such an embodiment of the present invention. Figure 3 The electronic device 300 shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0136] like Figure 3 As shown, the electronic device 300 is presented in the form of a general-purpose computing device. The components of the electronic device 300 may include, but are not limited to: at least one processing unit 310, at least one storage unit 320, a bus 330 connecting different system components (including storage unit 320 and processing unit 310), and a display unit 340.

[0137] The storage unit stores program code that can be executed by the processing unit 310, causing the processing unit 310 to perform the steps described in the "Exemplary Methods" section of this specification according to various exemplary embodiments of the present invention. For example, the processing unit 310 can perform actions such as... Figure 1 Steps S110 to S130 are shown in the diagram.

[0138] Storage unit 320 may include readable media in the form of volatile storage units, such as random access memory (RAM) 3201 and / or cache memory 3202, and may further include read-only memory (ROM) 3203.

[0139] Storage unit 320 may also include a program / utility 3204 having a set (at least one) program module 3205, such program module 3205 including but not limited to: operating system, one or more application programs, other program modules and program data, each or some combination of these examples may include an implementation of a network environment.

[0140] Bus 330 can represent one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of the various bus structures.

[0141] Electronic device 300 can also communicate with one or more external devices 370 (e.g., keyboard, pointing device, Bluetooth device, etc.), and with one or more devices that enable a user to interact with electronic device 300, and / or with any device that enables electronic device 300 to communicate with one or more other computing devices (e.g., router, modem, etc.). This communication can be performed via input / output (I / O) interface 350. Furthermore, electronic device 300 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 360. As shown, network adapter 360 communicates with other modules of electronic device 300 via bus 330. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with electronic device 300, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0142] From the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, terminal device, or network device, etc.) to execute the methods according to the embodiments of this disclosure.

[0143] In exemplary embodiments of this disclosure, a computer-readable storage medium is also provided, on which a program product capable of implementing the methods described above is stored. In some possible embodiments, various aspects of the invention may also be implemented as a program product comprising program code that, when the program product is run on a terminal device, causes the terminal device to perform the steps of the various exemplary embodiments of the invention described in the "Exemplary Methods" section above.

[0144] refer to Figure 4 As shown, a program product 400 for implementing the above-described method according to an embodiment of the present invention is described. This product may employ a portable compact disc read-only memory (CD-ROM) and include program code, and may run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto. In this document, the readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0145] The program product may employ any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0146] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium, capable of sending, propagating, or transmitting programs for use by or in conjunction with an instruction execution system, apparatus, or device.

[0147] The program code contained on the readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination thereof.

[0148] Program code for performing the operations of this invention can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's computing device, partially on the user's device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0149] Furthermore, the above figures are merely illustrative of the processes included in the method according to exemplary embodiments of the present invention, and are not intended to be limiting. It is readily understood that the processes shown in the above figures do not indicate or limit the temporal order of these processes. Additionally, it is readily understood that these processes may be executed synchronously or asynchronously, for example, in multiple modules.

[0150] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and embodiments are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the claims.

