Engineering mechanical equipment lease management method and system

Abstract

The invention relates to the technical field of engineering mechanical equipment lease management, in particular to a lease management method and system for engineering mechanical equipment. Comprising the following steps: S1, acquiring mechanical parameters, operation states, historical use data and historical maintenance data of engineering mechanical equipment, and dividing the engineering mechanical equipment into equipment to be leased and leased equipment; s2, performing performance index evaluation and working condition index evaluation on the to-be-leased equipment in combination with mechanical parameters, historical use data and historical maintenance data, and recording idle time of the to-be-leased equipment at the same time; s3, acquiring demand data of the leasing customer, performing combined analysis according to the demand data in combination with the performance index and the working condition index, acquiring to-be-leased equipment capable of meeting the demand data, and predicting the number of renewal days in the demand data; by accurately acquiring the mechanical parameters, the operation state and the historical use and maintenance data of the engineering mechanical equipment, the actual condition of each piece of equipment can be comprehensively known.

Description

Technical Field

[0001] The present invention relates to the technical field of engineering machinery equipment leasing management, and in particular to a leasing management method and system for engineering machinery equipment. Background Art

[0002] Traditional leasing management technology aims to achieve a reasonable allocation of equipment resources and meet the temporary needs of construction companies for machinery and equipment, so as to reduce construction costs and improve construction efficiency.

[0003] At present, leasing companies usually rely on manual recording of equipment information, select suitable equipment from a limited known equipment reserve and arrange transportation according to the general needs put forward orally or in writing by customers, but it is difficult to conduct comprehensive and real-time performance monitoring and working condition analysis of the equipment, and it is impossible to timely know the actual operating time and potential faults of the equipment under different complex working conditions, which leads to untimely equipment maintenance, shortened service life, increased maintenance costs, and may also affect the progress of customer projects due to sudden equipment failures. Therefore, a leasing management method and system for construction machinery equipment is proposed. Summary of the invention

[0004] The purpose of the present invention is to provide a leasing management method and system for construction machinery equipment to solve the problems raised in the above-mentioned background technology.

[0005] In order to solve the above technical problems, one of the purposes of the present invention is to provide a leasing management method for construction machinery equipment, comprising the following steps:

[0006] S1. Obtain mechanical parameters, operating status, historical usage data, and historical maintenance data of engineering machinery and equipment, and classify engineering machinery and equipment into equipment to be leased and equipment that has been leased;

[0007] S2. Evaluate the performance and working condition of the equipment to be leased in combination with mechanical parameters, historical usage data, and historical maintenance data, and record the idle time of the equipment to be leased;

[0008] S3. Obtain the demand data of the leasing customers, analyze the demand data in combination with the performance indicators and the working condition indicators, obtain the equipment to be leased that can meet the demand data, and predict the renewal days in the demand data;

[0009] S4. Analyze the renewal index of the equipment to be leased by combining the predicted renewal days with the performance index and the working condition index, and then make a priority recommendation calculation for the equipment to be leased by combining the idle time and the renewal index;

[0010] S5. Analyze the fault warning time by combining the operating status of the leased equipment with the mechanical parameters, and then compare the fault warning time with the remaining lease time. When the fault warning time is less than the remaining lease time, send a maintenance reminder to the equipment management end.

[0011] As a further improvement of the present technical solution, S1 collects relevant data of all engineering machinery equipment by establishing a database on the equipment management end, and then acquires relevant data of engineering machinery equipment from the database on the equipment management end by establishing a data transmission connection with the equipment management end, including mechanical parameters, operating status, historical usage data, and historical maintenance data of each engineering machinery equipment.

[0012] As a further improvement of the present technical solution, S1 sets the status of each construction machinery equipment at the equipment management end, namely, equipment to be rented and equipment already rented. When the construction machinery equipment is rented to a rental customer, it is adjusted to equipment already rented, and when it is idle, it is equipment to be rented.

