Occupational health hazard monitoring method, device and equipment and storage medium

Abstract

The invention discloses an occupational health hazard monitoring method, device and equipment and a storage medium, and the method comprises the steps: obtaining the time-varying concentration data of hazard factors in different stations of a production line, and generating the hazard factor monitoring data of each station; obtaining the stroke data of each worker on the production line, and obtaining the hazard contact duration of each worker on the corresponding station according to the stroke data; and calculating the average contact concentration of each worker and the dust hazard index of each station according to the hazard factor monitoring data and the hazard contact duration of each worker at the corresponding station. By associating the monitoring data with the actual contact conditions of the individual workers, the problem that the detection data is disjointed with the station features and the contact conditions of the individual workers in the prior art is solved, and the accuracy and effectiveness of occupational health monitoring are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of occupational health monitoring, and in particular to an occupational health hazard monitoring method, device, equipment and storage medium. BACKGROUND

[0002] In the field of occupational health monitoring, the existing technology mainly sets fixed monitoring points in the workplace to detect the concentration of harmful factors such as dust and toxic gas in the environment. These monitoring devices can collect environmental data in real time and provide evaluation basis for the overall health status of the workplace.

[0003] However, this detection method has obvious limitations. Since the monitoring data only reflects the concentration of harmful factors in the environment, it cannot be effectively associated with the specific work characteristics of the workstations and the actual exposure of individual workers, resulting in inaccurate assessment of the exposure of individual workers to harmful factors. In fact, even within the same workplace, workers at different workstations may face different health risks due to different work content, operation methods or protective measures, but the existing technology cannot combine these workstation characteristics with monitoring data, making it difficult to accurately assess the actual exposure level of workers at each workstation. The disconnection between this detection and the workstation characteristics and the exposure of individual workers makes the existing occupational health monitoring have a large error in individual health risk assessment, and it is difficult to meet the needs of precise occupational health management. SUMMARY

[0004] The main purpose of the present application is to provide an occupational health hazard monitoring method, device, equipment and storage medium, which aims to solve the technical problem that the existing occupational health detection only detects the environment of the place and cannot effectively associate the workstation characteristics and the workers.

[0005] To achieve the above purpose, the present application provides an occupational health hazard monitoring method, which comprises the following steps:

[0006] Obtain concentration data of harmful factors in different workstations of a production line over time to generate harmful factor monitoring data for each workstation;

[0007] Obtain travel data of each worker on the production line, and obtain the harmful exposure duration of each worker at the corresponding workstation according to the travel data;

[0008] According to the harmful factor monitoring data and the harmful exposure duration of each worker at the corresponding workstation, calculate the average exposure concentration of each worker and the dust hazard index of each workstation.

[0009] In an embodiment, the step of obtaining travel data of each worker on the production line comprises:

[0010] binding the worker with an identification device, the identification device configured to send a corresponding worker identification;

[0011] binding the workstation with a positioning device, the positioning device configured to send a corresponding workstation identification;

[0012] generating a first event record when detecting that the identification device enters the signal coverage range of the positioning device, the first event record comprising the worker identification, the workstation identification, and an entering timestamp;

[0013] generating a second event record when detecting that the identification device exits the signal coverage range of the positioning device, the second event record comprising the worker identification, the workstation identification, and an exiting timestamp;

[0014] integrating to generate travel data of each worker on the production line based on the first event record and the second event record of each worker.

[0015] In an embodiment, the step of obtaining the hazard exposure duration of each worker at the corresponding workstation according to the travel data comprises:

[0016] analyzing the travel data, and matching the first event record and the second event record according to the combination of the worker identification and the workstation identification;

[0017] for each matched event record group, extracting the entering timestamp and the exiting timestamp, and calculating the time difference between the exiting timestamp and the entering timestamp;

[0018] accumulating the time difference value into the associated data of the corresponding worker and workstation, and generating the hazard exposure duration of each worker at the corresponding workstation.

[0019] In an embodiment, the step of obtaining the travel data of each worker on the production line comprises:

[0020] analyzing the travel data, and identifying different workstation identifications associated with the same worker identification;

[0021] extracting the stay duration and stay period of the worker at the workstations corresponding to the different workstation identifications, and comparing the stay duration with a preset threshold value;

[0022] if the stay duration exceeds the preset threshold value, marking the corresponding stay period as a valid exposure period and counting it into the hazard exposure duration;

[0023] if the stay duration does not exceed the preset threshold value, marking the corresponding travel data as interference data and performing filtering processing.

[0024] In an embodiment, the step of calculating the average exposure concentration of each worker and the dust hazard index of each work station according to the hazard factor monitoring data and the hazard exposure duration of each worker at the corresponding work station comprises:

[0025] The hazard factor monitoring data of each worker at the corresponding work station is weighted and averaged to obtain the average exposure concentration of each worker, with the hazard exposure duration of each worker at the corresponding work station as the weight.

[0026] The ratio of the hazard factor monitoring data of each work station to the preset standard value is taken as the dust hazard index of each work station.

[0027] In an embodiment, the dust hazard index of each work station varies with the concentration of the hazard factor, the dust hazard index is classified, and different pre-warning reminders are set based on different classification results.

