Dynamic monitoring and early warning method for noise exposure of workplace

Abstract

The invention relates to a dynamic monitoring and early warning method for noise exposure of a workplace, and the method comprises the steps: periodically obtaining the noise monitoring data of a to-be-monitored site, calculating the A-weighting equivalent continuous sound level of the to-be-monitored site according to the noise monitoring data of the to-be-monitored site, and comparing the A-weighting equivalent continuous sound level with a preset value; therefore, different point locations of different A-weighting equivalent continuous sound levels are marked with different colors, the noise levels of the different point locations are visually displayed, and online monitoring of noise exposure is achieved. On the other hand, by collecting noise data, noise equipment data, staff personal data and other basic data of the staff operation environment, the risk is predicted through modeling analysis, and the risk of hearing loss caused by noise exposure of each staff of each type of work can be predicted; therefore, an employer is helped to establish a personalized and effective hearing protection plan for each employee.

Description

Technical Field

[0001] This application relates to the technical field of noise data monitoring and processing, and particularly to a method for dynamically monitoring and warning of workplace noise exposure. Background Art

[0002] Employees in noise-hazardous enterprises such as the construction industry and manufacturing industry are exposed to noise in the working environment all year round. However, enterprises lack methods for collecting noise data and for noise monitoring and warning. Summary of the Invention

[0003] Based on this, in view of the problems of traditional methods for dynamically monitoring and warning of workplace noise exposure, it is necessary to provide a method for dynamically monitoring and warning of workplace noise exposure.

[0004] This application provides a method for dynamically monitoring and warning of workplace noise exposure, and the method includes:

[0005] Obtain the noise monitoring data of the point to be monitored;

[0006] Calculate the A-weighted equivalent continuous sound level of the point to be monitored according to the noise monitoring data of the point to be monitored;

[0007] Judge whether the A-weighted equivalent continuous sound level of the point to be monitored is less than or equal to a first preset value;

[0008] If the A-weighted equivalent continuous sound level of the point to be monitored is less than or equal to the first preset value, mark the point to be monitored with a first color;

[0009] If the A-weighted equivalent continuous sound level of the point to be monitored is greater than the first preset value, further judge whether the A-weighted equivalent continuous sound level of the point to be monitored is less than or equal to a second preset value;

[0010] If the A-weighted equivalent continuous sound level of the point to be monitored is less than or equal to the second preset value, mark the point to be monitored with a second color;

[0011] If the A-weighted equivalent continuous sound of the point to be monitored is greater than the second preset value, mark the point to be monitored with a third color;

[0012] After a preset monitoring time period, return to obtaining the noise monitoring data of the point to be monitored;

[0013] Obtain the gender, age, normalized A-weighted noise exposure value for an 8-hour rated workday, and exposure work years of the object to be monitored, and calculate the risk percentage of hearing loss caused by noise exposure of the object to be monitored;

[0014] Analyze the percentage risk of hearing loss caused by noise exposure for the monitored objects, and output the risk prediction level of hearing loss caused by noise exposure for the monitored objects.

[0015] This application relates to a method for dynamic monitoring and early warning of workplace noise exposure. On the one hand, by periodically obtaining the noise monitoring data of the points to be monitored, calculating the A-weighted equivalent continuous sound level of the points to be monitored based on the noise monitoring data and comparing it with a preset value, different points with different A-weighted equivalent continuous sound levels are marked with different colors, visually displaying the noise levels of different points, and realizing the online monitoring of noise exposure. On the other hand, by collecting basic data such as the noise data, noise equipment data, and personal data of employees in the operation environment, the risk can be predicted through modeling analysis, and the risk of hearing loss caused by noise exposure for each employee in each job type can be predicted, thus helping the employer establish a personalized and effective hearing protection plan for each employee. Description of the Drawings

[0016] Figure 1 It is a flowchart of the methods from S100 to S450 in the method for dynamic monitoring and early warning of workplace noise exposure provided by an embodiment of this application.

[0017] Figure 2 It is a flowchart of the methods from S500 to S600 in the method for dynamic monitoring and early warning of workplace noise exposure provided by an embodiment of this application.

[0018] Figure 3 It is a schematic diagram of the hearing loss risk assessment in the method for dynamic monitoring and early warning of workplace noise exposure provided by an embodiment of this application. Detailed Embodiments

[0019] In order to make the purpose, technical solutions and advantages of this application clearer, the following further details this application in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not used to limit this application.

[0020] This application provides a method for dynamic monitoring and early warning of workplace noise exposure. It should be noted that the method for dynamic monitoring and early warning of workplace noise exposure provided by this application is applied to the workplace and employees of any job type in any kind of enterprise.

[0021] In addition, the dynamic monitoring and early warning method for workplace noise exposure provided by this application does not limit its execution subject. Optionally, the execution subject of the dynamic monitoring and early warning method for workplace noise exposure provided by this application can be a dynamic monitoring and early warning system. Specifically, the execution subject of the dynamic monitoring and early warning method for workplace noise exposure provided by this application can be one or more processors in the dynamic monitoring and early warning system.

[0022] As Figure 1 and Figure 2 shown, in an embodiment of this application, the dynamic monitoring and early warning method for workplace noise exposure includes:

[0023] S100. Obtain the noise monitoring data of the point to be monitored.

[0024] S200. Calculate the A-weighted equivalent continuous sound level of the point to be monitored based on the noise monitoring data of the point to be monitored.