[0013] As a further improvement of the technical solution, S2 comprises the following steps:

[0014] S2.1. Evaluate the performance and working condition of the equipment to be leased in combination with mechanical parameters, historical usage data, and historical maintenance data to obtain the performance and working condition indicators of each equipment to be leased;

[0015] The performance indicators are the engineering requirements that the equipment to be leased can adapt to;

[0016] The working condition indicator is the working time under different engineering requirements;

[0017] S2.2. Record the idle time of the equipment to be leased, and obtain the idle time of each equipment to be leased.

[0018] As a further improvement of the technical solution, the steps of S3 are as follows:

[0019] S3.1. Obtain the demand data of the leasing customer, and analyze and extract the engineering requirements and leasing time of the demand data to obtain the corresponding engineering requirements and leasing time of the leasing customer;

[0020] S3.2. Match and analyze each equipment to be leased by combining the demand data with the performance index and the working condition index, and obtain equipment to be leased that meets both the performance index and the working condition index of the demand data;

[0021] S3.3. Obtain customer information from the demand data, search for engineering information on the Internet based on the customer information, and then combine the demand data with the network engineering information to obtain the customer's engineering plan information and real-time engineering progress. Then, predict the equipment working time based on the engineering plan information and real-time engineering progress, and use the predicted working time minus the remaining time corresponding to the leasing customer as the predicted renewal days.

[0022] As a further improvement of the technical solution, the step of S4 is as follows:

[0023] S4.1. Combine the performance index and the working condition index with the engineering requirements to predict the normal working hours of the leased equipment, and then analyze the renewal index by combining the predicted normal working hours with the predicted renewal days. The more the predicted normal working hours exceed the predicted renewal days, the higher the renewal index. Conversely, when the predicted normal working hours are lower than the predicted renewal days, the lower the renewal index.

[0024] The longer the idle time, the higher the idle time score;

[0025] S4.2. Set weights for the renewal index and idle time, and then combine the idle time and renewal index of the equipment to be leased to perform priority recommendation calculation. The higher the priority recommendation score, the higher the ranking recommended to the leasing customer.

[0026] As a further improvement of the present technical solution, the formula of S4 is as follows:

[0027] T normal =a×P+b×C+c×E+d

[0028] Among them, T normal To predict normal working time, P is the performance index of the equipment to be rented, C is the working condition index, E is the engineering requirement, a, b, c are coefficients determined by fitting training of historical data, and d is a constant term;

[0029]

[0030] Among them, RI is the renewal index. The above formula indicates that the more the normal working hours exceed the renewal days, the higher the renewal index;

[0031] T normal ≤T remain ,RI=0

[0032] The above formula indicates that the equipment may not continue to work normally during the renewal period according to the forecast, and the renewal index is set to the minimum;

[0033] PRS=w RI ×RI+w IS ×IS

[0034] Among them, PRS is the priority recommendation score of the equipment to be leased, w RI is the renewal index weight, w IS is the idle time score weight, and IS is the idle time score.

[0035] As a further improvement of the technical solution, the step of S5 is as follows:

[0036] S5.1. Analyze the fault warning time by combining the operating status of the leased equipment with the mechanical parameters, and then compare the fault warning time with the remaining lease time;

[0037] S5.2: When S5.1 shows that the fault warning time is less than the remaining lease time, a maintenance reminder is sent to the equipment management terminal;

[0038] S5.3. When S5.1 shows that the fault warning time is greater than the remaining lease time, continue monitoring.

[0039] The second object of the present invention is to provide a leasing management system for construction machinery equipment, including any one of the above-mentioned leasing management methods for construction machinery equipment, including an equipment classification unit, a to-be-leased equipment management unit and a leased equipment management unit;

[0040] The equipment classification unit is used to obtain mechanical parameters, operating status, historical usage data, and historical maintenance data of the engineering machinery equipment, and to classify the engineering machinery equipment into equipment to be rented and equipment that has been rented;

[0041] The equipment management unit to be leased is used to evaluate the performance index and the working condition index, record the idle time of the equipment to be leased, and predict the renewal days in the demand data, analyze the renewal index of the equipment to be leased by combining the predicted renewal days with the performance index and the working condition index, and then perform priority recommendation calculation on the equipment to be leased in combination with the idle time and the renewal index;

[0042] The leased equipment management unit is used to analyze the fault warning time by combining the operating status of the leased equipment with the mechanical parameters, and then compare the fault warning time with the remaining lease time. When the fault warning time is less than the remaining lease time, a maintenance reminder is sent to the equipment management terminal.