[0028] In an embodiment, the step of calculating the average exposure concentration of each worker and the dust hazard index of each work station according to the hazard factor monitoring data and the hazard exposure duration of each worker at the corresponding work station comprises:

[0029] The wearing condition of the labor protection articles of the workers is evaluated, and a wearing unqualified period is obtained when the wearing evaluation result of the workers is unqualified.

[0030] When calculating the average exposure concentration of the workers, the hazard factor monitoring data of the wearing unqualified period is corrected by a preset correction coefficient.

[0031] In addition, to achieve the above-mentioned purpose, the present application also provides an occupational health hazard monitoring device, which comprises:

[0032] A first obtaining module is configured to obtain concentration data of a hazard factor varying with time in different work stations of a production line, and generate hazard factor monitoring data of each work station.

[0033] A second obtaining module is configured to obtain travel data of each worker on the production line, and obtain the hazard exposure duration of each worker at the corresponding work station according to the travel data.

[0034] A calculating module is configured to calculate the average exposure concentration of each worker and the dust hazard index of each work station according to the hazard factor monitoring data and the hazard exposure duration of each worker at the corresponding work station.

[0035] In addition, to achieve the above object, the present application also provides a terminal device, comprising a memory, a processor, and a professional health hazard monitoring program stored in the memory and executable on the processor, wherein the processor implements the steps of the professional health hazard monitoring method as described above when executing the professional health hazard monitoring program.

[0036] In addition, to achieve the above object, the present application also provides a computer readable storage medium, wherein the computer readable storage medium stores a professional health hazard monitoring program, and the processor implements the steps of the professional health hazard monitoring method as described above when executing the professional health hazard monitoring program.

[0037] The one or more technical solutions provided by the present application have at least the following technical effects:

[0038] By obtaining the concentration data of the hazard factors in different stations of the production line changing with time, the hazard factor monitoring data of each station is generated, the precise monitoring of the station environment hazard factors is realized, and the actual hazard level of each station is reflected. Secondly, combined with the travel data of workers in the production line, the hazard exposure duration of workers in the corresponding station is obtained, so that the monitoring data is associated with the actual exposure of individual workers. Then the average exposure concentration of workers in the corresponding station is calculated. Thus, the problem that the detection data is disconnected with the station characteristics and the individual exposure of workers in the prior art is solved, and the precision and effectiveness of the professional health monitoring are improved. BRIEF DESCRIPTION OF DRAWINGS

[0039] Figure 1 A flowchart of a first exemplary embodiment of the professional health hazard monitoring method of the present application;

[0040] Figure 2 A flowchart of a second exemplary embodiment of the professional health hazard monitoring method of the present application;

[0041] Figure 3 A flowchart of a third exemplary embodiment of the professional health hazard monitoring method of the present application;

[0042] Figure 4 A module structure diagram of the professional health hazard monitoring device of the embodiment of the present application;

[0043] Figure 5 A device structure diagram of the hardware running environment involved in the professional health hazard monitoring method of the embodiment of the present application.

[0044] The implementation, functional features and advantages of the present application will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0045] It should be understood that the specific embodiments described herein are merely exemplary and not intended to limit the present application.

[0046] The main technical solution of the present application is: obtaining concentration data of hazard factors changing with time in different stations of a production line, generating hazard factor monitoring data of each station; obtaining travel data of each worker on the production line, and obtaining hazard exposure time of each worker at the corresponding station according to the travel data; and calculating average exposure concentration of each worker and dust hazard index of each station according to the hazard factor monitoring data and the hazard exposure time of each worker at the corresponding station.

[0047] The present application actually considers that there are obvious limitations in the way of setting fixed monitoring points in workshops, factory buildings and other places to collect concentration data of dust, toxic gases and other hazard factors in the air to evaluate the health status of the working environment. For example, the dust concentration in different stations in the same workshop may differ by several times due to different process flows. In addition, when workers flow between different stations, the length of time and concentration of their exposure to hazard factors will also change, and the above detection method cannot track and record these dynamic changes in real time, resulting in inaccurate evaluation of individual occupational health risks. The disconnection between this detection and the actual exposure of workers makes the existing occupational health monitoring have a large error in evaluating individual health risks, and it is difficult to meet the needs of precise occupational health management.

[0048] Based on this, the present application proposes an occupational health hazard monitoring method, device, equipment and storage medium. Specifically, the following are the detailed steps of the first exemplary embodiment of the occupational health hazard monitoring method of the present application:

[0049] Reference Figure 1 , Figure 1 The flowchart of the first exemplary embodiment of the occupational health hazard monitoring method of the present application. In this embodiment, the occupational health hazard monitoring method comprises steps S10-S30:

[0050] Step S10, obtaining concentration data of hazard factors changing with time in different stations of a production line, generating hazard factor monitoring data of each station;

[0051] Specifically, monitoring devices capable of collecting concentration data of dust, toxic gases and other hazard factors in real time are deployed at each station of the production line. The monitoring device samples the station environment at a set time interval through sensor technology, and transmits the collected data to the data processing center. The concentration data of the collected hazard factors are recorded in time sequence and associated with the corresponding station information to form the hazard factor monitoring data of each station.

[0052] The data transmission can be realized through a wired or wireless network, ensuring the real-time and integrity of the data.

