CN112097825A - Environment monitoring method and environment monitoring system - Google Patents
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Abstract
The application discloses an environment monitoring method and an environment monitoring system, which are used in an intelligent safe production environment. Wherein, the method comprises the following steps: acquiring monitoring data corresponding to a monitoring environment, wherein the monitoring data comprises a plurality of monitoring parameters and a monitoring parameter value corresponding to each monitoring parameter; aiming at each monitoring data, acquiring an alarm threshold value and a weight coefficient corresponding to the monitoring parameter according to the monitoring environment and the monitoring parameter; comparing the monitoring parameter value corresponding to each monitoring parameter with an alarm threshold value to obtain a risk factor of each monitoring parameter; determining a total risk factor of the monitored environment according to the risk factor and the weight coefficient of each monitoring parameter; according to the total risk factor, whether the monitored environment is normal or not is determined, and the method can accurately determine the total risk factor of the monitored environment, so that whether the monitored environment is normal or not can be accurately judged, and the situations of false alarm and missing report caused by the self problem of a single-parameter detector are avoided.
Description
Technical Field
The present disclosure relates to the field of monitoring technologies, and in particular, to an environment monitoring method and an environment monitoring system.
Background
In the related art, the main hazard parameters change in a period of time before a dangerous accident occurs, and at the same time or later, concurrent parameters change, so that serious consequences can be caused after the hazard indexes are accumulated to a certain value, or an accident occurs under other inducing conditions, and therefore, how to better monitor the hazard parameters to avoid the accident becomes an urgent problem to be solved.
Disclosure of Invention
The present application aims to solve at least one of the technical problems in the related art to some extent.
To this end, a first object of the present application is to propose an environmental monitoring method. The method can accurately determine the total risk factor of the monitored environment, thereby accurately judging whether the monitored environment is normal or not and avoiding the situations of false alarm and missing report caused by the self problem of a single-parameter detector.
A second object of the present application is to provide an environmental monitoring system.
In order to achieve the above object, an embodiment of a first aspect of the present application provides an environmental monitoring method, where the method includes: acquiring monitoring data corresponding to a monitoring environment, wherein the monitoring data comprises a plurality of monitoring parameters and a monitoring parameter value corresponding to each monitoring parameter; aiming at each monitoring data, acquiring an alarm threshold value and a weight coefficient corresponding to the monitoring parameter according to the monitoring environment and the monitoring parameter; comparing the monitoring parameter value corresponding to each monitoring parameter with an alarm threshold value to obtain a risk factor of each monitoring parameter; determining a total risk factor of the monitored environment according to the risk factor and the weight coefficient of each monitoring parameter; and determining whether the monitored environment is normal or not according to the total risk factor.
According to the environment monitoring method, monitoring data corresponding to a monitoring environment can be obtained, wherein the monitoring data comprise a plurality of monitoring parameters and monitoring parameter values corresponding to each monitoring parameter, then, aiming at each monitoring data, according to the monitoring environment and the monitoring parameters, an alarm threshold value and a weight coefficient corresponding to the monitoring parameters are obtained, the monitoring parameter values corresponding to each monitoring parameter and the alarm threshold value are subjected to ratio to obtain the risk factor of each monitoring parameter, then, according to the risk factor and the weight coefficient of each monitoring parameter, the total risk factor of the monitoring environment is determined, and whether the monitoring environment is normal or not is determined according to the total risk factor. The method monitors the monitoring parameters in the environment through a plurality of monitoring detectors to further obtain the risk factor of each monitoring parameter, and can accurately determine the total risk factor of the monitoring environment according to the risk factors of the plurality of monitoring factors, so that whether the monitoring environment is normal can be accurately judged, and the situations of false alarm and missing alarm caused by the self problem of a single parameter detector are avoided.
According to an embodiment of the application, said determining whether said monitored environment is normal based on said total risk factor comprises: acquiring a preset risk factor threshold corresponding to the monitoring environment; judging whether the total risk factor is smaller than the preset risk factor threshold value or not; if the total risk factor is smaller than the preset risk factor threshold value, determining that the monitoring environment is normal; and if the total risk factor is not less than the preset risk factor threshold value, determining that the monitoring environment is abnormal.
