A digital twin model for port liquid bulk processes

Abstract

The present invention discloses a digital twin model for a port liquid bulk cargo process, relates to the field of bulk cargo loading and unloading, and solves the problem of potential safety hazards in existing port liquid bulk cargo methods, comprising: a cargo data module: used to obtain bulk cargo planning data, a port data module: used to obtain loading and unloading wave height difference data, a risk assessment module: used to obtain bulk cargo loading and unloading safety assessment classification data based on bulk cargo planning data and loading and unloading wave height difference data analysis, a scheduling optimization module: used to perform liquid bulk cargo loading and unloading scheduling optimization based on the bulk cargo loading and unloading safety assessment classification data. The present invention can effectively improve the loading and unloading safety of port liquid bulk cargo by performing safety assessment on different liquid bulk cargoes.

Description

Technical Field

[0001] The present invention belongs to the field of bulk cargo handling and relates to data analysis technology, and specifically is a digital twin model for port liquid bulk cargo technology. Background Art

[0002] Liquid bulk cargo refers to bulk cargo that is loaded and unloaded in liquid form during storage and transportation. Liquid bulk cargo can be various types of liquid products, including but not limited to fossil raw materials such as petroleum and asphalt. Liquid bulk cargo loading and unloading refers to the process of loading liquid products from storage facilities or transport vehicles into transport vehicles or storage facilities, or unloading liquid products from transport vehicles or storage facilities. Liquid bulk cargo loading and unloading is a very important link in the entire liquid bulk cargo transportation process, and has a key impact on the safe and efficient transportation of liquid products.

[0003] At present, ports have the following defects when handling liquid bulk cargoes:

[0004] 1. Failure to effectively evaluate the safety of loading and unloading of different types of liquid bulk cargoes in the natural environment, resulting in certain safety hazards when loading and unloading liquid bulk cargoes at the terminal;

[0005] 2. Liquid bulk cargo is loaded and unloaded according to fixed loading and unloading shifts. In the face of interference from various natural factors, it is impossible to optimize the loading and unloading shifts by analyzing the properties of the liquid bulk cargo itself, resulting in low efficiency of cargo loading and unloading at the terminal and difficulty in achieving ideal throughput.

[0006] To this end, a digital twin model for port liquid bulk processes is proposed. Summary of the invention

[0007] In view of the shortcomings of the prior art, the purpose of the present invention is to provide a digital twin model for port liquid bulk cargo processes. The present invention obtains bulk cargo planning data based on the cargo planned loading and unloading speed, planned loading and unloading time range and cargo stability data corresponding to each batch of port liquid bulk cargo, obtains the estimated wave height difference during the loading and unloading periods corresponding to multiple planned loading and unloading time ranges, obtains loading and unloading wave height difference data, calculates multiple bulk cargo loading and unloading safety assessment coefficients according to the bulk cargo planning data and the loading and unloading wave height difference data, obtains the bulk cargo loading and unloading safety assessment coefficient threshold value, and compares it numerically with multiple bulk cargo loading and unloading safety assessment coefficients to obtain bulk cargo loading and unloading safety assessment classification data, and optimizes liquid bulk cargo loading and unloading scheduling according to the bulk cargo loading and unloading safety assessment classification data.

[0008] In order to achieve the above purpose, the present invention includes a cargo data module, a port data module, a risk assessment module and a scheduling optimization module. The specific working process of each module is as follows:

[0009] Cargo data module: obtain the cargo planned loading and unloading speed, planned loading and unloading time range and cargo stability data corresponding to each batch of port liquid bulk cargo, and obtain bulk cargo planning data;

[0010] Port data module: obtain the estimated wave height difference during the loading and unloading periods corresponding to multiple planned loading and unloading time ranges, and obtain the loading and unloading wave height difference data;

[0011] Risk assessment module: Calculate multiple bulk cargo loading and unloading safety assessment coefficients based on bulk cargo plan data and loading and unloading wave height difference data, obtain bulk cargo loading and unloading safety assessment coefficient thresholds, compare them with multiple bulk cargo loading and unloading safety assessment coefficients, and obtain bulk cargo loading and unloading safety assessment classification data;

[0012] Scheduling optimization module: Optimize the scheduling of liquid bulk loading and unloading based on the classification data of bulk loading and unloading safety assessment.

[0013] Further, the cargo data module includes a first data unit and a second data unit;

[0014] The first data unit obtains the planned cargo loading and unloading speed and the planned loading and unloading time range;

[0015] The details are as follows:

[0016] Get the cargo quality corresponding to the current batch of port liquid cargo and obtain the real-time cargo quality;

[0017] Obtain the planned loading and unloading time range corresponding to the current batch of liquid, obtain the duration of the planned loading and unloading time range, and obtain the bulk cargo loading and unloading duration;

[0018] Calculate the ratio of real-time cargo mass to bulk cargo loading and unloading time to obtain the planned cargo loading and unloading speed;

[0019] The second data unit acquires cargo stability data;

[0020] The planned cargo loading and unloading speed, planned loading and unloading time range, and cargo stability data corresponding to each batch of liquid bulk cargo loaded and unloaded at the port on that day are obtained respectively to obtain bulk cargo planning data.