[0053] In a feasible implementation, during the data acquisition process, the equipment also needs to be calibrated periodically to ensure the accuracy of the measurement results. For this purpose, a beta-ray portable dust concentration calibrator can be used as a standard device to periodically calibrate the monitoring equipment. The calibration process is as follows:

[0054] First, the beta-ray portable dust concentration calibrator is turned on and placed near the monitoring equipment that needs to be calibrated. The calibrator identifies the nearby monitoring equipment that needs to be calibrated through close-range identification of the communication tag, and actively establishes a connection with it. Once the connection is successful, the calibrator and the monitoring equipment start the sampling program simultaneously, and collect dust concentration data in the same time period. After the sampling is completed, the calibrator outputs the standard concentration reading, and the monitoring equipment automatically calculates the correction coefficient based on this standard reading and corrects its own monitoring data.

[0055] Through this calibration method, the measurement errors that may occur in the long-term operation of the monitoring equipment can be effectively eliminated, ensuring the accuracy of the monitoring data. At the same time, the automatic correction function greatly reduces the need for manual intervention, improves the calibration efficiency, and ensures the long-term reliable operation of the monitoring equipment.

[0056] Step S20, obtaining the travel data of each worker on the production line, and obtaining the hazard exposure time of each worker at the corresponding work station according to the travel data;

[0057] Specifically, the workers are equipped with wearable identification devices, such as RFID tags or smart badges, and positioning devices are deployed on the workstations. When a worker enters a workstation, the identification device communicates with the positioning device through wireless signals to record the timestamp of the worker entering the workstation. Similarly, when the worker leaves the workstation, the timestamp of leaving is recorded again. The above timestamp data is transmitted to the data processing center in real time, and the data processing center calculates the residence time of the worker at each workstation according to the entering and leaving timestamps. Then, the residence records of all workstations are integrated to generate the travel data of each worker on the production line. These travel data can accurately reflect the activity trajectory and residence time of the workers at each workstation, providing key basis for subsequent calculation of hazard exposure time.

[0058] In a feasible implementation, the step of obtaining the travel data of each worker on the production line can include steps S21-S25:

[0059] Step S21, binding the worker with an identification device, the identification device being configured to send the corresponding worker identification;

[0060] Specifically, the identification device can be a passive RFID tag or a smart badge, and the worker can wear the identification device, which has a unique worker identification for identifying different workers. The identification device is associated with the personal information of the worker, so that the identification sent by the identification device can accurately correspond to a specific worker individual. By setting a reading device at the entrance of the production line or a specific area, when the worker enters the area, the worker identification can be automatically identified.

[0061] Exemplarily, a passive RFID identification tag (hereinafter referred to as "tag") is configured for each worker to be monitored. The tag is designed to be resistant to metal interference, has a unique electronic code (UID) built-in, and has a thickness of about 2 mm. The tag can be worn on a prominent position of the worker's body through a badge clip, a wristband, or a safety hat fixing buckle, etc., to ensure that the tag is not blocked by metal on the worker's body. The UID of the tag is one-to-one bound with the worker's identity information.

[0062] Step S22, binding the station with the positioning device, the positioning device being configured to send a corresponding station identification;

[0063] Specifically, the station is bound with the positioning device. The positioning device, such as a fixed RFID card reader or other positioning sensor, is installed at each station in the production site. Each positioning device has a unique station identification, which identifies the station position. The positioning device is bound with the detailed information of the station, so that the station identification sent can accurately reflect the specific situation of the station.

[0064] Exemplarily, for each station in the production line, an anti-metal interference RFID positioning card reader (hereinafter referred to as "card reader") is deployed above or beside the station operation area. The card reader can be installed in a wall-mounted manner, and the deployment interval of adjacent station card readers is strictly controlled to be ≤10 m to avoid signal blind area or overlapping interference. Each card reader is marked with a unique device number when it is shipped, and is bound with the corresponding station information when it is deployed: in the specific operation, the administrator selects the station to be bound in the platform, inputs the card reader device number, and associates the spatial coordinates, station type, and production line of the station, etc. information, the platform database will store the association relationship of "device number-station name-spatial coordinates-station type", and complete the binding of the station and the positioning device.

[0065] Step S23, when it is detected that the identification device enters the signal coverage range of the positioning device, a first event record is generated, the first event record including: the worker identification, the station identification, and an entry timestamp;

[0066] Specifically, when the worker with the identification device enters the signal coverage range of the station positioning device, the positioning device can activate the identification device by emitting a radio frequency signal, and the identification device feeds back the worker identification to the card reader after receiving the signal. The microprocessor built-in the positioning device analyzes the worker identification and verifies its validity. If the verification is passed, the positioning device records the current time as the "entry time stamp" through the built-in clock module, and packs the "worker identification, station identification, entry time stamp" three data as the first event record.

[0067] Step S24, when it is detected that the identification device leaves the signal coverage range of the positioning device, a second event record is generated, which includes the worker identification, the station identification, and the leaving time stamp;

[0068] Specifically, when the worker completes the operation and leaves the signal coverage range of the station positioning device, i.e., the identification device exceeds the signal radius of the positioning device or is shielded by metal, resulting in continuous multiple signal refreshes without feeding back the worker identification, the positioning device records the current time as the "leaving time stamp" through the clock module again, and generates the second event record. If the worker temporarily exceeds the coverage range due to a short-term leaving of the identification device, the positioning device does not generate a leaving record, avoiding false judgments caused by accidental shielding.

