Smart safety management system based on differential safety process for facility handling high level of hazardous gas

Abstract

The present invention relates to a smart safety management system based on a differential safety process for a facility handling a high level of hazardous gas, and, more specifically, to a smart safety management system that enables early response, for each piece of equipment or zone, to gas leakage accidents that frequently occur at facilities handling hazardous gases, which result in significant financial losses and casualties.

Description

Smart safety management system centered on differentiated safety processes for high-risk gas concentration facilities

[0001] The present invention relates to a smart safety management system centered on differential safety processes for high-risk gas-dense facilities.

[0002] Specifically, this relates to a smart safety management system capable of initial response by facility / zone, as gas leak accidents frequently occur in facilities handling high-risk gases, resulting in significant economic and human cost-cutting.

[0003] Now is the time for smart technology capable of accident prevention and response by monitoring risk factors in facilities with a high concentration of high-risk gases (flammable gases, toxic gases, etc.), performing real-time risk diagnosis and prediction, and implementing differentiated safety management based on on-site conditions.

[0004]

[0005] In the case of high-risk gas facilities, to prevent damage to the facilities caused by explosion accidents resulting from defects in the on-site systems themselves, the High Pressure Gas Act mandates that only products with explosion-proof certification must be installed for all systems installed on-site.

[0006] Therefore, it is necessary to develop continuous monitoring technologies for high-risk facilities and equipment at an efficient cost for large-scale areas of city gas, petrochemical, and gas plants managed under the three major gas laws.

[0007]

[0008] Meanwhile, in the case of high-risk facilities, ammonia and hydrogen are the representative flammable gases primarily used, and management is highly necessary because operating conditions often involve high-temperature and high-pressure processes. In the case of CO, a toxic gas, poisoning accidents occur frequently during processes and maintenance, and due to its high lethality, early detection is crucial.

[0009]

[0010] On the other hand, mobile carriers are pursuing a business that senses vibration, sound, and ambient temperature, transmits them via 5G, analyzes them using AI, and predicts failures.

[0011] However, while AI-based fault diagnosis technology has been secured, there is no wireless explosion-proof product technology yet to be installed in high-risk facilities such as hydrogen refueling stations, and preparations are underway to develop 5G-based terminals.

[0012] In addition, Korea Telecom and Smart Ocean have developed wired-based vibration, acoustic emission, and ambient temperature measurement systems for smart factories, installed them in telecommunications office generators and UPS systems, and are currently operating them, while pursuing expanded commercialization targeting Hyundai Heavy Industries, Kia Motors, and others.

[0013]

[0014] However, monitoring technology based on inspection is still inadequate, and accordingly, there is a need for domestic industrial site monitoring technology utilizing industrial standard wireless network technology.

[0015] Safety management for high-risk facilities engaged in the storage, use, sale, and filling of high-pressure gases is primarily carried out through visual inspections in accordance with safety management regulations, the installation of detectors, and alarms; each detector possesses a simple function of sounding an alarm based on the detection result, utilizing a simple detection capability specialized for the target gas or chemical substance.

[0016] Furthermore, due to limitations in domestic regulations, detectors, circuit breakers, and alarms possess a physical vulnerability requiring wired connections. In terms of detector performance, the key core technology lies in the performance of the sensor capable of detecting objects with high precision; while the related technology falls somewhat short of international standards, it is understood to meet the performance requirements stipulated by domestic regulations.

[0017]

[0018] Regarding predictive maintenance technology for high-risk gases, the past industrialization trend focused on economic growth, resulting in a concentration on construction while technological development for maintenance and safety management was lacking. Recently, with the advent of the Fourth Industrial Revolution, technological development is underway to enable predictive maintenance and integrity monitoring of high-risk facilities and equipment by utilizing advanced IT technologies.

[0019] Samchully has introduced a 'Smart Pipeline Network System' to collect and analyze on-site data necessary for managing underground city gas facilities, transmit it via IoT communication to monitor site conditions, and respond to abnormal situations.

[0020] In addition, Korea Gas Corporation has established an 'Electronic Device Diagnostic and Monitoring System (EDMS)' for predictive maintenance of gas facilities at four LNG production bases nationwide. By analyzing real-time status data of key power facilities (GIS, transformers, etc.), it enables advance warning of facility failures and allows for preemptive measures.

