Tension detection early warning method and system for crane

Abstract

The invention relates to the technical field of cranes, and discloses a tension detection early warning method and system for a crane, and the method comprises the following steps: judging whether to adjust the maximum safety tension according to the load gravity; when it is judged that the maximum safe pulling force is not adjusted, the real-time pulling force value of the crane is collected, and whether to give an alarm or not is judged according to the relation between the real-time pulling force value and the maximum safe pulling force; when it is judged that the maximum safety tension is adjusted, operation data of the crane are collected along with time, and the change rate of the operation data is calculated; adjusting the detection period of the operation data according to the change rate of the operation data; the maximum safety tension is adjusted in real time according to the inclination angle of the suspension arm, the load gravity and the acceleration of the load, and a dynamic tension threshold value is obtained; and the real-time tension value of the crane is collected, an early warning factor is calculated, and graded early warning is carried out. According to the invention, a more reliable and high-adaptability tension detection early warning function is provided under a complex working condition, so that an effective guarantee is provided for safe operation of the crane.

Description

Technical Field

[0001] The present invention relates to the technical field of cranes, and in particular to a tension detection and early warning method and system for cranes. Background Art

[0002] As heavy machinery, cranes are widely used in construction, transportation, ports and other fields. Their operational safety and stability are crucial to the safety of the work site. During the operation of the crane, the tension on the wire rope is one of the important indicators that determine the operating status of the equipment. If the tension exceeds the design range, it may cause the wire rope to break or other serious accidents.

[0003] Therefore, real-time monitoring and warning of abnormal tension have become key technical requirements to ensure the safe operation of cranes. Existing crane tension monitoring systems mostly monitor the tension of wire ropes or hooks, with static tension threshold settings. When the tension exceeds the preset threshold, the system issues an alarm.

[0004] However, in actual operation, the working conditions of the crane (such as load weight, boom angle, wind speed, etc.) vary greatly. A single threshold setting cannot adapt to complex and changeable working conditions, which can easily lead to false alarms or missed alarms. Summary of the invention

[0005] In view of this, the present invention proposes a tension detection and early warning method and system for a crane, aiming to solve the problem that the setting of the tension threshold of the crane in the current technology lacks the ability to cope with variable working conditions.

[0006] On the one hand, the present invention provides a tension detection and early warning method for a crane, comprising:

[0007] Obtaining the maximum safe pulling force of the crane in a static state, collecting the load gravity of the crane load, and determining whether to adjust the maximum safe pulling force according to the load gravity;

[0008] When it is determined that the maximum safe pulling force is not to be adjusted, the real-time pulling force value of the crane is collected, and whether to issue an alarm is determined according to the relationship between the real-time pulling force value and the maximum safe pulling force;

[0009] When it is determined that the maximum safe pulling force is to be adjusted, the operation data of the crane is collected over time, and the change rate of the operation data is calculated; the operation data includes: the inclination angle of the boom, the gravity of the load, and the acceleration of the load;

[0010] adjusting a detection period of the operating data according to a rate of change of the operating data;

[0011] The maximum safe pulling force is adjusted in real time according to the boom inclination angle, load gravity and load acceleration to obtain a dynamic pulling force threshold;

[0012] The real-time pulling force value of the crane is collected, an early warning factor is calculated according to the real-time pulling force value and a dynamic pulling force threshold, and a graded early warning is performed according to the early warning factor.

[0013] Further, when judging whether to adjust the maximum safety tension according to the load gravity, it includes:

[0014] When N is satisfied MAX When <a×G, it is judged that the maximum safe pulling force should be adjusted;

[0015] When N is satisfied MAX When ≥a×G, it is judged that the maximum safety tension is not adjusted;

[0016] Among them, N MAX It represents the maximum safe pulling force, a is the safety factor, and G represents the load gravity.