According to an embodiment of the application, after the determining the monitoring environment anomaly, the method further comprises: and controlling to cut off the electrical connection between the preset equipment in the monitoring environment and an external circuit.
According to an embodiment of the present application, before the comparing the monitoring parameter value corresponding to each of the monitoring parameters with the alarm threshold to obtain the risk factor of each of the monitoring parameters, the method further includes: normalizing the monitoring parameter value corresponding to each monitoring parameter to obtain a normalized monitoring parameter value of each monitoring parameter; the comparing the monitoring parameter value corresponding to each monitoring parameter with the alarm threshold value to obtain the risk factor of each monitoring parameter includes: and carrying out ratio on the normalized monitoring parameter value corresponding to each monitoring parameter and an alarm threshold value to obtain the risk factor of each monitoring parameter.
According to an embodiment of the application, the monitoring parameter value is a parameter variation value of the monitoring parameter in a current sampling period.
In order to achieve the above object, an embodiment of the second aspect of the present application provides an environmental monitoring system, including: the system comprises a plurality of monitoring detectors and at least one processor, wherein each monitoring detector is connected with the processor and is used for monitoring corresponding monitoring parameters in the environment to obtain monitoring parameter values corresponding to the corresponding monitoring parameters, the processor is used for acquiring monitoring data corresponding to the monitoring environment, and the monitoring data comprises a plurality of monitoring parameters and the monitoring parameter values corresponding to each monitoring parameter; aiming at each monitoring data, acquiring an alarm threshold value and a weight coefficient corresponding to the monitoring parameter according to the monitoring environment and the monitoring parameter; comparing the monitoring parameter value corresponding to each monitoring parameter with an alarm threshold value to obtain a risk factor of each monitoring parameter; determining a total risk factor of the monitored environment according to the risk factor and the weight coefficient of each monitoring parameter; and determining whether the monitored environment is normal or not according to the total risk factor.
According to the environment monitoring system of the embodiment of the application, monitoring data corresponding to a monitoring environment can be obtained, wherein the monitoring data comprise a plurality of monitoring parameters and monitoring parameter values corresponding to each monitoring parameter, then, aiming at each monitoring data, according to the monitoring environment and the monitoring parameters, alarm threshold values and weight coefficients corresponding to the monitoring parameters are obtained, the monitoring parameter values and the alarm threshold values corresponding to each monitoring parameter are subjected to ratio to obtain the risk factors of each monitoring parameter, then, according to the risk factors and the weight coefficients of each monitoring parameter, the total risk factors of the monitoring environment are determined, and whether the monitoring environment is normal or not is determined according to the total risk factors. The system monitors the monitoring parameters in the environment through the plurality of monitoring detectors, so that the risk factor of each monitoring parameter is obtained, and the total risk factor of the monitored environment can be accurately determined according to the risk factors of the plurality of monitoring factors, so that whether the monitored environment is normal or not can be accurately judged, and the condition that false alarm and missed alarm are caused by the self problem of the single parameter detector is avoided.
According to an embodiment of the application, the processor is specifically configured to: acquiring a preset risk factor threshold corresponding to the monitoring environment; judging whether the total risk factor is smaller than the preset risk factor threshold value or not; if the total risk factor is smaller than the preset risk factor threshold value, determining that the monitoring environment is normal; and if the total risk factor is not less than the preset risk factor threshold value, determining that the monitoring environment is abnormal.
According to an embodiment of the application, the processor is further configured to control to disconnect an electrical connection between a preset device in the monitoring environment and an external circuit after the monitoring environment is determined to be abnormal.
According to one embodiment of the application, the number of the processors is two, the two processors are electrically connected, and the system further comprises a communication module connected with the processors, and the communication module is used for carrying out data communication with an external central station.
