CN110379514A - A kind of welding fume occupational disease hazards methods of risk assessment - Google Patents
A kind of welding fume occupational disease hazards methods of risk assessment Download PDFInfo
- Publication number
- CN110379514A CN110379514A CN201910627699.7A CN201910627699A CN110379514A CN 110379514 A CN110379514 A CN 110379514A CN 201910627699 A CN201910627699 A CN 201910627699A CN 110379514 A CN110379514 A CN 110379514A
- Authority
- CN
- China
- Prior art keywords
- risk
- welding fume
- exposure
- pneumoconiosis
- dose
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Withdrawn
Links
- 239000003496 welding fume Substances 0.000 title claims abstract description 40
- 238000000034 method Methods 0.000 title claims abstract description 24
- 208000028571 Occupational disease Diseases 0.000 title claims abstract description 21
- 238000012502 risk assessment Methods 0.000 title claims abstract description 18
- 206010035653 pneumoconiosis Diseases 0.000 claims abstract description 24
- 231100000673 dose–response relationship Toxicity 0.000 claims abstract description 15
- 238000009826 distribution Methods 0.000 claims abstract description 8
- 239000003517 fume Substances 0.000 claims abstract description 8
- 238000012360 testing method Methods 0.000 claims abstract description 8
- 239000000428 dust Substances 0.000 claims abstract description 7
- 231100000727 exposure assessment Toxicity 0.000 claims abstract description 6
- 238000012512 characterization method Methods 0.000 claims abstract description 5
- 230000007774 longterm Effects 0.000 claims abstract description 5
- 238000000342 Monte Carlo simulation Methods 0.000 claims abstract description 4
- 230000000711 cancerogenic effect Effects 0.000 claims abstract description 4
- 231100000315 carcinogenic Toxicity 0.000 claims abstract description 4
- 239000013078 crystal Substances 0.000 claims abstract description 4
- 238000011156 evaluation Methods 0.000 claims abstract description 4
- 238000007689 inspection Methods 0.000 claims abstract 2
- 206010073310 Occupational exposures Diseases 0.000 claims description 5
- 231100000675 occupational exposure Toxicity 0.000 claims description 5
- 230000008821 health effect Effects 0.000 claims description 2
- 238000007477 logistic regression Methods 0.000 claims 3
- 230000001419 dependent effect Effects 0.000 claims 1
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims 1
- 230000005611 electricity Effects 0.000 claims 1
- 238000005516 engineering process Methods 0.000 abstract description 5
- 238000010276 construction Methods 0.000 abstract description 2
- 238000003466 welding Methods 0.000 description 7
- 238000004519 manufacturing process Methods 0.000 description 5
- 238000001514 detection method Methods 0.000 description 4
- 230000008569 process Effects 0.000 description 4
- 238000011161 development Methods 0.000 description 3
- CURLTUGMZLYLDI-UHFFFAOYSA-N Carbon dioxide Chemical compound O=C=O CURLTUGMZLYLDI-UHFFFAOYSA-N 0.000 description 2
- 230000001684 chronic effect Effects 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 238000005070 sampling Methods 0.000 description 2
- 230000009466 transformation Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 229910002092 carbon dioxide Inorganic materials 0.000 description 1
- 239000001569 carbon dioxide Substances 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 239000000835 fiber Substances 0.000 description 1
- 239000007789 gas Substances 0.000 description 1
- 231100000206 health hazard Toxicity 0.000 description 1
- 206010020718 hyperplasia Diseases 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000011835 investigation Methods 0.000 description 1
- 239000003973 paint Substances 0.000 description 1
- 238000005498 polishing Methods 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 210000004879 pulmonary tissue Anatomy 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 230000009711 regulatory function Effects 0.000 description 1
- 210000002345 respiratory system Anatomy 0.000 description 1
- 238000005507 spraying Methods 0.000 description 1
- 238000009423 ventilation Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
- G01N15/06—Investigating concentration of particle suspensions
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
Landscapes
- Health & Medical Sciences (AREA)
- Public Health (AREA)
- Engineering & Computer Science (AREA)
- Chemical & Material Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Pathology (AREA)
- Primary Health Care (AREA)
- Epidemiology (AREA)
- Databases & Information Systems (AREA)
- Data Mining & Analysis (AREA)
- Biomedical Technology (AREA)
- Dispersion Chemistry (AREA)
- Physics & Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a kind of welding fume occupational disease hazards methods of risk assessment, the present invention includes Risk Identification, dose-response evaluation, Exposure Assessment and risk characterization；The data that on-site test is carried out based on Weld fume concentration are carried out statistical distribution inspection to this using SPSS software, obtain the probability distribution for connecing dust concentration；Dose-response model of the logistic model as electric welder pneumoconiosis is selected, determines model parameter using population epidemiology data, obtains the dose-response model for sending a telegraph welder's pneumoconiosis for evaluating welding fume exposure；The Monte Carlo simulation that carcinogenic risk value is carried out using crystal ball software, characterizes the risk of electric welder pneumoconiosis caused by welding fume exposed population group in such circumstances long-term work.The present invention completely proposes welding fume occupational disease hazards risk assessment technology for the first time.The work such as the occupational disease hazards risk management applied to construction project and employing unit's Evaluation of Occupational Disease, electric welder pneumoconiosis.