[0043] Compared with the prior art, the present invention has the following beneficial effects:

[0044] 1. A leasing management method and system for construction machinery equipment, which can fully understand the actual condition of each equipment by accurately acquiring the mechanical parameters, operating status, historical use and maintenance data of construction machinery equipment. When facing a leasing order, it can quickly screen out the equipment to be leased whose performance indicators and working condition indicators meet the requirements, avoid equipment mismatch, greatly shorten the deployment time, improve the equipment rental rate, and reduce idleness.

[0045] 2. A leasing management method and system for construction machinery equipment, which monitors the leased equipment in real time, predicts the time of failure in advance, and notifies maintenance in time when the failure warning time is less than the remaining lease time, so as to avoid sudden serious failure of the equipment during the lease period and cause losses to customers. At the same time, it reduces contract disputes caused by equipment failure and maintains the company's good business image. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 It is the overall flow chart of the present invention;

[0047] Figure 2 A flowchart of obtaining the idle time of each device to be rented according to the present invention;

[0048] Figure 3 A flowchart of the present invention for obtaining the engineering requirements and leasing time corresponding to the leasing customer;

[0049] Figure 4 A flowchart of the present invention combining the idle time of the equipment to be leased and the renewal index to perform priority recommendation calculation;

[0050] Figure 5 A flowchart of sending a maintenance reminder to a device management terminal according to the present invention;

[0051] Figure 6 It is a structural principle diagram of the equipment classification unit of the present invention.

[0052] The meaning of each number in the figure is:

[0053] 10. Equipment classification unit; 20. Equipment management unit for lease; 30. Leased equipment management unit. DETAILED DESCRIPTION

[0054] 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.

[0055] like Figure 1 - Figure 6As shown, one of the purposes of the present invention is to provide a leasing management method for construction machinery equipment, comprising the following steps:

[0056] S1. Obtain mechanical parameters, operating status, historical usage data, and historical maintenance data of engineering machinery and equipment, and classify engineering machinery and equipment into equipment to be leased and equipment that has been leased;

[0057] S1 collects all the relevant data of engineering machinery equipment by establishing a database on the equipment management side, and then acquires the relevant data of engineering machinery equipment from the database on the equipment management side by establishing a data transmission connection with the equipment management side, including the mechanical parameters, operating status, historical usage data, and historical maintenance data of each engineering machinery equipment. The specific steps are as follows:

[0058] Database selection: Choose a suitable database management system based on the characteristics of engineering machinery data, the expected data volume, and future scalability requirements. If the data volume is large and the transaction processing and data consistency requirements are high, Oracle can be considered; if open source and ease of use are sought, MySQL is a good choice; for some scenarios with extremely high real-time requirements, frequent reading and writing, and relatively simple data structures, Redis can be used to cache some key data to assist in querying;

[0059] Data entry: Develop a data collection program, which can be a small program running on the device side, automatically collecting real-time data through sensors and uploading it to the database, or a manual entry interface for equipment maintenance personnel to enter relevant information after repair and maintenance, ensuring that all types of data are accurately entered into the corresponding database table;

[0060] Determine the connection protocol: If the device management end and the data acquisition end are in the same local area network and have high requirements for real-time performance and stability, TCP / IP protocol is preferred to ensure reliable and orderly data transmission and reduce the risk of data loss and disorder.