[0069] Step S25, based on the first event record and the second event record of each worker, the travel data of each worker on the production line is integrated and generated.

[0070] After receiving all the first event records and the second event records, the worker travel data is integrated and generated. Specifically, grouping is performed according to the worker identification, the records of the same worker are sorted according to the time stamp, the first event and the second event under the same station are matched, and are recorded as the same event record group.

[0071] The time difference of each same event record group is calculated as the contact duration of the worker at the station.

[0072] It should be noted that if the same worker switches to an adjacent station in a short time, the platform combines the spatial coordinates of the stations in the GIS map to determine that it is a "station switching", and only the last station record with a stay of more than 5 minutes is retained, and invalid short-term stay data is filtered out.

[0073] Finally, the travel data report of the worker on the same day is generated, for example: W001-20250523 travel: 08:05-12:10 No. 1 welding station, contact duration 4h5min; 13:30-17:20 No. 2 polishing station, contact duration 3h50min.

[0074] In an implementable embodiment, the step of obtaining the length of exposure to hazards of each worker at the corresponding work station according to the travel data can comprise steps S26-S28:

[0075] In step S26, the travel data is parsed, and the first event record and the second event record are matched according to the combination of the worker identification and the work station identification;

[0076] Specifically, after receiving the first event record and the second event record uploaded by each work station card reader, the travel data is first parsed. The travel data is stored in a structured JSON format, and the four core fields of “worker identification”, “work station identification”, “event type” and “time stamp” are extracted by a data parsing module.

[0077] Subsequently, all event records are grouped and matched according to the combination of “worker identification + work station identification”: through the GROUP BY operation of the database, the first and second event records of the same worker at the same work station are grouped into the same event record group. For example, the first event and the second event of worker W001 at the No. 1 welding work station are identified as the same group, while the first event and the second event of W001 at the No. 2 polishing work station are grouped into another group.

[0078] If there are abnormal records, such as a worker having only a first event at the same work station without a second event, or a second event earlier than a first event, a data verification mechanism is triggered: for the record without a second event, the time stamp of the daily production line closing time is used as the leaving time stamp by default; for the record with reversed time sequence, the time stamps are automatically exchanged and marked as “data abnormality” for manual checking.

[0079] In step S27, for each matched event record group, the entering time stamp and the leaving time stamp are extracted, and the time difference between the leaving time stamp and the entering time stamp is calculated;

[0080] In step S28, the time difference value is added to the associated data of the corresponding worker and work station, and the length of exposure to hazards of each worker at the corresponding work station is generated.

[0081] Specifically, after the time difference value of a single event record group is calculated, the time difference value is added to the associated data of the corresponding worker and work station. Through an SQL query statement, the existing length of exposure to hazards of a certain worker and the corresponding work station is retrieved; if the record exists, the newly calculated time difference value and the existing length of exposure to hazards are added to update the new length of exposure to hazards; if the record does not exist, a new record is inserted, and the time difference value is directly used as the length of exposure to hazards; finally, the length of exposure to hazards report of each worker at the corresponding work station is generated.

[0082] In addition, in order to meet the calculation requirements of multiple indicators in occupational health supervision, the cumulative exposure time is supported to be calculated according to daily, weekly, monthly and other cycles.

[0083] Step S30, according to the hazard factor monitoring data and the hazard exposure time length of each worker at the corresponding work station, calculate the average exposure concentration of each worker and the dust hazard index of each work station.

[0084] Specifically, for each worker, the hazard exposure time length of the worker at the corresponding work station and the hazard factor monitoring data of the corresponding work station are weighted and averaged. In this way, the average exposure concentration of each worker is obtained, thereby more accurately reflecting the actual exposure level of the worker to the hazard factor.

[0085] In addition, by calculating the ratio of the hazard factor monitoring data of each work station to the preset national standard or industry standard limit value, the dust hazard index of each work station is obtained. The dust hazard index can directly reflect the hazard degree of the work station, and can be classified according to the index size, providing a scientific basis for occupational health management.

[0086] In one possible implementation, the step S30 can include steps S31-S32:

[0087] Step S31, taking the hazard exposure time length of each worker at the corresponding work station as the weight, weightedly averaging the hazard factor monitoring data of each worker at the corresponding work station to obtain the average exposure concentration of each worker;

[0088] Specifically, for each worker, the hazard exposure time length data of the worker is matched with the hazard factor monitoring data of the worker at the corresponding work station in the time dimension through the data synchronization interface: for example, the exposure time period of worker W001 at the No. 1 welding work station is from 08:05:12 to 12:10:08, then all 1-minute interval concentration values of the No. 1 welding work station in this period are extracted and corresponded to the time stamp of the exposure time length in time sequence.

[0089] Subsequently, for each preset monitoring period of a worker at a work station, if the worker is at the work station in the period, i.e. the hazard exposure time length covers the period, then the hazard factor monitoring data of the period is multiplied by the length of the period to obtain the exposure contribution value of the period. The exposure contribution values of all covered periods of the worker at all work stations are added and then divided by the total exposure time length of the worker at all work stations, and finally the average exposure concentration of the worker is obtained.