[0021]

[0022] However, regarding predictive maintenance, the technology integrating configuration management is currently lacking. When applying the domestic market share within the global plant engineering software market, the size of the domestic plant-related configuration management market is estimated to be 1.342 billion won as of 2015, and is estimated to have reached 3.29 billion won by 2019, showing a growth rate of 25.12%.

[0023]

[0024] As a measurement technology applied within high-risk gas industrial facilities, Youngshin DNC Co., Ltd. and Daum Engineering Co., Ltd. hold a patent for an 'IoT-based urban construction site continuous safety management system'.

[0025] This requires installing unit IoT sensor units in areas at risk of structural anomalies and establishing a safety management server for constructing scenario data utilizing measurement data from the IoT sensor units, but

[0026] It does not include explosion-proof sensing / transmission terminal technology, industrial IoT communication technology, multi-type communication technology, and sensing terminal technology.

[0027]

[0028] In addition, Daewoo Engineering & Construction holds a patent for 'Intelligent Complex Hydrogen Station Operation Management System and Method,' which is a technology related to complex hydrogen stations and concerns an intelligent complex hydrogen station operation management system and method.

[0029] In other words, while it provides an intelligent complex hydrogen station operation management system and method based on demand response linked with a power management system, it differs from the differential safety management technology proposed by the applicant regarding the technology for the hydrogen station operation management system.

[0030]

[0031] Kyungdong City Gas is conducting research to develop a gas filling station predictive maintenance system that predicts signs of equipment abnormalities and lifespan in advance through big data-based predictive maintenance technology.

[0032] In addition, research is underway on the development of commercialization technologies for fault prediction and safety management at hydrogen refueling stations, but this covers only a tiny fraction of facilities with high concentrations of high-risk gases.

[0033] To elaborate, it is Public Patent Publication No. 10-2019-0086912.

[0034] This serves as a predictive maintenance system for gas filling stations. Through real-time data analysis of all operational aspects—including compression, electrical, personnel, routine, and billing management—it automatically alerts users to potential risks before an accident occurs based on risk levels when thresholds are exceeded, thereby preventing partial suspension of filling, eliminating potential fire and explosion hazards in the event of a gas leak, and preventing losses in city gas sales volume caused by leaks.

[0035]

[0036] In addition, Registered Patent Publication No. 10-1219182 describes a smart safety management operation system, which is a smart wear smart safety management operation system mounted on equipment or gear worn by a worker at an industrial site or a disaster site, and comprises: a terminal for a work manager to input safety matters related to a process in real time during a site patrol; a first smart wear that photographs the surrounding situation of the work manager or detects it with predetermined sensors, and wirelessly transmits the photographed and detected situation information and the safety matters input into the terminal; a second smart wear that photographs the surrounding situation of the worker or detects it with predetermined sensors and wirelessly transmits the detected situation information; a network module that relays wireless communication between the smart wear and a central control center; and a central control center that receives information from the first smart wear and the second smart wear through the network module, infers the safety situation of the industrial site and the safety situation of the worker based on the received information, and commands a control signal according to the inference result to the smart wear or provides a technology application service.

[0037] The objective of the present invention is to provide a smart safety management system capable of initial response by facility / zone, as gas leakage accidents frequently occur in facilities handling high-risk gases, resulting in significant economic and human resource losses.

[0038] The smart safety management system centered on differential safety processes for high-risk gas-dense facilities according to the present invention, devised to achieve the aforementioned purpose, is

[0039] A configuration management unit that performs configuration management for component information and facility information of high-risk gas facilities;

[0040] A compressor installed in a high-risk gas facility for compressing H2S gas; and a risk diagnosis and fault prediction unit that installs one or more vibration sensors at the inlet / outlet piping connection of the compressor and diagnoses a risk by determining whether the compressor is normal or faulty based on the vibration values ​​of the vibration sensors;

[0041] It is characterized by including a risk prediction unit that, when a risk is diagnosed based on the vibration of the compressor through the above-mentioned risk diagnosis and fault prediction unit, predicts the risk level within the facility in the event of a gas leak by linking the temperature information of a temperature sensor that measures the temperature in the atmosphere, the wind speed information of a wind speed sensor that measures the wind speed, the wind direction information of a wind direction sensor, and the humidity information of a humidity sensor that measures humidity.