According to an embodiment of the application, the system further comprises: the explosion-proof battery is connected with the processor and used for providing a power supply for the processor.
Additional aspects and advantages of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the present application.
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The above and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a flow diagram of an environmental monitoring method according to one embodiment of the present application.
FIG. 2 is a flow chart of an environmental monitoring method according to an embodiment of the present application.
FIG. 3 is a schematic diagram of an environment monitoring system according to one embodiment of the present application.
FIG. 4 is a schematic diagram of an environment monitoring system according to another embodiment of the present application.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.
In the related technology, a method for measuring and judging parameter gradient is combined with a description theory of measuring the dangerous condition of an operation site by a multi-parameter vector model method, in a period before a dangerous accident occurs, main harmful parameters change, and simultaneously or later concurrent parameters change, so that serious consequences can be generated after a harmful index is accumulated to a certain value, or an accident can be generated under other inducing conditions. Therefore, the application provides an environment monitoring method.
The environment monitoring method of the embodiment of the application obtains monitoring data corresponding to a monitoring environment in the environment monitoring process, wherein the monitoring data comprise a plurality of monitoring parameters and monitoring parameter values corresponding to each monitoring parameter, then obtains an alarm threshold value and a weight coefficient corresponding to each monitoring parameter according to the monitoring environment and the monitoring parameters aiming at each monitoring data, and carries out a ratio on the monitoring parameter value and the alarm threshold value corresponding to each monitoring parameter so as to obtain a risk factor of each monitoring parameter, then determines a total risk factor of the monitoring environment according to the risk factor and the weight coefficient of each monitoring parameter, and determines whether the monitoring environment is normal or not according to the total risk factor. The system monitors the monitoring parameters in the environment through the plurality of monitoring detectors, so that the risk factor of each monitoring parameter is obtained, and the total risk factor of the monitored environment can be accurately determined according to the risk factors of the plurality of monitoring factors, so that whether the monitored environment is normal or not can be accurately judged, and the condition that false alarm and missed alarm are caused by the self problem of the single parameter detector is avoided.
An environment monitoring method and an environment monitoring system according to an embodiment of the present application are described below with reference to the drawings. The environment monitoring method and the environment monitoring system can be applied to an intelligent safe production environment.
FIG. 1 is a flow diagram of an environmental monitoring method according to one embodiment of the present application. It should be noted that the environment monitoring method according to the embodiment of the present application may be applied to the environment monitoring system according to the embodiment of the present application, where the environment monitoring system includes a plurality of monitoring probes and at least one processor, and the environment monitoring method according to the embodiment of the present application may be described from the processor side.
As shown in fig. 1, the environment monitoring method includes:
and S110, acquiring monitoring data corresponding to the monitoring environment.
The monitoring data comprises a plurality of monitoring parameters and a monitoring parameter value corresponding to each monitoring parameter.
The monitoring environment includes, but is not limited to, a factory environment, a mine environment, a petrochemical environment, a construction site environment, a subway tunnel environment, and the like.
In the embodiment of the application, the environment can be monitored through the plurality of monitoring detectors to obtain the plurality of monitoring parameters and the monitoring parameter value corresponding to each monitoring parameter, and the obtained plurality of monitoring parameters and the monitoring parameter values corresponding to the plurality of monitoring parameters are sent to the processor, so that the processor can obtain the plurality of monitoring parameters corresponding to the monitoring environment and the monitoring parameter values corresponding to the plurality of monitoring parameters.
The monitoring parameters include but are not limited to environmental parameters, index characteristic parameters, accumulative parameters and the like, wherein the environmental parameters include but are not limited to parameters such as temperature, humidity and wind speed direction, the index characteristic parameters include but are not limited to parameters such as vibration, noise, polluted gas, explosive gas and dust, and the accumulative parameters include but are not limited to parameters such as air volume, water volume and individual flow.
