Human body static comprehensive testing device capable of recording personnel information

Abstract

The invention relates to the technical field of static electricity testing, and discloses a human body static electricity comprehensive testing device capable of recording personnel information, which comprises a static electricity measuring module, a personnel information recording module, a human body static electricity comprehensive testing module, a human body static electricity comprehensive testing module and a human body static electricity comprehensive testing module, the system comprises an electrostatic measurement module, a personnel information recording module, a data processing module, a voice output module, a voice file and an abnormity alarm module, wherein the personnel information recording module is used for recording names, job numbers, departments and current detection numerical value information of detection personnel; the data processing module is used for receiving, storing, analyzing and displaying data of the electrostatic measurement module and the personnel information recording module; through the personnel information recording module, information of testers can be recorded and matched with detection numerical values, effective tracking and management of anti-static measures are achieved, the accuracy and reliability of testing can be improved, and potential safety hazards caused by the static problem can be greatly reduced.

Description

Technical Field

[0001] The invention relates to the technical field of electrostatic testing, in particular to a comprehensive human body electrostatic testing device capable of recording personnel information. Background Art

[0002] Comprehensive static electricity testing is an important technical means to evaluate and manage static electricity risks, and is widely used in various industries, especially in the fields of electronics, chemicals, and pharmaceuticals. Static electricity accumulation may cause equipment damage, product defects, and even safety accidents, so it is crucial to understand and control the generation and distribution of static electricity.

[0003] The comprehensive internal static electricity test of the factory can identify potential static electricity accumulation areas and problems by measuring static electricity potential, monitoring environmental conditions and checking grounding conditions to ensure the safety of the production environment and prevent static electricity from affecting equipment and personnel.

[0004] In the existing electrostatic testing technology, although there are many human body electrostatic comprehensive testers, most of the equipment can only realize a single human body comprehensive resistance measurement function and cannot record the specific information of the tester. This leads to the fact that in the petrochemical, military, pyrotechnic and other industries, hazardous chemical, explosive production workshops and warehouses, where electrostatic prevention and control is key, from the perspective of emergency escape, it is not allowed to install devices with locks such as access control to force employees to measure the electrostatic protection performance of the wearables. In the implementation of daily anti-static measures, it is impossible to effectively track and manage the detection behavior of specific personnel. Therefore, the development of a human body electrostatic comprehensive test device that can record personnel information has important practical application value. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a comprehensive human body static electricity testing device that can record personnel information, thereby solving the problem of being unable to effectively track and manage the detection behavior of specific personnel during the implementation of daily anti-static measures.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a comprehensive human body static electricity testing device capable of recording personnel information, comprising the following modules:

[0007] The static electricity measurement module uses static electricity field sensors and circuit systems to detect the anti-static performance of wrist straps and work shoes worn by the human body, and transmits the data to the data processing module for processing;

[0008] The personnel information recording module uses a macro high-definition camera to capture the tester's face image and transmit it to the personnel information recording module. By comparing it with the pre-entered controlled group face information, the tester's basic information including name, work number, and department is recorded, and this information is associated with the electrostatic measurement data;

[0009] A data processing module receives data from the electrostatic measurement module and the personnel information recording module, and performs storage, analysis and display;

[0010] Voice output module, after completing the detection process, the voice output module will instantly play the voice file of the test results;

[0011] The abnormal alarm module regularly performs sensor self-inspection on the electrostatic field sensors at different positions, and determines whether it is necessary to perform an abnormal state alarm based on the self-inspection results. At the same time, the data processing module issues an abnormal alarm when electrostatic measurement abnormalities occur multiple times for the same person.

[0012] Preferably, the electrostatic measurement module is connected to a plurality of groups of electrostatic field sensors, and the sensing detection ranges of different electrostatic field sensors are identified according to the serial port coding numbers of the corresponding electrostatic field sensors.

[0013] Preferably, the personnel information recording module is used to control the video recording device to identify and detect the tester in the current detection area, and the personnel information recording module includes an edge recognition module, a motion control module, a video adjustment module and a data loading module.

[0014] Preferably, the edge recognition module uses a portrait recognition algorithm to identify the area where the current tester is located and calibrate the position of the tester's face. The motion control module is used to adjust the recording area of ​​the video recording device and control the angle of the video recording device driven by the electronic control device according to the area where the face is located identified by the edge recognition module.

