A hazardous chemical transportation vehicle security monitoring system

Abstract

The application discloses a dangerous chemical product transportation vehicle safety protection monitoring system and relates to the technical field of dangerous chemical product transportation vehicle monitoring, which comprises a data acquisition module, a processor, an alarm module, a communication module and a cloud platform. The processor is connected with the data acquisition module and the alarm module, and the processor is connected with the cloud platform through the communication module. The application can accurately monitor the physical state of a tank in a dangerous chemical product transportation process through functions such as real-time monitoring, early warning and remote control, effectively improves the safety and management efficiency of a vehicle, reduces the risk of accidents and guarantees the safe and smooth progress of the dangerous chemical product transportation process.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of dangerous chemical transportation vehicle monitoring, in particular to a dangerous chemical transportation vehicle security monitoring system. BACKGROUND

[0002] Currently, the dangerous chemical tank truck is a transportation carrier for transporting liquid or gas with flammable, explosive and other characteristics to the destination, with the increasing production and transportation of dangerous chemicals, the accidents in the transportation process of dangerous chemicals are also increasing, therefore, the safety problem in the transportation process of dangerous chemicals is more and more concerned by people.

[0003] However, at present, the dangerous chemical transportation vehicle does not monitor the physical state of the tank medium and the safety situation of the vehicle driving in the transportation process, so that the driver and the transportation unit cannot find and understand the safety situation of the vehicle and the tank in time, and make early warning and prevention to the accident.

[0004] Therefore, how to accurately monitor the physical state of the tank in the transportation process of dangerous chemicals is a problem to be solved by those skilled in the art. SUMMARY

[0005] Therefore, the present application provides a dangerous chemical transportation vehicle security monitoring system to solve the problems in the background art.

[0006] In order to achieve the above purpose, the present application adopts the following technical scheme:

[0007] A dangerous chemical transportation vehicle security monitoring system, comprising a data acquisition module, a processor, an alarm module, a communication module, a cloud platform; the processor is connected with the data acquisition module and the alarm module, and the processor is connected with the cloud platform through the communication module;

[0008] The data acquisition module acquires data of the vehicle and transmits the data to the processor;

[0009] The processor determines whether there is danger in the current system through the threshold parameters corresponding to each data type in the preset system threshold; if there is danger, the processor sends an alarm instruction to the alarm module;

[0010] The alarm module receives the alarm instruction sent by the processor, generates alarm information and sends the alarm information to the cloud platform through the communication module;

[0011] The cloud platform receives the alarm information and displays and takes corresponding emergency treatment measures.

[0012] Optionally, the data acquisition module comprises a temperature sensor, a pressure sensor and a liquid level sensor, and data is acquired through the arrangement of the temperature sensor, the pressure sensor and the liquid level sensor on the vehicle.

[0013] Optionally, the processor further comprises:

[0014] a data receiving module, configured to receive data collected by the data collecting module;

[0015] a comparison and evaluation module, configured to compare the data collected by the data collecting module with the corresponding preset system threshold value respectively, and when any one of the data collected by the data collecting module exceeds the corresponding preset system threshold value, evaluate the dangerous chemical product transportation vehicle by using a comprehensive evaluation model to obtain an evaluation score;

[0016] a judgment module, configured to compare the evaluation score with a preset evaluation score threshold value, and when the evaluation score is lower than the preset evaluation score threshold value, determine that the current dangerous chemical product transportation vehicle is dangerous.

[0017] Optionally, the alarm module is connected with a first-level alarm module and a second-level alarm module respectively, when one of the collected data exceeds the system set value, the first-level alarm module is preset with a matching corresponding first-level sound, light and electricity identification instruction to send to the alarm device; when all of the collected data exceed the system set value, the second-level alarm module is configured to have a matching corresponding second-level sound, light and electricity identification instruction to send to the alarm device, at this time, the alarm module sends a danger signal; at the same time, the cloud platform receives the information sent by the first-level and second-level alarm modules and displays and alarms.