[0021] Furthermore, the second data unit acquires cargo stability data as follows:

[0022] Select a unit mass of liquid cargo as a sample for liquid physical analysis;

[0023] Obtaining a volume value of the liquid analysis sample under a reference temperature environment to obtain a first sample liquid cargo volume;

[0024] Placing the liquid analysis sample and the port liquid cargo at the same dock location, obtaining the volume value of the liquid analysis sample under the dock simulated loading and unloading temperature environment, and obtaining the volume of the second sample liquid cargo;

[0025] Injecting a liquid physical analysis sample into a flow rate test container, obtaining a flow rate value of the liquid physical analysis sample under a reference temperature environment, and obtaining a first liquid flow rate;

[0026] The liquid physical analysis sample and the port liquid cargo are placed at the same dock location, and the above process of obtaining the first liquid flow rate is repeated to obtain the flow rate value of the liquid analysis sample under the dock simulated loading and unloading temperature environment to obtain the second liquid flow rate;

[0027] The first sample liquid cargo volume and the first liquid flow rate are calculated to obtain a cargo benchmark stability value;

[0028] The actual stability value of the cargo is obtained by calculating the volume of the second sample liquid cargo and the second liquid flow rate;

[0029] The cargo benchmark stability value and the cargo actual stability value are defined as cargo stability data;

[0030] The planned cargo loading and unloading speed, planned loading and unloading time range, and cargo stability data corresponding to each batch of liquid bulk cargo loaded and unloaded at the port on that day are obtained respectively to obtain bulk cargo planning data.

[0031] Furthermore, the second data unit acquires the first liquid flow rate as follows:

[0032] Mark two liquid position marking lines at both ends of the flow rate test container, and name them as the first liquid marking line and the second liquid marking line respectively;

[0033] The flow rate test container is tilted at a constant speed until it is inverted, and the time taken for the liquid level of the liquid physical analysis sample to be flush with the second liquid mark line from the first liquid mark line is obtained to obtain the test flow rate time;

[0034] The distance length value between the first liquid marking line and the second liquid marking line is obtained to obtain the marking line distance difference, and the ratio of the marking line distance difference to the test flow rate time is calculated to obtain the first liquid flow rate.

[0035] Furthermore, the port data module acquires the loading and unloading wave height difference data as follows:

[0036] Taking the current value as the starting point of the monitoring period, obtaining a characteristic monitoring duration before the starting point of the monitoring period as the wave height difference monitoring period, and naming several wave fluctuation periods appearing in the wave height difference monitoring period as the first to the i-th wave fluctuation periods respectively;

[0037] Get the real-time wave height difference of the port;

[0038] The wind speed range value of the wave height difference monitoring period is obtained through the weather forecast tool, and the average of the interval endpoints corresponding to the wind speed range value is calculated to obtain the port monitoring wind speed value;

[0039] Obtain bulk cargo planning data, and obtain the planned loading and unloading time range based on the bulk cargo planning data;

[0040] The planned loading and unloading time range is obtained as the future wind monitoring period, and the mainstream wind force value corresponding to the future wind monitoring period is obtained through the weather forecast tool to obtain the estimated wind force value during the loading and unloading period;

[0041] Calculate the estimated wave height difference during loading and unloading period by using the estimated wind force value during loading and unloading period, the real-time wave height difference at the port, and the wind force value monitored at the port;

[0042] The estimated wave height difference during the loading and unloading period is calculated, and the specific formula configuration is as follows:

[0043] ;

[0044] Among them, Hyg is the estimated wave height difference during the loading and unloading period, Fyf is the estimated wind force value during the loading and unloading period, Fsf is the port monitoring wind force value, Lgj is the real-time wave height difference of the port, b1 is the set proportional coefficient and b1 is greater than 0;

[0045] The wave height difference during the loading and unloading period is estimated for each batch of bulk cargo loaded and unloaded at the port on that day, and the loading and unloading wave height difference data is obtained.

[0046] Furthermore, the port data module acquires the real-time wave height difference of the port, as follows:

[0047] Dividing the first wave rising and falling cycle into a wave rising cycle and a wave falling cycle;

[0048] When the sea waves are in the rising cycle, the first sea wave height value is obtained by reading the intersection reading of the highest point of the sea wave and the port water level mark;

[0049] When the sea wave is in the falling cycle, the second sea wave height value is obtained by reading the intersection reading of the lowest point of the sea wave and the port water level mark;

[0050] Calculate the difference between the first wave height value and the second wave height value to obtain the first wave height difference;

[0051] Repeat the above process to obtain the wave height difference corresponding to each wave fluctuation cycle, and get the first to ith wave height differences. Arrange the first to ith wave height differences in descending order according to their numerical values, and define the wave height difference ranked first as the real-time wave height difference of the port.

[0052] Furthermore, the risk assessment module obtains the bulk cargo handling safety assessment classification data, as follows:

[0053] Obtain bulk cargo planning data, and obtain the cargo planned loading and unloading speeds, cargo benchmark stability values, and cargo actual stability values ​​corresponding to different batches of bulk cargo based on the bulk cargo planning data;

[0054] Obtain the estimated wave height difference during the loading and unloading period corresponding to different batches of bulk cargoes based on the loading and unloading wave height difference data;

[0055] The bulk cargo loading and unloading safety assessment coefficient is calculated by calculating the planned cargo loading and unloading speed, the estimated wave height difference during the loading and unloading period, the cargo baseline stability value, and the cargo actual stability value;

[0056] The safety assessment coefficient for bulk cargo loading and unloading is calculated, and the specific formula is configured as follows:

[0057] ;

[0058] Among them, Sax is the safety assessment coefficient for bulk cargo loading and unloading, Hws is the actual stability value of the cargo, Hwj is the benchmark stability value of the cargo, Vzx is the planned cargo loading and unloading speed, Hyg is the estimated wave height difference during the loading and unloading period, c1 and c2 are both set proportional coefficients and both c1 and c2 are greater than 0;

[0059] Obtain the bulk cargo loading and unloading safety assessment coefficients corresponding to different batches of bulk cargo respectively;

[0060] The bulk cargo loading and unloading safety assessment coefficient threshold is obtained, and the bulk cargo loading and unloading safety assessment coefficient is numerically compared with the bulk cargo loading and unloading safety assessment coefficient threshold to obtain the bulk cargo loading and unloading safety assessment classification data.