[0015] Preferably, the video adjustment module is used to recalibrate the focus, exposure and white balance of the video recording device according to the movement of the motion control module. The data loading module has a built-in user database and can recognize the current facial information after obtaining the current facial information, and store the recognized information in an information list.

[0016] Preferably, the data processing module adopts database technology to realize classified storage and retrieval of data, and the user can call the information list to view the electrostatic measurement data and basic information of the tester.

[0017] Preferably, the data processing module also adopts adaptive calibration technology, and automatically adjusts measurement parameters according to different environmental conditions and usage frequencies during data processing, and automatically compensates the measurement results of the data results detected in the electrostatic measurement module.

[0018] Preferably, the voice output module has a built-in voice database, and outputs a reply voice according to the feedback logic of the data processing module. In addition, the reply voice supports custom settings by managers.

[0019] Preferably, the abnormal alarm module includes a self-test alarm module and an abnormal data reporting module, wherein the self-test alarm module includes an electrostatic generator, an electrostatic voltmeter, an oscilloscope, and a power supply. An electrostatic field of known intensity is generated by the electrostatic generator, and an electrostatic field sensor and an electrostatic voltmeter are used to measure the error value, and it is calculated whether the error value is within a threshold range.

[0020] Preferably, the abnormal data reporting module is used to calculate the electrostatic data of the testers collected by the data processing module, and generate corresponding abnormal data reports for the testers who have been unqualified in electrostatic detection for a long time and transmit them to the corresponding management personnel.

[0021] The present invention provides a comprehensive human body static electricity testing device capable of recording personnel information.

[0022] Beneficial effects:

[0023] 1. The present invention can record the tester information and match the tester information with the detection value through the personnel information recording module, so as to realize the effective tracking and management of anti-static measures, which can not only improve the accuracy and reliability of the test, but also greatly reduce the safety hazards caused by static electricity problems.

[0024] 2. The data processing module set up in the present invention can automatically compensate the detection data of the electrostatic field sensor through an adaptive calibration algorithm during the detection process of the electrostatic measurement module, thereby ensuring that the final electrostatic field sensor data is more accurate and is not easily affected by factors such as ambient temperature and humidity.

[0025] 3. The present invention sets up an abnormal alarm module, which can preferentially perform a self-check on the electrostatic field sensor currently in use before the electrostatic field sensor performs electrostatic detection on the detection personnel, and determine whether there is an abnormality in the electrostatic field sensor currently in use based on the result of the self-check, thereby ensuring that the electrostatic field sensor can work normally and feedback accurate values ​​during the process of performing electrostatic detection on the detection personnel. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a system flow chart of the comprehensive human body static electricity testing device that can record personnel information;

[0027] Figure 2 This is the system flow chart of the personnel information recording module. DETAILED DESCRIPTION

[0028] The following will be combined with the drawings in the specification of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0029] Example:

[0030] Please see attached Figure 1 - Attachment Figure 2 The embodiment of the present invention provides a comprehensive human body static electricity testing device capable of recording personnel information, including the following modules:

[0031] The static electricity measurement module uses static electricity field sensors and circuit systems to detect the anti-static performance of wrist straps and work shoes worn by the human body, and transmits the data to the data processing module for processing;

[0032] The electrostatic measurement module is connected to multiple groups of electrostatic field sensors, and identifies the sensing detection ranges of different electrostatic field sensors according to the serial port coding numbers of the corresponding electrostatic field sensors;

[0033] The personnel information recording module uses a macro high-definition camera to capture the tester's face image and transmit it to the personnel information recording module. By comparing it with the pre-entered controlled group face information, the tester's basic information including name, work number, and department is recorded, and this information is associated with the electrostatic measurement data;

[0034] The personnel information recording module is used to control the video recording device to identify and detect the tester in the current detection area, and the personnel information recording module includes an edge recognition module, a motion control module, a video adjustment module and a data loading module;

[0035] The edge recognition module uses an advanced portrait recognition algorithm to quickly and accurately identify the area where the current tester is located in a complex environment.

