Traffic flow detection and analysis system for tunnel energy-saving control

Abstract

The invention belongs to the technical field of tunnel traffic control, and particularly relates to a traffic flow detection and analysis system for tunnel energy-saving control, which comprises a traffic flow segmented detection module, an illumination brightness decision module, a ventilation necessity detection module, a tunnel energy-saving control module and a background supervision terminal. The traffic flow segmentation detection module monitors and analyzes the traffic flow of each road section in the tunnel in real time, the illumination brightness decision module determines the optimal illumination brightness value of each road section in the tunnel through tunnel illumination decision analysis, and the ventilation necessity detection module analyzes the ventilation necessity of each road section in the tunnel. The illumination brightness of each road section in the tunnel can be automatically and accurately adjusted based on the traffic flow condition, and the traffic flow condition and the environment condition of each road section in the tunnel can be combined to realize timely and automatic ventilation of each road section in the tunnel, so that the automation level and the intelligent level are high; and the energy-saving effect is obviously improved while the tunnel driving safety is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of tunnel traffic control, and in particular to a vehicle flow detection and analysis system for tunnel energy-saving control. Background Art

[0002] Tunnels refer to engineering structures buried in the ground. The main function of tunnels is to shorten the mileage, increase the speed and improve the driving environment when vehicles and pedestrians pass through various obstacles. For traffic tunnels, they not only solve the problems caused by geographical barriers, but also promote economic development and exchanges between regions.

[0003] A Chinese invention patent with publication number CN116403396A discloses a tunnel vehicle detection method based on big data and video technology. It uses high-definition card ports, surveillance videos and other data to accurately identify the status of vehicles entering highway tunnels, and detects special events in tunnels to understand the driving status of hazardous chemical vehicles and tunnel traffic conditions, thereby speeding up the response to special events in tunnels.

[0004] However, in actual application, the above-mentioned technical solution is difficult to effectively monitor and reasonably evaluate the traffic conditions of each section in the tunnel, and it is impossible to automatically and adaptively adjust the lighting brightness of each section in the tunnel based on the traffic conditions and realize timely ventilation of each section, which is not conducive to improving the energy-saving effect of the tunnel and increases the management difficulty and operation cost of the tunnel.

[0005] In view of the above technical defects, a solution is now proposed. Summary of the invention

[0006] The purpose of the present invention is to provide a vehicle flow detection and analysis system for tunnel energy-saving control, which solves the problem that the prior art is difficult to effectively monitor and reasonably evaluate the traffic conditions of each section in the tunnel, and is unable to automatically adaptively adjust the lighting brightness of each section in the tunnel based on the traffic conditions and realize timely ventilation of each section, which is not conducive to improving the energy-saving effect of the tunnel and reducing the difficulty of tunnel management.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] A vehicle flow detection and analysis system for tunnel energy-saving control, comprising a vehicle flow segmentation detection module, a lighting brightness decision module, a ventilation necessity detection module, a tunnel energy-saving control module and a background supervision terminal;

[0009] The traffic flow segmentation detection module divides the interior of the tunnel into several sections, marks the corresponding section as the tunnel target section i, and i is a natural number greater than 1; and monitors the traffic flow of the tunnel target section i in real time, obtains the traffic flow analysis value of the tunnel target section i through analysis, and sends the traffic flow analysis value of the tunnel target section i to the lighting brightness decision module and the ventilation necessity detection module;

[0010] The lighting brightness decision module determines the optimal lighting brightness of each section in the tunnel through tunnel lighting decision analysis, and sends the optimal lighting brightness of each section in the tunnel to the tunnel energy-saving control module and the background supervision end. The tunnel energy-saving control module adjusts the brightness according to the optimal lighting brightness of each section;

[0011] The ventilation necessity detection module analyzes the ventilation necessity of each section in the tunnel, generates a ventilation warning signal or a ventilation non-essential signal for the tunnel target section i through analysis, and sends the ventilation warning signal or the ventilation non-essential signal for the tunnel target section i to the tunnel energy-saving control module and the background supervision end. When the tunnel energy-saving control module receives the ventilation warning signal, it starts ventilation for the tunnel target section i.