[0090] The average exposure concentration calculation formula of the worker is as follows:

[0091]

[0092] Wherein, C i is the hazard factor monitoring data of the work station in the i-th time period, T iis the hazard exposure time of worker in the ith time period, t is the total hazard exposure time of worker.

[0093] Take worker W001 as an example: the exposure time in the No. 1 welding station is 4 hours and 5 minutes, corresponding to 245 1-minute periods, and the concentration value in each period fluctuates between 2.8-3.5 mg / m 3 , and the total exposure after weighting is 13.8 mg·h / m 3 ; the exposure time in the No. 2 polishing station is 3 hours and 50 minutes, corresponding to 230 1-minute periods, and the concentration value fluctuates between 1.5-2.2 mg / m 3 , and the total exposure after weighting is 7.2 mg·h / m 3 . The total exposure is 21 mg·h / m 3 , and the total exposure time is 7.916 hours, so that C TWA = 21 ÷ 7.916 ≈ 2.65 mg / m 3 .

[0094] In step S32, the ratio of the hazard factor monitoring data of each station to the preset standard value is taken as the dust hazard index of each station.

[0095] Specifically, first, the preset standard value can be derived from the national occupational health standard, and different limits correspond to different dust types of different stations.

[0096] After obtaining the real-time hazard factor monitoring data of the station, the dust hazard index of each monitoring period is calculated, and the dust hazard index of the period is the ratio of the hazard factor monitoring data of the period to the standard value corresponding to the station.

[0097] For example, the hazard factor monitoring data of the No. 1 welding station in a period is 3.2 mg / m 3 , the standard value is 4 mg / m 3 , and the dust hazard index of the period is 0.8.

[0098] In a feasible implementation, to avoid misjudgment caused by instantaneous fluctuation, the dust hazard index is calculated by “rolling average”: the dust hazard indexes in the last 30 minutes are averaged to obtain the current dust hazard index of the station. If there is data missing within 30 minutes, the missing period data is excluded, and only the average value of the valid data is calculated; if the valid data is insufficient, the dust hazard index of the period is marked as data abnormality, which needs to be manually checked.

[0099] Based on this, in a feasible implementation, the dust hazard index of each station changes with the concentration change of the hazard factor, the dust hazard index is classified, and different pre-warning reminders are set based on different classification results.

[0100] Specifically, the risk classification is performed according to the dust hazard index after rolling average, for example: the dust hazard index ≤ 0.2 is level I (safe), 0.2-0.5 is level II (low risk), 0.5-0.8 is level III (medium risk), 0.8-1.0 is level IV (high risk), and > 1.0 is level V (serious risk), and the classification results are associated and displayed with the GIS map and the workstation information to provide an intuitive risk warning basis.

[0101] Further, with reference to Figure 2 , Figure 2 is a flowchart of a second exemplary embodiment of the occupational health hazard monitoring method of the present application. In this embodiment, on the basis of the first embodiment, the step of obtaining the travel data of each worker on the production line comprises steps S41-S44 after the step of obtaining the travel data of each worker on the production line:

[0102] Step S41, analyze the travel data and identify different workstation identifiers associated with the same worker identifier;

[0103] Step S42, extract the stay duration and stay period of the worker at the workstations corresponding to the different workstation identifiers, and compare the stay duration with a preset threshold value;

[0104] Step S43, if the stay duration exceeds the preset threshold value, mark the corresponding stay period as an effective contact period and count it into the hazard contact duration;

[0105] Step S44, if the stay duration does not exceed the preset threshold value, mark the corresponding travel data as interference data and perform filtering processing.

[0106] It should be noted that after obtaining the travel data of the worker on the production line, the interference data generated by the worker's brief stay is removed to ensure the accuracy of the hazard contact duration calculation.

[0107] In a feasible implementation, the travel data is stored in a structured table form, and each record corresponds to one entry and exit event of a worker at a workstation. By using SQL query statements, the data is grouped and filtered according to the worker identifier, and all travel records of the worker on the same day are extracted.

[0108] Subsequently, all travel records of the worker are traversed, the workstation identifier in each record is extracted, and different workstations associated with the worker on the same day are identified through a de-duplication operation.

[0109] For each identified workstation, the stay duration and stay period corresponding to the workstation are extracted, and the stay duration is compared with a preset threshold value.

[0110] The preset threshold is set based on the actual needs of occupational health monitoring: considering that the short stay of workers in non-operation areas does not constitute effective hazard exposure, the threshold can be set to 5 minutes. When comparing, the calculated stay duration is compared with the preset threshold in numerical value, and it is judged whether the threshold is exceeded.

[0111] If the stay duration at a certain station exceeds the preset threshold, the period is determined as an "effective exposure period", and is marked and counted into the hazard exposure duration by the following methods: first, a "whether effective" field is added to the "worker-station exposure duration table", and the "whether effective" of the record is set to "True"; then the stay duration is directly added to the associated data of the worker and the station.

[0112] If the stay duration at a certain station does not exceed the preset threshold, it is determined that the period is "interference data", and the following filtering operation is performed: in the "worker-station exposure duration table", the "whether effective" of the record is set to "False", and in the "remark" field, it is marked that "the stay duration is too short and is determined as interference"; in the subsequent calculation of the worker hazard exposure duration, the records marked as "False" are automatically excluded by SQL filtering conditions, to ensure that only effective duration is used to calculate the worker hazard exposure duration. TWA Calculation.