[0036] First, the module continuously receives image data from the video recording device, and detects areas where faces may exist by performing real-time analysis on these images and applying image processing technology. The portrait recognition algorithm extracts various features from the image, including facial contours, the shape and position of facial features. These features are compared with pre-stored facial feature templates to determine whether they are valid face areas.

[0037] Once the face area of ​​the tester is identified, the module will further accurately calibrate the position of the tester's face. It will calculate the coordinate position, angle, size and other parameters of the face in the image to provide accurate reference information for subsequent operations. For example, if the face is slightly off the center, the module will send an adjustment signal so that other modules can make corresponding adjustments in time to ensure that the tester's face is always in the best shooting position;

[0038] The motion control module cooperates closely with the video recording device and accurately adjusts the recording area of ​​the video recording device according to the face area information provided by the edge recognition module.

[0039] When the edge recognition module detects a change in the position of the face, the motion control module will respond immediately. It controls the electronic control device to drive the video recording device to adjust the angle. This process requires the accuracy and stability of the adjustment to ensure that the video recording device can quickly and accurately align with the tester's face.

[0040] For example, if the tester slightly moves his head, the motion control module will calculate the angle that needs to be adjusted based on the new position of the face. Then, it will send instructions to the electronic control device to make the video recording device rotate a certain angle accordingly to keep tracking the tester's face. At the same time, the motion control module will constantly monitor the changes in the face position and adjust the angle of the video recording device in real time to ensure the stability and accuracy of the shooting;

[0041] The video adjustment module is responsible for ensuring that the video recording device can always capture clear and recognizable images. When the motion control module adjusts the angle of the video recording device, the video adjustment module will recalibrate the focus, exposure and white balance of the video recording device according to the motion of the motion control module.

[0042] The focus adjustment is to ensure that the tester's face is always clearly visible. The video adjustment module will automatically adjust the focus according to the size and position of the face in the image to make the facial details clearly visible. If the face is close to or far away from the video recording device, the module will adjust the focus in real time to maintain the clarity of the image.

[0043] Exposure adjustment is to adapt to different lighting conditions. If the ambient light is too strong or too weak, the video adjustment module will automatically adjust the exposure to make the image brightness moderate to avoid overexposure or underexposure. It will analyze the brightness distribution of the image and adjust it according to the brightness of the face area to ensure the appropriate exposure of the face.

[0044] White balance adjustment is to ensure that the color of the image is true and natural. Under different lighting conditions, the color will change. The video adjustment module will automatically adjust the white balance according to the color temperature of the ambient light to make the color of the image conform to the actual situation. For example, when shooting in daylight and shooting under indoor lighting, the white balance needs to be adjusted differently to ensure the color of the face is true and accurate;

[0045] The data loading module has a built-in user database and can identify the current face information after obtaining it, and store the identified information in the information list; when the system obtains the current face information, the data loading module will immediately identify it. It will extract the features of the face image and compare it with the face features in the user database, and determine whether the current face already exists in the database through algorithms and pattern matching technology.

[0046] If the recognition is successful, the module will store the recognized information in the information list. This information list can include basic information such as the tester's name, work number, department, and additional information such as shooting time and location.

[0047] At the same time, the data loading module can also manage and update the user database. For example, when a new tester joins, his / her facial information can be entered into the database; when the tester's information changes, the content in the database can be updated in time. In this way, the system can always maintain accurate facial recognition and data storage functions;

[0048] The data processing module adopts database technology to realize classified storage and retrieval of data. The user can call the information list to view the electrostatic measurement data and basic information of the tester. The data processing module also adopts adaptive calibration technology, and automatically adjusts the measurement parameters according to different environmental conditions and usage frequency during the data processing process, and automatically compensates the measurement results for the data results detected in the electrostatic measurement module. The adaptive calibration process adopts the following algorithm:

[0049] A priori state estimate:

[0050] in is the prior state estimate at time k, is the posterior state estimate of the previous moment, A is the state transfer matrix, B is the control input matrix, u k is the control input;

[0051] A priori error covariance estimate:

[0052] in is the prior error covariance estimate, P k-1is the posterior error covariance estimate of the previous moment, Q is the process noise covariance matrix;

[0053] Gain calculation:

[0054] Where K k is the gain, H is the measurement matrix, and R is the observation noise covariance matrix;

[0055] Posterior state estimate:

[0056] in The posterior state estimate at time k, z k is the observed value;

[0057] Posterior error covariance estimate:

[0058] Where P k is the posterior error covariance estimate and I is the identity matrix.