[0012] Furthermore, the analysis and acquisition method of the traffic flow analysis value is as follows:

[0013] The real-time traffic flow of the target tunnel section i is collected, and the real-time traffic flow of the target tunnel section i at all times in a unit time is averaged to obtain the average traffic flow value, and the proportion of the time that the real-time traffic flow in a unit time exceeds the preset real-time traffic flow threshold is marked as the congestion detection value, and the maximum value of the real-time traffic flow in a unit time is marked as the traffic flow amplitude measurement value; the traffic flow analysis value is obtained by numerically calculating the average traffic flow value, the congestion detection value and the traffic flow amplitude measurement value of the target tunnel section i.

[0014] Furthermore, the specific analysis process of tunnel lighting decision analysis is as follows:

[0015] The traffic flow analysis value of the tunnel target section i is obtained, and several preset traffic flow analysis value ranges are set in advance, and each group of preset traffic flow analysis value ranges corresponds to a group of preset brightness standard values; the traffic flow analysis value of the tunnel target section i is compared with all the preset traffic flow analysis value ranges one by one, and the preset traffic flow analysis value range containing the corresponding traffic flow analysis value is determined and marked as the optimal range, and the preset brightness standard value corresponding to the optimal range is marked as the optimal value of the lighting brightness of the tunnel target section i.

[0016] Furthermore, the specific analysis process of the ventilation necessity detection module includes:

[0017] A number of detection points are set in the target tunnel section i, and the dust particle concentration and oxygen concentration at the corresponding detection points are collected. The dust particle concentrations of all detection points are averaged to obtain the visibility impact value, and the oxygen concentrations of all detection points are averaged to obtain the oxygen detection value;

[0018] And the gas quality anomaly value is obtained through gas toxicity detection and analysis, and the ventilation emergency value is obtained by numerically calculating the visibility impact value, oxygen detection value and gas quality anomaly value; a preset ventilation emergency threshold value corresponding to the tunnel target section i is assigned, and the ventilation emergency value is numerically compared with the corresponding preset ventilation emergency threshold value; if the ventilation emergency value exceeds the corresponding preset ventilation emergency threshold value, a ventilation warning signal for the tunnel target section i is generated; if the ventilation emergency value does not exceed the corresponding preset ventilation emergency threshold value, a ventilation non-essential signal for the tunnel target section i is generated.

[0019] Furthermore, the specific analysis process of gas harmfulness detection and analysis is as follows:

[0020] The types of harmful gases that need to be monitored in the tunnel are obtained, the real-time concentrations of the corresponding types of harmful gases in the target tunnel section i at all detection points are collected, and the real-time concentrations of the corresponding types of harmful gases at all detection points are averaged to obtain the gas concentration value; each type of harmful gas is set in advance to correspond to a set of preset hazard weight values, and the product of the gas concentration value of the corresponding type of harmful gas and the corresponding preset hazard weight value is marked as a gas danger value, and the gas danger values ​​of all types of harmful gases that need to be monitored in the target tunnel section i are summed and calculated to obtain the gas quality value.

[0021] Furthermore, the specific allocation process of allocating the preset ventilation emergency threshold value adapted to the tunnel target section i is as follows:

[0022] The traffic flow analysis value of the target tunnel section i is obtained, and the traffic flow analysis value is numerically compared with the preset traffic flow analysis threshold. If the traffic flow analysis value exceeds the preset traffic flow analysis threshold, the target tunnel section i is marked as a strict control section; if the traffic flow analysis value does not exceed the preset traffic flow analysis threshold, the target tunnel section i is marked as a weak control section;

[0023] If the tunnel target section i is a strict control section, a preset ventilation emergency threshold LP1 is allocated to the tunnel target section i; if the tunnel target section i is a weak control section, a preset ventilation emergency threshold LP2 is allocated to the tunnel target section i, and LP2>LP1>0.

[0024] Furthermore, the tunnel energy-saving control module is communicated with the tunnel line inspection module. The tunnel line inspection module obtains all power lines that need to be monitored in the tunnel, monitors all power lines, determines the faulty line through analysis, and sends the faulty line to the tunnel energy-saving control module. After receiving the faulty line, the tunnel energy-saving control module generates corresponding warning information, and sends the generated corresponding warning information to the background supervision end for display.

[0025] Furthermore, the specific analysis process of the tunnel line investigation module is as follows:

[0026] A number of split points are set on the power line, and the difference between the electric energy input from the corresponding split point and the electric energy output from the next adjacent split point is calculated to obtain a transmission loss value, and the transmission loss value is numerically compared with a preset transmission loss threshold. If the transmission loss value exceeds the preset transmission loss threshold, it is determined that there is an energy consumption anomaly between the corresponding two groups of split points, and the corresponding power line is marked as a fault line;

[0027] If all transmission loss values ​​do not exceed the preset transmission loss threshold, the average of all transmission loss values ​​on the corresponding power line is calculated to obtain the transmission loss measurement value, and the transmission loss measurement value is numerically compared with the preset transmission loss measurement threshold. If the transmission loss measurement value exceeds the preset transmission loss measurement threshold, the corresponding power line is marked as a faulty line.