[0061] S1 sets the status of each construction machinery equipment on the equipment management side, namely, equipment to be rented and equipment already rented. When the construction machinery equipment is rented to a rental customer, it is adjusted to equipment already rented, and when it is idle, it is equipment to be rented.

[0062] S2. Evaluate the performance and working condition of the equipment to be leased in combination with mechanical parameters, historical usage data, and historical maintenance data, and record the idle time of the equipment to be leased;

[0063] S2 includes the following steps:

[0064] S2.1. Evaluate the performance and working condition of the equipment to be leased in combination with mechanical parameters, historical usage data, and historical maintenance data to obtain the performance and working condition indicators of each equipment to be leased;

[0065] The performance indicators are the engineering requirements that the equipment to be leased can adapt to;

[0066] The working condition indicator is the working time under different engineering requirements. The specific steps are as follows:

[0067] Performance index evaluation: Obtain the mechanical parameters, historical usage data, and historical maintenance data of the equipment to be leased from the database. Since the data magnitude and units of different equipment may vary, the data must first be standardized. According to the type of construction machinery, key performance dimensions are divided and weights are set for each key performance dimension. The weights can be determined based on the experience of industry experts, market demand research, and historical data analysis.

[0068]

[0069] Among them, P is the comprehensive score of performance indicators, n is the number of key performance dimensions of the equipment, and w i is the weight of the i-th key performance dimension, s i is the score value;

[0070] Evaluation of working condition indicators: Classify the project requirements according to factors such as the complexity of working conditions and the intensity of operations, such as light working conditions (such as site leveling, material handling, etc.), medium working conditions (such as foundation excavation, small-scale building construction, etc.), and heavy working conditions (such as large-scale mining, large-scale bridge construction, etc.). Filter the equipment working time records corresponding to different working conditions from the historical usage data, calculate the proportion of working time of each equipment to be rented under different working conditions, and then set weights according to the importance of different working conditions;

[0071]

[0072] Among them, C is the comprehensive score of working condition indicators, m is the type of working condition, and w is k is the weight of the kth operating condition, r k is the proportion of working time under the corresponding working conditions.

[0073] S2.2. Record the idle time of the equipment to be leased and obtain the idle time of each equipment to be leased. The specific steps are as follows:

[0074] Determine the starting point of idle time recording: In the equipment management system, when the initial state of the equipment is set to the waiting-for-rental state, record the initial timestamp when the equipment enters the waiting-for-rental state;

[0075] Real-time monitoring of equipment status changes: By establishing a data interaction mechanism with relevant business operation modules, the system can obtain equipment status change information in real time. Whenever the equipment is returned after leasing or a new leasing order is signed, resulting in a change in equipment status, the system receives the corresponding status update signal.

[0076] Calculate idle time: When you need to obtain the idle time of the device, subtract the timestamp stored at the rental start time from the current time. The time difference is the idle time of the device.

[0077] S3. Obtain the demand data of the leasing customers, analyze the demand data in combination with the performance indicators and the working condition indicators, obtain the equipment to be leased that can meet the demand data, and predict the renewal days in the demand data;

[0078] The steps for S3 are as follows:

[0079] S3.1. Obtain the demand data of the leasing customer, and analyze and extract the engineering requirements and leasing time of the demand data to obtain the corresponding engineering requirements and leasing time of the leasing customer;

[0080] S3.2. Combine the demand data with the performance indicators and working condition indicators to perform matching analysis on each equipment to be rented, and obtain the equipment to be rented that meets both the performance indicators and working condition indicators of the demand data. The specific steps are as follows:

[0081] Establish demand data collection channels: Provide customers with a clear and easy-to-use rental demand submission interface on the rental business platform. Set corresponding form fields in the interface to guide customers to fill in key information, such as equipment type, expected location of use, expected rental start time, and expected rental end time. After the customer submits the demand data, use the programming language to write verification logic on the backend server to check the format and rationality of the input data;

[0082] Engineering requirements extraction: Extract engineering requirements from the fields such as equipment type and special function requirements filled in by the customer. By establishing a mapping table between equipment function and engineering requirements, the corresponding engineering requirement information can be accurately extracted according to the equipment type and special functions selected by the customer, and organized into a structured data form for subsequent analysis;