[0059] According to the above algorithm, we get the following example:

[0060] Suppose we want to calibrate the output of the electrostatic measurement sensor. The output of the sensor can be expressed as a voltage value y, and the actual amount of static electricity is x. A simple linear model can be established:

[0061] y=Cx+v;

[0062] Where C is the sensitivity coefficient of the sensor and v is the measurement noise;

[0063] The static electricity x is taken as the state variable of the system, and the sensor output y is taken as the observed value. Assume that the initial state is estimated as The initial error covariance is P 0 , the process noise covariance Q and the observation noise covariance R are set according to the actual situation;

[0064] At each time step, we first perform a prediction step to predict the current state and error covariance based on the state estimate and process model of the previous moment. Then, when the sensor outputs a new observation, an update step is performed to calculate the gain, update the state estimate and error covariance. By continuously iterating this process, the above filtering algorithm can dynamically adjust the state estimate according to the sensor's observations, thereby achieving adaptive calibration of electrostatic measurement;

[0065] For example, in a practical electrostatic measurement scenario, the initial state is estimated to be Initial error covariance P 0=1, process noise covariance Q = 0.01, observation noise covariance R = 0.1, sensor sensitivity coefficient C = 1.2, in a series of time steps, the sensor observation values ​​are 0.5, 0.8, 1.1, and 1.4 respectively. Adaptive calibration through filtering algorithm can obtain continuously optimized static electricity estimation values;

[0066] Voice output module, after completing the detection process, the voice output module will instantly play the voice file of the test results;

[0067] The voice output module has a built-in voice database, and outputs reply voice according to the feedback logic of the data processing module. In addition, the reply voice supports custom settings by managers;

[0068] The abnormal alarm module regularly performs sensor self-test on the electrostatic field sensors at different positions, and determines whether it is necessary to perform abnormal state alarm according to the self-test results. At the same time, the data processing module issues an abnormal alarm when the electrostatic measurement abnormalities occur multiple times for the same person;

[0069] The abnormal alarm module includes a self-check alarm module and an abnormal data reporting module, wherein the self-check alarm module includes an electrostatic generator, an electrostatic voltmeter, an oscilloscope, and a power supply. The specific self-check process is as follows:

[0070] Functional Check

[0071] Turn on the sensor power supply and observe whether the indicator light of the sensor lights up normally to confirm that the power supply system of the sensor is normal; at the same time, check whether the sensor can output data normally through the display screen or output interface of the sensor.

[0072] Accuracy check

[0073] Use an electrostatic generator to generate an electrostatic field of known strength, place the sensor in the electrostatic field, and observe the difference between the electrostatic field strength detected by the sensor and the known value; perform multiple tests at different electrostatic field strengths to evaluate the linearity and accuracy of the sensor; compare the results detected by the sensor with the measured values ​​of a high-precision electrostatic voltmeter to further verify the accuracy of the sensor;

[0074] Stability Check

[0075] Allow the sensor to work continuously in a stable electrostatic field environment for a period of time, and observe whether the data output by the sensor is stable and whether there is drift; record the output data of the sensor over a period of time, and evaluate the stability of the sensor through data analysis.

[0076] Response time check

[0077] Rapidly change the intensity of the electrostatic field and observe the sensor's response time to the change in the electrostatic field. Use a pulse electrostatic generator to generate instantaneous changes in the electrostatic field, and determine the sensor's response time by measuring the time interval from the sensor detecting the change in the electrostatic field to outputting a stable result.

[0078] The equipment used in the process includes:

[0079] Electrostatic generator: used to generate an electrostatic field of known strength to test the accuracy and response time of the sensor;

[0080] High-precision electrostatic voltmeter: used as a reference standard to compare the sensor's test results to evaluate the sensor's accuracy;

[0081] Oscilloscope: used to observe the waveform of the sensor output signal to help determine the working status and response characteristics of the sensor;

[0082] Power supply: Provides stable power to the sensor to ensure stable power supply to the sensor during the self-test process;

[0083] The abnormal data reporting module is used to calculate the electrostatic data of the testers collected by the data processing module, and generate corresponding abnormal data reports for the testers who have been unqualified in electrostatic detection for a long time and transmit them to the corresponding management personnel.