[0018] Optionally, the comprehensive evaluation model is as follows:

[0019] ;

[0020] wherein, M represents the evaluation score; n represents the number of parameter types including temperature, pressure and liquid level; represents a preset threshold parameter corresponding to the i-th parameter type; represents a detection value corresponding to the i-th parameter type when any one of the data parameters of temperature, pressure and liquid level exceeds the corresponding preset threshold parameter.

[0021] Optionally, the processor further comprises adjusting the threshold parameter by using a threshold adjustment model to obtain an adjusted threshold parameter when it is determined that the current vehicle operation is in a normal state;

[0022] real-time monitoring whether the temperature, pressure and liquid level in the vehicle operation process exceed the adjusted threshold parameter, when any one of the data parameters of temperature, pressure and liquid level exceeds the corresponding adjusted threshold parameter, controlling the vehicle to stop running and sounding an alarm; wherein, the threshold adjustment model is as follows:

[0023] ;

[0024] wherein, respectively represent the adjusted threshold parameters corresponding to the liquid level, temperature, and pressure; respectively represent the preset threshold parameters corresponding to the liquid level, temperature, and pressure; respectively represent the average parameter data corresponding to the liquid level, temperature, and pressure during the operation of the vehicle; respectively represent the maximum parameter data corresponding to the liquid level, temperature, and pressure during the operation of the vehicle; respectively represent the minimum values corresponding to the temperature detection data and the pressure detection data during the operation of the vehicle.

[0025] Optionally, the cloud platform comprises a sensor data analysis module, a display module, a recording module, and a query module, which are respectively used for real-time and historical data analysis, display, storage, and query. The processing device is connected to a human-computer interaction device to receive query instructions. The display module displays pressure, temperature, liquid level, time, and early warning danger information data.

[0026] Optionally, the processor further comprises a parameter setting module, which is used for setting and modifying relevant parameters of the set value range of the data for different vehicle-carrying media. The parameter setting module is connected to the judgment module, and the relevant parameters of the set value range are used for judgment.

[0027] Optionally, it further comprises an analog-to-digital conversion module, which is used for converting the analog signals collected by the data acquisition module into digital signals through A / D sampling, and transmitting the digital signals to the processor.

[0028] Optionally, it further comprises a loudspeaker, which is connected to the processor. Different frequencies of sound are used for alarm and prompt. Specifically, it comprises:

[0029] When the collected liquid level data exceeds the system set value, the first frequency of sound is used for alarm and prompt;

[0030] When the collected temperature data exceeds the system set value, the second frequency of sound is used for alarm and prompt;

[0031] When the collected pressure data exceeds the system set value, the third frequency of sound is used for alarm and prompt;

[0032] When the collected data of the liquid level, temperature, and pressure all exceed the system set value, the fourth frequency of sound is used for alarm and prompt.

[0033] Compared with the prior art, the safety monitoring system for dangerous chemical product transportation vehicle provided by the application comprises a data acquisition module, a processor, an alarm module, a communication module and a cloud platform, the processor is connected with the data acquisition module and the alarm module, and the processor is connected with the cloud platform through the communication module, the safety monitoring system can accurately monitor the physical state of the tank in the transportation process of dangerous chemical products through real-time monitoring, early warning and remote control, effectively improves the safety and management efficiency of the vehicle, reduces the risk of accidents and ensures the safe and smooth progress of the transportation process of dangerous chemical products. BRIEF DESCRIPTION OF DRAWINGS

[0034] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or the prior art description will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor on the basis of the provided drawings.

[0035] Figure 1 The system structure diagram provided by the present application is shown. DETAILED DESCRIPTION

[0036] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0037] The safety monitoring system for dangerous chemical product transportation vehicle disclosed by the embodiments of the present application comprises a data acquisition module, a processor, an alarm module, a communication module and a cloud platform, as shown in the figure. Figure 1 The processor is connected with the data acquisition module and the alarm module, and the processor is connected with the cloud platform through the communication module.

