CN113397568A - Method for setting range of operating force of engineering machinery and evaluating operation fatigue of driver - Google Patents
Method for setting range of operating force of engineering machinery and evaluating operation fatigue of driver Download PDFInfo
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- CN113397568A CN113397568A CN202110666908.6A CN202110666908A CN113397568A CN 113397568 A CN113397568 A CN 113397568A CN 202110666908 A CN202110666908 A CN 202110666908A CN 113397568 A CN113397568 A CN 113397568A
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/389—Electromyography [EMG]
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/16—Devices for psychotechnics; Testing reaction times ; Devices for evaluating the psychological state
- A61B5/18—Devices for psychotechnics; Testing reaction times ; Devices for evaluating the psychological state for vehicle drivers or machine operators
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7203—Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7225—Details of analog processing, e.g. isolation amplifier, gain or sensitivity adjustment, filtering, baseline or drift compensation
Abstract
The invention discloses a method for setting an operating force range of engineering machinery and evaluating the operating fatigue of a driver, belonging to the technical field of setting of operating force of the engineering machinery. The human subject manipulates the parts under the set operating force, including: acquiring subjective fatigue data of a testee according to a set time interval; collecting myoelectric signals fed back by muscles of a testee; carrying out data processing on the collected electromyographic signals to obtain the muscle activation degree of the testee under the set operating force; based on subjective fatigue data and muscle activation level values of all subjects, an operating force range of the part is determined. And acquiring the time for starting fatigue of the driver when the driver operates the component based on the acquired subjective fatigue data and the muscle activation degree values of all the testees, and evaluating the change condition of the work fatigue of the driver. From the perspective of a user, the reasonable range of the operation force of the part is determined, and meanwhile, the problem of quantitative evaluation of the control fatigue degree is solved.
Description
Technical Field
The invention belongs to the technical field of engineering machinery operating force setting, and particularly relates to a method for setting an engineering machinery operating force range and evaluating the operating fatigue of a driver.
Background
With the wide application and deep development of mechanical engineering and human ergonomics, more and more system designs need to consider many factors such as safety, comfort, high efficiency and the like, and the application and evaluation in the aspects of fatigue, comfort, safety and the like are also widely regarded. The fatigue state of the human-computer system operator not only affects the working efficiency, but also affects the physical and mental health of the operator, so that factors such as control fatigue become more concerned, and the operation fatigue degree test and evaluation become more important design requirements of system design, and are also the key problem for realizing the optimal matching among human, machine and environment.
The control fatigue is a sense of discomfort, which means that the operator feels subjective within a certain operation time, and affects the physical state of the operator, and objectively loses the ability to complete the original normal learning, activities or work under the same conditions. The fatigue research is very important for the human engineering research, and is to combine the related knowledge of physiology and psychology, and from the starting point of improving the production efficiency, research the working fatigue and recovery problem of operators, so as to reasonably exert the capability of the operators and exert high efficiency in the production process.
At present, the recommended value of the national standard on the component operating force is provided from the aspects of safety, mechanical structure and the like, and the comfort of operation is not considered, so that the provided reference value is large, and in actual use, the recommended value does not accord with human engineering and is easy to cause muscle fatigue; in the technical research on the control fatigue, the fatigue degree is judged by adopting a subjective evaluation or fuzzy analysis method, the control fatigue degree cannot be objectively measured, and a more intuitive, accurate and credible detection mode and means are lacked; and most of the experimental operations are relatively ideal in a laboratory, and the experimental laboratory experiment neglects the influence of the external environment on the driving behavior and the fatigue degree because the human-machine-environment system is a human-machine-environment research object, and has one-sidedness.