[0113] Further, with reference to Figure 3 , Figure 3 is a flowchart of the third exemplary embodiment of the occupational health hazard monitoring method of the present application. In this embodiment, steps S30 can include steps S51-S52 before step S30:

[0114] Step S51, evaluate the wearing of labor protection articles of the worker, and obtain the wearing evaluation result of the worker as an unqualified wearing unqualified period;

[0115] Specifically, image acquisition devices are deployed above or on the side of each operation area to ensure that the image acquisition devices cover the worker's face and upper body area, for example, to capture the wearing state of protective equipment such as masks and dust masks. Image acquisition devices can upload video streams or capture key frame images and other video data in real time, and analyze the video data:

[0116] An implementable embodiment is based on a pre-trained deep learning model to identify the wearing situation of labor protection articles. The identifiable types of labor protection articles include N95 masks, ordinary dust masks, half-face respirators, full-face respirator masks, etc. Specifically, first, the face area of the worker in the image is located to exclude background interference. For the face area, the coverage range and sealing degree of the labor protection articles are further detected. For mask articles, it is judged whether the upper edge of the mask covers the nose bridge, the lower edge covers the chin, and the ear band is tightly fitted to the ear. For mask articles, it is judged whether the mask edge is tightly fitted to the face and whether the headband is adjusted to a tight state. If the wearing state does not meet the standard, the model outputs a "wearing unqualified" label, and records the timestamp of the frame image.

[0117] All "wearing unqualified" timestamps are combined into a continuous period to finally generate a "wearing unqualified period".

[0118] Step S52, when calculating the average contact concentration of the worker, the hazard factor monitoring data of the wearing unqualified period is corrected by a preset correction coefficient.

[0119] Specifically, different correction coefficients (K values) are predefined according to the type of labor protection articles and the degree of protection failure. For example:

[0120] Ordinary dust mask does not cover the chin: K = 1.3; N95 mask ear band is loose: K = 1.5; half-face respirator edge gap 3mm: K = 2.0; full-face respirator mask headband is loose: K = 2.5.

[0121] When calculating C TWA , first, the hazard exposure time of the worker at each station is extracted, and it is cross-compared with the "wearing unqualified period" in the time dimension. For each 1-minute monitoring period, if the period belongs to the "wearing unqualified period", the hazard factor monitoring data of the period is multiplied by the corresponding correction coefficient to obtain the corrected hazard factor monitoring data; if the wearing is qualified or there is no wearing requirement, the original hazard factor monitoring data is directly used.

[0122] Through the above steps, the wearing situation of labor protection articles and the hazard factor monitoring data are deeply fused, which solves the defects in the traditional C TWA calculation method that only considers environmental concentration and ignores the actual effect of protection, significantly improving the accuracy of occupational health exposure assessment.

[0123] In addition, as Figure 4 shown, the present application also proposes an occupational health hazard monitoring device, which comprises:

[0124] The first obtaining module 10 is configured to obtain concentration data of a hazard factor changing with time in different stations of a production line, and generate hazard factor monitoring data of each station.

[0125] The second obtaining module 20 is configured to obtain travel data of each worker in the production line, and obtain a hazard exposure duration of each worker in a corresponding station according to the travel data.

[0126] The calculation module 30 is configured to calculate an average exposure concentration of each worker and a dust hazard index of each station according to the hazard factor monitoring data and the hazard exposure duration of each worker in the corresponding station.

[0127] The professional health hazard monitoring device provided by the present application adopts the professional health hazard monitoring method in the above embodiments, and aims to solve the technical problem that the existing professional health detection only detects the environment of a place and cannot effectively associate the station characteristics and the workers. Compared with the prior art, the professional health hazard monitoring device provided by the present application has the same beneficial effects as the professional health hazard monitoring method provided by the above embodiments, and other technical features in the professional health hazard monitoring device are the same as the features disclosed in the above method embodiments, which will not be repeated here.

[0128] The present application provides a professional health hazard monitoring device, which comprises at least one processor and a memory connected with the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the professional health hazard monitoring method in the above embodiment one.

[0129] The professional health hazard monitoring device in the embodiments of the present application can include but is not limited to mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), and the like, and fixed terminals such as digital TVs, desktop computers, and the like. Figure 5 The professional health hazard monitoring device shown is only an example, and should not bring any limitation to the functions and use range of the embodiments of the present application.

[0130] As Figure 5As shown, the occupational health hazard monitoring device can include a processing device 1001 (e.g., a central processing unit, a graphics processing unit, etc.) that can perform various appropriate actions and processes according to programs stored in a read-only memory 1002 or loaded from a storage device 1003 into a random access memory 1004. Various programs and data required for operation of the occupational health hazard monitoring device are also stored in the random access memory 1004. The processing device 1001, the read-only memory 1002, and the random access memory 1004 are connected to each other by a bus 1005. An input / output interface 1006 is also connected to the bus. Generally, the following systems can be connected to the input / output interface 1006: input devices 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; the storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the occupational health hazard monitoring device to communicate wirelessly or by wire with other devices to exchange data. Although the occupational health hazard monitoring device is shown as having various systems, it should be understood that all of the shown systems are not required to be implemented or possessed. More or fewer systems can alternatively be implemented or possessed.