[0025] S300. Determine whether the A-weighted equivalent continuous sound level of the point to be monitored is less than or equal to a first preset value.

[0026] S410. If the A-weighted equivalent continuous sound level of the point to be monitored is less than or equal to the first preset value, mark the point to be monitored with a first color.

[0027] S420. If the A-weighted equivalent continuous sound level of the point to be monitored is greater than the first preset value, further determine whether the A-weighted equivalent continuous sound level of the point to be monitored is less than or equal to a second preset value.

[0028] S430. If the A-weighted equivalent continuous sound level of the point to be monitored is less than or equal to the second preset value, mark the point to be monitored with a second color.

[0029] S440. If the A-weighted equivalent continuous sound of the point to be monitored is greater than the second preset value, mark the point to be monitored with a third color.

[0030] S450. After a preset monitoring time period, return to obtaining the noise monitoring data of the point to be monitored.

[0031] S500. Obtain the gender, age, A-weighted noise exposure value normalized for the rated 8-hour workday, and exposure work years of the object to be monitored, and calculate the risk percentage of hearing loss caused by noise exposure for the object to be monitored.

[0032] S600. Analyze the risk percentage of hearing loss caused by noise exposure for the object to be monitored, and output the risk prediction level of hearing loss caused by noise exposure for the object to be monitored.

[0033] Specifically, S100 to S450 are the dynamic monitoring process of the points in the workplace. The first preset value can be 85 dB, and the first color can be green. The second preset value is 90 dB, the second color can be yellow, and the third color can be red.

[0034] If the A-weighted equivalent continuous sound level of the point to be monitored is less than or equal to 85 dB, the point to be monitored is marked as green. If the A-weighted equivalent continuous sound level of the point to be monitored is greater than 85 dB and less than or equal to 90 dB, the point to be monitored is marked as yellow. If the A-weighted equivalent continuous sound level of the point to be monitored is greater than 90 dB, the point to be monitored is marked as red.

[0035] The preset monitoring time period can be 1 hour or 30 minutes, that is, the marked colors of all points to be monitored are updated every 30 minutes or 1 hour.

[0036] Optionally, the total number of points to be monitored marked with the second color can also be obtained, and the total number of points to be monitored marked with the third color can be obtained, so as to obtain the total number of points with excessive noise.

[0037] S500 to S600 are the risk prediction methods for hearing loss caused by noise exposure of the employees of the employer.

[0038] The dynamic monitoring and warning system is communicatively connected to the host computer. Optionally, when the risk prediction level of the object to be monitored for hearing loss caused by noise exposure is within the warning level range, the dynamic monitoring and warning system sends an alarm message to the host computer.

[0039] In this embodiment, on the one hand, by periodically obtaining the noise monitoring data of the points to be monitored, calculating the A-weighted equivalent continuous sound level of the points to be monitored based on the noise monitoring data of the points to be monitored and comparing it with the preset value, different points with different A-weighted equivalent continuous sound levels are marked with different colors, visually displaying the noise levels of different points, and realizing the online monitoring of noise exposure. On the other hand, by collecting basic data such as noise data, noise equipment data, and employee personal data in the employee's operating environment, and predicting risks through modeling analysis, the risk of hearing loss caused by noise exposure for each employee in each job type can be predicted, thereby helping the employer establish a personalized and effective hearing protection plan for each employee.

[0040] In an embodiment of the present application, S200 includes, that is, calculating the A-weighted equivalent continuous sound level of the point to be monitored based on the noise monitoring data of the point to be monitored, including:

[0041] S210, calculating the A-weighted equivalent continuous sound level of the point to be monitored according to formula 1.

[0042]

[0043] Among them, LAeq is the A-weighted equivalent continuous sound level of the point to be monitored, N is the total number of points to be detected, LAi is the A-weighted sound pressure level of the i-th point to be detected, and i is the serial number of the point to be monitored.

[0044] Specifically, for example, at 15:00, the LAeq of the point to be monitored is 87, then the period from 15:00 to 16:00 is all marked in yellow.

[0045] In this embodiment, the A-weighted equivalent continuous sound level is calculated by formula 1, which standardizes the noise exposure level of each point to be monitored.

[0046] In an embodiment of the present application, S500 includes, that is, obtaining the gender, age, A-weighted value of noise exposure normalized for the rated 8-hour working day, and exposure work years of the object to be monitored, and calculating the risk percentage of hearing loss caused by noise exposure of the object to be monitored, including:

[0047] S501, obtaining the noise exposure data of the object to be monitored in the most recent week, and calculating the weekly average A-weighted value of noise exposure of the object to be monitored based on the noise exposure data of the object to be monitored in the most recent week.

[0048] S502, calculating the calibrated weekly equivalent A-weighted value of noise exposure of the object to be monitored based on the type of work of the object to be detected and the weekly average A-weighted value of noise exposure of the object to be monitored.

[0049] S503, converting the calibrated weekly equivalent A-weighted value of noise exposure of the object to be monitored into the A-weighted value of noise exposure normalized for the rated 8-hour working day of the object to be monitored.

[0050] Specifically, in S501, first calculate the 8-hour A-weighted value of noise exposure of the object to be monitored according to formula 2.

[0051]

[0052] Among them, Lex,8h is the 8-hour A-weighted value of noise exposure, LAeq,Te is the A-weighted equivalent continuous sound level of the point to be monitored during the effective duration of the working day, Te is the effective duration of the working day, and T0 is the reference duration of the working day.