[0061] Furthermore, the risk assessment module obtains a threshold value of a bulk cargo handling safety assessment coefficient, as follows:

[0062] Obtain cargo planned loading and unloading speed, bulk cargo loading and unloading benchmark wave height difference, and cargo benchmark stability values;

[0063] The planned cargo loading and unloading speed, the bulk cargo loading and unloading reference wave height difference and the cargo reference stability value are calculated to obtain the bulk cargo loading and unloading safety assessment coefficient threshold;

[0064] The threshold value of the safety assessment factor for bulk cargo loading and unloading is calculated, and the specific formula configuration is as follows:

[0065] ;

[0066] Among them, Saxy is the threshold value of the safety assessment coefficient for bulk cargo loading and unloading, Hwj is the cargo benchmark stability value, Vzx is the cargo planned loading and unloading speed, Hyj is the bulk cargo loading and unloading benchmark wave height difference, c1 and c2 are both set proportional coefficients and both c1 and c2 are greater than 0;

[0067] The numerical comparison process of the bulk cargo handling safety assessment factor and the bulk cargo handling safety assessment factor threshold is as follows:

[0068] When the bulk cargo loading and unloading safety assessment coefficient is greater than or equal to the bulk cargo loading and unloading safety assessment coefficient threshold, it is determined that the current bulk cargo belongs to the first cargo loading and unloading interval;

[0069] When the bulk cargo loading and unloading safety assessment coefficient is less than the bulk cargo loading and unloading safety assessment coefficient threshold, it is determined that the current bulk cargo belongs to the second cargo loading and unloading interval.

[0070] Furthermore, the scheduling optimization module performs scheduling optimization of liquid bulk cargo loading and unloading, specifically as follows:

[0071] Obtaining classified data for bulk cargo handling safety assessment;

[0072] Optimize the dispatch of bulk cargo in the first cargo loading and unloading area;

[0073] For bulk cargo in the second cargo loading and unloading area, loading and unloading are carried out normally.

[0074] Furthermore, the scheduling optimization module performs scheduling optimization on the bulk cargo in the first cargo loading and unloading interval, as follows:

[0075] Marking several batches of bulk cargo in the first cargo loading and unloading interval as the first to jth batches of abnormal loading and unloading bulk cargo;

[0076] Obtain the planned loading and unloading time range corresponding to the first to j-th loading and unloading of abnormal bulk cargo, obtain the first to j-th loading and unloading time range, obtain the estimated wave height difference in the loading and unloading period corresponding to each planned loading and unloading time range, and obtain the estimated wave height difference in the first to j-th loading and unloading period;

[0077] Respectively obtain the cargo planned loading and unloading speed, cargo benchmark stability value, and cargo actual stability value corresponding to the first loading and unloading abnormal bulk cargo;

[0078] The planned cargo loading and unloading speed, cargo benchmark stability value, cargo actual stability value corresponding to the first loading and unloading abnormal bulk cargo and the estimated wave height difference during the second loading and unloading period are calculated to obtain the scheduling bulk cargo loading and unloading safety assessment coefficient;

[0079] When the bulk cargo loading and unloading safety assessment coefficient is less than or equal to the bulk cargo loading and unloading safety assessment coefficient threshold, the first loading and unloading abnormal bulk cargo is loaded and unloaded within the second loading and unloading time range;

[0080] When the dispatching bulk cargo loading and unloading safety assessment coefficient is greater than the bulk cargo loading and unloading safety assessment coefficient threshold, the dispatching bulk cargo loading and unloading safety assessment coefficient is calculated by obtaining the estimated wave height difference in the second loading and unloading period, and the calculated safety assessment coefficient is compared with the bulk cargo loading and unloading safety assessment coefficient threshold value;

[0081] The above process is repeated until the dispatching bulk cargo loading and unloading safety assessment coefficient corresponding to the first abnormal bulk cargo loading and unloading is less than or equal to the bulk cargo loading and unloading safety assessment coefficient threshold, and the cargo planned loading and unloading speed, cargo benchmark stability value and cargo actual stability value corresponding to the first abnormal bulk cargo loading and unloading are obtained, and the estimated wave height difference during the loading and unloading period corresponding to each abnormal bulk cargo loading and unloading is used to calculate the dispatching bulk cargo loading and unloading safety assessment coefficient;

[0082] Repeat the loading and unloading scheduling optimization process for the first loading and unloading abnormal bulk cargo, and perform loading and unloading scheduling optimization for each loading and unloading abnormal bulk cargo respectively.

[0083] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0084] 1. The present invention can effectively improve the loading and unloading safety of liquid bulk cargo in ports by acquiring bulk cargo planning data corresponding to liquid bulk cargo and estimated wind force values ​​during the loading and unloading period corresponding to the planned loading and unloading time range of liquid bulk cargo to evaluate the loading and unloading safety.

