CN106725290A - A kind of cable machine driver stress ability method of testing - Google Patents

Abstract

A method for testing the stress ability of a cable car driver. The helmet-type eye tracker records the pupil area A _{t of the subject at each moment in a stressful environment, and calculates the pupil area A t at} each moment recorded by the eye tracker. The instantaneous pupil area A _i under the driver's stress is obtained, and the average value of the pupil area A _t change in the stress scene T seconds in the i-th training of the cable car driver is used as the instantaneous pupil area A _i when the scene is triggered. SPSS18.0 obtained the logarithmic regression model of the pupil area change rate K _i and the number of driver training times. The number of driver training times refers to the number of training times that the driver can correctly and reasonably deal with dangerous scenes after training. of training times. The invention relates to a method for testing the stress ability of a cable machine driver, which can measure the driver's stress response ability according to the different operating environments of the cable machine driver, so as to formulate a reasonable number of training times for the driver to deal with dangerous scenes, and improve the safety of the cable car driver. machine operation safety.

Description

A test method for the stress ability of the cable car driver

technical field

The invention relates to a method for testing the stress ability of a cable car driver, which is used to obtain the number of training times for the driver to correctly respond to dangerous scenes.

Background technique

The hydropower project is limited by the construction technology, and the operations such as steel bar binding, formwork hoisting, and embedded parts laying on the surface of the dam preparation warehouse are often carried out at the same time as the cable crane lifting operation. In the limited space on the dam surface, the processes of laying cooling water pipes, unwinding, vibrating, quality inspection and other processes form cross operations with concrete entering the silo. Intersecting work space conflicts can easily lead to emergent and dangerous scenes. Test the stress response ability of the cable machine driver for long-sight operation, determine the stress response ability of the cable machine driver, and formulate a training plan to deal with dangerous scenarios. There's important meaning.

Contents of the invention

The invention provides a method for testing the stress ability of the cable machine driver, which can measure the driver's stress response ability according to the different operating environments of the cable machine driver, so as to formulate a reasonable number of training times for the driver to deal with dangerous scenes, and improve the The safety of the cable car operation.

The technical scheme that the present invention takes is:

A method for testing the stress ability of a cable car driver, comprising the following steps:

Step 1: The helmet-type eye tracker records the pupil area A _t of the test personnel at each moment in the stressful environment, and calculates the instantaneous pupil area A _t of the driver under stress according to the pupil area A t recorded by the eye tracker at each moment Area, the average value of the pupil area change within T seconds of the stress scene in the i-th training of the cable car driver is taken as the instantaneous pupil area when the scene is triggered, and the calculation formula of the instant pupil area is:

A _i represents the instantaneous pupil area of the driver within T seconds of the stress scene in the i-th training, and A _t represents the pupil area of the operator at time t.

Step 2: Use SPSS18.0 to conduct regression analysis on the eye movement test data of the test personnel in the simulated dangerous scene, and establish the functional relationship between the training times of the cable car driver and the pupil change rate K _i . The number of driver training refers to the number of _times the driver can correctly and reasonably deal with dangerous scenes after training. Ratio; the calculation formula of pupil area change rate is:

Step 3: Obtain the number of training times for the cable car driver to deal with dangerous scenes, and the pupil area change rate tends to be flat, that is, when the dangerous scene test is terminated, the difference between the pupil area change rate of the n-1th time and the nth time needs to satisfy the formula for:

|K _n -K _n-1 |<0.1％

Among them, the calculation formula of K _i is:

A method for testing the stress ability of a cable machine driver in the present invention has the advantages of:

1), the present invention utilizes the helmet-type eye tracker to record the pupil area of the cable car driver under stress, and can accurately measure the driver's stress state according to the pupil area, and judge the safety of the driver's operation.

2), the present invention can provide the number of times of training under the driver's dynamic stereotyping according to the pupil area change situation under the driver's stress condition.

3) The method of the present invention is simple and has high accuracy, which can effectively reduce the probability of human errors of cable crane drivers in hydropower projects.

Description of drawings

Fig. 1 is a flowchart of the present invention.

Fig. 2 is a curve diagram of the fitting training times of the cable car driver and the pupil change rate.

detailed description

A method for testing the stress ability of a cable car driver, comprising the following steps:

Step 1: The helmet-type eye tracker records the pupil area A _t of the test personnel at each moment in the stressful environment, and calculates the instantaneous pupil area A _t of the driver under stress according to the pupil area A t recorded by the eye tracker at each moment Area, the average value of the pupil area A _t change within T seconds of the stress scene in the i-th training of the cable car driver is taken as the instantaneous pupil area when the scene is triggered, and the calculation formula of the instant pupil area is:

A _i represents the instantaneous pupil area of the driver within T seconds of the stress scene in the i-th training, and A _t represents the pupil area of the operator at time t.

When the driver is responding to stress, there will be a series of physiological reactions such as the change of pupil area A _t , and the pupil area of the driver is recorded every second when the driver is responding to stress with a helmet-mounted eye tracker.

Step 2: Use SPSS18.0 to conduct regression analysis on the eye movement test data of the test personnel in the simulated dangerous scene, and establish the functional relationship between the training times of the cable car driver and the pupil change rate. The formula for calculating the rate of pupil area change is:

The number of driver training refers to the number of times the driver can correctly and reasonably respond to dangerous scenes after training.

Pupil change rate: the ratio of the change of the instantaneous pupil area A _t relative to the static pupil area A to the static pupil area A when the cable car driver is in stress state.