For example, the environment monitor may monitor the corresponding detection parameters in the environment a, obtain the temperature parameter, the humidity parameter, the wind speed direction parameter, and the parameter value corresponding to the temperature parameter, the parameter value corresponding to the humidity parameter, and the parameter value corresponding to the wind speed direction parameter, and send the obtained values to the processor, so that the processor may obtain the temperature parameter, the humidity parameter, the wind speed direction parameter, and the parameter value corresponding to the temperature parameter, the parameter value corresponding to the humidity parameter, and the parameter value corresponding to the wind speed direction parameter.
And S120, aiming at each monitoring data, acquiring an alarm threshold value and a weight coefficient corresponding to the monitoring parameter according to the monitoring environment and the monitoring parameter.
It should be understood that, in different monitoring environments, the alarm threshold and the weighting factor corresponding to the same monitoring parameter are usually different.
Specifically, after acquiring the monitoring data, the corresponding relationship between the monitoring parameter corresponding to the environmental parameter and the alarm threshold and the weight coefficient may be acquired based on the monitoring environment, and then the alarm threshold and the weight coefficient corresponding to the monitoring parameter in the monitoring environment may be acquired based on the corresponding relationship.
For example, a temperature parameter corresponding to the monitored environment a is obtained, and based on the correspondence between the temperature parameter and the alarm threshold value and the weight coefficient, a temperature alarm threshold value corresponding to the temperature is obtained as 40, and a weight coefficient of the temperature is obtained as 1; and acquiring a temperature parameter corresponding to the monitoring environment B, and acquiring a temperature alarm threshold value of 30 and a weight coefficient of 0.5 corresponding to the temperature based on the corresponding relationship among the temperature parameter, the alarm threshold value and the weight coefficient.
S130, carrying out ratio on the monitoring parameter value corresponding to each monitoring parameter and the alarm threshold value to obtain the risk factor of each monitoring parameter.
That is, the monitoring parameter value and the alarm threshold corresponding to each monitoring parameter are obtained, the ratio of the monitoring parameter value and the alarm threshold corresponding to the monitoring parameter can be obtained, and the ratio result is used as the risk factor of the monitoring parameter.
It should be noted that the larger the ratio of the monitoring parameter value to the alarm threshold value is, the higher the risk factor is, and the smaller the ratio of the monitoring parameter value to the alarm threshold value is, the lower the risk factor is.
In an embodiment of the application, a monitoring parameter value and an alarm threshold value corresponding to each monitoring parameter are obtained, a ratio of the monitoring parameter value and the alarm threshold value corresponding to each monitoring parameter is performed, and a risk factor of the monitoring parameter can be determined based on a corresponding relationship between the ratio of the monitoring parameter value and the alarm threshold value and the risk factor.
And S140, determining the total risk factor of the monitored environment according to the risk factor and the weight coefficient of each monitored parameter.
In the embodiment of the present application, after the risk factor of each monitoring parameter is obtained, the risk factor of each monitoring parameter and the weight coefficient of the monitoring parameter may be added to obtain the total risk factor of the monitored environment.
That is, after obtaining the risk factor of each monitoring parameter, the risk factor of each monitoring parameter may be weighted to obtain the risk factor of each monitoring parameter in the monitoring environment, wherein the risk factor of each monitoring parameter may be multiplied by the weighting factor, the obtained result may be used as the risk factor of each monitoring parameter in the monitoring environment, and then the risk factors of each monitoring parameter in the monitoring environment are added to determine the total risk factor of the monitoring environment.
For example, the total risk factor D is k1 · D1+ k2 · D2+ k3 · D3+ kn · Dn, where D1 is the risk factor of the first monitored parameter, D2 is the risk factor of the second monitored parameter, D3 is the risk factor of the third monitored parameter, Dn is the risk factor of the nth monitored parameter, k1 is the weight coefficient of the first monitored parameter, k2 is the weight coefficient of the second monitored parameter, k2 is the weight coefficient of the third monitored parameter, and kn is the weight coefficient of the nth monitored parameter.
And S150, determining whether the monitored environment is normal or not according to the total risk factor.