[0085] 2. The present invention optimizes the loading and unloading scheduling of abnormal bulk cargo by obtaining the bulk cargo planning data and scheduling bulk cargo loading and unloading safety assessment coefficients within different planned loading and unloading time ranges, which can effectively improve the cargo loading and unloading efficiency of the terminal and promote regional economic development by increasing the cargo throughput of the terminal. BRIEF DESCRIPTION OF THE DRAWINGS

[0086] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0087] Figure 1 is the overall system block diagram of the present invention;

[0088] Figure 2 It is a schematic diagram of the flow rate test container in the present invention;

[0089] In the figure: 1 is the top of the container, 2 is the first liquid marking line, 3 is the second liquid marking line, 4 is the liquid physical analysis sample, and 5 is the bottom of the container. DETAILED DESCRIPTION

[0090] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than 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.

[0091] Embodiment 1

[0092] See also Figure 1 , the present invention provides a technical solution: a digital twin model for port liquid bulk cargo process, comprising a cargo data module, a port data module, a risk assessment module, a scheduling optimization module and a server, wherein the cargo data module, the port data module, the risk assessment module and the scheduling optimization module are respectively connected to the server;

[0093] The cargo data module obtains bulk cargo planning data;

[0094] The cargo data module includes a first data unit and a second data unit;

[0095] The first data unit obtains the planned cargo loading and unloading speed and the planned loading and unloading time range, as follows:

[0096] Obtain the cargo mass corresponding to the current batch of port liquid bulk cargo and obtain the real-time cargo mass;

[0097] Get the planned loading and unloading time range corresponding to the current batch of liquid, obtain the duration of the planned loading and unloading time range, and obtain the bulk cargo loading and unloading duration.

[0098] It should be noted here that:

[0099] The planned loading and unloading time range involved here refers specifically to a time range specified for the current bulk cargo loading and unloading;

[0100] Calculate the ratio of real-time cargo mass to bulk cargo loading and unloading time to obtain the planned cargo loading and unloading speed.

[0101] The second data unit obtains cargo stability data, as follows:

[0102] Select a unit mass of liquid bulk cargo as a sample for liquid physical analysis4;

[0103] Obtaining a volume value of the liquid analysis sample under a reference temperature environment to obtain a first sample liquid bulk volume;

[0104] The liquid analysis sample and the port liquid bulk cargo are placed at the same dock location, the volume value of the liquid analysis sample under the dock simulated loading and unloading temperature environment is obtained, and the volume of the second sample liquid bulk cargo is obtained.

[0105] It should be noted here that:

[0106] In this application, the reference temperature environment specifically refers to the temperature value corresponding to the standard temperature environment of liquid bulk cargo during production and transportation;

[0107] The device for obtaining the volume of the liquid bulk cargo here is specifically a measuring cylinder, and the liquid physical analysis sample 4 is stored in the sealed measuring cylinder.

[0108] See also Figure 2 , injecting the liquid physical analysis sample 4 into the flow rate test container, obtaining the flow rate value of the liquid physical analysis sample 4 under the reference temperature environment, and obtaining a first liquid flow rate;

[0109] The first liquid flow rate is obtained as follows:

[0110] Mark two liquid position marking lines at both ends of the flow rate test container, and name them as the first liquid marking line 2 and the second liquid marking line 3 respectively;

[0111] It should be noted here that:

[0112] The distance value between the first liquid marking line 2 and the bottom 5 of the flow rate test container involved here is the same as the distance value between the second liquid marking line 3 and the top 1 of the flow rate test container;

[0113] The flow rate test container is tilted at a constant speed until it is inverted, and the time taken for the liquid level of the liquid physical analysis sample 4 to be flush with the second liquid mark line 3 from the first liquid mark line 2 is obtained to obtain the test flow rate time;

[0114] Obtain the distance length value between the first liquid marking line 2 and the second liquid marking line 3 to obtain the marking line distance difference, calculate the ratio of the marking line distance difference to the test flow rate time, and obtain the first liquid flow rate;

[0115] The liquid physical analysis sample 4 and the port liquid bulk cargo are placed at the same dock location, and the above process of obtaining the first liquid flow rate is repeated to obtain the flow rate value of the liquid analysis sample under the dock simulated loading and unloading temperature environment to obtain the second liquid flow rate.

[0116] It should be noted here that:

[0117] In this application, the simulated loading and unloading temperature environment of the terminal is specifically the temperature value corresponding to the time period mapped to the bulk cargo loading and unloading duration predicted by the weather forecast;

[0118] The first sample liquid bulk volume and the first liquid flow rate are calculated to obtain a cargo benchmark stability value;

[0119] To calculate the benchmark stability value of the cargo, the specific formula is as follows:

[0120] ;

[0121] Wherein, Hwj is the cargo reference stability value, Yyt1 is the first sample liquid bulk cargo volume, Yls1 is the first liquid flow rate, a1 is the set proportional coefficient and a1 is greater than 0;

[0122] The actual stability value of the cargo is obtained by calculating the second sample liquid bulk cargo volume and the second liquid flow rate;

[0123] To calculate the actual stability value of the goods, the specific formula configuration is as follows:

[0124] ;

[0125] Wherein, Hws is the actual stability value of the cargo, Yyt2 is the second sample liquid bulk cargo volume, Yls2 is the second liquid flow rate, a1 is the set proportional coefficient and a1 is greater than 0;

[0126] The cargo benchmark stability value and the cargo actual stability value are obtained for each batch of bulk cargo loaded and unloaded at the port on the same day to obtain cargo stability data;

[0127] Obtain the cargo planned loading and unloading speed, planned loading and unloading time range, and cargo stability data corresponding to each batch of liquid bulk cargo loaded and unloaded at the port on the same day, obtain bulk cargo planning data, and transmit the bulk cargo planning data to the risk assessment module;

[0128] The port data module obtains the height difference data of loading and unloading waves;

[0129] The current value is taken as the starting point of the monitoring period, and the characteristic monitoring duration before the starting point of the monitoring period is obtained as the wave height difference monitoring period. Several wave fluctuation periods that appear in the wave height difference monitoring period are named as the first to i-th wave fluctuation periods respectively.