Disclosure of Invention
In order to solve the defects in the prior art, the invention provides a method for setting the range of the operating force of the engineering machinery and evaluating the operation fatigue of a driver, which is used for determining the reasonable range of the operating force of a part from the perspective of a user and solving the problem of quantitative evaluation of the operation fatigue.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
in a first aspect, there is provided a method for setting an operating force range of a component of a construction machine, in which a subject manipulates the component with a set operating force, the method including: acquiring subjective fatigue data of a testee according to a set time interval; collecting myoelectric signals fed back by muscles of a testee; carrying out data processing on the collected electromyographic signals to obtain the muscle activation degree of the testee under the set operating force; based on subjective fatigue data and muscle activation level values of all subjects, an operating force range of the part is determined.
Further, the preprocessing the collected electromyographic signals to obtain the muscle activation degree of the human subject under the set operation force includes: carrying out data preprocessing on the collected electromyographic signals; performing data filtration on the preprocessed electromyographic signals through a low-pass filter and solving the root mean square value of the electromyographic signals; acquiring the muscle activation degree based on the root mean square value of the electromyographic signal and the root mean square value of the maximum autonomous contraction of the muscle:
where Act represents the degree of muscle activation, RMS represents the root mean square value of the electromyographic signal, and MVC represents the root mean square value of the maximum voluntary contraction of the muscle.
Further, the data preprocessing comprises: and carrying out 50Hz trap wave, 30Hz zero phase shift high-pass filtering and full-wave rectification on the electromyographic signals.
Further, the determining the operating force range of the component based on the acquired subjective fatigue data and the muscle activation degree of all the subjects specifically comprises: based on the muscle activation degree that obtains, carry out the analysis to driver's fatigue degree under different operating modes, include: respectively intercepting different myoelectric signals of all the testees to obtain the mean value of muscle activation degrees of all the testees under different operating forces; the method comprises the steps of obtaining the growth rate of muscle activation degree based on the mean value of the muscle activation degree of all testees under different operation forces, and determining the operation force range of a component by taking the growth rate of the muscle activation degree as a key index and combining subjective fatigue data of the testees.
In a second aspect, a method for evaluating driver working fatigue is provided, which includes: determining an operating force range of a component based on the method for setting an operating force range of a construction machine component according to the first aspect; setting an operation force of the member based on the determined operation force range; acquiring subjective fatigue data of a testee when the testee operates the component under a set operating force according to a set time interval; collecting myoelectric signals fed back by muscles when a tested person operates a component under a set operating force; carrying out data processing on the collected electromyographic signals to obtain the muscle activation degree of the testee under the set operating force; and acquiring the time for starting fatigue of the driver when the driver operates the component based on the acquired subjective fatigue data and the muscle activation degree values of all the testees, and evaluating the change condition of the work fatigue of the driver.
Further, the processing of the collected electromyographic signals to obtain the muscle activation degree of the subject under the set operation force includes: carrying out data preprocessing on the collected electromyographic signals; performing data filtration on the preprocessed electromyographic signals through a low-pass filter and solving the root mean square value of the electromyographic signals; acquiring the muscle activation degree based on the root mean square value of the electromyographic signal and the root mean square value of the maximum autonomous contraction of the muscle:
where Act represents the degree of muscle activation, RMS represents the root mean square value of the electromyographic signal, and MVC represents the root mean square value of the maximum voluntary contraction of the muscle.
Further, the data preprocessing comprises: and carrying out 50Hz trap wave, 30Hz zero phase shift high-pass filtering and full-wave rectification on the electromyographic signals.
Further, the parts comprise a steering wheel, a handle and a pedal of the original vehicle, and a steering wheel, a handle and a pedal of the original vehicle.