Description
Technical field
The present invention relates to risk assessment technology field, specially a kind of welding fume occupational disease hazards methods of risk assessment.
Background technique
Quality, essence with the development of modern medical equipment technology, to welding fume occupational disease hazards methods of risk assessment
Desired continuous improvement is spent, is also existed to raising working efficiency, reduction production cost, the requirement with quick mobile regulatory function
It is promoted.The development of welding fume occupational disease hazards methods of risk assessment has to adapt to wanting for modern medical equipment technology development
It asks.
Existing welding fume occupational disease hazards methods of risk assessment on the market is moved easily in processing cannot be effectively
It is controlled, cannot be fast moved so as to cause welding fume occupational disease hazards methods of risk assessment and reduces working efficiency, shadow
The problem of ringing staff's normal use, for this purpose, it is proposed that a kind of welding fume occupational disease hazards methods of risk assessment.
Summary of the invention
In view of the deficiencies of the prior art, the purpose of the present invention is to provide a kind of welding fume occupational disease hazards risk assessment
Method, to solve the problems, such as welding fume occupational disease hazards methods of risk assessment mentioned above in the background art in processing.
To achieve the above object, the invention provides the following technical scheme: a kind of welding fume occupational disease hazards risk assessment
Method, including the evaluation of Risk Identification, Exposure Assessment, dose-response, risk characterization；Specific step is as follows:
The Risk Identification is to be recognized by welding fume occupational exposure to workplace and potential risk, is collected
Related data, including occupational history, exposed population group's quantity, gender, age distribution, exposure chamber, exposure duration, worker's protection condition
Deng, welding fume health effect, population epidemiology data etc.；
The Exposure Assessment is the data that on-site test is carried out based on Weld fume concentration, using SPSS software to this progress
Statistical distribution is examined, and the probability distribution for connecing dust concentration is obtained；
The dose-response is evaluated as the dose-response model for selecting logistic model as electric welder pneumoconiosis, utilizes
Population epidemiology data determines model parameter, obtains the dose-response that welder's pneumoconiosis is sent a telegraph for evaluating welding fume exposure
Model；
The risk characterization is that welding fume prediction concentrations are substituted into dose-response model to calculate, and solves noises for various working years hair
The risk of raw electric welder pneumoconiosis, the Monte Carlo simulation of carcinogenic risk value is carried out using crystal ball software, to welding fume exposure
The risk of crowd's electric welder pneumoconiosis caused by long-term work in such circumstances characterizes.
Compared with prior art, the beneficial effects of the present invention are:
The present invention is accurate to the risk for solving noises for various working years generation electric welder pneumoconiosis, carries out carcinogenic wind using crystal ball software
The Monte Carlo simulation being nearly worth, to the risk of electric welder pneumoconiosis caused by welding fume exposed population group in such circumstances long-term work
It is characterized.
Detailed description of the invention
Fig. 1: welding fume occupational exposure assessment technique route map；
Fig. 2: welding fume occupational exposure leads to electric welder pneumoconiosis dose-response assessment technique route map；
Fig. 3: welding fume occupational disease hazards risk assessment technology route map；
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
Figure is please referred to, the present invention provides a kind of technical solution: (1) Occupational Hazard Factors and route of exposure
Certain large-scale agricultural machinery equipment company invests new construction machinery item, which mainly produces 6 tons or less four-wheels
Loading machine, 30 tons or less crawler-mounted excavator and four-wheel excavators are driven, production scale is to produce 2850 per year.Production district includes machine
Manufacturing procedure, welding sequence, polishing operation, pretreatment procedure, spraying process, baking process, touch-up paint process, assembly process, survey
Trial work sequence.Wherein welding sequence proposed adoption carbon dioxide gas arc welding, semi-automatic welding technique.Welding fume is in production environment
In mainly enter human body through respiratory tract.
(2) health hazard of welding fume exposure
Weld fumes can be deposited on intrapulmonary, cause the occupational hazards based on chronic pulmonary tissue fibers hyperplasia, form electric welding
Work pneumoconiosis.Welding fume has been included in " occupational classified catalogue "；Pneumoconiosis (electric welder pneumoconiosis) has been included in " occupational disease
Classification and catalogue ".