[0130] It should be noted here that:

[0131] In the present application, i here refers specifically to the numerical value corresponding to the wave fluctuation period, and i is an integer greater than 0;

[0132] Dividing the first wave rising and falling cycle into a wave rising cycle and a wave falling cycle;

[0133] When the sea waves are in the rising cycle, the first sea wave height value is obtained by reading the intersection reading of the highest point of the sea wave and the port water level mark;

[0134] When the sea wave is in the falling cycle, the second sea wave height value is obtained by reading the intersection reading of the lowest point of the sea wave and the port water level mark;

[0135] Calculate the difference between the first wave height value and the second wave height value to obtain the first wave height difference;

[0136] Repeat the above process to obtain the wave height difference corresponding to each wave fluctuation cycle, obtain the first to i-th wave height differences, arrange the first to i-th wave height differences in descending order according to their numerical values, and define the wave height difference ranked first as the real-time wave height difference of the port;

[0137] The wind speed range value of the wave height difference monitoring period is obtained through the weather forecast tool, and the average of the interval endpoints corresponding to the wind speed range value is calculated to obtain the port monitoring wind speed value;

[0138] Obtain bulk cargo planning data, and obtain the planned loading and unloading time range based on the bulk cargo planning data;

[0139] The planned loading and unloading time range is obtained as the future wind monitoring period, and the mainstream wind force value corresponding to the future wind monitoring period is obtained through the weather forecast tool to obtain the estimated wind force value during the loading and unloading period;

[0140] It should be noted here that:

[0141] The mainstream wind force values ​​involved here are specifically the wind force values ​​predicted by the weather forecast tool.

[0142] For example, if the weather forecast tool predicts that the wind speed value range of the port in the future wind speed monitoring period is 7-8m / s, the mainstream wind speed value is the average of the end points of the wind speed value range, and the predicted wind speed monitoring period in the future is 7.5m / s.

[0143] The weather prediction tools involved here can be weather forecast;

[0144] Calculate the estimated wave height difference during loading and unloading period by using the estimated wind force value during loading and unloading period, the real-time wave height difference at the port, and the wind force value monitored at the port;

[0145] The estimated wave height difference during the loading and unloading period is calculated, and the specific formula configuration is as follows:

[0146] ;

[0147] Among them, Hyg is the estimated wave height difference during the loading and unloading period, Fyf is the estimated wind force value during the loading and unloading period, Fsf is the port monitoring wind force value, Lgj is the real-time wave height difference of the port, b1 is the set proportional coefficient and b1 is greater than 0;

[0148] The wave height difference during the loading and unloading period is estimated for each batch of bulk cargo loaded and unloaded at the port on that day, and the loading and unloading wave height difference data is obtained;

[0149] It should be noted here that:

[0150] Since the port is close to the sea on many sides, the effect of wind direction on wave height difference is not considered in this application;

[0151] The estimated wave height difference during loading and unloading period is transmitted to the risk assessment module;

[0152] The risk assessment module conducts bulk cargo loading and unloading safety assessment based on bulk cargo planning data and estimated wave height differences during loading and unloading periods;

[0153] Obtain bulk cargo planning data, and obtain the cargo planned loading and unloading speeds, cargo benchmark stability values, and cargo actual stability values ​​corresponding to different batches of bulk cargo based on the bulk cargo planning data;

[0154] Obtain the estimated wave height difference during the loading and unloading period corresponding to different batches of bulk cargoes based on the loading and unloading wave height difference data;

[0155] The bulk cargo loading and unloading safety assessment coefficient is calculated by calculating the planned cargo loading and unloading speed, the estimated wave height difference during the loading and unloading period, the cargo baseline stability value, and the cargo actual stability value;

[0156] The safety assessment coefficient for bulk cargo loading and unloading is calculated, and the specific formula is configured as follows:

[0157] ;

[0158] Among them, Sax is the safety assessment coefficient for bulk cargo loading and unloading, Hws is the actual stability value of the cargo, Hwj is the benchmark stability value of the cargo, Vzx is the planned cargo loading and unloading speed, Hyg is the estimated wave height difference during the loading and unloading period, c1 and c2 are both set proportional coefficients and both c1 and c2 are greater than 0;

[0159] Obtain the bulk cargo loading and unloading safety assessment coefficients corresponding to different batches of bulk cargo respectively;

[0160] Obtaining a bulk cargo loading and unloading safety assessment coefficient threshold, comparing the bulk cargo loading and unloading safety assessment coefficient with the bulk cargo loading and unloading safety assessment coefficient threshold, and obtaining bulk cargo loading and unloading safety assessment classification data;

[0161] The threshold value of the safety assessment factor for bulk cargo loading and unloading is obtained as follows:

[0162] Obtain cargo planned loading and unloading speed, bulk cargo loading and unloading benchmark wave height difference, and cargo benchmark stability values;

[0163] The planned cargo loading and unloading speed, the bulk cargo loading and unloading reference wave height difference and the cargo reference stability value are calculated to obtain the bulk cargo loading and unloading safety assessment coefficient threshold;

[0164] It should be noted here that:

[0165] The reference wave height difference for bulk cargo loading and unloading involved here is the average of the endpoints of the ideal wave height difference range when the current type of loading and unloading is carried out at the port;

[0166] The threshold value of the safety assessment factor for bulk cargo loading and unloading is calculated, and the specific formula configuration is as follows:

[0167] ;

[0168] Among them, Saxy is the threshold value of the safety assessment coefficient for bulk cargo loading and unloading, Hwj is the cargo benchmark stability value, Vzx is the planned cargo loading and unloading speed, Hyj is the benchmark wave height difference for bulk cargo loading and unloading, c1 and c2 are both set proportional coefficients and both c1 and c2 are greater than 0.

