A mine operation environment-based risk analysis method and computer device

Abstract

The application discloses a kind of based on the risk analysis method and computer equipment of mine operation environment, belong to industrial data processing technical field, comprising the following steps: S1: obtain the multi-source data set when mine operation car works;S2: respectively to the data in the multi-source data set Threshold comparison is carried out, when at least one data in multi-source data set is greater than or equal to preset threshold value, alarm signal is formed, and multi-source data set is uploaded to cloud platform;S3: cloud platform carries out analysis to multi-source data set and outputs risk coefficient.The risk analysis method based on the mine operation environment solves the problem that accurate prediction cannot be made according to monitoring data in the prior art.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of industrial data processing, and particularly relates to a risk analysis method based on a mine operation environment. BACKGROUND

[0002] The safety monitoring of the mine operation environment faces complex and changeable environmental conditions and potential dangerous factors. The traditional monitoring method often has the problems of reaction lag and untimely early warning, and it is difficult to effectively respond to sudden on-site safety accidents. Specifically, the monitoring system needs to pay attention to multiple key indicators at the same time, but the correlation and potential risk patterns between these key indicators are not obvious. Therefore, it is currently difficult to make accurate predictions based on monitoring data, so as to select appropriate emergency plans to deal with potential risks. SUMMARY

[0003] In order to overcome the defects existing in the prior art, the present application provides a risk analysis method based on a mine operation environment to solve the above problems.

[0004] The technical scheme adopted by the present application to solve its technical problems is: a risk analysis method based on a mine operation environment, comprising the following steps:

[0005] S1: acquiring a multi-source data set of a mine operation vehicle during work;

[0006] S2: performing threshold comparison on the data in the multi-source data set respectively, forming an alarm signal when at least one data in the multi-source data set is greater than or equal to a preset threshold value, and uploading the multi-source data set to a cloud platform;

[0007] S3: the cloud platform analyzes the multi-source data set and outputs a risk coefficient.

[0008] It is worth noting that in the step S2, a first early warning threshold value and a second early warning threshold value are respectively set for each data in the multi-source data set, a first alarm signal is formed when the data of the multi-source data set is between the corresponding first early warning threshold value and the second early warning threshold value, and a second alarm signal is formed and the system power of the mine operation vehicle is cut off when the data of the multi-source data set is greater than or equal to the corresponding second early warning threshold value.

[0009] Specifically, the multi-source data set includes a working voltage of an explosion-proof display screen arranged on the mine operation vehicle; the working voltage is output to a comparator circuit through a spark elimination circuit to realize threshold comparison.

[0010] Specifically, the spark elimination circuit comprises a resistor R1, a resistor R2, a capacitor C1 and an inductor L2, the resistor R1 and the capacitor C1 are connected in series and then connected in parallel between the positive and negative poles of a power supply U3, and the resistor R2 and the inductor L2 are connected in series and then connected in parallel between the positive and negative poles of the power supply U3; the voltage between the positive and negative poles of the power supply U3 is the working voltage of the explosion-proof display screen.

[0011] The comparator circuit comprises a comparator U1, a comparator U2, a resistor R3, a resistor R4, a resistor R5 and a resistor R6; the negative feedback input end -IN1 of the comparator U1 and the negative feedback input end -IN2 of the comparator U2 are electrically connected to the positive pole of the power supply U3; the first end of the resistor R3 is electrically connected to a reference voltage power supply, the second end of the resistor R3 is electrically connected to the positive pole feedback input end +IN1 of the comparator U1 and the first end of the resistor R4 respectively, and the second end of the resistor R4 is grounded; the first end of the resistor R5 is electrically connected to the reference voltage power supply, the second end of the resistor R5 is electrically connected to the positive pole feedback input end +IN2 of the comparator U2 and the first end of the resistor R6 respectively, and the second end of the resistor R6 is grounded; the input voltage of the positive pole feedback input end +IN1 of the comparator U1 is a first pre-warning threshold, and the input voltage of the positive pole feedback input end +IN2 of the comparator U2 is a second pre-warning threshold.