[0028] Furthermore, the tunnel energy-saving control module is communicatively connected to the operation monitoring and evaluation module. The operation monitoring and evaluation module analyzes the lighting and ventilation control performance of the tunnel energy-saving control module, generates an energy-saving control qualification signal or an energy-saving control abnormality signal through the analysis, and sends the energy-saving control qualification signal or the energy-saving control abnormality signal to the background supervision end via the tunnel energy-saving control module.

[0029] Furthermore, the specific analysis process of the operation monitoring and evaluation module is as follows:

[0030] A detection period is set, and the real-time lighting brightness of the tunnel target segment i is collected. The deviation value of the real-time lighting brightness compared with the corresponding preset lighting brightness optimal value is marked as the tunnel lighting deviation value. The tunnel lighting deviation value is numerically compared with the preset tunnel lighting deviation threshold. If the tunnel lighting deviation value exceeds the preset tunnel lighting deviation threshold, it is determined that the tunnel target segment i is currently in a poor lighting control state.

[0031] Obtain all single durations of the tunnel target section i being in a poor lighting control state during the detection period, mark the number of occurrences of the single duration of the poor lighting control state exceeding the corresponding preset duration threshold as the lighting control abnormality detection value, and sum up all single durations of the poor lighting control state to obtain the total lighting control abnormality time value;

[0032] When ventilating the target tunnel section i, the deviation value of the real-time ventilation speed of the target tunnel section i compared with the set standard ventilation speed is marked as the ventilation speed deviation value, and the ventilation speed deviation value is numerically compared with the preset ventilation speed deviation threshold. If the ventilation speed deviation value exceeds the preset ventilation speed deviation threshold, the corresponding ventilation speed deviation value is marked as the ventilation speed abnormal value, and the number of ventilation speed abnormal values ​​in the detection period is calculated by ratio with the number of ventilation speed deviation values ​​to obtain the ventilation abnormal detection value; and the excess value of the ventilation speed abnormal value compared with the preset ventilation speed deviation threshold is marked as the ventilation speed excess value, and the average of all ventilation speed excess values ​​in the detection period is calculated to obtain the ventilation excess analysis value;

[0033] The ventilation and lighting evaluation value is obtained by numerically calculating the lighting control abnormality detection value, the total lighting control abnormality time value, the ventilation speed detection value and the ventilation super-analysis value of the tunnel target section i during the detection period, and the ventilation and lighting evaluation value is numerically compared with the preset ventilation and lighting evaluation threshold. If the ventilation and lighting evaluation value exceeds the preset ventilation and lighting evaluation threshold, the tunnel target section i is marked as a non-optimal section for control;

[0034] The percentage of non-optimal sections in the tunnel is obtained and marked as the tunnel abnormal section value, and the ventilation and lighting evaluation values ​​of all sections in the tunnel are averaged to obtain the tunnel control and inspection value, and the ventilation and lighting evaluation value with the largest value is marked as the control abnormal amplitude measurement value; the energy-saving control coefficient is obtained by numerically calculating the tunnel abnormal section value, the tunnel control and inspection value and the control abnormal amplitude measurement value, and the energy-saving control coefficient is numerically compared with the preset energy-saving control coefficient threshold. If the energy-saving control coefficient exceeds the preset energy-saving control coefficient threshold, an energy-saving control abnormal signal is generated; if the energy-saving control coefficient does not exceed the preset energy-saving control coefficient threshold, an energy-saving control qualified signal is generated.