[0053] The unit of Te can be selected as minutes, and T0 is 480.

[0054] Then calculate the weekly average A-weighted value of noise exposure of the object to be monitored according to formula 3.

[0055]

[0056] Among them, Lex,W is the weekly average A-weighted noise exposure value, Lex,8h is the 8-hour A-weighted noise exposure value, Tw is the actual total working hours per week, and T1 is the reference weekly working hours.

[0057] The unit of Tw is selected as hours, and T1 can be selected as 40, representing 50 hours.

[0058] In S502, according to Formula 4, the calibrated weekly equivalent A-weighted noise exposure value of the object to be monitored is calculated.

[0059]

[0060] Among them, Lex,W' is the calibrated weekly equivalent A-weighted noise exposure value, Lex,W is the weekly average A-weighted noise exposure value, λ is the calibration parameter, β N is the actual influence factor of the work type, β G is the reference influence factor of the work type.

[0061] λ can take 6.2, and β G can take 3.

[0062] In S503, Lex,W' is substituted into the left side of Formula 3 to obtain the normalized A-weighted noise exposure value Lex,8h' for the rated 8-hour working day.

[0063] In this embodiment, the normalized A-weighted noise exposure value for the rated 8-hour working day of the object to be monitored is specially processed by the work type, so that the normalized A-weighted noise exposure value for the rated 8-hour working day incorporates the work type influence factor, making the normalized A-weighted noise exposure value for the rated 8-hour working day more accurate and closer to the actual situation.

[0064] In an embodiment of the present application, S500 further includes, that is, obtaining the gender, age, normalized A-weighted noise exposure value for the rated 8-hour working day, and exposure work years of the object to be monitored, and calculating the risk percentage of hearing loss caused by noise exposure for the object to be monitored, and further includes:

[0065] S510, select the frequency and boundary according to the work type of the object to be monitored.

[0066] S520, under the selected frequency and boundary, obtain the age-related hearing threshold levels at each percentile within the range of 5% to 95% for the non-noise-exposed population.

[0067] S530, under the selected frequency and boundary, obtain the age- and noise-related hearing threshold levels at each percentile within the range of 5% to 95% for the noise-exposed population.

[0068] S540. Draw a schematic diagram for evaluating the risk of hearing loss based on the age-related hearing threshold levels of the non-noise-exposed population at each percentile within the range of 5% to 95%, and the hearing threshold levels related to age and noise of the noise-exposed population at each percentile within the range of 5% to 95%.

[0069] S550. Determine whether both the age-related hearing threshold level curve of the non-noise-exposed population and the hearing threshold level curve related to age and noise of the noise-exposed population intersect with the boundary line.

[0070] S561. If both the age-related hearing threshold level curve of the non-noise-exposed population and the hearing threshold level curve related to age and noise of the noise-exposed population intersect with the boundary line, then take the intersection point of the age-related hearing threshold level curve of the non-noise-exposed population and the boundary line as the first intersection point, and take the intersection point of the hearing threshold level curve related to age and noise of the noise-exposed population and the boundary line as the second intersection point.

[0071] S562. Subtract the abscissa value of the first intersection point from the abscissa value of the second intersection point, and take the result of multiplying the obtained difference by 100% as the risk percentage of hearing loss caused by noise exposure of the object to be monitored.

[0072] Specifically, in S510, in combination with the purpose of evaluating the risk of hearing loss caused by noise exposure of the object to be monitored, select the frequencies to be considered and the appropriate boundary line, such as:

[0073] a) Evaluate the average hearing threshold level of the high frequencies (3000 Hz, 4000 Hz, and 6000 Hz) of either ear according to the "High-Frequency Standard Threshold Shift" specified in the "Hearing Protection Specification for Industrial Enterprise Workers", and the boundary line is 10 dB, which is used as the management value for the risk of noise occupational disease hazards.

[0074] b) Evaluate the average hearing threshold level of the high frequencies (3000 Hz, 4000 Hz, 6000 Hz) of both ears according to the prerequisite for diagnosing occupational noise-induced deafness specified in Chapter 4 of GBZ 49-2014, and the boundary line is 40 dB, which is used as the early warning value for the risk of noise occupational disease hazards.

[0075] c) Evaluate the weighted hearing threshold values of the better ear's speech frequencies (500 Hz, 1000 Hz, and 2000 Hz) and the high frequency of 4000 Hz according to the diagnostic grading of occupational noise-induced deafness specified in Chapter 4 of GBZ 49-2014, and the boundary line is 25 dB, which is used as the warning value for the risk of noise occupational disease hazards.

[0076] Optionally, for example, we select the frequencies and the boundary line in Option c), that is, select four frequencies of 500 Hz, 1000 Hz, 2000 Hz, and 4000 Hz, and the boundary line is selected as 25 dB.

[0077] In S520, under the selected frequency and boundary, obtain the age-related hearing threshold levels of the non-noise-exposed population at each percentile within the range of 5% to 95%, denoted as H.

[0078] In S530, under the selected frequency and boundary, obtain the hearing threshold levels related to age and noise of the noise-exposed population at each percentile within the range of 5% to 95%, denoted as H'.

[0079] In S540, with H at each percentile, we can generate a curve with the percentile on the abscissa and H on the ordinate. With H' at each percentile, we can generate a curve with the percentile on the abscissa and H' on the ordinate. Based on the H curve and the H' curve, draw a schematic diagram for hearing loss risk assessment. The schematic diagram for hearing loss risk assessment is as Figure 3 shown.