[0012] Specifically, in the step S3, the multi-source data set comprises a gas concentration and a working voltage of the explosion-proof display screen; wherein the gas concentration and the working voltage of the explosion-proof display screen are obtained by corresponding sensors on the mine operation vehicle;

[0013] After the gas concentration and the working voltage of the explosion-proof display screen are normalized, the normalized gas concentration in the interval [0, 1] and the normalized working voltage of the explosion-proof display screen in the interval [0, 1] are obtained, and the risk coefficient is determined according to the normalized gas concentration and the normalized working voltage of the explosion-proof display screen, the risk coefficient , represents the feature weight corresponding to the gas concentration, represents the normalized gas concentration, represents the feature weight corresponding to the working voltage of the explosion-proof display screen, represents the normalized working voltage of the explosion-proof display screen.

[0014] Optionally, after the step S3, the step S4 is further included, the step S4 comprises:

[0015] The cosine similarity algorithm is used to calculate the similarity values of the historical case data and the gas concentration and the working voltage of the explosion-proof display screen in the multi-source data set, and the historical evaluation risk coefficient corresponding to the historical case data with the highest similarity value exceeding the threshold is output; the feature weight in the risk coefficient calculation is adjusted by comparing the risk coefficient and the output historical evaluation risk coefficient.

[0016] Preferably, in the step S4, the historical evaluation risk coefficient is obtained by comparing the risk coefficient calculated by the risk coefficient formula with the risk coefficient calculated by the risk coefficient formula .

[0017] If the difference between the historical evaluation risk coefficient and the risk coefficient calculated by the risk coefficient formula is greater than the set difference threshold value, the feature with a feature contribution greater than the preset feature threshold value is obtained; wherein the feature includes the gas concentration and the working voltage of the explosion-proof display screen; the feature contribution is obtained by multiplying the difference value and the feature weight corresponding to the feature;

[0018] According to the feature with the feature contribution greater than the preset feature threshold value, the feature weight of the feature in the risk coefficient calculation is updated, and then the feature weight of another feature is adjusted according to the updated feature weight of the feature.

[0019] Preferably, a computer device comprises a memory and a processor, the memory stores a computer program, and the processor realizes the risk analysis method based on the mine operation environment when executing the computer program.

[0020] The beneficial effects of the present application are that in the risk analysis method based on the mine operation environment, the data during the mine operation is obtained by the sensor arranged on the mine operation vehicle, and then a multi-source data set is formed, through the multi-source data set, first, the threshold value comparison analysis is carried out in the system of the mine operation vehicle, and whether the alarm signal is formed on the spot is judged according to the result of the threshold value comparison analysis, so as to ensure the timeliness of the early warning. When the alarm is generated, the multi-source data set is uploaded to the cloud platform, the cloud platform analyzes the multi-source data set through big data, outputs the risk coefficient, and then selects the corresponding emergency plan according to the risk coefficient, so as to ensure that the selected emergency plan can meet the environment of the current mine operation vehicle, and the purpose of improving the prediction accuracy is achieved. BRIEF DESCRIPTION OF DRAWINGS

[0021] Figure 1 The flowchart of the risk analysis method based on the mine operation environment in an embodiment of the present application;

[0022] Figure 2 The working voltage acquisition circuit of the explosion-proof display screen of the mine operation vehicle in an embodiment of the present application. Detailed Implementation

[0023] The specific embodiments of the present invention will be further described below with reference to the accompanying drawings. It should be noted that these descriptions are for the purpose of aiding understanding the present invention, but do not constitute a limitation thereof. Furthermore, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0024] like Figure 1 and 2 As shown, a risk analysis method based on the mining operation environment includes the following steps:

[0025] S1: Obtain a multi-source data set during the operation of the mining vehicle;

[0026] S2: Perform threshold comparisons on the data in the multi-source data set respectively. When at least one data in the multi-source data set is greater than or equal to a preset threshold, an alarm signal is generated, and the multi-source data set is uploaded to the cloud platform.