[0038] The data acquisition module acquires data of the vehicle and transmits the data to the processor.

[0039] The processor determines whether there is danger in the current system through the threshold parameters corresponding to each data type in the preset system threshold, and sends an alarm instruction to the alarm module if there is danger.

[0040] The alarm module receives the alarm instruction sent by the processor, generates alarm information and sends the alarm information to the cloud platform through the communication module.

[0041] The cloud platform receives the alarm information for display and takes corresponding emergency treatment measures.

[0042] In one specific embodiment, the data acquisition module comprises a temperature sensor, a pressure sensor, and a liquid level sensor, and data is collected by arranging the temperature sensor, the pressure sensor, and the liquid level sensor on the vehicle.

[0043] Specifically, the data acquisition module can further comprise an air pressure sensor, and latitude and longitude information is collected by using a geographic information system (GIS).

[0044] In one specific embodiment, the processor further comprises:

[0045] a data receiving module configured to receive data collected by the data acquisition module;

[0046] a comparison and evaluation module configured to compare the data collected by the data acquisition module with corresponding preset system thresholds, respectively, and when any one of the data collected by the data acquisition module exceeds the corresponding preset system threshold, to evaluate the dangerous chemical transport vehicle by using a comprehensive evaluation model and obtain an evaluation score;

[0047] a judgment module configured to compare the evaluation score with a preset evaluation score threshold, and when the evaluation score is lower than the preset evaluation score threshold, to determine that the current dangerous chemical transport vehicle is dangerous.

[0048] In one specific embodiment, the alarm module is connected with a first-level alarm module and a second-level alarm module, respectively, and when one of the collected data exceeds the system set value, the first-level alarm module is preset to send a corresponding first-level sound and light electric identification instruction to the alarm device.

[0049] When all of the collected data exceed the system set value, the second-level alarm module is configured to send a corresponding second-level sound and light electric identification instruction to the alarm device, at which time the alarm module sends a danger signal; at the same time, the cloud platform receives information sent by the first-level and second-level alarm modules and displays and alarms.

[0050] In one specific embodiment, the comprehensive evaluation model is as follows:

[0051] ;

[0052] wherein M represents the evaluation score, n represents the number of parameter types including temperature, pressure, and liquid level, and represents a preset threshold parameter corresponding to the i-th parameter type. represents a detection value corresponding to the i-th parameter type when any one of the data parameters of temperature, pressure, and liquid level exceeds the corresponding preset threshold parameter.

[0053] In a specific embodiment, the processor further comprises adjusting the threshold parameter using a threshold adjustment model when it is determined that the vehicle is operating in a normal state, obtaining an adjusted threshold parameter;

[0054] Real-time monitoring of temperature, pressure, and liquid level during vehicle operation to determine whether they exceed the adjusted threshold parameters. When any of the temperature, pressure, or liquid level data exceeds its corresponding adjusted threshold parameter, the vehicle is stopped and an audible alarm is sounded. The threshold adjustment model is as follows:

[0055] ;

[0056] Wherein, represents the adjusted threshold parameter corresponding to the liquid level, temperature, and pressure, respectively; represents the preset threshold parameter corresponding to the liquid level, temperature, and pressure, respectively; represents the average parameter data corresponding to the liquid level, temperature, and pressure during vehicle operation, respectively; represents the maximum parameter data corresponding to the liquid level, temperature, and pressure during vehicle operation, respectively; represents the minimum value corresponding to the temperature detection data and pressure detection data during vehicle operation, respectively.

[0057] In a specific embodiment, the cloud platform includes a sensor data analysis module, a display module, a recording module, and a query module for real-time and historical data analysis, display, storage, and query. The processing device is connected to a human-machine interaction device to receive query instructions. The display module displays pressure, temperature, liquid level, time, and early warning danger information data.

[0058] In a specific embodiment, the sensor data analysis module specifically includes a data receiving module, a feature extraction module, a deep learning module, an early warning module, and a feedback module.