[0131] In particular, the processes described above with reference to the flowcharts can be implemented as a computer software program according to embodiments of the present disclosure. For example, embodiments of the present disclosure include a computer program product comprising a computer program carried on a computer readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network by a communication device, or installed from the storage device 1003, or installed from the ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the methods of embodiments of the present disclosure are performed.

[0132] The occupational health hazard monitoring device provided by the present disclosure adopts the occupational health hazard monitoring method in the above embodiments, aiming to solve the technical problem that the existing occupational health detection can only detect the environment of a place and cannot effectively associate the workstations and workers. Compared with the prior art, the occupational health hazard monitoring device provided by the present disclosure has the same beneficial effects as the occupational health hazard monitoring method provided by the above embodiments, and other technical features in the occupational health hazard monitoring device are the same as the features disclosed in the previous embodiment method, which will not be repeated here.

[0133] It should be understood that various parts of the present application can be realized in hardware, software, firmware, or a combination thereof. In the above description of embodiments, specific functional, structural, material or characteristic features are combined in a manner appropriate for the particular example or embodiment, but other examples or embodiments can combine different features in a different manner.

[0134] The above description is merely illustrative of the application, and the scope of the application is not limited thereto. Any variations and modifications of the application, which fall within the scope of the application, are to be considered as within the scope of the application. Therefore, the scope of the application is to be determined by the claims.

[0135] The present application provides a computer readable storage medium having stored thereon computer readable program instructions (i.e., computer programs) for performing the occupational health hazard monitoring method in the above-described embodiments.

[0136] The computer readable storage medium provided by the present application may, for example, be a U disk, but is not limited to an electric, magnetic, optical, electromagnetic, infrared, or semiconductor system or device, or any combination thereof. More specific examples of the computer readable storage medium can include, but are not limited to, an electric connection having one or more conductive wires, a portable computer disk, a hard disk, a random access memory (RAM), a read only memory (ROM), an erasable programmable read only memory (EPROM or flash memory), an optical fiber, a portable compact disk read only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present embodiment, the computer readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system or device. The program code contained on the computer readable storage medium can be transmitted by any suitable medium, including but not limited to an electric wire, an optical cable, an RF (Radio Frequency), etc., or any suitable combination thereof.

[0137] The above-described computer readable storage medium can be contained in the occupational health hazard monitoring device; or can exist separately without being assembled into the occupational health hazard monitoring device.

[0138] Computer program code for carrying out operations of the present application can be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0139] The flow diagrams and the block diagrams in the drawings are illustrations of architectures, functionalities, and operations of possible implementations of systems, methods, and computer program products according to various embodiments of the present application. In this regard, each block in the flow diagrams or block diagrams can represent a module, a segment, or a portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that in some alternative implementations, the functions noted in the blocks can occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently or the blocks may

[0140] The modules involved in the embodiments of the present application can be implemented in the form of software or in the form of hardware. In some cases, the name of the module does not constitute a limitation on the module itself.

[0141] The readable storage medium provided by the present application is a computer readable storage medium, which stores computer readable program instructions (i.e., a computer program) for executing the above-mentioned occupational health hazard monitoring method, and aims to solve the technical problem that the existing occupational health detection can only detect the environment of a place and cannot effectively associate the workstations and workers. Compared with the prior art, the computer readable storage medium provided by the present application has the same beneficial effects as the occupational health hazard monitoring method provided by the above-mentioned embodiments, and will not be described here.

[0142] The application also provides a computer program product comprising a computer program which, when executed by a processor, implements the steps of the occupational health hazard monitoring method as described above.

[0143] The computer program product provided by the application aims to solve the technical problem that the existing occupational health detection only detects the environment of a place and cannot effectively associate the workstations and workers. Compared with the prior art, the beneficial effects of the computer program product provided by the application are the same as those of the occupational health hazard monitoring method provided by the above-described embodiments, and are not described here in detail.

[0144] Compared with the prior art, the occupational health hazard monitoring method, device, equipment, medium and computer product provided by the embodiments of the application can extract the service feature information of a target service, perform data standardization processing on the service feature information to obtain standard feature data, perform hash processing on the standard feature data to obtain unique feature data, perform numerical value processing and splicing processing on the unique feature data to obtain a first service feature value, accumulate the first service feature value of the target service to obtain a target service feature value, and finally compare the target service feature value with a feature value set to obtain an occupational health hazard monitoring result. Compared with the traditional method of generating a unique key value or a continuous serial number for each service to identify repeated services, the method is more efficient, flexible and reliable. Based on the solution of the application, the service in a complex scenario is converted through a series of simple transformations, and finally converted into the comparison of two numbers, so that the comparison process is very intuitive and efficient. The system only needs to simply compare whether the two values are equal, and can quickly determine whether the two services are exactly the same.

[0145] It should be noted that in this document, the terms "comprise", "comprise", or any other variant thereof are intended to cover non-exclusive inclusion, so that processes, methods, articles or systems including a series of elements not only include those elements, but also include other elements not explicitly listed, or include elements inherent to such processes, methods, articles or systems. Without more limitations, the element defined by the statement "comprises a" does not exclude the presence of additional identical elements in the process, method, article or system that includes the element.