[0169] The numerical comparison process of the bulk cargo handling safety assessment factor and the bulk cargo handling safety assessment factor threshold is as follows:

[0170] When the bulk cargo loading and unloading safety assessment coefficient is greater than or equal to the bulk cargo loading and unloading safety assessment coefficient threshold, it is determined that the current bulk cargo belongs to the first cargo loading and unloading interval;

[0171] When the bulk cargo loading and unloading safety assessment coefficient is less than the bulk cargo loading and unloading safety assessment coefficient threshold, it is determined that the current bulk cargo belongs to the second cargo loading and unloading interval;

[0172] The risk assessment module obtains the classified data of bulk cargo handling safety assessment and transmits it to the scheduling optimization module;

[0173] The scheduling optimization module optimizes the scheduling of liquid bulk cargo loading and unloading based on the classification data of bulk cargo loading and unloading safety assessment;

[0174] Obtaining classified data for bulk cargo handling safety assessment;

[0175] For bulk cargo in the first cargo loading and unloading area, the terminal optimizes its scheduling as follows:

[0176] Marking several batches of bulk cargo in the first cargo loading and unloading interval as the first to jth batches of abnormal loading and unloading bulk cargo;

[0177] It should be noted here that:

[0178] In this application, j is the total number of batches corresponding to the loading and unloading of abnormal bulk cargo, and j involved here is an integer greater than 0;

[0179] Obtain the planned loading and unloading time range corresponding to the first to j-th loading and unloading of abnormal bulk cargo, obtain the first to j-th loading and unloading time range, obtain the estimated wave height difference in the loading and unloading period corresponding to each planned loading and unloading time range, and obtain the estimated wave height difference in the first to j-th loading and unloading period;

[0180] Respectively obtain the cargo planned loading and unloading speed, cargo benchmark stability value, and cargo actual stability value corresponding to the first loading and unloading abnormal bulk cargo;

[0181] The planned cargo loading and unloading speed, cargo benchmark stability value, cargo actual stability value corresponding to the first loading and unloading abnormal bulk cargo and the estimated wave height difference during the second loading and unloading period are calculated to obtain the scheduling bulk cargo loading and unloading safety assessment coefficient;

[0182] When the bulk cargo loading and unloading safety assessment coefficient is less than or equal to the bulk cargo loading and unloading safety assessment coefficient threshold, the first loading and unloading abnormal bulk cargo is loaded and unloaded within the second loading and unloading time range;

[0183] When the dispatching bulk cargo loading and unloading safety assessment coefficient is greater than the bulk cargo loading and unloading safety assessment coefficient threshold, the dispatching bulk cargo loading and unloading safety assessment coefficient is calculated by obtaining the estimated wave height difference in the second loading and unloading period, and the calculated safety assessment coefficient is compared with the bulk cargo loading and unloading safety assessment coefficient threshold value;

[0184] The above process is repeated until the dispatching bulk cargo loading and unloading safety assessment coefficient corresponding to the first abnormal bulk cargo loading and unloading is less than or equal to the bulk cargo loading and unloading safety assessment coefficient threshold, and the cargo planned loading and unloading speed, cargo benchmark stability value and cargo actual stability value corresponding to the first abnormal bulk cargo loading and unloading are obtained, and the estimated wave height difference during the loading and unloading period corresponding to each abnormal bulk cargo loading and unloading is used to calculate the dispatching bulk cargo loading and unloading safety assessment coefficient;

[0185] Repeat the loading and unloading scheduling optimization process for the first loading and unloading abnormal bulk cargo, and optimize the loading and unloading scheduling for each loading and unloading abnormal bulk cargo respectively;

[0186] For bulk cargo in the second cargo loading and unloading area, the terminal will load and unload it normally;

[0187] In this application, if corresponding calculation formulas appear, the above calculation formulas are all dimensionless and take their numerical calculations. The weight coefficients, proportional coefficients and other coefficients in the formulas are set to a result value obtained by quantifying each parameter. The size of the weight coefficient and the proportional coefficient can be determined as long as it does not affect the proportional relationship between the parameter and the result value.