[0027] S3: The cloud platform analyzes multi-source data sets and outputs risk coefficients.

[0028] In the aforementioned risk analysis method based on the mining operation environment, sensors installed on the mining vehicle acquire data during mining operations, which is then compiled into a multi-source data set. This multi-source data set is used to first perform threshold comparison analysis within the mining vehicle's system. The results of this analysis determine whether an alarm signal should be generated on-site, ensuring timely early warning. When an alarm is triggered, the multi-source data set is uploaded to a cloud platform. The cloud platform performs big data analysis based on the multi-source data set, outputting a risk coefficient. Based on this risk coefficient, a corresponding emergency plan is selected to ensure that the chosen emergency plan is suitable for the current environment of the mining vehicle, thereby improving the accuracy of predictions.

[0029] In this embodiment, after obtaining the risk coefficient, the priority of each emergency plan in the emergency plan list is adjusted according to the risk coefficient, and then the emergency plan with the highest priority is selected.

[0030] It is worth noting that in step S2, a first warning threshold and a second warning threshold are set for each type of data in the multi-source data set. When the data in the multi-source data set is between the corresponding first warning threshold and the second warning threshold, a first alarm signal is generated. When the data in the multi-source data set is greater than or equal to the corresponding second warning threshold, a second alarm signal is generated and the system power supply of the mining vehicle is cut off.

[0031] In the embodiment, the grading of the early warning level is realized by setting the first early warning threshold and the second early warning threshold. That is, the first early warning threshold is the limit value of the low-level early warning level, and the second early warning threshold is the limit value of the high-level early warning level. When the low-level early warning level is triggered, the first alarm signal is formed, the anti-explosion display screen of the mine operation vehicle flashes yellow and reminds the staff through the loudspeaker. When the high-level early warning level is triggered, the second alarm signal is formed, the anti-explosion display screen of the mine operation vehicle flashes red and reminds the staff through the loudspeaker, and the system power supply of the mine operation vehicle is cut off.

[0032] Preferably, the multi-source data set includes a working voltage of the anti-explosion display screen of the mine operation vehicle; and the working voltage is output to the comparator circuit through the spark elimination circuit to realize threshold comparison.

[0033] The spark elimination circuit includes a resistor R1, a resistor R2, a capacitor C1 and an inductor L2. The resistor R1 and the capacitor C1 are connected in series and then connected in parallel between the positive and negative poles of the power supply U3. The resistor R2 and the inductor L2 are connected in series and then connected in parallel between the positive and negative poles of the power supply U3. The voltage between the positive and negative poles of the power supply U3 is the working voltage of the anti-explosion display screen.

[0034] The comparator circuit includes a comparator U1, a comparator U2, a resistor R3, a resistor R4, a resistor R5 and a resistor R6. The negative feedback input end -IN1 of the comparator U1 and the negative feedback input end -IN2 of the comparator U2 are electrically connected with the positive pole of the power supply U3. The first end of the resistor R3 is electrically connected with the reference voltage power supply (+5V). The second end of the resistor R3 is electrically connected with the positive pole feedback input end +IN1 of the comparator U1 and the first end of the resistor R4 respectively. The second end of the resistor R4 is grounded. The first end of the resistor R5 is electrically connected with the reference voltage power supply (+5V). The second end of the resistor R5 is electrically connected with the positive pole feedback input end +IN2 of the comparator U2 and the first end of the resistor R6 respectively. The second end of the resistor R6 is grounded. The input voltage of the positive pole feedback input end +IN1 of the comparator U1 is the first early warning threshold, and the input voltage of the positive pole feedback input end +IN2 of the comparator U2 is the second early warning threshold.