[0146] The above-mentioned serial numbers of the embodiments of the application are only for description, and do not represent the advantages and disadvantages of the embodiments.

[0147] Those skilled in the art can clearly understand the above-mentioned embodiment method can be realized by means of software and the necessary general hardware platform, of course, can also be through hardware, but in many cases the former is a better embodiment. Based on such understanding, the technical solutions of the present application essentially or say the part of the prior art contribution can be embodied in the form of software products, the computer software product is stored in the above-mentioned storage medium (such as ROM / RAM, magnetic disc, optical disc), including a number of instructions to make a terminal device (may be a mobile phone, computer, server, controlled terminal, or network equipment, etc.) executes the method of each embodiment of the present application.

[0148] The above is only the preferred embodiment of the present application, not therefore limit the patent scope of the present application, any equivalent structure or equivalent process transformation using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A method of monitoring occupational health hazards, characterized by, The occupational health hazard monitoring method comprises: obtaining concentration data of hazard factors in different stations of a production line changing with time, and generating hazard factor monitoring data of each station; obtaining travel data of each worker on the production line, and obtaining hazard exposure time of each worker at a corresponding station according to the travel data; calculating average exposure concentration of each worker and dust hazard index of each station according to the hazard factor monitoring data and the hazard exposure time of each worker at the corresponding station.

2. The method of monitoring occupational health hazards of claim 1, wherein, The step of obtaining travel data of each worker on the production line comprises: binding the worker with an identification device configured to send a corresponding worker identification; binding the station with a positioning device configured to send a corresponding station identification; when detecting that the identification device enters the signal coverage range of the positioning device, generating a first event record, the first event record comprising: the worker identification, the station identification and the entering timestamp; when detecting that the identification device leaves the signal coverage range of the positioning device, generating a second event record, the second event record comprising: the worker identification, the station identification and the leaving timestamp; based on the first event record and the second event record of each worker, the travel data of each worker on the production line is integrated and generated.

3. The method of monitoring occupational health hazards of claim 2, wherein, The step of obtaining hazard exposure time of each worker at a corresponding station according to the travel data comprises: analyzing the travel data, matching the first event record and the second event record according to the combination of worker identification and station identification; for each matched event record group, extracting the entering timestamp and the leaving timestamp, and calculating the time difference between the leaving timestamp and the entering timestamp; adding the time difference value to the associated data of the corresponding worker and station, and generating the hazard exposure time of each worker at the corresponding station.

4. The method of monitoring occupational health hazards of claim 2, wherein, The step of obtaining travel data of each worker on the production line comprises: analyzing the travel data, identifying different station identifications associated with the same worker identification; extracting the stay duration and stay period of the worker at the corresponding station of the different station identifications, and comparing the stay duration with a preset threshold value; if the stay duration exceeds the preset threshold value, the corresponding stay period is marked as an effective exposure period and counted into the hazard exposure time; if the stay duration does not exceed the preset threshold value, the corresponding travel data is marked as interference data and filtered.

5. The method of monitoring occupational health hazards of claim 1, wherein, The step of calculating average exposure concentration of each worker and dust hazard index of each station according to the hazard factor monitoring data and the hazard exposure time of each worker at the corresponding station comprises: using the hazard exposure time of each worker at the corresponding station as a weight, and performing weighted average calculation on the hazard factor monitoring data of each worker at the corresponding station to obtain the average exposure concentration of each worker; using the ratio of the hazard factor monitoring data of each station to a preset standard value as the dust hazard index of each station.

6. The method of monitoring occupational health hazards of claim 5, wherein, The dust hazard index of each work station varies with the concentration of the hazard factor, the dust hazard index is classified, and different pre-warning reminders are set based on different classification results.

7. The method of monitoring occupational health hazards of claim 1, wherein, The step of calculating the average exposure concentration of each worker and the dust hazard index of each work station according to the hazard factor monitoring data and the hazard exposure duration of each worker at the corresponding work station comprises: Evaluating the wearing condition of the labor protection articles of the workers, and obtaining a wearing evaluation result of the workers as an unqualified wearing period when the wearing is unqualified; When calculating the average exposure concentration of the workers, the hazard factor monitoring data of the unqualified wearing period is corrected by a preset correction coefficient.

8. An occupational health hazard monitoring device, characterized by The device comprises: A first obtaining module configured to obtain concentration data of a hazard factor varying with time in different work stations of a production line, and generate hazard factor monitoring data of each work station; A second obtaining module configured to obtain travel data of each worker on the production line, and obtain hazard exposure duration of each worker at the corresponding work station according to the travel data; A calculating module configured to calculate the average exposure concentration of each worker and the dust hazard index of each work station according to the hazard factor monitoring data and the hazard exposure duration of each worker at the corresponding work station.

9. An occupational health hazard monitoring device, characterized by The device comprises a memory, a processor, and a computer program stored on the memory and executable on the processor, and the computer program is configured to implement the steps of the occupational health hazard monitoring method according to any one of claims 1 to 7.

10. A storage medium, characterized by The storage medium is a computer readable storage medium, and the storage medium stores a computer program, and the computer program is executed by the processor to implement the steps of the occupational health hazard monitoring method according to any one of claims 1 to 7.

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