According to occupation epidemiology data, electric welder pneumoconiosis is one of the main occupational disease that weld job worker occurs.Make
Industry workers with long time is engaged in weld job, and the long-term welding fume that sucks can cause operating worker chronic healthy to endanger, and serious person can lead
Send a telegraph welder's pneumoconiosis.
2, Exposure Assessment
(1) welding fume on-site test result
At the scene on the basis of occupational Hygienic Investigation, according to GBZ159-2004 " nuisance quality supervision in workplace air
The sampling specification of survey " related request spot sampling is carried out to the welding fume of the Work places welding sequence, and according to GBZ/
T192.1-2007 " in workplace air dust determination part 1: total dust concentration " carries out experimental determination.
The workshop is after the pre-detection carried out for the first time to Work places Weld fume concentration, to the workshop welding region
Ventilation equipment be transformed three times, and the detection of Work places Weld fume concentration has been carried out after each transformation, totally four times
Detection, testing result is as shown in 1~table of table 4.
Welding fume testing result in 1 pre-detection workplace air of table
Weld fume concentration testing result in workplace air after table 2 is transformed for the first time
Weld fume concentration testing result in workplace air after second of table 3 transformation
It although an embodiment of the present invention has been shown and described, for the ordinary skill in the art, can be with
A variety of variations, modification, replacement can be carried out to these embodiments without departing from the principles and spirit of the present invention by understanding
And modification, the scope of the present invention is defined by the appended.
Claims (3)
1. a kind of welding fume occupational disease hazards methods of risk assessment, including the evaluation of Risk Identification, Exposure Assessment, dose-response,
Risk characterization；It is characterized by: specific step is as follows:
The Risk Identification is to be recognized by welding fume occupational exposure to workplace and potential risk, is collected related
Data, including occupational history, exposed population group's quantity, gender, age distribution, exposure chamber, exposure duration, worker's protection condition etc.,
Welding fume health effect, population epidemiology data etc.；
The Exposure Assessment is the data that on-site test is carried out based on Weld fume concentration, is counted using SPSS software to this
Distribution inspection obtains the probability distribution for connecing dust concentration；
The dose-response is evaluated as the dose-response model for selecting logistic model as electric welder pneumoconiosis, utilizes crowd
Epidemiologic data determines model parameter, obtains the dose-response model that welder's pneumoconiosis is sent a telegraph for evaluating welding fume exposure；
The risk characterization is that welding fume prediction concentrations are substituted into dose-response model to calculate, and solves noises for various working years and electricity occurs
The risk of welder's pneumoconiosis carries out the Monte Carlo simulation of carcinogenic risk value using crystal ball software, to welding fume exposed population group
The risk of electric welder pneumoconiosis caused by long-term work is characterized in such circumstances.
2. a kind of welding fume occupational disease hazards methods of risk assessment according to claim 1, it is characterised in that: using system
The nonlinear regression and fitting welding fume occupational exposure that meter learns software SPSS19.0.0 leads to the dose-response mould of electric welder pneumoconiosis
Shape parameter；The hazard factor of electric welder pneumoconiosis be will affect as independent variable, electric welder pneumoconiosis illness rate carries out more as dependent variable
Logistic Model of Factors is fitted logistic regression model, expression formula are as follows:
3. a kind of welding fume occupational disease hazards methods of risk assessment according to claim 1, it is characterised in that: wherein,
Pi is the electric welder pneumoconiosis disease incidence that difference connects dust concentration, Exposure work year, βi0For the constant term of logistic regression analysis, βi1
For the regression coefficient of logistic regression analysis, a is to meet dust concentration mg/m3, and b is Exposure work year.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910627699.7A CN110379514A (en) | 2019-07-12 | 2019-07-12 | A kind of welding fume occupational disease hazards methods of risk assessment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910627699.7A CN110379514A (en) | 2019-07-12 | 2019-07-12 | A kind of welding fume occupational disease hazards methods of risk assessment |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110379514A true CN110379514A (en) | 2019-10-25 |
Family
ID=68252857