[0080] As Figure 3 shown, we respectively obtain the intersection point of the H curve and the boundary, and the intersection point of the H' curve and the boundary. If both curves have intersection points with the boundary, then take the intersection point of the H curve and the boundary as the first intersection point, take the intersection point of the H' curve and the boundary as the second intersection point, subtract the abscissa value of the first intersection point from the abscissa value of the second intersection point, and take the result of multiplying the obtained difference by 100% as the risk percentage of hearing loss caused by noise exposure for the object to be monitored.

[0081] In this embodiment, by collecting basic data such as noise data, noise equipment data, and employee personal data in the employee's operating environment, and predicting risks through modeling analysis, it is possible to predict the risk of hearing loss caused by noise exposure for each employee in each job type, thereby helping the employer establish a personalized and effective hearing protection plan for each employee.

[0082] In an embodiment of the present application, S520 includes, that is, under the selected frequency and boundary, obtaining the age-related hearing threshold levels of the non-noise-exposed population at each percentile within the range of 5% to 95% includes:

[0083] S521, under the selected frequency and boundary, calculate the median of the age-related hearing threshold levels of the non-noise-exposed population at each frequency based on the age of the object to be monitored.

[0084] S522, based on the median of the age-related hearing threshold levels of the non-noise-exposed population at each frequency, calculate the age-related hearing threshold levels of the non-noise-exposed population at each frequency at each percentile within the range of 5% to 95%.

[0085] S523. Calculate the age-related hearing threshold levels of the non-noise-exposed population at each percentile within the range of 5% to 95% based on the age-related hearing threshold levels of the non-noise-exposed population at each frequency at each percentile within the range of 5% to 95% and the weights of each frequency.

[0086] Specifically, determine the weights of each selected frequency and under the boundary according to Table 1. This weight will be used in S523 later.

[0087]

[0088] Specifically, determine the weights of each selected frequency and under the boundary according to Table 1. This weight is used in S523.

[0089] For example, male workers in a certain workshop of an enterprise have been exposed to occupational noise (8 hours per day, 5 days per week, 50 weeks per year) since the age of 26. The daily average noise exposure level is represented by the noise exposure A-weighted value normalized to an 8-hour working day. The noise exposure A-weighted value normalized to an 8-hour working day LEX,8h = 93 dB. Predict the risk prediction level of hearing loss caused by noise exposure in this population at the age of 55 through this application.

[0090] The characteristics of this population are: no ear diseases, no non-occupational noise exposure, and no other risk factors affecting hearing loss.

[0091] Based on the above information, an input data example table can be generated, as shown in Table 2.

[0092]

[0093]

[0094] In S521, calculate the median value H50,f of the age-related hearing threshold levels of the non-noise-exposed population at each frequency according to Formula 5.

[0095] H50,f = a(f) × (age - 18) 2 Formula 5

[0096] Where H50,f is the median value of the age-related hearing threshold levels of the non-noise-exposed population at frequency f, f is the frequency, and a is the calculation coefficient. The selection of the calculation coefficient is shown in Table 3.

[0097]

[0098] After calculation, H50,500 = 0.0024 × (55 - 18) 2 = 4.7915, H50,1000 = 0.004 × (55 - 18) 2= 5.476, H50,2000 = 0.007×(55 - 18) 2 = 9.583, H50,4000 = 0.016×(55 - 18) 2 = 21.904。

[0099] S522, calculate the age-related hearing threshold levels of the non-noise-exposed population at each frequency for each percentile within the range of 5% to 95% according to Formula 6, Formula 7, and Formula 8.

[0100] HQ,f = H50,f + k(Q)×Su,f

[0101] Su,f = bu,f + 0.445×H50,f for 5 ≤ Q < 50

[0102] Formula 6

[0103] HQ,f = H50,f when Q = 50

[0104] Formula 7 HQ,f = H50,f - k(Q)×S1,f S1,f = b1,f + 0.356×H50,f for 50 < Q ≤ 95

[0105] For the selection of k(Q), please refer to Table 4.

[0106] Table 4. k values corresponding to every 5% of Q value

[0107]

[0108] For the selection of bu,f and b1,f, please refer to Table 5.

[0109]

[0110] Continuing from the above embodiment, since the amount of data for calculating HQ,f for each 1% within the range of 5% to 95% is very large, for the sake of concise writing, the calculation process of H10,f is described here. 10 is between 5 and 50, so Formula 6 is used:

[0111] H10,500 = H50,500 + k(10)×(bu,500 + 0.445×H50,500) = 4.7915 + 1.282×(6.12 + 0.445×4.7915) = 15.37084.

[0112] H10,1000 = H50,1000 + k(10)×(bu,1000 + 0.445×H50,1000) = 5.476 + 1.282×(6.12 + 0.445×5.476) = 16.44584.

[0113] H10,2000 = H50,2000 + k(10)×(bu,2000 + 0.445×H50,2000) = 9.583 + 1.282×(7.23 + 0.445×9.583) = 24.31887.

[0114] H10,4000 = H50,4000 + k(10)×(bu,4000 + 0.0445×H50,4000) = 21.904 + 1.282×(8.34 + 0.445×21.904) = 45.09189.

[0115] S523. Calculate the age-related audiometric thresholds of the non-noise-exposed population at each percentile within the range of 5% to 95% according to the calculation results of S522 and the weights of each frequency in Table 1, according to Formula 9.