[0042]

[0043] At this time, the above-mentioned configuration management unit,

[0044] A user information management module that generates and manages user information about an operator;

[0045] A parts management module that registers, modifies, deletes, searches, and stores search results for parts information provided in high-risk dense gas facilities, and manages drawing information and document information regarding the parts information;

[0046] A facility management module that manages facility code, facility name, model name, person in charge, facility status, basic information, COM information, facility maintenance history, facility document information, and facility drawing information regarding facility information provided in high-risk dense gas facilities;

[0047] A change management module that manages the occurrence of changes to pre-stored part information or equipment information;

[0048] A facility BOM management module that enables the registration, modification, revision, and deletion of BOM history for facility information;

[0049] It is characterized by including a drawing management module that manages information by 2D and 3D drawings related to part information and equipment information, and information by version according to the drawing file version.

[0050] According to the smart safety management system centered on differential safety processes for high-risk gas-dense facilities of the present invention, since gas leakage accidents frequently occur in facilities handling high-risk gases, resulting in massive economic and human resource losses, it has the advantage of enabling initial response by facility / zone.

[0051] FIG. 1 is a block diagram of a smart safety management system according to the present invention.

[0052] Figure 2 shows an example of an interface according to the configuration management unit of a smart safety management system according to the present invention.

[0053] Figure 3 shows an example of outputting the number of pieces of information regarding equipment information as a graph through an equipment management module configured in the configuration management unit of a smart safety management system according to the present invention.

[0054] Figure 4 is an example of BOM history management output through the configuration management unit of the smart safety management system according to the present invention.

[0055] Figure 5 is an example of a screen output through a drawing management module configured in the shape management unit of a smart safety management system according to the present invention.

[0056] FIG. 6 is an example of a divided screen output through a drawing management module configured in the shape management unit of a smart safety management system according to the present invention.

[0057] FIG. 7 shows an example of comparing vibration values ​​in the risk diagnosis and fault prediction unit of a smart safety management system according to the present invention.

[0058] FIG. 8 shows an example of the diagnosis result of a compressor according to the risk diagnosis and fault prediction unit of the smart safety management system according to the present invention.

[0059] Terms and words used in this specification and claims should not be interpreted as being limited to their ordinary or dictionary meanings, but should be interpreted in a meaning and concept consistent with the technical spirit of the invention, based on the principle that the inventor can appropriately define the concept of the terms to best describe his invention.

[0060]

[0061] Therefore, it should be understood that the embodiments described in this specification and the items illustrated in the drawings are merely the most preferred embodiments of the invention and do not represent all of the technical ideas of the invention, and that various equivalents and modifications that can replace them may exist at the time of filing this application.

[0062]

[0063] Before proceeding with the following description with reference to the drawings, it should be noted that matters not necessary to reveal the gist of the invention, namely known configurations that a person skilled in the art with ordinary knowledge can obviously add, have not been illustrated or described in detail.

[0064]

[0065] The present invention relates to a smart safety management system centered on differential safety processes for high-risk gas-dense facilities.

[0066] Specifically, this relates to a smart safety management system capable of initial response by facility / zone, as gas leak accidents frequently occur in facilities handling high-risk gases, resulting in significant economic and human cost-cutting.

[0067]

[0068] A smart safety management system centered on differential safety processes for high-risk gas-dense facilities according to the present invention will be explained with reference to the attached drawings.

[0069] FIG. 1 is a block diagram of a smart safety management system according to the present invention.

[0070]

[0071] The smart safety management system according to the present invention includes a configuration management unit that performs configuration management based on the CM2 model, which is a US information configuration management software certification model.

[0072] At this time, the configuration management unit is configured to include a user information management module, a parts management module, an equipment management module, an equipment spring management module, a drawing management module, and a change management module.

[0073] At this time, the user information management module enables the creation and management of user information regarding the operator, which may include, for example, the creation of user information, modification of information, password recovery, password change and reset, and search of usage records.

[0074]

[0075] In addition, the parts management module registers, modifies, deletes, searches, and stores search results for parts information equipped in high-risk dense gas facilities, and manages drawing information and document information regarding the parts information as information.

[0076] The facility management module manages information such as facility code, facility name, model name, person in charge, facility status, basic information, COM information, facility maintenance history, facility document information, and facility drawing information regarding facility information equipped in high-risk dense gas facilities.

[0077]

[0078] At this time, document information and drawing information are classified by document number, document name, file name, version, description, etc., so that the information can be managed. In particular, drawing information can be stored as 2D and 3D information regarding equipment and parts.

[0079]

[0080] In addition, the above configuration management unit further includes a change management module that, when a change occurs in pre-stored part information or equipment information, reviews and approves it, and then manages the results of the implemented change as information.