Further, the time for starting fatigue of the driver when operating the component is obtained based on the acquired subjective fatigue data and the muscle activation degree values of all the testees, and the time is used for evaluating the change condition of the work fatigue of the driver, and the method comprises the following steps: based on the data of the original vehicle test, the average time of the fatigue degree of the original vehicle test is measured, the change condition of the operation fatigue degree of a driver is evaluated by comparing the time of the driver driving the original vehicle with the time of starting fatigue of a sample vehicle, and the specific measurement formula is as follows:
wherein, P represents the fatigue time prolonging rate of the driver;
representing the average time for the Act value to reach fatigue in a prototype test;
representing the average time for the Act value to reach fatigue in the original vehicle test;
wherein, TiRepresenting the time when the Act value reaches fatigue when the ith sample is subjected to a prototype test; n represents the number of test samples;
wherein, TjAnd the time when the Act value reaches fatigue when the jth sample is subjected to the original vehicle test is shown.
Further, the time to onset of fatigue is determined by the time when the rate of increase in the degree of muscle activation changes abruptly.
Compared with the prior art, the invention has the following beneficial effects:
(1) the method comprises the steps of carrying out data processing by collecting subjective fatigue data of a tested person and myoelectric signals fed back by muscles of the tested person, and obtaining the muscle activation degree of the tested person under a set operation force so as to determine the operation force range of a component; from the perspective of a user, the control resistance range of a key component is determined, reference is provided for setting the operation force of the component, and the problems that the national standard setting is wide and the man-machine design cannot be effectively guided are solved;
(2) according to the fatigue evaluation method, the operation force range of the component is reasonably set, and meanwhile, the subjective fatigue data of a tested person and the myoelectric signals fed back by muscles of the tested person are based on, so that the subjective and objective evaluation on the fatigue of an engineering machinery driver in the operation process is realized, and the problem of quantitative evaluation on the control fatigue is solved;
(3) the invention adopts real vehicle scenes for verification and evaluation, solves the defect that the prior art ignores influence factors such as external environment and the like under relatively ideal environment of a laboratory, ensures that the experimental result is more real and credible, and makes up the unreal and inaccurate property of laboratory test.
Drawings
Fig. 1 is a schematic flow chart of a method for setting an operating force range of a construction machine according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of an experiment for setting the range of the operation force according to the embodiment of the present invention;
FIG. 3 is a schematic flow chart illustrating data analysis of an electromyographic signal according to an embodiment of the present invention;
FIG. 4 is a schematic main flow chart of a method for evaluating driver's work fatigue according to an embodiment of the present invention;
FIG. 5 is a block diagram of a system for evaluating driver work fatigue in an embodiment of the present invention.
Detailed Description
The invention is further described below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present invention is not limited thereby.
The first embodiment is as follows:
a method for setting an operating force range of a component of a construction machine, in which a subject manipulates the component under a set operating force, includes: acquiring subjective fatigue data of a testee according to a set time interval; collecting myoelectric signals fed back by muscles of a testee; carrying out data processing on the collected electromyographic signals to obtain the muscle activation degree of the testee under the set operating force; based on subjective fatigue data and muscle activation level values of all subjects, an operating force range of the part is determined.
The data preprocessing is carried out on the collected electromyographic signals to obtain the muscle activation degree of the testee under the set operating force, and the method comprises the following steps: carrying out data preprocessing on the collected electromyographic signals; performing data filtration on the preprocessed electromyographic signals through a low-pass filter and solving the root mean square value of the electromyographic signals; acquiring the muscle activation degree based on the root mean square value of the electromyographic signal and the root mean square value of the maximum autonomous contraction of the muscle:
where Act represents the degree of muscle activation, RMS represents the root mean square value of the electromyographic signal, and MVC represents the root mean square value of the maximum voluntary contraction of the muscle. The data preprocessing comprises the following steps: and carrying out 50Hz trap wave, 30Hz zero phase shift high-pass filtering and full-wave rectification on the electromyographic signals.