[0035] Compared with the prior art, the present invention has the following beneficial effects:

[0036] 1. In the present invention, the vehicle flow of each section in the tunnel is monitored and analyzed in real time through the vehicle flow segmentation detection module, the lighting brightness decision module determines the optimal lighting brightness of each section in the tunnel through the tunnel lighting decision analysis, and adjusts the brightness according to the optimal lighting brightness of each section, and the ventilation necessity detection module analyzes the ventilation necessity of each section in the tunnel, and starts the ventilation of the corresponding section in the tunnel when the ventilation warning signal is generated. It can not only automatically and accurately adjust the lighting brightness of each section in the tunnel based on the traffic flow conditions, but also combine the traffic flow conditions and environmental conditions of each section in the tunnel to achieve timely and automatic ventilation of each section in the tunnel, which is conducive to ensuring tunnel driving safety and significantly improving energy saving effects;

[0037] 2. In the present invention, all power lines that need to be monitored in the tunnel are monitored and analyzed through the tunnel line inspection module to determine the faulty line. After the faulty line is determined, the back-end management personnel are reminded to inspect and repair the corresponding faulty line in time, thereby improving the energy-saving effect of the tunnel and reducing the difficulty of tunnel management. In addition, the tunnel energy-saving control module is used to analyze the lighting and ventilation control performance of the tunnel through the operation monitoring and evaluation module. When an energy-saving control abnormality signal is generated, the back-end management personnel are reminded to strengthen the subsequent supervision of the tunnel, ensure the subsequent operation control performance and energy-saving performance, and further reduce the difficulty of tunnel management. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings;

[0039] Figure 1 This is a system block diagram of Embodiment 1 of the present invention;

[0040] Figure 2 This is a system block diagram of Embodiment 2 and Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0041] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0042] Embodiment 1: Figure 1 As shown, the present invention proposes a vehicle flow detection and analysis system for tunnel energy-saving control, including a vehicle flow segmentation detection module, a lighting brightness decision module, a ventilation necessity detection module, a tunnel energy-saving control module and a background supervision terminal;

[0043] The traffic flow segmentation detection module divides the interior of the tunnel into several sections, marks the corresponding section as the tunnel target section i, and i is a natural number greater than 1; and monitors the traffic flow of the tunnel target section i in real time, obtains the traffic flow analysis value of the tunnel target section i through analysis, and sends the traffic flow analysis value of the tunnel target section i to the lighting brightness decision module and the ventilation necessity detection module, which can reasonably analyze the traffic flow conditions of each section inside the tunnel, and provide information support for the analysis process of the lighting brightness decision module and the ventilation necessity detection module, ensuring the accuracy of the analysis results, which is conducive to realizing energy-saving control inside the tunnel; the analysis and acquisition method of the traffic flow analysis value is as follows:

[0044] The real-time traffic flow of the target tunnel section i is collected, and the real-time traffic flow of the target tunnel section i at all times within a unit time is averaged to obtain the average traffic flow value, and the real-time traffic flow is numerically compared with the preset real-time traffic flow threshold, and the proportion of the time that the real-time traffic flow within a unit time exceeds the preset real-time traffic flow threshold is marked as the congestion detection value, and the maximum value of the real-time traffic flow within a unit time is marked as the traffic flow amplitude measurement value;

[0045] The traffic flow analysis value YRi is obtained by numerically calculating the average traffic flow value YHi, the traffic jam detection value YSi and the traffic flow amplitude measurement value YNi of the tunnel target section i through the formula YRi=sr2*YSi+(sr1*YHi+sr3*YNi) / 2; wherein sr1, sr2 and sr3 are preset proportional coefficients, sr2>sr1>sr3>0.253; and the larger the value of the traffic flow analysis value YRi is, the larger the traffic flow of the tunnel target section i is in general, and the more it is necessary to appropriately increase the lighting brightness.

[0046] The lighting brightness decision module determines the optimal lighting brightness of each section in the tunnel through tunnel lighting decision analysis, and sends the optimal lighting brightness of each section in the tunnel to the tunnel energy-saving control module and the background supervision end;

[0047] The tunnel energy-saving control module adjusts the brightness according to the optimal value of the lighting brightness of each section. It can automatically and accurately adjust the lighting brightness of each section in the tunnel based on the traffic conditions, ensuring the safety of tunnel driving while significantly reducing energy consumption, reducing tunnel operating costs and improving energy-saving effects. The specific analysis process of tunnel lighting decision analysis is as follows:

[0048] The traffic flow analysis value of the tunnel target section i is obtained, and several preset traffic flow analysis value ranges are set in advance, and each group of preset traffic flow analysis value ranges corresponds to a group of preset brightness standard values; it should be noted that the larger the value of the preset traffic flow analysis value range is, the larger the value of the preset brightness standard value adapted thereto is;

[0049] The traffic flow analysis value of the tunnel target segment i is compared with all preset traffic flow analysis value ranges one by one, and the preset traffic flow analysis value range containing the corresponding traffic flow analysis value is determined and marked as the optimal range, and the preset brightness standard value corresponding to the optimal range is marked as the optimal value of the lighting brightness of the tunnel target segment i.