[0059] The data receiving module receives data collected by the data collection module, which can include temperature, pressure, and liquid level data at different altitudes and latitudes.

[0060] The feature extraction module pre-processes the collected data, extracts features related to vehicle safety threats, and associates the extracted features to obtain an association mathematical model.

[0061] The deep learning module uses a deep learning algorithm to train the association mathematical model, learns and identifies the associated features, and further obtains a mathematical model based on vehicle safety conditions and association conditions.

[0062] The early warning module intelligently judges the vehicle safety condition based on the output result of the mathematical model based on the vehicle safety condition and the association condition.

[0063] The feedback module is responsible for recording the vehicle safety events and warning results that have occurred, archiving the data and forming a knowledge base, which can be used for recording and querying by the recording module and the query module.

[0064] The feature extraction module extracts features related to vehicle threats, including temperature, pressure, liquid level and other features during vehicle operation at different altitudes, latitudes, etc. The feature extraction module associates the extracted features related to vehicle safety threats according to the standards of exceeding, equaling or being less than the preset threshold.

[0065] The feature extraction module sets the association condition as G, the extracted feature as m, and the identification value as L. Then, a mathematical model of feature association related to safety threats is established as follows:

[0066] ;

[0067] wherein, is the occurrence coefficient.

[0068] The association condition G outputs a string containing features related to vehicle safety threats and identification values according to the change of the occurrence coefficient in the association mathematical model, and transmits the string to the deep learning module.

[0069] The deep learning module trains the string output by the association condition G using a convolutional neural network or a recurrent neural network to obtain a vehicle safety condition Y, and further obtains a mathematical model based on the vehicle safety condition Y and the association condition G as follows:

[0070] ;

[0071] wherein, f represents the relationship between the association condition G and the vehicle safety condition Y, and T is a warning threshold for determining whether the vehicle safety condition reaches a warning level;

[0072] To further clarify the variables and parameters in the model, it can be expressed in the following form:

[0073] ;

[0074] wherein, is the weight coefficient of the corresponding association condition, is the code of the string output by the association condition G in different time periods.

[0075] When the Y value output by the deep learning module is positive, the vehicle has a safety threat, and the warning module is started. When the Y value output by the deep learning module is negative, the vehicle has no threat, and the warning module is not started.

[0076] The early warning module sends a vehicle danger signal when the value of the network security condition Y is positive, compares the value of Y with a preset early warning value, classifies the danger signal according to the comparison, classifies and disposes the danger signal according to the classification, and sends the result to the display module for display.

[0077] The collected data can be divided into static data and dynamic data, including: obtaining the data type of each data of the historical different dangerous chemical product transport vehicle in the running process, identifying the data attribute of each data of the historical vehicle in the running process according to the data type; according to the data attribute, judging whether each data of the historical vehicle in the running process is in a dynamic change state; if the data is not in a dynamic change state, the data is divided into static data; if the data is in a dynamic change state, the data is divided into dynamic data.

[0078] In a specific embodiment, the processor further comprises a parameter setting module for setting and modifying the related parameters of the set value range of the data for different vehicle-carrying media; the parameter setting module is connected to the judgment module, and the related parameters of the set value range are used for judgment.

[0079] In a specific embodiment, an analog-to-digital conversion module is further included, an AD9528 chip is used, the AD9528 chip is a channel high-speed driving chip, the analog signal collected by the data acquisition module is converted into a digital signal by the analog-to-digital conversion module through A / D sampling, and the digital signal is transmitted to the processor.

[0080] In a specific embodiment, a loudspeaker is further included, and the loudspeaker is connected to the processor; different frequencies of sound are used for alarm prompt; specifically including:

[0081] When the collected liquid level data exceeds the system set value, a first frequency of sound is used for alarm prompt;

[0082] When the collected temperature data exceeds the system set value, a second frequency of sound is used for alarm prompt;

[0083] When the collected pressure data exceeds the system set value, a third frequency of sound is used for alarm prompt;

[0084] When the collected liquid level, temperature and pressure data all exceed the system set value, a fourth frequency of sound is used for alarm prompt.