[0017] Furthermore, the safety factor is determined by the following method:

[0018] The historical maximum wind force level, real-time wind force level and accumulated working time of the crane in the working area are collected, and the safety factor is:

[0019]

[0020] Wherein, a0 is a constant, and its value is 3; Wr is the real-time wind force level; Wh is the historical maximum wind force level, and the values ​​of Wr and Wh are any one of 1, 2, ..., 13; Tu is the accumulated working time of the crane; Th is the maximum service time of the crane wire rope;

[0021] When the safety factor a obtained by calculation is greater than 3, the value of a is 3; when the safety factor a obtained by calculation is less than 2.5, the value of a is 2.5.

[0022] Further, when it is determined that the maximum safe pulling force is not to be adjusted, the real-time pulling force value of the crane is collected, and it is determined whether to issue an alarm according to the relationship between the real-time pulling force value and the maximum safe pulling force, including:

[0023] The real-time tension value is compared with the maximum safe tension value. When the real-time tension value is less than or equal to the maximum safe tension value, no alarm is issued;

[0024] When the real-time tension value is greater than the maximum safe tension, an alarm is issued.

[0025] Further, when the detection period of the operating data is adjusted according to the change rate of the operating data, it includes:

[0026] Preset an initial detection cycle, collect five sets of data of the load gravity and load acceleration, and calculate the load gravity change rate and the load acceleration change rate;

[0027] The adjusted detection cycle satisfies the following relationship:

[0028]

[0029] Wherein, Tnew is the adjusted detection period; T0 is the initial detection period; N is the number of data points, which is 5; Gi is the data of the i-th load gravity; is the average value of the five groups of load gravity; Ai is the acceleration data of the i-th load; is the average value of the acceleration of five groups of loads; R G is the rate of change of load gravity; R A is the rate of change of the acceleration of the load; ∈ is a positive number, used to prevent the denominator from being zero; max(X,Y) means selecting the larger value between X and Y.

[0030] Furthermore, when the maximum safe pulling force is adjusted in real time according to the boom inclination angle, load gravity and load acceleration to obtain a dynamic pulling force threshold, it includes:

[0031] The dynamic tension threshold satisfies the following relationship:

[0032] F t =F max ×(1-f(θ))(1-f(G))(1-f(A));

[0033] Among them, Ft is the dynamic tension threshold, Fmax is the maximum safe tension, f(θ) is the influence coefficient of the boom inclination angle, f(G) is the influence coefficient of the load gravity, and f(A) is the influence coefficient of the load acceleration.

[0034] Furthermore, the inclination angle of the boom of the crane when it is not working is obtained, and the inclination angle influence coefficient of the boom satisfies the following relationship:

[0035]

[0036] Where, θ is the boom inclination angle, θ m It is the inclination angle of the crane boom when it is not working.

[0037] Furthermore, the load gravity influence coefficient is determined by the following method:

[0038]

[0039] The load acceleration influence coefficient is determined by the following method:

[0040]

[0041] Among them, G is the load gravity collected in real time; Gmin is the minimum load gravity data in historical data; Gmax is the maximum load gravity data in historical data; A is the load acceleration collected in real time; Amin is the minimum load acceleration data in historical data; Amax is the maximum load acceleration data in historical data.

[0042] Furthermore, a warning factor is calculated according to the real-time tension value and the dynamic tension threshold, and a graded warning is performed according to the warning factor, including:

[0043] The real-time tension value is collected and recorded as F, the dynamic tension threshold is recorded as Fx, and the warning factor P satisfies the following relationship:

[0044] P = F / Fx;

[0045] When P≤85%, no warning is given; when 85%<P≤100%, a warning is given for the current state of the crane; when P>100%, an alarm is given for the current state of the crane.