[0050] The ventilation necessity detection module analyzes the ventilation necessity of each section in the tunnel, generates a ventilation warning signal or a ventilation non-essential signal of the tunnel target section i through analysis, and sends the ventilation warning signal or the ventilation non-essential signal of the tunnel target section i to the tunnel energy-saving control module and the background supervision end. When the tunnel energy-saving control module receives the ventilation warning signal, it starts ventilation for the tunnel target section i;

[0051] By combining the traffic conditions and environmental conditions of each section in the tunnel to accurately judge the ventilation urgency, timely and automatic ventilation of each section in the tunnel is achieved, with a high level of automation and intelligence, further improving the energy saving effect of the tunnel; the specific analysis process of the ventilation necessity detection module is as follows:

[0052] A number of detection points are set in the target tunnel section i, and the dust particle concentration and oxygen concentration at the corresponding detection points are collected. The dust particle concentrations of all detection points are averaged to obtain the visibility impact value, and the oxygen concentrations of all detection points are averaged to obtain the oxygen detection value;

[0053] And the gas quality value is obtained through gas harmfulness detection and analysis, specifically: the type of harmful gas that needs to be monitored in the tunnel is obtained (mainly referring to the pollutant gas in the exhaust gas emitted by the car, including carbon monoxide, sulfur dioxide, nitrogen monoxide, etc.), the real-time concentration of the corresponding type of harmful gas at all detection points in the target section i of the tunnel is collected, and the real-time concentration of the corresponding type of harmful gas at all detection points is averaged to obtain the gas concentration value;

[0054] A set of preset hazard weight values ​​is set in advance for each type of harmful gas. It should be noted that the preset hazard weight values ​​are all positive numbers, and the greater the harm caused by the corresponding type to the environment and human health, the greater the value of the preset hazard weight value adapted to it;

[0055] The product of the gas concentration value of the corresponding type of harmful gas and the corresponding preset hazard weight value is marked as the gas danger value, and the gas danger values ​​of all types of harmful gases that need to be monitored in the tunnel target section i are summed up to obtain the gas quality abnormality value; wherein, the larger the value of the gas quality abnormality value is, the more serious the gas pollution in the tunnel target section i is, and the more timely ventilation of the tunnel target section i is needed;

[0056] By formula The visibility impact value Qi, the oxygen detection value Gi and the gas quality value Mi are numerically calculated to obtain the ventilation emergency value EKi; wherein ny1, ny2 and ny3 are preset proportional coefficients with values ​​greater than zero, and the larger the value of the ventilation emergency value EKi, the worse the environmental condition of the tunnel target section i is, and the more timely ventilation is needed;

[0057] Assign a preset ventilation emergency threshold value adapted to the tunnel target section i, specifically: obtain the traffic flow analysis value YRi of the tunnel target section i, compare the traffic flow analysis value YRi with the preset traffic flow analysis threshold, if the traffic flow analysis value YRi exceeds the preset traffic flow analysis threshold, mark the tunnel target section i as a strict control section; if the traffic flow analysis value YRi does not exceed the preset traffic flow analysis threshold, mark the tunnel target section i as a weak control section;

[0058] If the tunnel target section i is a strict control section, the preset ventilation emergency threshold LP1 is assigned to the tunnel target section i; if the tunnel target section i is a weak control section, the preset ventilation emergency threshold LP2 is assigned to the tunnel target section i, and LP2>LP1>0; by assigning the corresponding preset ventilation emergency thresholds to the traffic conditions of different sections in the tunnel, the accuracy of the ventilation urgency analysis results is significantly improved;

[0059] The ventilation emergency value EKi is numerically compared with the corresponding preset ventilation emergency threshold. If the ventilation emergency value EKi exceeds the corresponding preset ventilation emergency threshold, it indicates that the environmental condition of the tunnel target section i is poor and timely ventilation is required, and a ventilation warning signal for the tunnel target section i is generated; if the ventilation emergency value EKi does not exceed the corresponding preset ventilation emergency threshold, it indicates that the tunnel target section i does not need to be ventilated in time, and a ventilation non-essential signal for the tunnel target section i is generated.