[0151] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

Claims

1. A method for evaluating the human-machine compatibility of a single-soldier tractor based on multiple sensors, characterized in that, The method includes: Based on a pre-set test personnel wearing a human-machine matching evaluation device and load for a single-soldier towing vehicle, a pre-set number of pre-set test actions are completed. These pre-set test actions include standing still, moving forward at a constant speed, turning left, and turning right. Between each set of test actions, the pre-set test personnel are given a pre-set rest period. Throughout the entire test process: Force data Fx between the tractor and the predetermined test personnel along the vehicle's direction of travel is collected using a tension / compression sensor at a preset sampling period; torque M1 in the YOZ plane and torque M2 in the XOZ plane between the predetermined test personnel and the tractor are collected using a torque sensor; and electromyography (EMG) signals of the lumbar muscles of the predetermined test personnel are collected using an EMG sensor. Using the preset indicators collected by the sensors as input, and based on the preset evaluation standard calculation rules, multiple sets of evaluation standards are generated to evaluate the human-machine matching degree of the individual soldier towing vehicle, including: The proportion η of the sampling points where the force data Fx exceeds the preset force range during the entire motion process is calculated, and a first evaluation standard P1 is generated based on the proportion η. Force data F based on adjacent sampling times T and T+1 xT F xT+1 The average value of the difference is used as the second evaluation standard P2, which reflects the degree of fluctuation in traction force between the tractor and the preset test personnel. Based on the maximum tension F during the entire motion pull Maximum thrust F pus The ratio between the average force and the average force generates the third evaluation criterion P3; The torque M1 of the pre-set test personnel and the human-machine matching degree evaluation device of the single-soldier tractor on the YOZ plane of the traction workshop is collected, and a reference torque is set. The evaluation standard P4 is set based on the value of M1 to measure the magnitude of the average steering torque. The torque M2 of the traction workshop XOZ plane between the pre-set test personnel and the human-machine matching evaluation device of the single-soldier tractor is collected. After the personnel put on the tractor and remain stationary, the initial torque is measured and recorded as follows. Calculate the torque at each moment and The difference is calculated, and the average value of the difference is used to reflect the degree of torque change of the tractor, and the evaluation standard P5 is set accordingly; The root mean square values ​​calculated from two electromyography (EMG) sensors in the lumbar muscles were summed and the results were normalized to obtain the evaluation standard P6 based on EMG signals. The evaluation criteria P1 to P6 are normalized by min-max, and the corresponding weight coefficient group is set according to the type of the preset test action. The weight of the turning-related evaluation criteria is reduced when standing still and moving forward at a constant speed, and the weight of the turning-related evaluation criteria is increased when turning left and turning right. The P1 to P6 are weighted and summed to obtain the human-machine matching degree evaluation score of the corresponding preset test action. Based on the human-machine matching evaluation scores of each preset test action, the human-machine matching evaluation results of the single-soldier tractor under typical operating conditions are determined.

2. The method as described in claim 1, characterized in that, Generate the first evaluation standard ; The force between the tractor and the preset test personnel is greater than the first preset tension. or less than the second preset tension The proportion of sampling points to all sampling points.

3. The method as described in claim 2, characterized in that, Generate a second evaluation criterion ,in, The force between the personnel and the tractor in the X-axis direction at time T is N, where N is the preset number of groups.

4. The method as described in claim 3, characterized in that, Generate a third evaluation standard 。 5. The method as described in claim 4, characterized in that, Generate the fourth evaluation standard ,in, To preset the reference torque, The torque between the preset test personnel and the tractor in the YOZ plane at the i-th sampling time is given.

6. The method as described in claim 5, characterized in that, Generate the fifth evaluation standard ,in, For the initial torque, The torque between the preset test personnel and the tractor in the XOZ plane at the i-th sampling time is given.

7. The method as described in claim 6, characterized in that, Generate the sixth evaluation standard ,in The electromyographic signals of the preset test subjects, The weights are the root mean square values ​​of the electromyography (EMG) signal sensor signals.

8. The method as described in claim 7, characterized in that, Based on the evaluation criteria and the preset weight coefficients corresponding to the evaluation criteria, the human-machine matching degree evaluation result is calculated and generated. ,in These are preset weighting coefficients.

9. A human-machine matching evaluation device for a single-soldier tractor based on multiple sensors, characterized in that, Based on the method according to any one of claims 1-8, the device includes a host computer, a tension / compression sensor, a torque sensor, an electromyography (EMG) signal sensor, a Bluetooth data acquisition device, and a tractor, wherein: The tractor is connected to a pre-set tester's clothing and is used to collect pre-set indicators based on tension and compression sensors, torque sensors, electromyography signal sensors, and Bluetooth data acquisition devices when the pre-set tester completes a pre-set test action. The tension / compression sensor and torque sensor are arranged at the connection point between the pre-set test personnel and the tractor, and are used to collect torque in the pre-set coordinate direction, respectively. The electromyography (EMG) signal sensors are arranged on the left and right psoas major muscles of the preset test subject to collect EMG signals from the preset test subject. The host computer establishes a communication connection with the tension / compression sensor, torque sensor, and electromyography signal sensor based on the Bluetooth data acquisition device.

10. An electronic device, characterized in that, include Processor; and A memory storing computer-readable instructions that, when executed by the processor, implement the method according to any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that, It stores a computer program thereon, which, when executed by a processor, implements the method according to any one of claims 1 to 8.

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