[0083] Lease time analysis: directly obtain the expected lease start time and expected lease end time filled in by the customer, and calculate the lease duration;

[0084] Performance index matching judgment: for each equipment to be rented, judge whether its performance index meets the customer's engineering requirements, formulate detailed matching rules according to the equipment type and specific engineering requirements. For excavators, customers require the digging depth to be at least 5 meters. If the digging depth in the performance index of a certain excavator to be rented can meet this requirement, then the performance index matching item is considered to meet the conditions. A matching score can be set. If the requirements are met, it is assigned a value of 1, and if not, it is assigned a value of 0. Such judgments are made for multiple key performance dimensions and then considered comprehensively;

[0085] Working condition index matching judgment: Matching judgment is made based on the project working conditions expected during the customer's rental period and the working condition index of the equipment under the corresponding working conditions. The formula is as follows:

[0086] S totali =w P ×S Pi +w C ×S Ci

[0087] Among them, S totali Calculate the comprehensive matching score for each equipment to be leased, w P is the performance index matching weight, S Pi is the matching score of the performance index, w C is the working condition index matching weight, S Ci It is the matching score of the working condition index score.

[0088] S3.3, obtain customer information from the demand data, search for engineering information on the Internet based on the customer information, and then combine the demand data with the network engineering information to obtain the customer's engineering plan information and real-time engineering progress. Then, predict the equipment working time based on the engineering plan information and real-time engineering progress, and use the predicted working time minus the corresponding rental time of the leasing customer as the remaining time as the predicted renewal days. The specific steps are as follows:

[0089] Customer information extraction: From the demand data form submitted by the leasing customer, accurately extract basic information such as customer name, industry, past leasing history), contact number, email address, as well as key content such as the customer's special requirements for the equipment and the expected leasing time range;

[0090] Internet engineering information search: Using web crawler technology and keywords in customer information as clues, we can search for relevant engineering information in professional engineering information websites, industry forums, government engineering project bidding platforms and other Internet resources;

[0091] Project plan information analysis: Through in-depth text analysis of information searched on the Internet and customer demand data, natural language processing technology is used to identify key milestones in the project plan, construction task arrangements for each stage, and expected human and material resources;

[0092] Real-time project progress acquisition: Continue to use web crawler technology to pay attention to the official website of the client's project, social media accounts, and project progress bulletins issued by government regulatory authorities. Regularly capture real-time project progress information, such as the specific proportion of completed foundation construction and the number of floors of the main structure. Convert the real-time progress information into a standardized format, compare and integrate it with the previous project plan information, and update the project progress database table in real time.

[0093] Equipment working time prediction: Based on the project plan information and real-time project progress, combined with the operating characteristics and efficiency of the construction machinery and equipment, estimate the time the equipment needs to work during the entire project cycle;

[0094] Calculation of renewal days: We already know the rental time in the customer demand data. Subtract the rental time from the predicted equipment working time. The remaining time is the predicted renewal days. Taking the excavator as an example, the formula is as follows:

[0095]

[0096] Among them, T wrok is the theoretical working time, G z is the earthwork volume, G w is the rated mining efficiency, α is the efficiency reduction coefficient, which can be obtained through industry experience or historical data statistics;

[0097] T remain =T work -T rental

[0098] Among them, T remain To predict the number of renewal days, T rental The rental time in the customer demand data.

[0099] S4. Analyze the renewal index of the equipment to be leased by combining the predicted renewal days with the performance index and the working condition index, and then make a priority recommendation calculation for the equipment to be leased by combining the idle time and the renewal index;

[0100] The steps of S4 are as follows;

[0101] S4.1. Combine the performance index and the working condition index with the engineering requirements to predict the normal working hours of the leased equipment, and then analyze the renewal index by combining the predicted normal working hours with the predicted renewal days. The more the predicted normal working hours exceed the predicted renewal days, the higher the renewal index. Conversely, when the predicted normal working hours are lower than the predicted renewal days, the lower the renewal index.