[0060] Embodiment 2: Figure 2 As shown, the difference between this embodiment and the first embodiment is that the tunnel energy-saving control module is connected to the tunnel line checking module in communication, the tunnel line checking module obtains all power lines that need to be monitored in the tunnel, monitors all power lines, determines the faulty line through analysis, and sends the faulty line to the tunnel energy-saving control module;

[0061] After receiving the fault line, the tunnel energy-saving control module generates corresponding warning information and sends the generated corresponding warning information to the background supervision end for display, so as to remind the background management personnel to check and repair the corresponding fault line in time, so as to avoid power line leakage, abnormal heating, etc., reduce energy consumption and reduce the risk of power operation, improve the tunnel energy-saving effect and reduce the difficulty of tunnel management; the specific analysis process of the tunnel line investigation module is as follows:

[0062] A number of split points are set on the power line, and the difference between the electric energy input from the corresponding split point and the electric energy output from the next adjacent split point is calculated to obtain a transmission loss value, and the transmission loss value is numerically compared with a preset transmission loss threshold. If the transmission loss value exceeds the preset transmission loss threshold, it is judged that there is an energy consumption abnormality between the corresponding two groups of split points (that is, the electric energy consumed when transmitting electricity between the corresponding two groups of split points is too large, and there is a high probability of abnormal heating or leakage), and the corresponding power line is marked as a fault line;

[0063] If all transmission loss values ​​do not exceed the preset transmission loss threshold, the average of all transmission loss values ​​on the corresponding power line is calculated to obtain the transmission loss measurement value, and the transmission loss measurement value is numerically compared with the preset transmission loss measurement threshold. If the transmission loss measurement value exceeds the preset transmission loss measurement threshold, it indicates that the transmission energy consumption of the corresponding power line is greater overall, and the corresponding power line needs to be inspected and maintained in time, and the corresponding power line is marked as a faulty line.

[0064] Embodiment 3: Figure 2 As shown, the difference between this embodiment and the first and second embodiments is that the tunnel energy-saving control module is communicatively connected to the operation monitoring and evaluation module, and the operation monitoring and evaluation module analyzes the lighting and ventilation control performance of the tunnel by the tunnel energy-saving control module, and generates an energy-saving control qualified signal or an energy-saving control abnormal signal through the analysis;

[0065] The energy-saving control qualified signal or energy-saving control abnormal signal is sent to the background monitoring end through the tunnel energy-saving control module. When the background monitoring end receives the energy-saving control abnormal signal, it issues an early warning to remind the background management personnel to strengthen the subsequent supervision of the tunnel, thereby ensuring the subsequent operation control performance and energy-saving performance, and further reducing the management difficulty of the tunnel; the specific analysis process of the operation monitoring and evaluation module is as follows:

[0066] A detection period is set, and the real-time lighting brightness of the tunnel target segment i is collected. The deviation value of the real-time lighting brightness compared with the corresponding preset lighting brightness optimal value is marked as the tunnel lighting bias value. The tunnel lighting bias value is numerically compared with the preset tunnel lighting bias threshold. If the tunnel lighting bias value exceeds the preset tunnel lighting bias threshold, it indicates that the current lighting control condition for the tunnel target segment i is not good, and it is judged that the tunnel target segment i is currently in a poor lighting control state;

[0067] Obtain all single durations of the tunnel target section i being in a poor lighting control state during the detection period, mark the number of occurrences of the single duration of the poor lighting control state exceeding the corresponding preset duration threshold as the lighting control abnormality detection value, and sum up all single durations of the poor lighting control state to obtain the total lighting control abnormality time value;

[0068] When ventilating the target tunnel section i, the deviation value of the real-time ventilation speed of the target tunnel section i compared with the set standard ventilation speed is marked as the ventilation speed deviation value, and the ventilation speed deviation value is numerically compared with the preset ventilation speed deviation threshold value. If the ventilation speed deviation value exceeds the preset ventilation speed deviation threshold value, the corresponding ventilation speed deviation value is marked as the ventilation speed abnormal value;

[0069] The ventilation abnormality detection value is obtained by calculating the ratio of the number of ventilation speed abnormal values ​​to the number of ventilation speed deviation values ​​during the detection period, and the value exceeding the preset ventilation speed deviation threshold is marked as the ventilation speed excess value, and the ventilation speed excess values ​​during the detection period are averaged to obtain the ventilation excess analysis value;

[0070] By formula The lighting control abnormality detection value XSi, the total lighting control abnormality time value XFi, the ventilation speed detection value XKi and the ventilation super-analysis value XNi of the tunnel target section i during the detection period are numerically calculated to obtain the ventilation and lighting evaluation value XPi; wherein b1, b2, b3, and b4 are preset proportional coefficients with values ​​greater than zero, and the larger the value of the ventilation and lighting evaluation value XPi, the less ideal the control of the tunnel target section i during the detection period is;