Based on the acquired subjective fatigue data and the muscle activation degrees of all the testees, determining the operating force range of the component, specifically: based on the muscle activation degree that obtains, carry out the analysis to driver's fatigue degree under different operating modes, include: respectively intercepting different myoelectric signals of all the testees to obtain the mean value of muscle activation degrees of all the testees under different operating forces; the method comprises the steps of obtaining the growth rate of muscle activation degree based on the mean value of the muscle activation degree of all testees under different operation forces, and determining the operation force range of a component by taking the growth rate of the muscle activation degree as a key index and combining subjective fatigue data of the testees.
As shown in fig. 1 to 3, in the present embodiment, an experiment was designed with the operation force as an independent variable and the subjective evaluation value and the electromyogram signal data as a dependent variable. The method mainly comprises two parts including laboratory experiments and vehicle verification experiments. The comfort range is reduced through subjective data, long-time dynamic fatigue strength testing is conducted through combination of surface myoelectricity, the comfortable value of the operating force is accurately determined, and then verification is conducted through combination of a real vehicle and a real operating environment.
The method mainly develops research around parts such as a steering wheel, a handle, a pedal and the like frequently used by a user, simulates the operating force of main operating parts of the engineering machinery by means of an operating force simulation test system, and researches the influence of the operating force on the work efficiency of the parts by adopting a method combining objective experiments and subjective evaluation, so that the design requirement of the operating force of the parts is provided, and the fatigue of the user is reduced.
The provided operating force is applied to an actual vehicle, a new prototype is manufactured, the vehicle is taken out of a laboratory, the influence of the operating environment on a driver is combined, and the operating fatigue degree change condition of the driver is verified and evaluated through a fatigue degree comparison experiment of the prototype with the new scheme and the old scheme.
Firstly, preparation before experiment: preparation before the experiment was carried out according to the contents of table 1:
TABLE 1 Experimental preparations and requirements
Second, Experimental procedure
(1) Operating force test range determination
a) Firstly, preliminarily determining the operating force range of a main component by investigating the set ranges of the operating forces of related components related to the existing products (including competitive products), standards, documents and the like;
b) then, carrying out an operation force range reduction experiment, and collecting subjective evaluation values of a testee (namely a driver operating the engineering machinery) on different operation forces;
c) and (4) reducing the testing range of the operating force through preliminary data analysis, and taking the testing range as the testing range of the operating force of the formal experiment.
(2) Initial experiment
Firstly, introducing an experiment purpose, an experiment process and related requirements to a testee, training the testee and solving possible problems in the process of the testee, and starting formal testing after the testee is completely familiar with the whole experiment;
removing by using a hair scraping knife and repeatedly wiping the skin at and near the placement point of the myoelectric sensor by using an alcohol cotton ball so as to remove oil stains and necrotic cuticle on the surface of the skin;
thirdly, attaching a sensor by using double-sided adhesive tape, wherein the electrode placement point is the most bulged part of the muscle abdomen, and recording a test channel corresponding to each muscle, and taking a tested person as an example, the channel corresponding to the muscle group is shown in table 2;
TABLE 2 muscle groups corresponding to the main operating parts
And fourthly, calibrating each muscle group according to a maximum autonomous muscle contraction calibration procedure. Before calibration, each subject needs to perform a warm-up exercise for 5-10 minutes, including a stretching exercise, a hypoxia exercise, and the like. When the calibration action is carried out, the muscle of the tested person is required to exert force gradually, the maximum force exerting degree is reached after 3-5 seconds, the force is continuously kept for 3 seconds, and the muscle is calmed down within 3 seconds; each muscle calibration action is repeated three times, and a rest is carried out for 60 seconds between each action;
fifthly, the tested person keeps sitting, the left and right positions and the up and down positions of the seat are adjusted to enable the left and right positions of the seat and the tested part to be consistent with the specified initial position, and the front and back positions of the seat are adjusted to enable the front and back distance between the seat and the tested part to be comfortable and fix the seat;
sixthly, after the testee is familiar with the action of the operating component, operating the component at a normal speed under a set operating force, reporting a subjective fatigue value (by referring to a Borg meter in a table 1) every 1 minute by the testee, and stopping after operating for 5 minutes;
and seventhly, the testee takes a rest for 10 minutes, changes one operation force, and repeats the fifth step until all the operation force test values to be tested are tested.