[0081] In other words, it involves managing and reflecting the results of the changes, as well as information regarding the users who performed the changes and those who reviewed and approved them.

[0082] For the interface of this configuration management unit, refer to Figure 2 of the attached drawings.

[0083] Figure 2 shows an example of an interface according to the configuration management unit of a smart safety management system according to the present invention.

[0084]

[0085] In addition, the number of maintenance cases for equipment information can be aggregated through the equipment management module and provided in the form of a graph. This is exemplified in Figure 3 of the attached drawings.

[0086] Figure 3 shows an example of outputting the number of pieces of information regarding equipment information as a graph through an equipment management module configured in the configuration management unit of a smart safety management system according to the present invention.

[0087]

[0088] In addition, the above configuration management unit enables the registration, modification, revision, and deletion of BOM (Bill of Material) history for equipment information through the equipment spring management module.

[0089] For an example of this, refer to Fig. 4 of the attached drawings.

[0090] Figure 4 is an example of BOM history management output through the configuration management unit of the smart safety management system according to the present invention.

[0091]

[0092] In addition, as described above, through the drawing management module, various documents and 2D / 3D drawings related to parts and equipment can be registered, modified, revised, deleted, searched, and viewed, and documents and drawings of each part and equipment can be managed by version, which can be done by referring to Fig. 5 of the attached drawing.

[0093] Figure 5 is an example of a screen output through a drawing management module configured in the shape management unit of a smart safety management system according to the present invention.

[0094]

[0095] In addition, the drawing management module of the configuration management department can manage drawing information for each part information and equipment information separately for 2D and 3D drawings, and by enabling the storage and management of each drawing by version, it can provide an interface that splits windows to display drawing information by version through the split windows, allowing the user to clearly identify the differences between versions.

[0096] This is the same as Figure 6 of the attached drawings.

[0097] FIG. 6 is an example of a divided screen output through a drawing management module configured in the shape management unit of a smart safety management system according to the present invention.

[0098]

[0099] In addition, the configuration management system further includes a risk diagnosis and fault prediction unit capable of diagnosing the risk of gas leakage and predicting failures by monitoring equipment information of high-risk gas facilities.

[0100] The above-mentioned risk diagnosis and fault prediction unit installs vibration sensors on the inlet / outlet piping connections and the compressor enclosure of a compressor that compresses H2S gas to detect gas leaks installed in high-risk gas facilities, and determines whether the compressor is normal or faulty using the vibration values. More specifically, it predicts a fault by determining the probability of normal operation versus the probability of failure, and if the probability of the compressor failure is determined to be high, the risk can be diagnosed.

[0101] To this end, the risk diagnosis and fault prediction unit receives vibration values ​​and diagnoses risks by performing analysis and learning based on the received vibration values, wherein the analysis, learning, and verification are performed using an LSTM classifier / LSTM regression model.

[0102] To elaborate on the LSTM model, the above model is a representative algorithm used for time series classification / prediction, and it is an algorithm capable of learning long-term dependency problems by solving the vanishing gradient problem of Recurrent Neural Networks (RNN) (see [Table 1]).

[0103]

[0104]

[0105]

[0106] The performance of the diagnostic algorithm using the LSTM Classifier model is binary cross-entropy 0.0025, and the accuracy of the prediction algorithm using the LSTM Regression model is 2.4 minutes (MAE).

[0107] In addition, the received vibration values ​​are amplified using Jittering technology.

[0108] At this time, for analysis, a sample vibration value to be compared is stored in advance, and said sample vibration value is a value where a dangerous situation is expected due to a gas leak. By comparing this sample vibration value with the received actual vibration value, a diagnosis is performed to anticipate the dangerous situation.

[0109] An example of the comparison of these vibration values ​​is shown in Fig. 7 of the attached drawings.

[0110] FIG. 7 shows an example of comparing vibration values ​​in the risk diagnosis and fault prediction unit of a smart safety management system according to the present invention.

[0111]

[0112] Through this comparison, the compressor diagnosis result is determined by the probability of normal operation and the probability of failure, and compressor failure is predicted based on the failure probability. Alternatively, it may be a prediction of the time remaining until the compressor fails.

[0113] At this time, predicting the time remaining until failure involves deriving results for each point in time of the analyzed data (e.g., every 0.5 seconds) and calculating the average for the entire time series of the data.