[0071] The ventilation and lighting evaluation value XPi is numerically compared with the preset ventilation and lighting evaluation threshold. If the ventilation and lighting evaluation value XPi exceeds the preset ventilation and lighting evaluation threshold, it indicates that the control performance of the tunnel target section i during the detection period is poor, and the tunnel target section i is marked as a non-optimal section for control;

[0072] The number and proportion of the non-optimal sections in the tunnel are obtained and marked as the tunnel abnormal section value, and the ventilation and lighting evaluation values ​​of all sections in the tunnel are averaged to obtain the tunnel control value, and the ventilation and lighting evaluation value with the largest value is marked as the control abnormal amplitude measurement value;

[0073] The energy-saving control coefficient LM is obtained by numerically calculating the tunnel difference value HF, the tunnel control inspection value HY and the control difference amplitude measurement value HP through the formula LM=mp1*HF+(mp2*HY+mp3*HP) / 2; wherein mp1, mp2 and mp3 are preset proportional coefficients, mp1>mp2>mp3>0.157; and the larger the value of the energy-saving control coefficient LM is, the worse the overall operation control performance of the tunnel during the detection period is;

[0074] The energy-saving control coefficient LM is numerically compared with the preset energy-saving control coefficient threshold. If the energy-saving control coefficient LM exceeds the preset energy-saving control coefficient threshold, it indicates that the operation control performance of the tunnel during the detection period is generally poor, and an energy-saving control abnormality signal is generated; if the energy-saving control coefficient LM does not exceed the preset energy-saving control coefficient threshold, it indicates that the operation control performance of the tunnel during the detection period is generally good, and an energy-saving control qualified signal is generated.

[0075] The working principle of the present invention is as follows: when in use, the vehicle flow segmentation detection module is used to monitor and analyze the vehicle flow of each section in the tunnel in real time, and the vehicle flow analysis value of each section in the tunnel is sent to the lighting brightness decision module and the ventilation necessity detection module. The lighting brightness decision module determines the optimal lighting brightness of each section in the tunnel through tunnel lighting decision analysis. The tunnel energy-saving control module adjusts the brightness according to the optimal lighting brightness of each section. The ventilation necessity detection module analyzes the ventilation necessity of each section in the tunnel to generate a ventilation warning signal or a ventilation non-essential signal. When the tunnel energy-saving control module receives the ventilation warning signal, it starts ventilation of the corresponding section in the tunnel. It can not only automatically and accurately adjust the lighting brightness of each section in the tunnel based on the traffic conditions, but also combine the traffic conditions and environmental conditions of each section in the tunnel to accurately judge the ventilation urgency, so as to realize timely and automatic ventilation of each section in the tunnel, with high automation and intelligence levels, and significantly reduce energy consumption while ensuring tunnel driving safety, reduce tunnel operating costs and improve energy-saving effects.

[0076] The above formulas are all dimensionless and numerical calculations. The formula is a formula obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formula are set by technicians in this field according to actual conditions. The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the contents of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that technicians in the relevant technical field can understand and use the present invention well. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. A vehicle flow detection and analysis system for tunnel energy-saving control, characterized in that: It includes traffic flow segmentation detection module, lighting brightness decision module, ventilation necessity detection module, tunnel energy saving control module and background supervision terminal; The traffic flow segmentation detection module divides the interior of the tunnel into several sections, and marks the corresponding section as the tunnel target section i, where i is a natural number greater than 1; The vehicle flow of the target tunnel section i is monitored in real time, and the vehicle flow analysis value of the target tunnel section i is obtained through analysis, and the vehicle flow analysis value of the target tunnel section i is sent to the lighting brightness decision module and the ventilation necessity detection module; The lighting brightness decision module determines the optimal lighting brightness of each section in the tunnel through tunnel lighting decision analysis, and the tunnel energy-saving control module adjusts the brightness according to the optimal lighting brightness of each section; the ventilation necessity detection module analyzes the ventilation necessity of each section in the tunnel, and generates a ventilation warning signal or a ventilation non-essential signal for the tunnel target section i through analysis. When the ventilation warning signal is generated, the tunnel energy-saving control module starts ventilation for the tunnel target section i.