[0035] As Figure 2When the power supply accumulates charges, the charges will be released through the RC loop composed of resistor R1 and capacitor C1 and the RL loop composed of resistor R2 and inductor L2 in the spark elimination circuit, ensuring the safety and stability of the subsequent comparator circuit acquisition. In this embodiment, by setting different sizes of resistor R4 and resistor R6, different voltage trigger thresholds can be set for comparator U1 and comparator U2, thereby forming a first warning threshold and a second warning threshold to realize the grading of the warning level of the working voltage of the explosion-proof display screen. In this embodiment, the resistor R4 and the resistor R6 are slide rheostats, the voltage across the resistor R4 is the input voltage of the positive feedback input terminal +IN1 of the comparator U1, and the voltage across the resistor R6 is the input voltage of the positive feedback input terminal +IN2 of the comparator U2. By changing the resistance value of the resistor R4 or the resistor R6, the voltage across the resistor R4 or the resistor R6 can be changed. The purpose of adjusting the input voltage of the positive feedback input terminal +IN1 of the comparator U1 or the input voltage of the positive feedback input terminal +IN2 of the comparator U2 is achieved. Specifically, by comparing the outputs of the comparator U1 and the comparator U2, that is, the output levels of the I / O1 and the I / O2 detection terminals in Figure 2 , whether the working voltage exceeds the first warning threshold or the second warning threshold can be obtained. Specifically, the models of the comparator U1 and the comparator U2 are both LM339.

[0036] In the actual mine operation environment, temperature can easily cause the working voltage of the explosion-proof display screen to fluctuate, leading to false positives or false negatives. Therefore, a temperature sensor is integrated into the power supply to detect the working temperature of the power supply, and the voltage trigger threshold of the comparator circuit is updated in real time based on the working temperature, so that it is self-adaptively corrected with temperature changes, avoiding false alarms caused by environmental temperature fluctuations.

[0037] Specifically, the voltage trigger threshold = V0 * [1 + a(T-T0) + b(T-T0)^2], wherein T0 represents a reference temperature; T represents a real-time temperature; V0 represents an original voltage threshold at the reference temperature T0; it can be understood that the reference temperatures T0 of I / O1 and I / O2 are different, and thus the original voltage thresholds of I / O1 and I / O2 are different; for example, the reference temperature T0 of I / O1 is 20°C, and the original voltage threshold V0 is 10V; the reference temperature T0 of I / O2 is 22°C, and the original voltage threshold V0 is 11V; a represents a linear temperature compensation coefficient, and b represents a nonlinear temperature compensation coefficient. When the power supply operating temperature (i.e., the real-time temperature) is in a first temperature range, a and b are 0; when the power supply operating temperature is in a second temperature range, a is greater than 0, and b is 0. When the power supply operating temperature is in a third temperature range, a and b are both greater than 0. By dynamically adjusting the original voltage thresholds of I / O1 and I / O2, false positives caused by temperature drift are effectively suppressed, and the reliability of the alarm is improved. For I / O1, after obtaining the corresponding voltage trigger threshold, the voltage trigger threshold is taken as the target first early warning threshold, and then the input voltage of the positive feedback input end +IN1 of the comparator U1 can be adjusted to the target first early warning threshold by adjusting the corresponding sliding resistor of the resistor R4. For I / O2, after obtaining the corresponding voltage trigger threshold, the voltage trigger threshold is taken as the target second early warning threshold, and then the input voltage of the positive feedback input end +IN2 of the comparator U2 can be adjusted to the target first early warning threshold by adjusting the corresponding sliding resistor of the resistor R6.