Before analyzing the surface electromyographic signals, the 5min electromyographic signals collected in the experimental process need to be processed.
The data is first preprocessed. Mainly comprises 3 steps: (1) trapping at 50Hz to remove power frequency interference; (2) carrying out 30Hz zero phase shift high-pass filtering to remove motion artifacts; (3) and (4) full-wave rectification, wherein the absolute value of the signal is obtained, and the negative half shaft of the signal can be turned to the positive half shaft. And then, performing data filtering on the preprocessed signals through a low-pass filter and solving a root mean square value. And finally, carrying out data normalization processing, and comparing the RMS value of the electromyographic signal obtained in the experiment with the root mean square value of the maximum autonomous contraction of the muscle to obtain the muscle activation degree (Act) as shown in a formula (1).
After the muscle activation degree is obtained, the fatigue degree of a driver under different working conditions can be analyzed, and the larger the Act value is, the fatigued muscle is indicated. And respectively intercepting myoelectric data of all tested different muscles to obtain Act mean values of the muscles under different resistances. In the data analysis process, the method of variance analysis is adopted to judge the correlation and the data validity.
The fatigue feeling is slowly increased along with the increase of the set value of the operating force, if the fatigue feeling is suddenly increased greatly, the muscle is obviously fatigued in the operation process, and therefore in the data analysis process, the Act value increase rate is selected as a key index for judging the muscle fatigue. Therefore, in the embodiment, the "inflection point" is adopted to determine the experimental result, that is, the Act value increase rate is selected as an index, and the increase rate and the subjective evaluation data are combined to finally give the optimal operating force setting range of the measured component.
In the embodiment, the subjective fatigue data of a tested person and the myoelectric signals fed back by the muscles of the tested person are collected for data processing, and the muscle activation degree of the tested person under the set operating force is obtained so as to determine the operating force range of the component; from the perspective of a user, the control resistance range of the key component is determined, reference is provided for component operation force setting, and the problems that the national standard setting is wide and man-machine design cannot be effectively guided are solved.
Example two:
as shown in fig. 4 and 5, based on the method for setting the operating force range of the engineering mechanical component in the first embodiment, the first embodiment provides a method for evaluating the fatigue degree of a driver, a typical product is selected, a new prototype is made, that is, the operating force set value of the main operating component in the cab is changed, a method similar to the laboratory experiment in the first embodiment is adopted to perform the original vehicle and prototype tests, and subjective evaluation data and electromyographic data are collected; the method comprises the following steps: determining the operating force range of the component based on the method for setting the operating force range of the engineering machinery component in the first embodiment; setting an operation force of the member based on the determined operation force range; acquiring subjective fatigue data of a testee when the testee operates the component under a set operating force according to a set time interval; collecting myoelectric signals fed back by muscles when a tested person operates a component under a set operating force; carrying out data processing on the collected electromyographic signals to obtain the muscle activation degree of the testee under the set operating force; and acquiring the time for starting fatigue of the driver when the driver operates the component based on the acquired subjective fatigue data and the muscle activation degree values of all the testees, and evaluating the change condition of the work fatigue of the driver.