Specifically, after determining the total risk factor of the monitored environment, the total risk factor may be compared with a preset risk factor threshold, and if greater than the preset risk factor threshold, the monitored environment may be determined to be abnormal, and if less than the preset risk factor threshold, the monitored environment may be determined to be normal.
According to the environment monitoring method, monitoring data corresponding to a monitoring environment can be obtained, wherein the monitoring data comprise a plurality of monitoring parameters and monitoring parameter values corresponding to each monitoring parameter, then, aiming at each monitoring data, according to the monitoring environment and the monitoring parameters, an alarm threshold value and a weight coefficient corresponding to the monitoring parameters are obtained, the monitoring parameter values corresponding to each monitoring parameter and the alarm threshold value are subjected to ratio to obtain the risk factor of each monitoring parameter, then, according to the risk factor and the weight coefficient of each monitoring parameter, the total risk factor of the monitoring environment is determined, and whether the monitoring environment is normal or not is determined according to the total risk factor. The method monitors the monitoring parameters in the environment through a plurality of monitoring detectors to further obtain the risk factor of each monitoring parameter, and can accurately determine the total risk factor of the monitoring environment according to the risk factors of the plurality of monitoring factors, so that whether the monitoring environment is normal can be accurately judged, and the situations of false alarm and missing alarm caused by the self problem of a single parameter detector are avoided.
FIG. 2 is a flow chart of an environmental monitoring method according to an embodiment of the present application. Specifically, as shown in fig. 2, the environment monitoring method may include:
s210, acquiring monitoring data corresponding to a monitoring environment, wherein the monitoring data comprises a plurality of monitoring parameters and a monitoring parameter value corresponding to each monitoring parameter.
In the embodiment of the application, the environment can be monitored through the plurality of monitoring detectors to obtain the plurality of monitoring parameters and the monitoring parameter value corresponding to each monitoring parameter, and the obtained plurality of monitoring parameters and the monitoring parameter values corresponding to the plurality of monitoring parameters are sent to the processor, so that the processor can obtain the plurality of monitoring parameters corresponding to the monitoring environment and the monitoring parameter values corresponding to the plurality of monitoring parameters.
And the monitoring parameter value is a parameter change value of the monitoring parameter in the current sampling period.
For example, the detector a is in an environment where a monitoring target is constructed, where the response sensitivity of the detector a to the field strength C of the number of the detection targets is α, and the function of the detection signal S of the detector in the response time period is: s ═ α · C.
When a digital field is applied to the detector, the data of the detector is increased by one parameter, and the rising trend of the signal in the time tau is greatly different under different field strengths, so that the signal can be fully utilized, and the formula S-alpha-C can be developed into the formula S-alpha-C
For the formula
Due to the linear relation of S to time,
wherein tau and alpha are constants,
the gradient k of a response straight line of the detector at the point P can be regarded as k, k is tan theta, the k value directly reflects the magnitude field intensity, the larger k is, the higher the rising trend of the risk index is, and the higher the potential risk is.
And S220, acquiring an alarm threshold value and a weight coefficient corresponding to the monitoring parameters according to the monitoring environment and the monitoring parameters aiming at each monitoring data.
For example, the dust parameter corresponding to the monitored environment a is obtained, and based on the correspondence between the dust parameter and the alarm threshold value and the weight coefficient, the dust alarm threshold value corresponding to the dust is 35, and the weight coefficient of the dust is 3.
And S230, comparing the monitoring parameter value corresponding to each monitoring parameter with the alarm threshold value to obtain the risk factor of each monitoring parameter.
In an embodiment of the application, before a ratio between a monitoring parameter value corresponding to each monitoring parameter and an alarm threshold is performed to obtain a risk factor of each monitoring parameter, normalization processing may be performed on the monitoring parameter value corresponding to each monitoring parameter to obtain a normalized monitoring parameter value of each monitoring parameter.
That is, after the normalization processing is performed on the monitoring parameter value corresponding to each monitoring parameter, the ratio of the normalized monitoring parameter value corresponding to each monitoring parameter to the alarm threshold value can be performed to obtain the risk factor of each monitoring parameter.