[0038] In the step S3, the multi-source data set includes a gas concentration and a working voltage of the explosion-proof display screen; wherein the gas concentration and the working voltage of the explosion-proof display screen are obtained by corresponding sensors on the mine operation vehicle; in this embodiment, the gas concentration around the sensor is obtained by the sensor on the mine operation vehicle as the gas concentration around the mine operation vehicle; specifically, a general mine operation vehicle will be provided with a sensor for collecting the gas concentration and a sensor for collecting the working voltage of the explosion-proof display screen;

[0039] After the gas concentration and the working voltage of the explosion-proof display screen are normalized, the normalized gas concentration in the interval [0, 1] and the normalized working voltage of the explosion-proof display screen in the interval [0, 1] are obtained, and the risk coefficient is determined according to the normalized gas concentration and the normalized working voltage of the explosion-proof display screen, wherein the risk coefficient , represents the feature weight corresponding to the gas concentration, represents the normalized gas concentration, represents the feature weight corresponding to the working voltage of the explosion-proof display screen, represents the normalized working voltage of the explosion-proof display screen.

[0040] The multi-source data set after forming the alarm signal is reported to the cloud platform through the communication mechanism by using the TCP / IP protocol. After receiving the multi-source data set, the cloud platform stores the data to the data storage module of the command center through the HTTP protocol. Exemplarily, in the mine operation environment, the system extracts the gas concentration and the working voltage of the explosion-proof display screen from the records of the past year, for example, the records of a certain mine area show that the gas concentration fluctuates between 0.8% and 1.2% on a certain day, and the working voltage of the explosion-proof display screen changes in the voltage interval; these data are collected by the sensor and stored in the historical database of the cloud platform, providing a basis for subsequent analysis. The weighted key features reflect the comprehensive influence degree of each factor. According to the formula for calculating the risk coefficient, the combination of feature weights and key feature values can quantify the risk.

[0041] It is worth noting that after the step S3, there is also a step S4, which includes:

[0042] The cosine similarity algorithm is used to calculate the similarity value of the gas concentration and the working voltage of the explosion-proof display screen of the historical case data and the multi-source data set, and the historical evaluation risk coefficient corresponding to the historical case data with the highest similarity value and the similarity value exceeding the threshold value is output. The risk coefficient and the output historical evaluation risk coefficient are compared, and the feature weight in the risk coefficient calculation is adjusted.

[0043] For example, according to the input gas concentration and the working voltage of the explosion-proof display screen, the matching degree of the historical case data and the input gas concentration and the working voltage of the explosion-proof display screen is calculated first, and the similarity value is obtained; when the similarity value exceeds the set threshold value, the corresponding historical evaluation risk coefficient is obtained from the historical case data, and the historical evaluation risk coefficient corresponding to the historical case data with the highest similarity value is output. Specifically, the historical evaluation risk system obtains it by looking up the table. In the historical accident database, different rating intervals are set, each rating interval corresponds to a historical evaluation risk coefficient, and experts assign the historical case data to different rating intervals according to the historical case data and the accidents that have occurred corresponding to the historical case data, thereby forming a table of historical case data and historical evaluation risk coefficient mapping each other.

[0044] Specifically, in the mine gas monitoring scenario, the historical accident database stores historical accident data composed of daily gas concentration, working voltage of the explosion-proof display screen and related accident records in the past N years, for example, a record shows that the gas concentration reaches 1.3%, the working voltage of the explosion-proof display screen is 12V, and then a device failure occurs. These data provide a reliable basis for subsequent analysis. In this embodiment, the cosine similarity algorithm is used to calculate the matching degree of the historical case data and the gas concentration and the working voltage of the explosion-proof display screen of the multi-source data set. It can be understood that the cosine similarity measures the similarity of two groups of data by comparing the included angle between vectors. For example, compare the current gas concentration 1.1% and the working voltage Y of the explosion-proof display screen with the gas concentration 1.2% and the working voltage Z of the explosion-proof display screen in the historical case, calculate the similarity value, and when the similarity value exceeds the set threshold value, it indicates that the two modes are close, and then take the historical case data with the highest similarity value. This method can quickly filter out the most relevant historical case data from the historical accident database.