[0085] Specifically, the loudspeaker can also be set to different volumes at different danger levels, so as to distinguish different alarm information.

[0086] The various embodiments described in this specification are implemented in a progressive manner, each embodiment focusing on the differences from other embodiments, and the same or similar parts between embodiments can be mutually referred to. For the apparatus disclosed by the embodiments, since it corresponds to the method disclosed by the embodiments, the description is relatively simple, and the relevant parts can be referred to the description of the method part.

[0087] The above description of disclosed embodiments enables a person skilled in the art to implement or use the present application. Various modifications to the embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A hazardous chemical transportation vehicle security monitoring system, characterized in that, The system comprises a data acquisition module, a processor, an alarm module, a communication module and a cloud platform; the processor is connected to the data acquisition module and the alarm module, and the processor is connected to the cloud platform through the communication module; The data acquisition module acquires data of the vehicle and transmits the data to the processor; the data acquisition module comprises a temperature sensor, a pressure sensor and a liquid level sensor, and data is acquired through arrangement of the temperature sensor, the pressure sensor and the liquid level sensor on the vehicle; the data acquisition module further comprises an air pressure sensor, which acquires air pressure data and collects latitude and longitude information by using a geographic information system; The processor determines whether there is a danger in the current system by using threshold parameters corresponding to each data type in a preset system threshold; if there is a danger, the processor sends an alarm instruction to the alarm module; The alarm module receives the alarm instruction sent by the processor, generates alarm information and sends the alarm information to the cloud platform through the communication module; The cloud platform receives the alarm information and displays the alarm information and takes corresponding emergency measures; The processor further comprises a threshold adjustment model for adjusting the threshold parameters when it is determined that the current vehicle is running in a normal state, so as to obtain adjusted threshold parameters; Real-time monitoring is performed on whether the temperature, pressure and liquid level during the running of the vehicle exceed the adjusted threshold parameters; when any one of the temperature, pressure and liquid level exceeds the corresponding adjusted threshold parameter, the vehicle is controlled to stop running and sound an alarm; the threshold adjustment model is as follows: ； wherein, respectively represent the adjusted threshold parameters corresponding to the liquid level, temperature, and pressure; respectively represent the preset threshold parameters corresponding to the liquid level, temperature, and pressure; respectively represent the average parameter data corresponding to the liquid level, temperature, and pressure during the operation of the vehicle; respectively represent the maximum parameter data corresponding to the liquid level, temperature, and pressure during the operation of the vehicle; respectively represent the minimum values corresponding to the temperature detection data and the pressure detection data during the operation of the vehicle; The sensor data analysis module specifically comprises a data receiving module, a feature extraction module, a deep learning module, a pre-warning module and a feedback module; The data receiving module receives data collected by the data acquisition module; the data comprises temperature, pressure and liquid level data at different altitudes and latitudes; The feature extraction module pre-processes the collected data, extracts features related to vehicle safety threats and associates the extracted features to obtain an associated mathematical model; The deep learning module trains the associated mathematical model by using a deep learning algorithm, learns and identifies the associated features, and further obtains a mathematical model based on vehicle safety conditions and associated conditions; The pre-warning module intelligently judges the vehicle safety conditions according to an output result of the mathematical model based on the vehicle safety conditions and the associated conditions; The feedback module is responsible for recording vehicle safety events and pre-warning results, archiving data and forming a knowledge base, so as to record and query the data by using the recording module and the query module; The feature extraction module extracts features related to vehicle threats, including temperature, pressure and liquid level features of the vehicle during running at different altitudes and latitudes; the feature extraction module associates the extracted features related to vehicle safety threats according to a standard of exceeding a preset threshold, being equal to the preset threshold and being less than the preset threshold; The feature extraction module sets the associated condition as G, the extracted features as m and the identification value as L, and establishes a feature association mathematical model related to safety threats as follows: ； wherein is the occurrence coefficient; The associated condition G outputs a string containing the features related to vehicle safety threats and the identification value according to a change of an occurrence coefficient in the associated mathematical model, and transmits the string to the deep learning module. The deep learning module adopts a convolutional neural network or a recurrent neural network to train the string output by the correlation condition G to obtain a vehicle safety condition Y, and further obtain a mathematical model based on the vehicle safety condition Y and the correlation condition G: ； wherein, f represents the relationship between the correlation condition G and the vehicle safety condition Y, T is a warning threshold value for determining whether the vehicle safety condition reaches a warning level; In order to clearly define the variables and parameters in the model, it is expressed in the following form: ； wherein, is a weight coefficient of the respective correlation condition, is a code of the correlation condition G output string in different time periods; When the Y value output by the deep learning module is positive, the vehicle is in a safety threat, and the warning module is started. When the Y value output by the deep learning module is negative, the vehicle is not in a threat, and the warning module is not started. When the network security condition Y value is positive, the warning module sends a vehicle danger signal, compares the Y value with the preset warning value, classifies the danger signal according to the comparison, classifies and disposes according to the level, and sends the result to the display module for display.