[0116]

[0117] Where Q is the percentile, HQ is the age-related audiometric threshold of the non-noise-exposed population at percentile Q, HQ,f is the age-related audiometric threshold of the non-noise-exposed population at frequency f at percentile Q, and Zf is the weight of frequency f.

[0118] Still taking the calculation of H10 as an example, H10 = H10,500×0.03 + H10,1000×0.03 + H10,2000×0.03 + H10,4000×0.01 = 15.37084×0.03 + 16.44584×0.03 + 24.31887×0.03 + 45.09189×0.01 = 21.34985.

[0119] The calculation result of H50 will not be elaborated either, which is 8.14555.

[0120] In an embodiment of the present application, S530 includes, that is, under the selected frequency and boundary, obtain the age- and noise-related audiometric thresholds of the noise-exposed population at each percentile within the range of 5% to 95%, including:

[0121] S531. Under the selected frequency and boundary, calculate the median value of the permanent threshold shift at each frequency according to the A-weighted noise exposure value normalized by the rated 8-hour working day of the object to be monitored and the exposure working years.

[0122] S532. According to the median value of the permanent threshold shift at each frequency, calculate the permanent threshold shift at each frequency at each percentile within the range of 5% to 95%.

[0123] S533. Calculate the age- and noise-related hearing threshold levels of the noise-exposed population at each percentile within the range of 5% to 95% based on the age-related hearing threshold levels of the non-noise-exposed population at each frequency at each percentile within the range of 5% to 95%, the permanent threshold shift at each frequency at each percentile within the range of 5% to 95%, and the weights at each frequency.

[0124] Specifically, in S531, calculate the median N50,f of the permanent threshold shift at each frequency according to Formula 10.

[0125] (a) --- Lex,8h < L0,f N50,f = 0

[0126] (b) --- Lex,8h > L0,f and exposure working years > 10 years

[0127] N50,f = (u,f + v,f × lg exposure working years) × (Lex,8h - L0,f) 2

[0128] (c) -- Lex,8h > L0,f and exposure working years < 10 years

[0129] N50,f = [lg(exposure working years + 1) / lg11]

[0130] × (u,f + v,f × lg10) × (Lex,8h - L0,f) 2

[0131] Formula 10

[0132] For the values of u, v, and L0, please refer to Table 6.

[0133] Continuing with the above example, the user belongs to case (b). After calculation, N50,500 = 0, N50,1000 = 1.317886, N50,2000 = 8.365883, N50,4000 = 19.41164.

[0134]

[0135] In S532, calculate the permanent threshold shift NQ at each frequency at each percentile within the range of 5% to 95% according to Formula 11.

[0136] (a) --- NQ,f = N50,f + k(Q) × du,f

[0137] du,f = (Xu,f + Yu,f × lg exposure working years) × (Lex,8h - L0,f) 2

[0138] 5 ≤ Q < 50

[0139] (b) --- NQ, f = N50, f

[0140] Q = 50

[0141] (c) -- NQ, f = N50, f - k(Q)×d1, f

[0142] D1, f = (X1, f + Y1, f × lg exposure work years)×(Lex, 8h - L0, f) 2

[0143] 50 ≤ Q < 95

[0144] Formula 11

[0145] For the values of Xu, Yu, X1, and Y1, please refer to Table 7.

[0146]

[0147] Continuing the above example, still taking N10, f as an example for calculation. After calculation, N10,500 = 0, N10,1000 = 2.249097, N10,2000 = 14.7893, N10,4000 = 27.48916.

[0148] In S533, according to the calculation results of S523, the calculation results of S532, and the weights of each frequency in Table 1, calculate the age-related hearing threshold levels of the non-noise-exposed population at each percentile within the range of 5% to 95% according to Formula 12.

[0149]

[0150] Continuing the above example, still taking H10 as an example for calculation, H10’ = 27.18572.

[0151] Subsequently, execute S540 to generate a schematic diagram of the hearing loss risk assessment, as Figure 3 shown. Figure 3 Among them, 1 is the abscissa of the first intersection point, 2 is the risk percentage of hearing loss caused by noise exposure (i.e., the difference between 1 and 6), 3 is the hearing threshold level curve H’ related to age and noise of the noise-exposed population, 4 is N10, 5 is the boundary line, 6 is the abscissa of the second intersection point, 7 is N50, 8 is the age-related hearing threshold level curve H of the non-noise-exposed population, and 9 is N90.

[0152] After generating the schematic diagram of the hearing loss risk assessment, when executing S550 to S562, the first intersection point is Figure 3 the point X in Figure 3At point Y, the abscissa of point X is 13.9 and the abscissa of point Y is 5.1. Therefore, in this example, the risk percentage of hearing loss caused by noise exposure for the object to be monitored = 13.9% - 5.1% = 8.8%.

[0153] When executing S600, the risk prediction level evaluation table can be retrieved, and by looking up the table, the risk prediction level of hearing loss caused by noise exposure for the object to be monitored can be obtained.

[0154] The risk prediction level evaluation table is shown in Table 8.

[0155] Continuing with the above example, by querying Table 8, it can be seen that when the boundary is 25 dB, the risk percentage of hearing loss caused by noise exposure for the user is 8.8%, hitting the risk percentage range of higher risk. Therefore, the risk prediction level of the user is defined as: higher risk.