[0114] An example of the diagnostic result screen of such a compressor is shown in Fig. 8 of the attached drawings.

[0115] FIG. 8 shows an example of the diagnosis result of a compressor according to the risk diagnosis and fault prediction unit of the smart safety management system according to the present invention.

[0116]

[0117] In order to ensure the reliability of the results of diagnosis and prediction performed using the algorithm described above, the applicant conducted a quality verification test evaluation through the Korea Testing Laboratory (KTL) and obtained a test report. This is as shown in [Table 2].

[0118]

[0119]

[0120]

[0121] In addition, the smart safety management system according to the present invention may further include a risk prediction unit; wherein, when a risk is diagnosed based on the vibration of the compressor through the risk diagnosis and fault prediction unit, the risk prediction unit performs the function of predicting the risk level within the facility in the event of a gas leak by linking with temperature information from a temperature sensor measuring the temperature in the atmosphere, wind speed information from a wind speed sensor measuring the wind speed, wind direction information from a wind direction sensor, and humidity information from a humidity sensor measuring humidity.

[0122] In this case, the risk level can be classified into specific stages, for example, dangerous, moderately dangerous, normal, moderately safe, and safe. Additionally, based on the above information, the risk distance can be predicted and reported.

[0123] As another example, in the event of a gas leak, it is possible to generate the accident scenario with the highest probability of occurrence regarding the leaked gas.

[0124]

[0125] At this time, the accident scenario generated by the risk prediction unit can be visualized by securing map information of the facility in advance and mapping it onto the map information.

[0126] For example, when a gas leak occurs, the point where the leak will first occur is marked, and based on wind speed information, wind direction information, temperature information, and humidity information, the path of the leaked gas and the associated risk are individually marked, and the maximum expected distance the leaked gas will travel is also marked. For instance, based on the general spreading speed of gas, a weight of 100% (2 times) is applied to the direction in which the wind is facing to predict a spreading of twice, and for angles within a predetermined range with respect to the wind direction (e.g., ± 30°), a weight of -10% (90%) is applied for every predetermined angle (e.g., 5°).

[0127] In addition, a weight of -50% is applied to the opposite direction of the wind to predict spreading, and an additional weight of 10% is applied for every ±10° of the wind direction, in the order of -40, -30, ..., until no weight is applied at the point that becomes the center of the wind direction.

[0128]

[0129] According to the smart safety management system centered on differential safety processes for high-risk gas-dense facilities configured as described above, it has the advantage of enabling initial response by facility / zone, as gas leakage accidents frequently occur in facilities handling high-risk gases, resulting in massive economic and human resource losses.

[0130]

[0131] The description above using the drawings describes only the main aspects of the present invention, and it is obvious that the present invention is not limited to the configuration of the drawings, as various designs are possible within the technical scope.

Claims

1. A configuration management unit that performs configuration management for component information and facility information of high-risk gas facilities; A compressor installed in a high-risk gas facility for compressing H2S gas; and a risk diagnosis and fault prediction unit that installs one or more vibration sensors at the inlet / outlet piping connection of the compressor and diagnoses a risk by determining whether the compressor is normal or faulty based on the vibration values ​​of the vibration sensors; A smart safety management system for a high-risk gas-dense facility, characterized by including: a risk prediction unit that predicts the risk level within the facility in the event of a gas leak by linking temperature information from a temperature sensor that measures the temperature in the atmosphere, wind speed information from a wind speed sensor that measures wind speed, wind direction information from a wind direction sensor, and humidity information from a humidity sensor that measures humidity, when a risk is diagnosed based on the vibration of the compressor through the above-mentioned risk diagnosis and fault prediction unit.

2. In Claim 1, The above configuration management unit is, A user information management module that generates and manages user information about an operator; A parts management module that registers, modifies, deletes, searches, and stores search results for parts information provided in high-risk dense gas facilities, and manages drawing information and document information regarding the parts information; A facility management module that manages facility code, facility name, model name, person in charge, facility status, basic information, COM information, facility maintenance history, facility document information, and facility drawing information regarding facility information provided in high-risk dense gas facilities; A change management module that manages the occurrence of changes to pre-stored part information or equipment information; A facility BOM management module that enables the registration, modification, revision, and deletion of BOM history for facility information; A smart safety management system for a high-risk gas-dense facility, characterized by including a drawing management module that manages information by 2D and 3D drawings related to part information and equipment information, and information by version according to the drawing file version.

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