And S240, determining the total risk factor of the monitored environment according to the risk factor and the weight coefficient of each monitored parameter.
In the embodiment of the application, the risk factor of each monitoring parameter is obtained, the risk factor of each monitoring parameter in the current monitoring environment can be obtained after weighting the risk factor of each monitoring parameter, wherein the risk factor of each monitoring parameter can be multiplied by the weighting coefficient, the obtained result is used as the risk factor of each monitoring parameter in the current monitoring environment, and then the risk factors of each monitoring parameter in the current monitoring environment are added to determine the total risk factor of the current monitoring environment.
And S250, acquiring a preset risk factor threshold corresponding to the monitored environment.
Wherein the preset risk factor threshold may be pre-stored in the processor.
When determining the total risk factor of the monitored environment, a preset risk factor threshold corresponding to the monitored environment may be obtained.
And S260, judging whether the total risk factor is smaller than a preset risk factor threshold value.
That is, determining the total risk factor of the monitored environment and obtaining a preset risk factor threshold corresponding to the monitored environment, it may be determined whether the total risk factor of the monitored environment is less than the preset risk factor threshold.
And S270, if the total risk factor is smaller than a preset risk factor threshold value, determining that the monitoring environment is normal.
In an embodiment of the application, when it is determined that the monitoring environment is normal, based on the connection between the processor and the communication module in the environment monitoring system, the processor may send the monitoring data in the monitoring environment to the communication module, so that the communication module performs data communication between the monitoring data and an external central station, and further, monitoring parameters in the monitoring environment can be grasped in real time.
And S280, if the total risk factor is not less than the preset risk factor threshold value, determining that the monitoring environment is abnormal.
In one embodiment of the application, when the currently monitored environment is determined to be abnormal, an alarm signal can be sent out through the alarm device to prompt that the currently monitored environment is easy to cause danger or accidents.
The alarm device can be connected with the processor, and the processor can send the abnormal signal to the alarm device when judging that the monitoring environment is abnormal, so that the alarm device generates the alarm signal, wherein the alarm signal can be sent out in the modes of voice, indicator lights and the like.
In one embodiment of the application, after the monitoring environment is determined to be abnormal, the electrical connection between the preset equipment in the monitoring environment and the external circuit is controlled to be cut off, so that the loss of the external equipment caused by the abnormality of the current monitoring environment is avoided.
In an embodiment of the present application, the specific implementation manner of performing normalization processing on the monitoring parameter value corresponding to each monitoring parameter to obtain the normalized monitoring parameter value of each monitoring parameter is as follows:
the maximum value Vmax and the minimum value Vmin of each parameter are allowed under a normal operation state, the corresponding difference Vq is Vmax-Vmin, the method is suitable for parameter standardization conversion, the quantized parameters are defined as a quantization interval Qi (quantization interval), the quantization of the quantization interval Qi can be large or small according to the resolution and precision of a monitoring detector and the requirements of a system or equipment, the precision and the accuracy rate are higher when the number is larger, and meanwhile, the requirement on the monitoring detector is higher.
For the instant number Vn of any one of the m monitoring parameters during operation, the quantization value Qn algorithm in the corresponding quantization interval is calculated as follows: qn ═ Qi ═ (Vn-Vmin)/(Vmax-Vmin);
after the quantization algorithm is adopted, the m kinds of monitoring parameter quantization values are all limited in the interval of 0-Qi.
In one embodiment of the application, when monitoring parameters are described by using images, change curves of the parameters can be accurately described according to time under the same coordinate, if a system or equipment normally operates, trends of the curves form a very regular graph, the graph is a normal condition of a monitoring environment, the graph can form different forms according to different loads, but the graphs are standard and ordered, and a key effect is played on safe production.