[0084] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A comprehensive human body static electricity testing device capable of recording personnel information, characterized in that: Includes the following modules: The static electricity measurement module uses static electricity field sensors and circuit systems to detect the anti-static performance of wrist straps and work shoes worn by the human body, and transmits the data to the data processing module for processing; The personnel information recording module uses a macro high-definition camera to capture the tester's face image and transmit it to the personnel information recording module. By comparing it with the pre-entered controlled group face information, the tester's basic information including name, work number, and department is recorded, and this information is associated with the electrostatic measurement data; A data processing module receives data from the electrostatic measurement module and the personnel information recording module, and performs storage, analysis and display; Voice output module, after completing the detection process, the voice output module will instantly play the voice file of the test results; The abnormal alarm module regularly performs sensor self-inspection on the electrostatic field sensors at different positions, and determines whether it is necessary to perform an abnormal state alarm based on the self-inspection results. At the same time, the data processing module issues an abnormal alarm when electrostatic measurement abnormalities occur multiple times for the same person.

2. A comprehensive human body static electricity testing device capable of recording personnel information according to claim 1, characterized in that: The electrostatic measurement module is connected to a plurality of groups of electrostatic field sensors, and identifies the sensing detection ranges of different electrostatic field sensors according to the serial port coding numbers of the corresponding electrostatic field sensors.

3. A comprehensive human body static electricity testing device capable of recording personnel information according to claim 1, characterized in that: The personnel information recording module is used to control the video recording device to identify and detect the tester in the current detection area. The personnel information recording module includes an edge recognition module, a motion control module, a video adjustment module and a data loading module.

4. A comprehensive human body static electricity testing device capable of recording personnel information according to claim 3, characterized in that: The edge recognition module uses a portrait recognition algorithm to identify the area where the current tester is located and calibrate the position of the tester's face. The motion control module is used to adjust the recording area of ​​the video recording device and control the angle of the video recording device driven by the electronic control device according to the area where the face is located recognized by the edge recognition module.

5. A comprehensive human body static electricity testing device capable of recording personnel information according to claim 3, characterized in that: The video adjustment module is used to recalibrate the focus, exposure and white balance of the video recording device according to the movement of the motion control module. The data loading module has a built-in user database and can recognize the current face information after obtaining the current face information, and store the recognized information in an information list.

6. A comprehensive human body static electricity testing device capable of recording personnel information according to claim 1, characterized in that: The data processing module adopts database technology to realize classified storage and retrieval of data, and the user can call the information list to view the electrostatic measurement data and basic information of the tester.

7. A comprehensive human body static electricity testing device capable of recording personnel information according to claim 1, characterized in that: The data processing module also uses an adaptive calibration technology, and automatically adjusts measurement parameters according to different environmental conditions and usage frequencies during the data processing process, and automatically compensates the measurement results of the data results detected in the electrostatic measurement module.

8. A comprehensive human body static electricity testing device capable of recording personnel information according to claim 1, characterized in that: The voice output module has a built-in voice database, and outputs reply voices according to the feedback logic of the data processing module. In addition, the reply voices support customized settings by managers.

9. A comprehensive human body static electricity testing device capable of recording personnel information according to claim 1, characterized in that: The abnormal alarm module includes a self-test alarm module and an abnormal data reporting module, wherein the self-test alarm module includes an electrostatic generator, an electrostatic voltmeter, an oscilloscope, and a power supply. The electrostatic generator generates an electrostatic field of known intensity and simultaneously uses an electrostatic field sensor and an electrostatic voltmeter to measure the error value, and calculates whether the error value is within a threshold range.

10. A comprehensive human body static electricity testing device capable of recording personnel information according to claim 9, characterized in that: The abnormal data reporting module is used to calculate the electrostatic data of the testers collected by the data processing module, and generate corresponding abnormal data reports for the testers who have been unqualified in electrostatic detection for a long time and transmit them to the corresponding management personnel.

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