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910627699.7A Withdrawn CN110379514A (en) | 2019-07-12 | 2019-07-12 | A kind of welding fume occupational disease hazards methods of risk assessment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110379514A (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11027038B1 (en) | 2020-05-22 | 2021-06-08 | Delta T, Llc | Fan for improving air quality |
| CN112990620A (en) * | 2019-12-02 | 2021-06-18 | 天津市德安圣保安全卫生评价监测有限公司 | Electric welding smoke occupational disease risk assessment method |
| CN114420295A (en) * | 2022-03-30 | 2022-04-29 | 天津渤化讯创科技有限公司 | Low-dose benzene occupational exposure assessment method and system |
| US11400177B2 (en) | 2020-05-18 | 2022-08-02 | Wangs Alliance Corporation | Germicidal lighting |
| CN116824258A (en) * | 2023-06-30 | 2023-09-29 | 哈尔滨工业大学 | A method for detecting smoke and dust in construction sites based on back projection |
-
2019
- 2019-07-12 CN CN201910627699.7A patent/CN110379514A/en not_active Withdrawn
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112990620A (en) * | 2019-12-02 | 2021-06-18 | 天津市德安圣保安全卫生评价监测有限公司 | Electric welding smoke occupational disease risk assessment method |
| US11400177B2 (en) | 2020-05-18 | 2022-08-02 | Wangs Alliance Corporation | Germicidal lighting |
| US11433154B2 (en) | 2020-05-18 | 2022-09-06 | Wangs Alliance Corporation | Germicidal lighting |
| US11612670B2 (en) | 2020-05-18 | 2023-03-28 | Wangs Alliance Corporation | Germicidal lighting |
| US11696970B2 (en) | 2020-05-18 | 2023-07-11 | Wangs Alliance Corporation | Germicidal lighting |
| US12109338B2 (en) | 2020-05-18 | 2024-10-08 | Wangs Alliance Corporation | Germicidal lighting |
| US11027038B1 (en) | 2020-05-22 | 2021-06-08 | Delta T, Llc | Fan for improving air quality |
| CN114420295A (en) * | 2022-03-30 | 2022-04-29 | 天津渤化讯创科技有限公司 | Low-dose benzene occupational exposure assessment method and system |
| CN114420295B (en) * | 2022-03-30 | 2022-06-24 | 天津渤化讯创科技有限公司 | Low-dose benzene occupational exposure assessment method and system |
| CN116824258A (en) * | 2023-06-30 | 2023-09-29 | 哈尔滨工业大学 | A method for detecting smoke and dust in construction sites based on back projection |
| CN116824258B (en) * | 2023-06-30 | 2024-05-14 | 哈尔滨工业大学 | A construction site smoke detection method based on back projection |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110379514A (en) | A kind of welding fume occupational disease hazards methods of risk assessment | |
| Li et al. | Evaluating the impacts of high-temperature outdoor working environments on construction labor productivity in China: A case study of rebar workers | |
| AU2015329347B2 (en) | Fluid leakage data management apparatus and management system | |
| Cheriyan et al. | Assessing the distributional characteristics of PM10, PM2. 5, and PM1 exposure profile produced and propagated from a construction activity | |
| CN105760675A (en) | Analysis method for risk of electric welder pneumoconiosis caused by electrowelding fume occupation exposure | |
| CN109508844B (en) | A security risk analysis method and system for collaborative operations | |
| CN114496262B (en) | High-risk dust risk early warning method and management system based on quantitative risk assessment | |
| CN105139146A (en) | A method and system for evaluating the maturity of enterprise budget management | |
| Dement et al. | Mortality of older construction and craft workers employed at Department of Energy (DOE) nuclear sites | |
| CN118674563A (en) | Security risk information management system based on risk assessment | |
| CN116625896A (en) | A system and method for monitoring dust concentration of personnel in a workplace | |
| CN109101001B (en) | A composite probe value chain data acquisition and monitoring method | |
| CN118969286A (en) | A health management system for production workers in construction projects | |
| CN113254883A (en) | Group noise risk degree evaluation method | |
| CN113780813A (en) | A production environment risk assessment method, device and storage medium | |
| CN118691661A (en) | Building curtain wall measurement system and method based on three-dimensional modeling | |
| CN115585953B (en) | Mask leakage point distribution condition detection system and platform | |
| WO2020093644A1 (en) | Fatigue early-warning method based on small data dynamic prediction model | |
| CN112990620A (en) | Electric welding smoke occupational disease risk assessment method | |
| CN114358538A (en) | Coal mine coal face safety risk assessment method and system | |
| Lombardi et al. | European data and framework analysis of human-machine interaction in manufacturing 4.0: an update | |
| CN116703130B (en) | Engineering measurement wisdom planning design management system | |
| Liu et al. | Multi-dimensional assessment of metal welding fumes exposure and oxidative stress-driven health risks: Insights from external monitoring, respiratory replica monitoring, and DTT activity | |
| CN103399529A (en) | Computer control method for carbon content of molten iron | |
| Wenzl et al. | Comparisons between magnetic field exposure indices in an automobile transmission plant |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WW01 | Invention patent application withdrawn after publication | ||
| WW01 | Invention patent application withdrawn after publication |
Application publication date: 20191025 |