[0102] The longer the idle time, the higher the idle time score;

[0103] S4.2. Set weights for renewal indicators and idle time, and then combine the idle time and renewal indicators of the equipment to be leased for priority recommendation calculation. The higher the priority recommendation score, the higher the ranking recommended to the leasing customer. Collect the actual working time records of the same type of equipment in similar projects in the past as reference data samples. The prediction model formula is as follows:

[0104] T normal =a×P+b×C+c×E+d

[0105] Among them, T normal To predict the normal working time, P is the performance index of the equipment to be rented, C is the working condition index, E is the engineering requirement, a, b, c are the coefficients determined by fitting and training the historical data, and d is the constant term. The historical data is substituted into the model to repeatedly train the optimization coefficients, so that the model can accurately predict the normal working time according to the equipment index and engineering requirements;

[0106]

[0107] Among them, RI is the renewal index. The above formula indicates that the more the normal working time exceeds the renewal days, the higher the renewal index is, which means that the equipment is more likely to stably meet the project needs during the renewal period;

[0108] T normal ≤T remain ,RI=0

[0109] The above formula indicates that the equipment may not continue to work normally during the renewal period according to the forecast, and the renewal index is set to the minimum;

[0110] PRS=w RI ×RI+w IS ×IS

[0111] Among them, PRS is the priority recommendation score of the equipment to be leased, w RI is the renewal index weight, w IS is the idle time score weight, IS is the idle time score;

[0112] Determine the renewal index weight and idle time score weight based on the enterprise operation strategy, market demand research and other factors. If the current market equipment is in short supply, and more attention is paid to the rapid rental of equipment to reduce idle time, the w can be appropriately increased. IS If you focus on the long-term stable income brought by customer renewal, you can appropriately increase w RI .

[0113] S5. Analyze the fault warning time by combining the operating status of the leased equipment with the mechanical parameters, and then compare the fault warning time with the remaining lease time. When the fault warning time is less than the remaining lease time, send a maintenance reminder to the equipment management end.

[0114] The steps of S5 are as follows:

[0115] S5.1. Analyze the fault warning time by combining the operating status of the leased equipment with the mechanical parameters, and then compare the fault warning time with the remaining lease time;

[0116] Taking neural network as an example, a multi-layer perceptron neural network model is constructed. The input layer nodes receive the pre-processed operating status data and mechanical parameter data. The hidden layer extracts and transforms the input data through nonlinear activation functions. The output layer outputs a curve representing the change of equipment failure probability over time.

[0117] The fault prediction model is trained using historical equipment failure data and the corresponding historical operating status and mechanical parameter data. A large amount of equipment data that has failed is divided into a training set ratio and a test set ratio. By continuously adjusting the model's weights, thresholds and other parameters, the prediction accuracy of the model on the test set is made to reach a high level, ensuring that the model can accurately capture the potential laws of equipment failures.

[0118] According to the failure probability change curve output by the fault prediction model, a fault warning threshold is set. It is usually determined based on factors such as the severity of the equipment failure, the maintenance cost, and the impact on the project progress. For example, for key equipment, an early warning is triggered when the failure probability reaches (30)% of the leased equipment management unit. When the failure probability predicted by the model exceeds the warning threshold for the first time, the corresponding time point is the failure warning time.

[0119] S5.2: When S5.1 shows that the fault warning time is less than the remaining lease time, a maintenance reminder is sent to the equipment management terminal;

[0120] S5.3. When S5.1 shows that the fault warning time is greater than the remaining lease time, continue monitoring.