2. The dangerous chemical transportation vehicle security monitoring system according to claim 1, wherein, The processor further comprises: A data receiving module receives data collected by the data collection module; A comparison and evaluation module compares the data collected by the data collection module with the corresponding preset system threshold value, and when any one of the data parameters in the data collected by the data collection module exceeds the corresponding preset system threshold value, evaluates the dangerous goods transport vehicle using a comprehensive evaluation model to obtain an evaluation score; A judgment module compares the evaluation score with a preset evaluation score threshold value, and when the evaluation score is lower than the preset evaluation score threshold value, determines that the current dangerous goods transport vehicle is in danger.

3. The dangerous chemical transportation vehicle security monitoring system according to claim 1, wherein, The alarm module is connected with a first-level alarm module and a second-level alarm module. When one of the collected data exceeds the system set value, the first-level alarm module is preset to send a matching corresponding first-level sound and light electric identification instruction to the alarm device. When all of the collected data exceed the system set value, the second-level alarm module is configured to send a matching corresponding second-level sound and light electric identification instruction to the alarm device, at which time the alarm module sends a danger signal. At the same time, the cloud platform receives the information sent by the first-level and second-level alarm modules and displays and alarms.

4. The dangerous chemical transportation vehicle security monitoring system according to claim 2, wherein, The comprehensive evaluation model is as follows: ； Wherein, M represents the evaluation score; n represents the number of parameter types including temperature, pressure, liquid level; represents the preset threshold parameter corresponding to the i-th parameter type; represents the detection value corresponding to the i-th parameter type when the value of any one of the data parameters of temperature, pressure, and liquid level exceeds the corresponding preset threshold parameter.

5. The hazardous chemical transportation vehicle security monitoring system of claim 1, wherein, The cloud platform comprises a sensor data analysis module, a display module, a recording module, and a query module, which are respectively used for real-time and historical data analysis, display, storage, and query. The processing device is connected to a human-computer interaction device to receive query instructions. The display module displays pressure, temperature, liquid level, time, and warning danger information data.

6. The hazardous chemical transportation vehicle security monitoring system of claim 1, wherein, The processor further comprises a parameter setting module for setting and modifying the related parameters of the data set value range according to different vehicle carrying media. The parameter setting module is connected to the judgment module, and the related parameters of the data set value range are used for judgment.

7. The hazardous chemical transportation vehicle security monitoring system of claim 1, wherein, It also includes a loudspeaker connected to the processor; different frequencies of sound are used for alarm prompt; specifically including: When the collected liquid level data exceeds the system set value, a first frequency of sound is used for alarm prompt; When the collected temperature data exceeds the system set value, a second frequency of sound is used for alarm prompt; When the collected pressure data exceeds the system set value, a third frequency of sound is used for alarm prompt; When the collected liquid level, temperature, and pressure data all exceed the system set value, a fourth frequency of sound is used for alarm prompt.

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