[0156] Table 8. Risk Prediction Level Evaluation Table

[0157]

[0158] In an embodiment of the present application, after S550, that is, after determining whether the age-related audiogram curve of the non-noise-exposed population and the age- and noise-related audiogram curve of the noise-exposed population both intersect with the boundary, it further includes:

[0159] S571, if the age-related audiogram curve of the non-noise-exposed population and the age- and noise-related audiogram curve of the noise-exposed population do not both intersect with the boundary, then determine whether any one of the age-related audiogram curve of the non-noise-exposed population and the age- and noise-related audiogram curve of the noise-exposed population intersects with the boundary.

[0160] S572a, if none of the age-related audiogram curve of the non-noise-exposed population and the age- and noise-related audiogram curve of the noise-exposed population intersects with the boundary, then determine whether the boundary value is greater than 5% of the age- and noise-related audiogram of the noise-exposed population.

[0161] S572b, if the boundary value is greater than 5% of the age- and noise-related audiogram of the noise-exposed population, then define the risk percentage of hearing loss caused by noise exposure for the object to be monitored as being in the range greater than or equal to 0 and less than or equal to 5%.

[0162] Specifically, there are four cases of the intersection of curve H and curve H' with the boundary:

[0163] Case 1) Curve H intersects with the boundary to produce an intersection point, and curve H' intersects with the boundary to produce an intersection point;

[0164] Case 2) The curve H does not intersect the boundary line. Does the curve H' intersect the boundary line?

[0165] Case 3) The curve H intersects the boundary line to produce an intersection point, and the curve H' does not intersect the boundary line.

[0166] Case 4) The curve H does not intersect the boundary line, and the curve H' intersects the boundary line to produce an intersection point.

[0167] The embodiments of S561 to S562 described above are Case 1). The present embodiment describes Case 2).

[0168] If the curve H does not intersect the boundary line and the curve H' does not intersect the boundary line, there will be two sub-cases:

[0169] Sub-case 2.1) Both the curve H and the curve H' are below the boundary line.

[0170] This is the situation described in S572b. At this time, the risk is relatively small. Therefore, the risk percentage of the object to be monitored suffering from hearing loss due to noise exposure is defined to be in the range of greater than or equal to 0 and less than or equal to 5%. Therefore, according to Table 8, the subsequent risk prediction level can be defined as negligible risk or acceptable risk, either is acceptable.

[0171] In an embodiment of the present application, after S572a, that is, after determining whether the boundary line value is greater than the hearing threshold level related to age and noise of the 5% noise-exposed population, it further includes:

[0172] S572c. If the boundary line value is not greater than the hearing threshold level related to age and noise of the 5% noise-exposed population, then further determine whether the boundary line value is less than the hearing threshold level related to age and noise of the 95% noise-exposed population.

[0173] S572d. If the boundary line value is less than the hearing threshold level related to age and noise of the 95% noise-exposed population, then define the risk percentage of the object to be monitored suffering from hearing loss due to noise exposure to be in the range of greater than or equal to 95% and less than or equal to 100%.

[0174] Specifically, the present embodiment describes another sub-case of Case 2):

[0175] Sub-case 2.1) Both the curve H and the curve H' are above the boundary line.

[0176] This is the situation described in S572d. At this time, the risk is relatively large. Therefore, the risk percentage of the object to be monitored suffering from hearing loss due to noise exposure is defined to be in the range of greater than or equal to 95% and less than or equal to 100%. Therefore, according to Table 8, the subsequent risk prediction level can be defined as extremely high risk.

[0177] In an embodiment of the present application, after S571, after determining whether there is an intersection between any one of the age-related hearing threshold level curve of the non-noise-exposed population and the hearing threshold level curve related to age and noise of the noise-exposed population and the boundary line, the following is further included:

[0178] S573, if there is an intersection between any one of the age-related hearing threshold level curve of the non-noise-exposed population and the hearing threshold level curve related to age and noise of the noise-exposed population and the boundary line, determine whether there is an intersection between the age-related hearing threshold level curve of the non-noise-exposed population and the boundary line.

[0179] S574a, if there is an intersection between the age-related hearing threshold level curve of the non-noise-exposed population and the boundary line, calculate the value of the abscissa of the intersection between the age-related hearing threshold level curve of the non-noise-exposed population and the boundary line as the first value.

[0180] S574b, use the result of subtracting the first value from 95% as the risk percentage of hearing loss caused by noise exposure for the object to be monitored.

[0181] Specifically, there are four cases of the intersection of curve H and curve H' and the boundary line:

[0182] Case 1) Curve H intersects with the boundary line to produce an intersection point, and curve H' intersects with the boundary line to produce an intersection point;

[0183] Case 2) Curve H does not intersect with the boundary line, and curve H' does not intersect with the boundary line;

[0184] Case 3) Curve H intersects with the boundary line to produce an intersection point, and curve H' does not intersect with the boundary line;

[0185] Case 4) Curve H does not intersect with the boundary line, and curve H' intersects with the boundary line to produce an intersection point.

[0186] This embodiment introduces Case 3).

[0187] In an embodiment of the present application, after S573, after determining whether there is an intersection between the age-related hearing threshold level curve of the non-noise-exposed population and the boundary line, the following is further included:

[0188] S575a, if there is no intersection between the age-related hearing threshold level curve of the non-noise-exposed population and the boundary line, determine that there is an intersection between the hearing threshold level curve related to age and noise of the noise-exposed population and the boundary line, and calculate the value of the abscissa of the intersection between the hearing threshold level curve related to age and noise of the noise-exposed population and the boundary line as the second value.