[0045] Specifically, in the step S4, the historical evaluation risk coefficient is obtained, and the risk coefficient calculated by the risk coefficient formula The difference between the historical evaluation risk coefficient and the risk coefficient calculated by the risk coefficient formula is calculated.

[0046] If the difference between the historical evaluation risk coefficient and the risk coefficient calculated by the risk coefficient formula is greater than the set difference threshold value, the features whose difference contributions are greater than the preset feature threshold value are obtained; wherein the features include the gas concentration and the working voltage of the explosion-proof display screen; the difference contribution is obtained by multiplying the difference and the feature weight corresponding to the feature;

[0047] According to the features whose difference contributions are greater than the preset feature threshold value, the feature weight of the feature in the risk coefficient calculation is updated, and then the feature weight of another feature is adjusted according to the updated feature weight of the feature.

[0048] Assuming that the historical evaluation risk coefficient is 0.7. The risk coefficient calculated by the risk coefficient formula can be based on the actual monitoring data, assuming that the risk coefficient is 0.65. The difference between 0.7 and 0.65 is 0.05, which is greater than the set difference threshold 0.04, and this difference may be affected by certain features. Specifically, the feature threshold can be set to 0.03; assuming that in the difference of 0.05, it is found that the contribution of gas concentration to the difference is more than 0.03, and the influence of the working voltage of the explosion-proof display screen is less than 0.03, then the feature weight corresponding to the gas concentration is increased, and the feature weight corresponding to the working voltage of the explosion-proof display screen is decreased (the increase and decrease amount of the feature weight can be preset to 0.01 each time, such as for the operation of increasing the feature weight corresponding to the gas concentration, the original feature weight of the gas concentration is 0.6, then the updated feature weight of the gas concentration is 0.61, and the updated feature weight of the working voltage of the explosion-proof display screen is 0.39), and then the risk coefficient is recalculated according to the updated feature weight, and step S4 is repeatedly executed until the difference between the historical evaluation risk coefficient and the risk coefficient calculated by the risk coefficient formula is less than or equal to the set difference threshold, to obtain the updated feature weight corresponding to the gas concentration and the feature weight corresponding to the working voltage of the explosion-proof display screen.

[0049] A computer device comprising a memory and a processor, the memory storing a computer program, and the processor implementing the method for risk analysis based on mine operation environment when executing the computer program.

[0050] The embodiments of the present application are described in detail above with reference to the drawings, but the present application is not limited to the described embodiments. For those skilled in the art, various changes, modifications, replacements and variations can be made to the embodiments without departing from the principles and spirits of the present application, and still fall within the protection scope of the present application.​