According to the environment monitoring method, normalization processing is carried out on the monitoring parameter value corresponding to each monitoring parameter, so that the ratio of the normalized monitoring parameter value corresponding to each monitoring parameter to the alarm threshold value is carried out, the risk factor of each monitoring parameter is obtained, then the total risk factor of the monitored environment is determined according to the risk factor and the weight coefficient of each monitoring parameter, and whether the monitored environment is normal or not is determined according to the total risk factor. The method monitors the monitoring parameters in the environment through a plurality of monitoring detectors to further obtain the risk factor of each monitoring parameter, and can accurately determine the total risk factor of the monitoring environment according to the risk factors of the plurality of monitoring factors, so that whether the monitoring environment is normal can be accurately judged, and the situations of false alarm and missing alarm caused by the self problem of a single parameter detector are avoided.
In order to realize the embodiment, the application further provides an environment monitoring system.
FIG. 3 is a schematic diagram of an environment monitoring system according to one embodiment of the present application. As shown in fig. 3, the environmental monitoring system 300 includes:
the monitoring system comprises a plurality of monitoring detectors 310 and at least one processor 320, wherein each monitoring detector 310 is connected with the processor 320, the monitoring detectors 310 are used for monitoring corresponding monitoring parameters in the environment to obtain monitoring parameter values corresponding to the corresponding monitoring parameters, the processor 320 is used for acquiring monitoring data corresponding to the monitored environment, and the monitoring data comprises a plurality of monitoring parameters and monitoring parameter values corresponding to each monitoring parameter; aiming at each monitoring data, acquiring an alarm threshold value and a weight coefficient corresponding to the monitoring parameter according to the monitoring environment and the monitoring parameter; comparing the monitoring parameter value corresponding to each monitoring parameter with an alarm threshold value to obtain a risk factor of each monitoring parameter; determining a total risk factor of the monitored environment according to the risk factor and the weight coefficient of each monitoring parameter; and determining whether the monitored environment is normal or not according to the total risk factor.
According to the environment monitoring system of the embodiment of the application, monitoring data corresponding to a monitoring environment can be obtained, wherein the monitoring data comprise a plurality of monitoring parameters and monitoring parameter values corresponding to each monitoring parameter, then, aiming at each monitoring data, according to the monitoring environment and the monitoring parameters, alarm threshold values and weight coefficients corresponding to the monitoring parameters are obtained, the monitoring parameter values and the alarm threshold values corresponding to each monitoring parameter are subjected to ratio to obtain the risk factors of each monitoring parameter, then, according to the risk factors and the weight coefficients of each monitoring parameter, the total risk factors of the monitoring environment are determined, and whether the monitoring environment is normal or not is determined according to the total risk factors. The system monitors the monitoring parameters in the environment through the plurality of monitoring detectors, so that the risk factor of each monitoring parameter is obtained, and the total risk factor of the monitored environment can be accurately determined according to the risk factors of the plurality of monitoring factors, so that whether the monitored environment is normal or not can be accurately judged, and the condition that false alarm and missed alarm are caused by the self problem of the single parameter detector is avoided.
In an embodiment of the present application, the processor 320 is specifically configured to: acquiring a preset risk factor threshold corresponding to the monitoring environment; judging whether the total risk factor is smaller than the preset risk factor threshold value or not; if the total risk factor is smaller than the preset risk factor threshold value, determining that the monitoring environment is normal; and if the total risk factor is not less than the preset risk factor threshold value, determining that the monitoring environment is abnormal. As an example, the processor 320 is further configured to control to disconnect an electrical connection between a preset device in the monitoring environment and an external circuit after the determination that the monitoring environment is abnormal.
In one embodiment of the present application, the number of the processors 320 is two, two of the processors 320 are electrically connected, and the system further includes a communication module connected to the processors, and the communication module is configured to perform data communication with an external central station.
In one embodiment of the present application, as shown in fig. 4, the system 300 further comprises: an explosion-proof battery 330, the explosion-proof battery 330 being connected with the processor for providing power supply for the processor 320.
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and the scope of the preferred embodiments of the present application includes other implementations in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present application.
The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present application may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc. Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application, and that variations, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present application.