2. A vehicle flow detection and analysis system for tunnel energy-saving control according to claim 1, characterized in that: The specific method for obtaining the traffic flow analysis value is as follows: The traffic flow analysis value is obtained by numerically calculating the average traffic flow value, congestion time detection value and traffic flow amplitude measurement value of the tunnel target section i.

3. The vehicle flow detection and analysis system for tunnel energy-saving control according to claim 1 is characterized in that: The specific analysis process of tunnel lighting decision analysis is as follows: The traffic flow analysis value of the tunnel target segment i is obtained, and the traffic flow analysis value of the tunnel target segment i is compared with all preset traffic flow analysis value ranges one by one, thereby determining the preset traffic flow analysis value range containing the corresponding traffic flow analysis value and marking it as the optimal range, and marking the preset brightness standard value corresponding to the optimal range as the optimal value of the lighting brightness of the tunnel target segment i.

4. The vehicle flow detection and analysis system for tunnel energy-saving control according to claim 1 is characterized in that: The specific analysis process of the ventilation necessity detection module includes: A number of detection points are set in the tunnel target section i, and the gas quality anomaly value is obtained through gas toxicity detection and analysis. The ventilation emergency value is obtained by numerically calculating the visibility impact value, oxygen detection value and gas quality anomaly value. A preset ventilation emergency threshold value corresponding to the tunnel target section i is allocated. If the ventilation emergency value exceeds the corresponding preset ventilation emergency threshold value, a ventilation warning signal for the tunnel target section i is generated; if the ventilation emergency value does not exceed the corresponding preset ventilation emergency threshold value, a ventilation non-essential signal for the tunnel target section i is generated.

5. The vehicle flow detection and analysis system for tunnel energy-saving control according to claim 4 is characterized in that: The specific analysis process of gas harmfulness detection and analysis is as follows: Obtain the type of harmful gas that needs to be monitored in the tunnel, calculate the average of the real-time concentration of the corresponding type of harmful gas at all detection points to obtain the gas concentration value; mark the product of the gas concentration value of the corresponding type of harmful gas and the corresponding preset hazard weight value as the gas danger value, and sum up all the gas danger values ​​in the tunnel target section i to obtain the gas quality value.

6. A vehicle flow detection and analysis system for tunnel energy-saving control according to claim 4, characterized in that: The specific allocation process of allocating the preset ventilation emergency threshold value adapted to the tunnel target section i is as follows: The traffic flow analysis value of the target tunnel segment i is obtained. If the traffic flow analysis value exceeds the preset traffic flow analysis threshold, the target tunnel segment i is marked as a strict control segment; if the traffic flow analysis value does not exceed the preset traffic flow analysis threshold, the target tunnel segment i is marked as a weak control segment; If the tunnel target section i is a strict control section, a preset ventilation emergency threshold LP1 is allocated to the tunnel target section i; if the tunnel target section i is a weak control section, a preset ventilation emergency threshold LP2 is allocated to the tunnel target section i, and LP2>LP1>0.

7. The vehicle flow detection and analysis system for tunnel energy-saving control according to claim 1 is characterized in that: The tunnel energy-saving control module is communicated with the tunnel line inspection module. The tunnel line inspection module obtains all the power lines that need to be monitored in the tunnel, determines the faulty line through analysis, and sends the faulty line to the tunnel energy-saving control module. After receiving the faulty line, the tunnel energy-saving control module sends the corresponding warning information to the background supervision end.

8. The vehicle flow detection and analysis system for tunnel energy-saving control according to claim 7 is characterized in that: The specific analysis process of the tunnel line investigation module is as follows: Several segmentation points are set on the power line. If the transmission loss value exceeds the preset transmission loss threshold, it is judged that there is an energy consumption anomaly between the corresponding two groups of segmentation points, and the corresponding power line is marked as a faulty line. If all transmission loss values ​​do not exceed the preset transmission loss threshold, all transmission loss values ​​on the corresponding power line are averaged to obtain the transmission consumption measurement value. If the transmission consumption measurement value exceeds the preset transmission consumption measurement threshold, the corresponding power line is marked as a faulty line.

9. The vehicle flow detection and analysis system for tunnel energy-saving control according to claim 7 is characterized in that: The tunnel energy-saving control module is communicated with the operation monitoring and evaluation module. The operation monitoring and evaluation module analyzes the lighting and ventilation control performance of the tunnel by the tunnel energy-saving control module, and generates an energy-saving control qualified signal or an energy-saving control abnormal signal through the analysis.

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