[0188] 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 content 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 those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A digital twin model for port liquid bulk cargo process, characterized in that: include: Cargo data module: obtain the cargo planned loading and unloading speed, planned loading and unloading time range and cargo stability data corresponding to each batch of port liquid bulk cargo, and obtain bulk cargo planning data; Port data module: obtain the estimated wave height difference during the loading and unloading periods corresponding to multiple planned loading and unloading time ranges, and obtain the loading and unloading wave height difference data; Risk assessment module: Calculate multiple bulk cargo loading and unloading safety assessment coefficients based on bulk cargo plan data and loading and unloading wave height difference data, obtain bulk cargo loading and unloading safety assessment coefficient thresholds, compare them with multiple bulk cargo loading and unloading safety assessment coefficients respectively, and obtain bulk cargo loading and unloading safety assessment classification data; Scheduling optimization module: optimizes liquid bulk cargo loading and unloading scheduling based on bulk cargo loading and unloading safety assessment classification data; The port data module acquires the loading and unloading wave height difference data as follows: Taking the current value as the starting point of the monitoring period, obtaining a characteristic monitoring duration before the starting point of the monitoring period as the wave height difference monitoring period, and naming several wave fluctuation periods appearing in the wave height difference monitoring period as the first to the i-th wave fluctuation periods respectively; Get the real-time wave height difference of the port; Obtain the wind force range value during the wave height difference monitoring period, calculate the average of the interval endpoints corresponding to the wind force range value, and obtain the port monitoring wind force value; Obtain bulk cargo planning data, and obtain the planned loading and unloading time range based on the bulk cargo planning data; Obtain the planned loading and unloading time range as the future wind monitoring period, obtain the mainstream wind force value corresponding to the future wind monitoring period, and obtain the estimated wind force value during the loading and unloading period; Calculate the estimated wave height difference during loading and unloading period by using the estimated wind force value during loading and unloading period, the real-time wave height difference at the port, and the wind force value monitored at the port; The estimated wave height difference during the loading and unloading period is calculated, and the specific formula configuration is as follows: ； Among them, Hyg is the estimated wave height difference during the loading and unloading period, Fyf is the estimated wind force value during the loading and unloading period, Fsf is the port monitoring wind force value, Lgj is the real-time wave height difference of the port, b1 is the set proportional coefficient and b1 is greater than 0; The wave height difference during the loading and unloading period is estimated for each batch of bulk cargo loaded and unloaded at the port on that day, and the loading and unloading wave height difference data is obtained; The port data module obtains the real-time wave height difference of the port, as follows: Dividing the first wave rising and falling cycle into a wave rising cycle and a wave falling cycle; When the sea waves are in the rising cycle, the first sea wave height value is obtained by reading the intersection reading of the highest point of the sea wave and the port water level mark; When the sea wave is in the falling cycle, the second sea wave height value is obtained by reading the intersection reading of the lowest point of the sea wave and the port water level mark; Calculate the difference between the first wave height value and the second wave height value to obtain the first wave height difference; The wave height difference corresponding to each wave fluctuation cycle is obtained respectively to obtain the first to ith wave height differences, the first to ith wave height differences are arranged in descending order, and the wave height difference ranked first is defined as the real-time wave height difference of the port; The risk assessment module obtains the classified data of bulk cargo handling safety assessment, as follows: Obtain bulk cargo planning data, and obtain the cargo planned loading and unloading speeds, cargo benchmark stability values, and cargo actual stability values ​​corresponding to different batches of bulk cargo based on the bulk cargo planning data; Obtain the estimated wave height difference during the loading and unloading period corresponding to different batches of bulk cargoes based on the loading and unloading wave height difference data; The bulk cargo loading and unloading safety assessment coefficient is calculated by calculating the planned cargo loading and unloading speed, the estimated wave height difference during the loading and unloading period, the cargo baseline stability value, and the cargo actual stability value; The safety assessment factor for bulk cargo loading and unloading is calculated using the following formula: ； Among them, Sax is the safety assessment coefficient for bulk cargo loading and unloading, Hws is the actual stability value of the cargo, Hwj is the benchmark stability value of the cargo, Vzx is the planned cargo loading and unloading speed, Hyg is the estimated wave height difference during the loading and unloading period, c1 and c2 are both set proportional coefficients and both c1 and c2 are greater than 0; The bulk cargo loading and unloading safety assessment coefficients corresponding to different batches of bulk cargo are obtained respectively to obtain a plurality of bulk cargo loading and unloading safety assessment coefficients; Obtaining a bulk cargo loading and unloading safety assessment coefficient threshold, and numerically comparing a plurality of bulk cargo loading and unloading safety assessment coefficients with the bulk cargo loading and unloading safety assessment coefficient threshold to obtain bulk cargo loading and unloading safety assessment classification data; The risk assessment module obtains the threshold value of the bulk cargo loading and unloading safety assessment coefficient, as follows: Obtain cargo planned loading and unloading speed, bulk cargo loading and unloading benchmark wave height difference, and cargo benchmark stability values; The planned cargo loading and unloading speed, the bulk cargo loading and unloading reference wave height difference and the cargo reference stability value are calculated to obtain the bulk cargo loading and unloading safety assessment coefficient threshold; The threshold value of the safety assessment factor for bulk cargo loading and unloading is calculated, and the specific formula configuration is as follows: ； Among them, Saxy is the threshold value of the safety assessment coefficient for bulk cargo loading and unloading, Hwj is the cargo benchmark stability value, Vzx is the cargo planned loading and unloading speed, Hyj is the bulk cargo loading and unloading benchmark wave height difference, c1 and c2 are both set proportional coefficients and both c1 and c2 are greater than 0; The numerical comparison process of the bulk cargo handling safety assessment factor and the bulk cargo handling safety assessment factor threshold is as follows: When the bulk cargo loading and unloading safety assessment coefficient is greater than or equal to the bulk cargo loading and unloading safety assessment coefficient threshold, it is determined that the current bulk cargo belongs to the first cargo loading and unloading interval; When the bulk cargo loading and unloading safety assessment coefficient is less than the bulk cargo loading and unloading safety assessment coefficient threshold, it is determined that the current bulk cargo belongs to the second cargo loading and unloading interval.