The method for processing the collected electromyographic signals and acquiring the muscle activation degree of the testee under the set operating force comprises the following steps: carrying out data preprocessing on the collected electromyographic signals; performing data filtration on the preprocessed electromyographic signals through a low-pass filter and solving the root mean square value of the electromyographic signals; acquiring the muscle activation degree based on the root mean square value of the electromyographic signal and the root mean square value of the maximum autonomous contraction of the muscle:
where Act represents the degree of muscle activation, RMS represents the root mean square value of the electromyographic signal, and MVC represents the root mean square value of the maximum voluntary contraction of the muscle. The data preprocessing comprises the following steps: and carrying out 50Hz trap wave, 30Hz zero phase shift high-pass filtering and full-wave rectification on the electromyographic signals. The parts comprise a steering wheel, a handle and a pedal of the original vehicle, and a steering wheel, a handle and a pedal of the original vehicle. Acquiring the time for starting fatigue of a driver when operating a component based on the acquired subjective fatigue data and the muscle activation degree values of all the testees, and evaluating the change condition of the work fatigue of the driver, wherein the time comprises the following steps:
based on the data of the original vehicle test, the average time of the fatigue degree of the original vehicle test is measured and calculated, the change condition of the operation fatigue degree of the driver is evaluated by comparing the time of the driver driving the original vehicle with the time of the sample vehicle beginning to be fatigued, the time of beginning to be fatigued is determined by the corresponding time when the growth rate of the muscle activation degree is suddenly changed,
the specific measurement formula is as follows:
wherein, P represents the fatigue time prolonging rate of the driver;
representing the average time for the Act value to reach fatigue in a prototype test;
representing the average time for the Act value to reach fatigue in the original vehicle test;
wherein, TiRepresenting the time when the Act value reaches fatigue when the ith sample is subjected to a prototype test; n represents the number of test samples;
wherein, TjAnd the time when the Act value reaches fatigue when the jth sample is subjected to the original vehicle test is shown.
According to the method, the range of the operating force of the component is reasonably set, and meanwhile, the subjective fatigue data of a tested person and the myoelectric signals fed back by the muscles of the tested person are based on, so that the subjective and objective evaluation of the fatigue of a driver of the engineering machinery in the operation process is realized, and the problem of quantitative evaluation of the control fatigue is solved; the real-vehicle real scene is adopted for verification and evaluation, so that the defect that influence factors such as external environment and the like are neglected in a relatively ideal environment of a laboratory in the prior art is overcome, the experimental result is more real and credible, and unreal and inaccurate laboratory tests are made up.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.
Claims (10)
1. A method for setting an operating force range of a component of a construction machine, in which a subject manipulates the component under a set operating force, comprising:
acquiring subjective fatigue data of a testee according to a set time interval;
collecting myoelectric signals fed back by muscles of a testee;
carrying out data processing on the collected electromyographic signals to obtain the muscle activation degree of the testee under the set operating force;
based on subjective fatigue data and muscle activation level values of all subjects, an operating force range of the part is determined.
2. The method for setting the range of the operating force of the engineering mechanical component according to claim 1, wherein the step of preprocessing the collected electromyographic signals to obtain the muscle activation degree of the human subject under the set operating force comprises the following steps:
carrying out data preprocessing on the collected electromyographic signals;
performing data filtration on the preprocessed electromyographic signals through a low-pass filter and solving the root mean square value of the electromyographic signals;
acquiring the muscle activation degree based on the root mean square value of the electromyographic signal and the root mean square value of the maximum autonomous contraction of the muscle:
where Act represents the degree of muscle activation, RMS represents the root mean square value of the electromyographic signal, and MVC represents the root mean square value of the maximum voluntary contraction of the muscle.
3. The method for setting the range of the operating force of a work machine component according to claim 2, wherein the data preprocessing includes: and carrying out 50Hz trap wave, 30Hz zero phase shift high-pass filtering and full-wave rectification on the electromyographic signals.
4. The method for setting the range of the operating force of the component of the construction machine according to claim 1, wherein the range of the operating force of the component is determined based on the acquired subjective fatigue data and the degree of muscle activation of all the subjects, and specifically comprises:
based on the muscle activation degree that obtains, carry out the analysis to driver's fatigue degree under different operating modes, include: respectively intercepting different myoelectric signals of all the testees to obtain the mean value of muscle activation degrees of all the testees under different operating forces;
the method comprises the steps of obtaining the growth rate of muscle activation degree based on the mean value of the muscle activation degree of all testees under different operation forces, and determining the operation force range of a component by taking the growth rate of the muscle activation degree as a key index and combining subjective fatigue data of the testees.