[0121] For the equipment that has been leased out, we continuously monitor its operating status in real time, and calculate the time point when the failure may occur based on the mechanical parameters of the equipment to obtain the failure warning time. We compare this warning time with the remaining time of the customer's lease. If the warning time is shorter than the remaining time of the lease, it means that the equipment is very likely to fail during the lease period. At this time, we immediately send a maintenance reminder to the department or personnel responsible for equipment management, such as the maintenance team, the leasing business manager, etc., and explain the equipment status and failure prediction details in detail, so that they can quickly organize maintenance forces, eliminate hidden dangers in a timely manner, ensure the normal use of the equipment by customers, and maintain a good leasing business relationship.

[0122] The second object of the present invention is to provide a leasing management system for construction machinery equipment, including any one of the above-mentioned leasing management methods for construction machinery equipment, including an equipment classification unit 10, a to-be-leased equipment management unit 20 and a leased equipment management unit 30;

[0123] The equipment classification unit 10 is used to obtain the mechanical parameters, operating status, historical usage data, and historical maintenance data of the engineering machinery equipment, and classify the engineering machinery equipment into equipment to be rented and equipment that has been rented;

[0124] The equipment management unit 20 to be leased is used to evaluate the performance index and the working condition index, and record the idle time of the equipment to be leased, and predict the renewal days in the demand data, and analyze the renewal index of the equipment to be leased by combining the predicted renewal days with the performance index and the working condition index, and then perform priority recommendation calculation on the equipment to be leased in combination with the idle time and the renewal index;

[0125] The leased equipment management unit 30 is used to analyze the fault warning time by combining the operating status of the leased equipment with the mechanical parameters, and then compare the fault warning time with the remaining lease time. When the fault warning time is less than the remaining lease time, a maintenance reminder is sent to the equipment management terminal.

[0126] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and descriptions are only preferred examples of the present invention and are not intended to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A leasing management method for construction machinery and equipment, characterized in that: The steps include: S1. Obtain mechanical parameters, operating status, historical usage data, and historical maintenance data of engineering machinery and equipment, and classify engineering machinery and equipment into equipment to be leased and equipment that has been leased; S2. Evaluate the performance and working condition of the equipment to be leased in combination with mechanical parameters, historical usage data, and historical maintenance data, and record the idle time of the equipment to be leased; S3. Obtain the demand data of the leasing customers, analyze the demand data in combination with the performance indicators and the working condition indicators, obtain the equipment to be leased that can meet the demand data, and predict the renewal days in the demand data; S4. Analyze the renewal index of the equipment to be leased by combining the predicted renewal days with the performance index and the working condition index, and then make a priority recommendation calculation for the equipment to be leased by combining the idle time and the renewal index; S5. Analyze the fault warning time by combining the operating status of the leased equipment with the mechanical parameters, and then compare the fault warning time with the remaining lease time. When the fault warning time is less than the remaining lease time, send a maintenance reminder to the equipment management end.

2. The method for leasing and managing construction machinery and equipment according to claim 1, characterized in that: The S1 collects relevant data of all engineering machinery equipment by establishing a database at the equipment management end, and then acquires relevant data of the engineering machinery equipment from the database of the equipment management end by establishing a data transmission connection with the equipment management end, including mechanical parameters, operating status, historical usage data, and historical maintenance data of each engineering machinery equipment.

3. The method for leasing and managing construction machinery equipment according to claim 1, characterized in that: The S1 sets the status of each construction machinery equipment at the equipment management end, which are respectively equipment to be rented and equipment already rented. When the construction machinery equipment is rented to a rental customer, it is adjusted to equipment already rented, and when it is idle, it is equipment to be rented.

4. The method for leasing and managing construction machinery equipment according to claim 1, characterized in that: The S2 comprises the following steps: S2.

1. Evaluate the performance and working condition of the equipment to be leased in combination with mechanical parameters, historical usage data, and historical maintenance data to obtain the performance and working condition indicators of each equipment to be leased; The performance indicators are the engineering requirements that the equipment to be leased can adapt to; The working condition indicator is the working time under different engineering requirements; S2.

2. Record the idle time of the equipment to be leased, and obtain the idle time of each equipment to be leased.

5. The method for leasing and managing construction machinery equipment according to claim 1, characterized in that: The steps of S3 are as follows: S3.

