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Air traffic controller fatigue detection method based on clustering analysis, device and system

A technology for air traffic and fatigue detection, applied in instruments, alarms, etc., can solve the problems of comprehensiveness, lack of comprehensiveness, less quantitative research, and less engineering applications, and achieves strong practicability and operability, and a high degree of recognition. , Algorithm easy effect

Active Publication Date: 2016-01-20
THE SECOND RES INST OF CIVIL AVIATION ADMINISTRATION OF CHINA
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Problems solved by technology

[0003] The existing research on controller fatigue detection mainly has the following deficiencies: (1) In terms of research methods, there are more qualitative research and less quantitative research, resulting in insufficient objectivity; (2) In terms of detection indicators, the index dimension is relatively single and comprehensive (3) Existing studies use the same index detection standard for all controllers, ignoring the individual differences in fatigue indicators, and the detection results are not accurate enough; (4) In terms of applicability, it is oriented to the actual situation of air traffic control units. There are few engineering applications and it is difficult to realize
Due to the above deficiencies, the current research on controller fatigue detection at home and abroad is lacking in objectivity, comprehensiveness, comprehensiveness, accuracy and operability.

Method used

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  • Air traffic controller fatigue detection method based on clustering analysis, device and system
  • Air traffic controller fatigue detection method based on clustering analysis, device and system
  • Air traffic controller fatigue detection method based on clustering analysis, device and system

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Embodiment 1

[0033] figure 1 It is a system structure diagram of the present invention. The fatigue detection system integrating face and voice provided by the present invention includes a real-time audio and video full data collection platform for control seats, a controller fatigue detection database integrating face recognition and land-air call voice analysis, and a controller fatigue detection system. Indicator detection module, controller fatigue alarm module: Based on the historical statistical results in the controller fatigue detection database integrated with facial recognition and ground-air call voice analysis, the cluster analysis method is used to construct controller work status files, and the controller fatigue indicators The controller fatigue indicator detection data in the detection module is classified and comprehensively detected, and if the similarity exceeds the threshold range, an alarm is triggered.

Embodiment 2

[0035] A kind of integrated face and voice air traffic controller fatigue detection method, it is characterized in that, comprising the following steps:

[0036] Step 1: Receive the control seat video monitoring data and land-air call data obtained by the real-time audio and video full data collection device. The process of receiving the control seat video monitoring data is to collect video information in real time, perform noise reduction and filtering processing, and extract Characteristic value; the process of receiving the land-air call data is to use a cable to connect the voice signal from the distribution frame to the voice processor, and when the sound signal is detected in the system audio channel, start recording; when the audio channel is detected If there is no sound for 3 seconds, stop recording, that is to say, one recording is completed. The next time a sound signal is detected, the recording will be repeated. If there is no sound signal in the audio channel, no...

Embodiment 3

[0041]An air traffic controller fatigue detection method that integrates face and voice, detects the fatigue degree of the controller through 8 fatigue indicators, specifically includes: calculating and counting the facial expression characteristics of the controller through the video surveillance data of the control seat, so as to analyze Obtain the statistical data of PERCLOS value, average eye-closing time and yawning frequency, and analyze and analyze the land and air call data collected and processed by the real-time audio and video full data collection platform of the control seat: channel occupancy rate, number of calls, average audio frequency , the average sound intensity, and the occurrence rate of key words in land and air calls in the sector.

[0042] Among them, the PERCLOS value detection uses the ratio of the eye closure time to 60 seconds. The PERCLOS value was calculated using the P80 measurement method (the proportion of time when the area of ​​the eyelid cov...

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Abstract

The invention provides an air traffic controller fatigue detection method based on clustering analysis, a device and a system. The method comprises steps that, 1, control seat video monitoring data and air-ground conversation data acquired by an audio and video full data acquiring device in real time are received; 2, the control seat video monitoring data and the air-ground conversation data are detected and analyzed to acquire controller fatigue index detection data; 3, referring to preset controller fatigue index detection data samples, controller work state archives are established by utilizing a clustering analysis method; and 4, classification integration detection is carried out by utilizing the controller fatigue index detection data acquired in the step 2, if similarity exceeds a threshold scope, alarming is triggered. The fatigue detection method can be applied to the air traffic control field and has relatively great practicality and maneuverability.

Description

technical field [0001] The invention provides an air traffic controller fatigue detection method, device and system integrating face and voice, belonging to the technical field of image processing and pattern recognition. technical background [0002] At present, the relevant research on controller fatigue is mainly carried out from two aspects, namely, controller fatigue detection based on facial recognition, and controller fatigue detection based on workload evaluation. The former is based on the analysis of the facial features of the controller, and obtains the data of three fatigue detection indicators such as PERCLOS (percentage of eyelid closure) value, average eye closure time, and yawn frequency. Threshold, the fatigue of the controller is detected, such as application number CN104112335A provides a driver fatigue detection method based on multi-information fusion, which adopts the method of quantifying the fatigue level, extracting fatigue state characteristic param...

Claims

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Application Information

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IPC IPC(8): G08B21/06
CPCG08B21/06
Inventor 张建平叶青张瑞平徐祥刚
Owner THE SECOND RES INST OF CIVIL AVIATION ADMINISTRATION OF CHINA
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