Claims

1. A risk analysis method based on a mine work environment, characterized by, The method comprises the following steps: S1: obtaining a multi-source data set of a mine operation vehicle during operation; S2: performing threshold comparison on the data in the multi-source data set respectively, forming an alarm signal when at least one data in the multi-source data set is greater than or equal to a preset threshold value, and uploading the multi-source data set to a cloud platform; The multi-source data set includes a working voltage of an explosion-proof display screen of the mine operation vehicle; the working voltage is output to a comparator circuit through a spark elimination circuit to realize threshold comparison; The spark elimination circuit comprises resistors R1 and R2, a capacitor C1 and an inductor L2, the resistors R1 and the capacitor C1 are connected in series and then connected in parallel between the positive and negative electrodes of a power supply U3, and the resistor R2 and the inductor L2 are connected in series and then connected in parallel between the positive and negative electrodes of the power supply U3; the voltage between the positive and negative electrodes of the power supply U3 is the working voltage of the explosion-proof display screen; The comparator circuit comprises comparators U1 and U2, resistors R3, R4, R5 and R6; the negative feedback input end -IN1 of the comparator U1 and the negative feedback input end -IN2 of the comparator U2 are electrically connected to the positive electrode of the power supply U3; the first end of the resistor R3 is electrically connected to a reference voltage power supply, the second end of the resistor R3 is electrically connected to the positive feedback input end +IN1 of the comparator U1 and the first end of the resistor R4 respectively, and the second end of the resistor R4 is grounded; the first end of the resistor R5 is electrically connected to the reference voltage power supply, the second end of the resistor R5 is electrically connected to the positive feedback input end +IN2 of the comparator U2 and the first end of the resistor R6 respectively, and the second end of the resistor R6 is grounded; the input voltage of the positive feedback input end +IN1 of the comparator U1 is a first early warning threshold value, and the input voltage of the positive feedback input end +IN2 of the comparator U2 is a second early warning threshold value; S3: the cloud platform analyzes the multi-source data set to output a risk coefficient; after obtaining the risk coefficient, the priority of each emergency plan in the emergency plan list is adjusted according to the risk coefficient, and the emergency plan with the highest priority is selected; The multi-source data set includes gas concentration and working voltage of the explosion-proof display screen; the gas concentration and the working voltage of the explosion-proof display screen are obtained by corresponding sensors on the mine operation vehicle; The normalized gas concentration and the normalized working voltage of the explosion-proof display screen in the interval [0, 1] are obtained after normalization of the gas concentration and the working voltage of the explosion-proof display screen. The risk coefficient is determined according to the normalized gas concentration and the normalized working voltage of the explosion-proof display screen. The risk coefficient , indicates the characteristic weight corresponding to the gas concentration, indicates the normalized gas concentration, indicates the characteristic weight corresponding to the working voltage of the explosion-proof display screen, indicates the normalized working voltage of the explosion-proof display screen. S4: a cosine similarity algorithm is used to calculate the similarity value of the gas concentration and the working voltage of the explosion-proof display screen in the multi-source data set and historical case data, and output the historical evaluation risk coefficient corresponding to the historical case data with the highest similarity value exceeding a threshold value; the historical evaluation risk system is obtained by looking up a table, different rating intervals are set in the historical accident database, each rating interval corresponds to a historical evaluation risk coefficient, and experts allocate the historical case data to different rating intervals according to the historical case data and the accident that has already occurred, thereby forming a table in which the historical case data and the historical evaluation risk coefficient are mapped to each other. obtaining a historical evaluation risk factor and calculating a risk factor by a risk factor formula obtaining a historical evaluation risk factor and calculating a risk factor by a risk factor formula obtaining a historical evaluation risk factor and calculating a risk factor by a risk factor formula If the difference between the historical evaluation risk coefficient and the calculated risk coefficient through the risk coefficient formula is greater than a set difference threshold value, then the features that contribute more than a preset feature threshold value to the difference are obtained; wherein the features include gas concentration and working voltage of the explosion-proof display screen; the contribution of the features to the difference is obtained by multiplying the difference and the feature weight corresponding to the features; According to the feature whose difference contribution is greater than the preset feature threshold, the feature weight of the feature in the risk coefficient calculation is updated, and then the feature weight of another feature is adjusted according to the updated feature weight of the feature; Then the risk coefficient is recalculated according to the updated feature weight, and step S4 is repeatedly executed until the difference between the historical evaluation risk coefficient and the risk coefficient calculated by the risk coefficient formula The difference between the calculated risk coefficients is less than or equal to the set difference threshold, and the updated feature weight corresponding to the gas concentration and the feature weight corresponding to the working voltage of the explosion-proof display screen are obtained.

2. The method of claim 1, wherein: In the step S2, a first early warning threshold and a second early warning threshold are respectively set for each data in the multi-source data set, when the data of the multi-source data set is between the corresponding first early warning threshold and the second early warning threshold, a first alarm signal is formed, and when the data of the multi-source data set is greater than or equal to the corresponding second early warning threshold, a second alarm signal is formed and the system power supply of the mine operation vehicle is cut off.

3. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that, The processor implements the risk analysis method based on the mine operation environment in claim 1 or 2 when executing the computer program.

Images