Claims (10)
1. An environmental monitoring method, the method comprising:
acquiring monitoring data corresponding to a monitoring environment, wherein the monitoring data comprises a plurality of monitoring parameters and a monitoring parameter value corresponding to each monitoring parameter;
aiming at each monitoring data, acquiring an alarm threshold value and a weight coefficient corresponding to the monitoring parameter according to the monitoring environment and the monitoring parameter;
comparing the monitoring parameter value corresponding to each monitoring parameter with an alarm threshold value to obtain a risk factor of each monitoring parameter;
determining a total risk factor of the monitored environment according to the risk factor and the weight coefficient of each monitoring parameter;
and determining whether the monitored environment is normal or not according to the total risk factor.
2. The environmental monitoring method of claim 1, wherein said determining whether the monitored environment is normal based on the overall risk factor comprises:
acquiring a preset risk factor threshold corresponding to the monitoring environment;
judging whether the total risk factor is smaller than the preset risk factor threshold value or not;
if the total risk factor is smaller than the preset risk factor threshold value, determining that the monitoring environment is normal;
and if the total risk factor is not less than the preset risk factor threshold value, determining that the monitoring environment is abnormal.
3. The environmental monitoring method of claim 2, wherein after said determining said monitored environmental anomaly, said method further comprises:
and controlling to cut off the electrical connection between the preset equipment in the monitoring environment and an external circuit.
4. The environmental monitoring method of claim 2, wherein before said comparing the value of the monitoring parameter corresponding to each of the monitoring parameters with the alarm threshold to obtain the risk factor of each of the monitoring parameters, the method further comprises:
normalizing the monitoring parameter value corresponding to each monitoring parameter to obtain a normalized monitoring parameter value of each monitoring parameter;
the comparing the monitoring parameter value corresponding to each monitoring parameter with the alarm threshold value to obtain the risk factor of each monitoring parameter includes: and carrying out ratio on the normalized monitoring parameter value corresponding to each monitoring parameter and an alarm threshold value to obtain the risk factor of each monitoring parameter.
5. The environmental monitoring method according to any one of claims 1 to 4, wherein the monitoring parameter value is a parameter variation value of the monitoring parameter in a current sampling period.
6. An environmental monitoring system, the system comprising: the system comprises a plurality of monitoring detectors and at least one processor, wherein each monitoring detector is connected with the processor and is used for monitoring corresponding monitoring parameters in the environment to obtain monitoring parameter values corresponding to the corresponding monitoring parameters, the processor is used for acquiring monitoring data corresponding to the monitoring environment, and the monitoring data comprises a plurality of monitoring parameters and the monitoring parameter values corresponding to each monitoring parameter; aiming at each monitoring data, acquiring an alarm threshold value and a weight coefficient corresponding to the monitoring parameter according to the monitoring environment and the monitoring parameter; comparing the monitoring parameter value corresponding to each monitoring parameter with an alarm threshold value to obtain a risk factor of each monitoring parameter; determining a total risk factor of the monitored environment according to the risk factor and the weight coefficient of each monitoring parameter; and determining whether the monitored environment is normal or not according to the total risk factor.
7. The environmental monitoring system of claim 6, wherein the processor is specifically configured to: acquiring a preset risk factor threshold corresponding to the monitoring environment; judging whether the total risk factor is smaller than the preset risk factor threshold value or not; if the total risk factor is smaller than the preset risk factor threshold value, determining that the monitoring environment is normal; and if the total risk factor is not less than the preset risk factor threshold value, determining that the monitoring environment is abnormal.
8. The environmental monitoring system of claim 7, wherein the processor is further configured to control disconnection of electrical connections between predetermined devices in the monitored environment and external circuits after the determination of the abnormality in the monitored environment.
9. The environmental monitoring system of claim 7, wherein the number of processors is two, two of the processors being electrically connected to each other, the system further comprising a communication module connected to the processors for data communication with an external central station.
10. The environmental monitoring system of any one of claims 6-9, wherein the system further comprises: the explosion-proof battery is connected with the processor and used for providing a power supply for the processor.
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