1. Obtain the demand data of the leasing customer, and analyze and extract the engineering requirements and leasing time of the demand data to obtain the corresponding engineering requirements and leasing time of the leasing customer; S3.

2. Match and analyze each equipment to be leased by combining the demand data with the performance index and the working condition index, and obtain equipment to be leased that meets both the performance index and the working condition index of the demand data; S3.

3. Obtain customer information from the demand data, search for engineering information on the Internet based on the customer information, and then combine the demand data with the network engineering information to obtain the customer's engineering plan information and real-time engineering progress. Then, predict the equipment working time based on the engineering plan information and real-time engineering progress, and use the predicted working time minus the remaining time corresponding to the leasing customer as the predicted renewal days.

6. The method for leasing and managing construction machinery and equipment according to claim 1, characterized in that: The steps of S4 are as follows: S4.

1. Combine the performance index and the working condition index with the engineering requirements to predict the normal working hours of the leased equipment, and then analyze the renewal index by combining the predicted normal working hours with the predicted renewal days. The more the predicted normal working hours exceed the predicted renewal days, the higher the renewal index. Conversely, when the predicted normal working hours are lower than the predicted renewal days, the lower the renewal index. The longer the idle time, the higher the idle time score; S4.

2. Set weights for the renewal index and idle time, and then combine the idle time and renewal index of the equipment to be leased to perform priority recommendation calculation. The higher the priority recommendation score, the higher the ranking recommended to the leasing customer.

7. The method for leasing and managing construction machinery and equipment according to claim 1, characterized in that: The formula of S4 is as follows: T normal =a×P+b×C+c×E+d Among them, T normal To predict normal working time, P is the performance index of the equipment to be rented, C is the working condition index, E is the engineering requirement, a, b, c are coefficients determined by fitting training of historical data, and d is a constant term; T normal >T remain , Among them, RI is the renewal index. The above formula indicates that the more the normal working hours exceed the renewal days, the higher the renewal index; T normal ≤T remain ,RI=0 The above formula indicates that the equipment may not continue to work normally during the renewal period according to the forecast, and the renewal index is set to the minimum; PRS=w RI ×RI+w IS ×IS Among them, PRS is the priority recommendation score of the equipment to be leased, w RI is the renewal index weight, w IS is the idle time score weight, and IS is the idle time score.

8. The method for leasing and managing construction machinery equipment according to claim 1, characterized in that: The steps of S5 are as follows: S5.

1. Analyze the fault warning time by combining the operating status of the leased equipment with the mechanical parameters, and then compare the fault warning time with the remaining lease time; S5.2: When S5.1 shows that the fault warning time is less than the remaining lease time, a maintenance reminder is sent to the equipment management terminal; S5.

3. When S5.1 shows that the fault warning time is greater than the remaining lease time, continue monitoring.

9. A leasing management system for construction machinery equipment, used to implement a leasing management method for construction machinery equipment as claimed in any one of claims 1 to 8, characterized in that: It comprises an equipment classification unit (10), a to-be-rented equipment management unit (20) and a rented equipment management unit (30); The equipment classification unit (10) is used to obtain mechanical parameters, operating status, historical usage data, and historical maintenance data of the engineering machinery equipment, and to classify the engineering machinery equipment into equipment to be rented and equipment that has been rented; The equipment management unit (20) to be leased is used to evaluate performance indicators and working condition indicators, record idle time of the equipment to be leased, predict renewal days in demand data, analyze renewal indicators of the equipment to be leased by combining the predicted renewal days with performance indicators and working condition indicators, and then perform priority recommendation calculation on the equipment to be leased in combination with idle time and renewal indicators; The leased equipment management unit (30) is used to analyze the fault warning time by combining the operating status of the leased equipment with the mechanical parameters, and then compare the fault warning time with the remaining lease time. When the fault warning time is less than the remaining lease time, a maintenance reminder is sent to the equipment management terminal.

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