[0189] S575b, use the result of subtracting 0 from the second value as the risk percentage of hearing loss caused by noise exposure for the object to be monitored.

[0190] Specifically, there are four cases of the intersection of curve H, curve H' and the boundary line:

[0191] Case 1) Curve H intersects the boundary line to generate an intersection point, and curve H' intersects the boundary line to generate an intersection point;

[0192] Case 2) Curve H does not intersect the boundary line, and curve H' does not intersect the boundary line;

[0193] Case 3) Curve H intersects the boundary line to generate an intersection point, and curve H' does not intersect the boundary line;

[0194] Case 4) Curve H does not intersect the boundary line, and curve H' intersects the boundary line to generate an intersection point.

[0195] This embodiment introduces Case 4).

[0196] The technical features of the above-described embodiments can be combined arbitrarily, and there is no limitation on the execution order of each method step. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0197] The above-described embodiments only represent several implementation manners of the present application. The description is relatively specific and detailed, but it should not be construed as a limitation on the scope of the patent of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several deformations and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. A dynamic monitoring and early warning method for workplace noise exposure, characterized in that The method includes: Obtaining the noise monitoring data of the point to be monitored; Calculating the A-weighted equivalent continuous sound level of the point to be monitored based on the noise monitoring data of the point to be monitored; Judging whether the A-weighted equivalent continuous sound level of the point to be monitored is less than or equal to a first preset value; If the A-weighted equivalent continuous sound level of the point to be monitored is less than or equal to the first preset value, marking the point to be monitored with a first color; If the A-weighted equivalent continuous sound level of the point to be monitored is greater than the first preset value, further judging whether the A-weighted equivalent continuous sound level of the point to be monitored is less than or equal to a second preset value; If the A-weighted equivalent continuous sound level of the point to be monitored is less than or equal to the second preset value, marking the point to be monitored with a second color; If the A-weighted equivalent continuous sound of the point to be monitored is greater than the second preset value, marking the point to be monitored with a third color; After a preset monitoring time period, returning to obtain the noise monitoring data of the point to be monitored; Obtaining the gender, age, A-weighted noise exposure value normalized for a rated 8-hour workday, and exposure work years of the object to be monitored, and calculating the risk percentage of hearing loss caused by noise exposure of the object to be monitored; Analyzing the risk percentage of hearing loss caused by noise exposure of the object to be monitored, and outputting the risk prediction level of hearing loss caused by noise exposure of the object to be monitored.

2. The dynamic monitoring and early warning method for workplace noise exposure according to claim 1, wherein, The calculating the A-weighted equivalent continuous sound level of the point to be monitored based on the noise monitoring data of the point to be monitored includes: Calculating the A-weighted equivalent continuous sound level of the point to be monitored according to Formula 1; Wherein, LAeq is the A-weighted equivalent continuous sound level of the point to be monitored, N is the total number of points to be detected, LAi is the A-weighted sound pressure level of the i-th point to be detected, and i is the serial number of the point to be monitored.

3. The dynamic monitoring and early warning method for workplace noise exposure according to claim 2, wherein, The obtaining the gender, age, A-weighted noise exposure value normalized for a rated 8-hour workday, and exposure work years of the object to be monitored, and calculating the risk percentage of hearing loss caused by noise exposure of the object to be monitored includes: Obtaining the noise exposure data of the object to be monitored within the most recent week, and calculating the weekly average A-weighted noise exposure value of the object to be monitored based on the noise exposure data of the object to be monitored within the most recent week; Calculating the calibrated weekly equivalent A-weighted noise exposure value of the object to be monitored according to the work type of the object to be detected and the weekly average A-weighted noise exposure value of the object to be monitored; Converting the calibrated weekly equivalent A-weighted noise exposure value of the object to be monitored into the A-weighted noise exposure value normalized for a rated 8-hour workday of the object to be monitored.

4. The dynamic monitoring and early warning method for workplace noise exposure according to claim 3, characterized in that The obtaining the gender, age, A-weighted noise exposure value normalized for a rated 8-hour workday, and exposure work years of the object to be monitored, and calculating the risk percentage of hearing loss caused by noise exposure of the object to be monitored further includes: Selecting frequencies and boundaries according to the work type of the object to be monitored; Obtaining the age-related hearing threshold levels of the non-noise-exposed population at each percentile within the range of 5% to 95% under the selected frequencies and boundaries; Obtaining the age- and noise-related hearing threshold levels of the noise-exposed population at each percentile within the range of 5% to 95% under the selected frequencies and boundaries; Draw a schematic diagram for evaluating the risk of hearing loss based on the age-related hearing threshold levels of the non-noise-exposed population at each percentile within the range of 5% to 95%, and the age- and noise-related hearing threshold levels of the noise-exposed population at each percentile within the range of 5% to 95%. Determine whether both the age-related hearing threshold level curve of the non-noise-exposed population and the age- and noise-related hearing threshold level curve of the noise-exposed population intersect the boundary line. If both the age-related hearing threshold level curve of the non-noise-exposed population and the age- and noise-related hearing threshold level curve of the noise-exposed population intersect the boundary line, then take the intersection point of the age-related hearing threshold level curve of the non-noise-exposed population and the boundary line as the first intersection point, and take the intersection point of the age- and noise-related hearing threshold level curve of the noise-exposed population and the boundary line as the second intersection point. Subtract the abscissa value of the first intersection point from the abscissa value of the second intersection point, and take the result of multiplying the obtained difference by 100% as the risk percentage of hearing loss caused by noise exposure for the object to be monitored.