5. An evaluation method for driver operation fatigue is characterized by comprising the following steps:
determining an operating force range of a component based on the method for setting an operating force range of a construction machine component according to any one of claims 1 to 4;
setting an operation force of the member based on the determined operation force range;
acquiring subjective fatigue data of a testee when the testee operates the component under a set operating force according to a set time interval;
collecting myoelectric signals fed back by muscles when a tested person operates a component under a set operating force;
carrying out data processing on the collected electromyographic signals to obtain the muscle activation degree of the testee under the set operating force;
and acquiring the time for starting fatigue of the driver when the driver operates the component based on the acquired subjective fatigue data and the muscle activation degree values of all the testees, and evaluating the change condition of the work fatigue of the driver.
6. The method for evaluating the working fatigue of the driver as claimed in claim 5, wherein the step of performing data processing on the collected electromyographic signals to obtain the muscle activation degree of the human subject under the set operating force comprises:
carrying out data preprocessing on the collected electromyographic signals;
performing data filtration on the preprocessed electromyographic signals through a low-pass filter and solving the root mean square value of the electromyographic signals;
acquiring the muscle activation degree based on the root mean square value of the electromyographic signal and the root mean square value of the maximum autonomous contraction of the muscle:
where Act represents the degree of muscle activation, RMS represents the root mean square value of the electromyographic signal, and MVC represents the root mean square value of the maximum voluntary contraction of the muscle.
7. The method for evaluating driver's work fatigue according to claim 6, wherein the data preprocessing comprises: and carrying out 50Hz trap wave, 30Hz zero phase shift high-pass filtering and full-wave rectification on the electromyographic signals.
8. The method for evaluating the working fatigue of a driver as claimed in claim 5, wherein the parts comprise a steering wheel, a handle and a pedal of a prototype vehicle, and the steering wheel, the handle and the pedal of the prototype vehicle.
9. The method for evaluating driver's work fatigue according to claim 8, wherein the step of obtaining the time for starting fatigue of the driver when operating the component for evaluating the change of the driver's work fatigue based on the collected subjective fatigue data and the muscle activation level values of all the subjects comprises:
based on the data of the original vehicle test, the average time of the fatigue degree of the original vehicle test is measured, the change condition of the operation fatigue degree of a driver is evaluated by comparing the time of the driver driving the original vehicle with the time of starting fatigue of a sample vehicle, and the specific measurement formula is as follows:
wherein, P represents the fatigue time prolonging rate of the driver;
representing the average time for the Act value to reach fatigue in a prototype test;
representing the average time for the Act value to reach fatigue in the original vehicle test;
wherein, TiRepresenting the time when the Act value reaches fatigue when the ith sample is subjected to a prototype test; n represents the number of test samples;
wherein, TjAnd the time when the Act value reaches fatigue when the jth sample is subjected to the original vehicle test is shown.
10. The method for evaluating driver's work fatigue according to claim 5, wherein the time for starting fatigue is determined by a time corresponding to a time when a sudden change occurs in the rate of increase in the degree of muscle activation.