When the driver is responding to stress, if the change rate K _i of the cable car driver’s pupil area tends to be flat, it means that the cable car driver has been able to cope with the stress situation stably, that is to say, the driver has established a good coping ability. Impulse reaction dynamics are finalized, and the driver already has the ability to deal with dangerous scenarios.

Step 3: Obtain the number of training times for the cable car driver to deal with dangerous scenes: In order to obtain the driver's good stress response dynamics, it is necessary to train the driver's stress response ability in dangerous scenes. According to SPSS18.0, the test personnel Regression analysis of the eye movement test data in the simulated dangerous scene shows that the training times are correlated with the driver's stress response ability.

The number of driver training sessions refers to the number of times the driver can correctly and reasonably respond to dangerous scenes after training. According to SPSS18.0, the data of the eye movement test of the test personnel in the simulated dangerous scene, the data of the regression analysis shows that the number of driver training and the pupil area change rate K _i satisfy the mathematical relationship: k=a-blni, a, b The specific value of is determined according to the experimental data, and i represents the i-th test.

The pupil area change rate K _i of the cable car driver tends to be flat, that is, when the dangerous scene test is terminated, the difference between the pupil area change rate K _i of the n-1th and the nth time needs to satisfy the formula:

|K _n -K _n-1 |<0.1%

Calculation case:

Using the static pupil diameter of the cable car driver recorded by the eye tracker, the static pupil area of the left eye of the cable car driver is calculated to be 68.10mm ² , and the static pupil area of the right eye is 78.72mm ² .

Carry out the operation under the stress scene of the cable car driver for the first time, and use the driver’s pupil changes recorded by the eye tracker to calculate the driver’s stress state. The pupil area of the left eye is 94.86mm ² , and the pupil area of the right eye is 109.66mm ² . At this time, the pupil area change rate K ₁ is 0.393.

Carry out the operation under the stress scene of the cable car driver for the second time, use the eye tracker to record the driver's pupil changes, calculate the driver's stress state, the pupil area of the left eye is 94.45mm ² , and the pupil area of the right eye is 109.18mm ² . At this time, the pupil area change rate K ₂ is 0.387, which is |K ₂ -K ₁ |=0.006 compared with the first test. The test results cannot meet the requirements of the driver's stress ability, and it is necessary to continue the stress ability training for the driver.

Carry out the operation under the stress scene of the cable car driver for the third time, use the eye tracker to record the driver's pupil changes, and calculate the driver's stress state. The pupil area of the left eye is 94.18mm ² , and the pupil area of the right eye is 108.87mm ² . At this time, the pupil area change rate K ₃ is 0.383, which is |K ₃ -K ₂ |=0.004 compared with the second test. The test results cannot meet the requirements of the driver's stress ability, and it is necessary to continue the stress ability training for the driver.

Carry out the operation under the stress scene of the cable car driver for the fourth time, use the driver's pupil changes recorded by the eye tracker, and calculate the driver's stress state. The pupil area of the left eye is 93.97mm ² , and the pupil area of the right eye is 108.63mm ² . At this time, the pupil area change rate K ₄ is 0.380, compared with the third test |K ₄ -K ₃ |=0.003. The test results cannot meet the requirements of the driver's stress ability, and it is necessary to continue the stress ability training for the driver.

Carry out the operation under the stress scene of the fifth cable car driver, use the driver's pupil changes recorded by the eye tracker, calculate the driver's stress state, the pupil area of the left eye is 93.91mm ² , and the pupil area of the right eye is 108.56mm ² . At this time, the pupil area change rate K ₅ is 0.379, which is |K ₅ -K ₄ |=0.001 compared with the fourth test. At this time, the experimental results can meet the requirements of the driver's stress ability.

It can be seen that in this stress scenario, the driver only needs to be trained 5 times to meet the driver's motivational stereotypes.

Table 1 Changes in pupil diameter of a driver during a certain stress process

Claims (1)

1. A method for testing the stress ability of a cable car driver, characterized in that it may further comprise the steps: Step 1: The helmet-type eye tracker records the pupil area A _t of the test personnel at each moment in the stressful environment, and calculates the instantaneous pupil area A _t of the driver under stress according to the pupil area A t recorded by the eye tracker at each moment Area, the average value of the pupil area A _t change within T seconds of the stress scene in the i-th training of the cable car driver is taken as the instantaneous pupil area when the scene is triggered, and the calculation formula of the instant pupil area is: ${\mathrm{<span\; class="notranslate">\; A</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; T</span>}}\underset{\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; T</span>}}{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; A</span>}}_{\mathrm{<span\; class="notranslate">\; t</span>}}$ A _i represents the instantaneous pupil area of the driver within T seconds of the stress scene in the ith training, and A _t represents the pupil area A t of the operator at time _t ; Step 2: Carry out regression analysis on the eye movement test data of the subjects in the simulated dangerous scene, and establish the functional relationship between the training times of the cable car driver and the pupil change rate. The calculation formula of the pupil area change rate is: ${\mathrm{<span\; class="notranslate">\; K</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; A</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; A</span>}}{\mathrm{<span\; class="notranslate">\; A</span>}}<span\; class="notranslate">\; ;</span>$ Step 3: Obtain the number of training times for the cable car driver to deal with dangerous scenes, and the pupil area change rate tends to be flat, that is, when the dangerous scene test is terminated, the difference between the pupil area change rate of the n-1th time and the nth time needs to satisfy the formula for: |K _n -K _n-1 |<0.1% Among them, the calculation formula of K _i is: ${\mathrm{<span\; class="notranslate">\; K</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; A</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; A</span>}}{\mathrm{<span\; class="notranslate">\; A</span>}}<span\; class="notranslate">\; .</span>$