5. The dynamic monitoring and early warning method for workplace noise exposure according to claim 4, wherein The obtaining of the age-related hearing threshold levels of the non-noise-exposed population at each percentile within the range of 5% to 95% under the selected frequency and boundary line includes: Under the selected frequency and boundary line, calculate the median value of the age-related hearing threshold levels of the non-noise-exposed population at each frequency based on the age of the object to be monitored. Based on the median value of the age-related hearing threshold levels of the non-noise-exposed population at each frequency, calculate the age-related hearing threshold levels of the non-noise-exposed population at each frequency at each percentile within the range of 5% to 95%. Based on the age-related hearing threshold levels of the non-noise-exposed population at each frequency at each percentile within the range of 5% to 95%, and the weights of each frequency, calculate the age-related hearing threshold levels of the non-noise-exposed population at each percentile within the range of 5% to 95%.

6. The dynamic monitoring and early warning method for workplace noise exposure according to claim 5, characterized in that The obtaining of the age- and noise-related hearing threshold levels of the noise-exposed population at each percentile within the range of 5% to 95% under the selected frequency and boundary line includes: Under the selected frequency and boundary line, calculate the median value of the permanent threshold shift at each frequency based on the A-weighted noise exposure value normalized to the rated 8-hour workday of the object to be monitored and the exposure work years. Based on the median value of the permanent threshold shift at each frequency, calculate the permanent threshold shift at each frequency at each percentile within the range of 5% to 95%. Based on the age-related hearing threshold levels of the non-noise-exposed population at each frequency at each percentile within the range of 5% to 95%, the permanent threshold shift at each frequency at each percentile within the range of 5% to 95%, and the weights of each frequency, calculate the age- and noise-related hearing threshold levels of the noise-exposed population at each percentile within the range of 5% to 95%.

7. The dynamic monitoring and early warning method for workplace noise exposure according to claim 6, wherein After determining whether both the age-related hearing threshold level curve of the non-noise-exposed population and the age- and noise-related hearing threshold level curve of the noise-exposed population intersect the boundary line, it further includes: If the age-related audiometric threshold level curve of the non-noise-exposed population and the audiometric threshold level curve related to age and noise of the noise-exposed population do not both intersect the boundary line, then determine whether there is any intersection between the age-related audiometric threshold level curve of the non-noise-exposed population and the boundary line or between the audiometric threshold level curve related to age and noise of the noise-exposed population and the boundary line; If there is no intersection between the age-related audiometric threshold level curve of the non-noise-exposed population and the boundary line or between the audiometric threshold level curve related to age and noise of the noise-exposed population and the boundary line, then determine whether the boundary value is greater than the audiometric threshold level of 5% of the noise-exposed population related to age and noise; If the boundary value is greater than the audiometric threshold level of 5% of the noise-exposed population related to age and noise, then define the risk percentage of hearing loss caused by noise exposure of the object to be monitored as being in the range greater than or equal to 0 and less than or equal to 5%.

8. The dynamic monitoring and early warning method for workplace noise exposure according to claim 7, characterized in that After determining whether the boundary value is greater than the audiometric threshold level of 5% of the noise-exposed population related to age and noise, it further includes: If the boundary value is not greater than the audiometric threshold level of 5% of the noise-exposed population related to age and noise, then further determine whether the boundary value is less than the audiometric threshold level of 95% of the noise-exposed population related to age and noise; If the boundary value is less than the audiometric threshold level of 95% of the noise-exposed population related to age and noise, then define the risk percentage of hearing loss caused by noise exposure of the object to be monitored as being in the range greater than or equal to 95% and less than or equal to 100%.

9. The dynamic monitoring and early warning method for workplace noise exposure according to claim 8, characterized in that, After determining whether there is any intersection between the age-related audiometric threshold level curve of the non-noise-exposed population and the audiometric threshold level curve related to age and noise of the noise-exposed population and the boundary line, it further includes: If there is any intersection between the age-related audiometric threshold level curve of the non-noise-exposed population and the audiometric threshold level curve related to age and noise of the noise-exposed population and the boundary line, determine whether there is an intersection between the age-related audiometric threshold level curve of the non-noise-exposed population and the boundary line; If there is an intersection between the age-related audiometric threshold level curve of the non-noise-exposed population and the boundary line, then calculate the value of the abscissa of the intersection point between the age-related audiometric threshold level curve of the non-noise-exposed population and the boundary line as the first value; Take the result of subtracting the first value from 95% as the risk percentage of hearing loss caused by noise exposure of the object to be monitored.

10. The dynamic monitoring and early warning method for workplace noise exposure according to claim 9, wherein After determining whether there is an intersection between the age-related audiometric threshold level curve of the non-noise-exposed population and the boundary line, it further includes: If there is no intersection between the age-related audiometric threshold level curve of the non-noise-exposed population and the boundary line, then determine that there is an intersection between the audiometric threshold level curve related to age and noise of the noise-exposed population and the boundary line, and calculate the value of the abscissa of the intersection point between the audiometric threshold level curve related to age and noise of the noise-exposed population and the boundary line as the second value; Take the result of subtracting 0 from the second value as the risk percentage of hearing loss caused by noise exposure of the object to be monitored.

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