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Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2002224072A (en) * | 2001-02-02 | 2002-08-13 | Mazda Motor Corp | Muscular fatigue evaluating device, muscular fatigue evaluating method, computer program for executing this method and storage medium for storing this computer program |
| US20060079800A1 (en) * | 2004-07-01 | 2006-04-13 | Mega Elektroniikka Oy | Method and device for measuring exercise level during exercise and for measuring fatigue |
| US20100139395A1 (en) * | 2007-07-09 | 2010-06-10 | The Yokohama Rubber Co., Ltd. | Method for evaluating an instrument operating force |
| CN103892847A (en) * | 2013-12-25 | 2014-07-02 | 北京师范大学 | Portable muscle isotonic contraction power curve testing system |
| JP2015062658A (en) * | 2013-08-30 | 2015-04-09 | 国立大学法人鳥取大学 | Muscle fatigue quantitative evaluation method, muscle fatigue display device, and muscle fatigue quantitative evaluation apparatus |
| CN106491127A (en) * | 2016-10-11 | 2017-03-15 | 广州汽车集团股份有限公司 | Drive muscular strain early warning value method of testing and device and drive muscular strain prior-warning device |
| CN108742610A (en) * | 2018-04-03 | 2018-11-06 | 吉林大学 | A kind of realization myoelectricity and subjective associated steering Comfort Evaluation method |
| CN109760691A (en) * | 2019-03-18 | 2019-05-17 | 吉林大学 | It is a kind of consider electromyography signal driver comfort drive posture under the matched method of man-machine arrangement parameter |
| CN109833041A (en) * | 2017-11-24 | 2019-06-04 | 北京航空航天大学 | Exercise induced fatigue intelligent measurement and analysis system |
| CN110786871A (en) * | 2019-10-31 | 2020-02-14 | 清华大学 | Human body electromyographic signal testing device, data processing and activation level calculating method |
| CN112353393A (en) * | 2020-11-09 | 2021-02-12 | 清华大学 | Intelligent driving automobile passenger state detection system |
-
2021
- 2021-06-16 CN CN202110666908.6A patent/CN113397568B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2002224072A (en) * | 2001-02-02 | 2002-08-13 | Mazda Motor Corp | Muscular fatigue evaluating device, muscular fatigue evaluating method, computer program for executing this method and storage medium for storing this computer program |
| US20060079800A1 (en) * | 2004-07-01 | 2006-04-13 | Mega Elektroniikka Oy | Method and device for measuring exercise level during exercise and for measuring fatigue |
| US20100139395A1 (en) * | 2007-07-09 | 2010-06-10 | The Yokohama Rubber Co., Ltd. | Method for evaluating an instrument operating force |
| JP2015062658A (en) * | 2013-08-30 | 2015-04-09 | 国立大学法人鳥取大学 | Muscle fatigue quantitative evaluation method, muscle fatigue display device, and muscle fatigue quantitative evaluation apparatus |
| CN103892847A (en) * | 2013-12-25 | 2014-07-02 | 北京师范大学 | Portable muscle isotonic contraction power curve testing system |
| CN106491127A (en) * | 2016-10-11 | 2017-03-15 | 广州汽车集团股份有限公司 | Drive muscular strain early warning value method of testing and device and drive muscular strain prior-warning device |
| CN109833041A (en) * | 2017-11-24 | 2019-06-04 | 北京航空航天大学 | Exercise induced fatigue intelligent measurement and analysis system |
| CN108742610A (en) * | 2018-04-03 | 2018-11-06 | 吉林大学 | A kind of realization myoelectricity and subjective associated steering Comfort Evaluation method |
| CN109760691A (en) * | 2019-03-18 | 2019-05-17 | 吉林大学 | It is a kind of consider electromyography signal driver comfort drive posture under the matched method of man-machine arrangement parameter |
| CN110786871A (en) * | 2019-10-31 | 2020-02-14 | 清华大学 | Human body electromyographic signal testing device, data processing and activation level calculating method |
| CN112353393A (en) * | 2020-11-09 | 2021-02-12 | 清华大学 | Intelligent driving automobile passenger state detection system |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116269393A (en) * | 2023-05-22 | 2023-06-23 | 南京航空航天大学 | Interactive fitness fatigue monitoring method and device integrating myoelectricity and subjective perception |
| CN116269393B (en) * | 2023-05-22 | 2023-08-01 | 南京航空航天大学 | Interactive fitness fatigue monitoring method and device integrating myoelectricity and subjective perception |
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