2. A digital twin model for port liquid bulk cargo process according to claim 1, characterized in that: The cargo data module includes a first data unit and a second data unit; The first data unit obtains the planned cargo loading and unloading speed and the planned loading and unloading time range, which specifically includes the following: Get the cargo quality corresponding to the current batch of port liquid cargo and obtain the real-time cargo quality; Obtain the planned loading and unloading time range corresponding to the current batch of liquid, obtain the duration of the planned loading and unloading time range, and obtain the bulk cargo loading and unloading duration; Calculate the ratio of real-time cargo mass to bulk cargo loading and unloading time to obtain the planned cargo loading and unloading speed; The second data unit is used to obtain cargo stability data; The planned cargo loading and unloading speed, planned loading and unloading time range, and cargo stability data corresponding to each batch of liquid bulk cargo loaded and unloaded at the port on that day are obtained to obtain bulk cargo planning data.

3. A digital twin model for port liquid bulk cargo process according to claim 2, characterized in that: The second data unit acquires cargo stability data as follows: Select a unit mass of liquid cargo as a sample for liquid physical analysis; Obtaining a volume value of the liquid analysis sample under a reference temperature environment to obtain a first sample liquid cargo volume; Placing the liquid analysis sample and the port liquid cargo at the same dock location, obtaining the volume value of the liquid analysis sample under the dock simulated loading and unloading temperature environment, and obtaining the volume of the second sample liquid cargo; Injecting a liquid physical analysis sample into a flow rate test container, obtaining a flow rate value of the liquid physical analysis sample under a reference temperature environment, and obtaining a first liquid flow rate; The liquid physical analysis sample and the port liquid cargo are placed at the same dock location, and the process of obtaining the first liquid flow rate is repeated to obtain the flow rate value of the liquid analysis sample under the dock simulated loading and unloading temperature environment to obtain the second liquid flow rate; The first sample liquid cargo volume and the first liquid flow rate are calculated to obtain a cargo benchmark stability value; The actual stability value of the cargo is obtained by calculating the volume of the second sample liquid cargo and the second liquid flow rate; The cargo benchmark stability value and the cargo actual stability value are defined as cargo stability data; The planned cargo loading and unloading speed, planned loading and unloading time range, and cargo stability data corresponding to each batch of liquid bulk cargo loaded and unloaded at the port on that day are obtained respectively to obtain bulk cargo planning data.

4. A digital twin model for port liquid bulk cargo process according to claim 3, characterized in that: The second data unit acquires the first liquid flow rate as follows: Mark two liquid position marking lines at both ends of the flow rate test container, and name them as the first liquid marking line and the second liquid marking line respectively; The flow rate test container is tilted at a uniform speed to an inverted state, and the time taken for the liquid level of the liquid physical analysis sample to be flush with the second liquid mark line from the first liquid mark line is obtained to obtain the test flow rate time; The distance length value between the first liquid marking line and the second liquid marking line is obtained to obtain the marking line distance difference, and the ratio of the marking line distance difference to the test flow rate time is calculated to obtain the first liquid flow rate.

5. The digital twin model for port liquid bulk cargo process according to claim 1, characterized in that: The scheduling optimization module performs scheduling optimization for liquid bulk cargo loading and unloading, as follows: Obtaining classified data for bulk cargo handling safety assessment; Optimize the dispatch of bulk cargo in the first cargo loading and unloading area; For bulk cargo in the second cargo loading and unloading area, load and unload it normally; The scheduling optimization of bulk cargo in the first cargo loading and unloading area is as follows: Marking several batches of bulk cargo in the first cargo loading and unloading interval as the first to jth batches of abnormal loading and unloading bulk cargo respectively; Obtain the planned loading and unloading time range corresponding to the first to j-th loading and unloading of abnormal bulk cargo, obtain the first to j-th loading and unloading time range, obtain the estimated wave height difference in the loading and unloading period corresponding to each planned loading and unloading time range, and obtain the estimated wave height difference in the first to j-th loading and unloading period; respectively obtaining the cargo planned loading and unloading speed, cargo benchmark stability value, and cargo actual stability value corresponding to the first loading and unloading abnormal bulk cargo; The planned cargo loading and unloading speed, cargo benchmark stability value, cargo actual stability value corresponding to the first loading and unloading abnormal bulk cargo and the estimated wave height difference during the second loading and unloading period are calculated to obtain the scheduling bulk cargo loading and unloading safety assessment coefficient; When the bulk cargo loading and unloading safety assessment coefficient is less than or equal to the bulk cargo loading and unloading safety assessment coefficient threshold, the first loading and unloading abnormal bulk cargo is loaded and unloaded within the second loading and unloading time range; When the dispatching bulk cargo loading and unloading safety assessment coefficient is greater than the bulk cargo loading and unloading safety assessment coefficient threshold, the dispatching bulk cargo loading and unloading safety assessment coefficient is calculated by obtaining the estimated wave height difference in the second loading and unloading period, and the calculated safety assessment coefficient is compared with the bulk cargo loading and unloading safety assessment coefficient threshold value; The above process is repeated until the dispatching bulk cargo loading and unloading safety assessment coefficient corresponding to the first abnormal bulk cargo loading and unloading is less than or equal to the bulk cargo loading and unloading safety assessment coefficient threshold, and the cargo planned loading and unloading speed, cargo benchmark stability value and cargo actual stability value corresponding to the first abnormal bulk cargo loading and unloading are obtained, and the estimated wave height difference during the loading and unloading period corresponding to each abnormal bulk cargo loading and unloading is used to calculate the dispatching bulk cargo loading and unloading safety assessment coefficient; Repeat the loading and unloading scheduling optimization process for the first loading and unloading abnormal bulk cargo, and perform loading and unloading scheduling optimization for each loading and unloading abnormal bulk cargo respectively.

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