[0046] On the other hand, the present invention also proposes a system for implementing the above-mentioned tension detection and early warning method for a crane, the system comprising:

[0047] A data acquisition unit, comprising: a wind speed sensor, an inclination sensor and a load sensor for acquiring monitoring data, wherein the load sensor is used to acquire the load gravity of the crane;

[0048] The data acquisition unit is further configured to acquire instructions for crane acceleration;

[0049] The data processing module is configured to calculate the boom inclination influence coefficient, the load gravity influence coefficient, the load acceleration influence coefficient, adjust the detection cycle, calculate the dynamic tension threshold, and generate an early warning factor;

[0050] The alarm module is configured for early warning or alarm.

[0051] Compared with the prior art, the present invention has the following beneficial effects:

[0052] The tension threshold is calculated by comprehensively considering the three factors of boom inclination, load gravity and load acceleration, thereby improving the accuracy of early warning. Through graded early warning, different levels of response measures are provided according to the early warning factors, so that potential dangers can be handled more accurately in actual operation. By calculating the change rate of operating data to dynamically adjust the detection cycle, it can not only ensure that the detection frequency matches the actual working condition changes, but also avoid the system burden and resource waste caused by too frequent detection, and improve the response speed and efficiency of the system. In addition, by integrating multiple data collection methods such as wind speed, inclination and load gravity, comprehensive operation information is ensured. By calculating the early warning factor to judge the tension state, the equipment condition can be evaluated more scientifically, the risk of human misjudgment can be reduced, and the overall reliability of the system can be improved. The function of real-time monitoring and dynamic adjustment of the tension threshold enables the system to identify potential tension anomalies in advance and take preventive measures in time. This all-round safety guarantee can effectively reduce the occurrence of equipment failures and safety accidents and ensure the safe operation of the crane. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0054] Figure 1 This is a flow chart of a tension detection and early warning method for a crane according to an embodiment of the present invention;

[0055] Figure 2 The present invention is a functional block diagram of a tension detection and early warning system for a crane according to an embodiment of the present invention. DETAILED DESCRIPTION

[0056] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, in the absence of conflict, the embodiments of the present invention and the features described in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0057] See also Figure 1 As shown, an embodiment of the present invention provides a tension detection and early warning method for a crane, comprising:

[0058] S1: Obtain the maximum safe pulling force of the crane in a static state, collect the load gravity of the crane load, and determine whether to adjust the maximum safe pulling force according to the load gravity;

[0059] S21: when it is determined that the maximum safe pulling force is not to be adjusted, the real-time pulling force value of the crane is collected, and whether to issue an alarm is determined according to the relationship between the real-time pulling force value and the maximum safe pulling force;

[0060] S22: when it is determined that the maximum safe pulling force is to be adjusted, the operation data of the crane is collected over time, and the change rate of the operation data is calculated; the operation data includes: the inclination angle of the boom, the gravity of the load, and the acceleration of the load;

[0061] S3: adjusting the detection period of the operating data according to the change rate of the operating data;

[0062] S4: adjusting the maximum safe pulling force in real time according to the boom inclination angle, load gravity and load acceleration to obtain a dynamic pulling force threshold;

[0063] S5: Collect the real-time pulling force value of the crane, calculate the early warning factor according to the real-time pulling force value and the dynamic pulling force threshold, and perform graded early warning according to the early warning factor.

[0064] It is understandable that by dynamically adjusting the maximum safe tension to obtain the dynamic tension threshold, the system can reflect the load changes, boom angle and load acceleration in the actual working conditions in real time. This adjustment improves the accuracy of the threshold, avoids the false alarm or missed alarm problem caused by the static threshold setting, and thus enhances the adaptability and reliability of the system. This method comprehensively considers the influence of the boom inclination, load gravity and load acceleration on the safe tension, and can accurately respond to the load changes under different working conditions. This adaptability enables the system to handle complex and changeable operating environments, provide more accurate tension warnings, and ensure the safe operation of the crane under various working conditions. The detection cycle is adjusted according to the change rate of the operating data to ensure that the detection frequency matches the changes in the actual working conditions. This not only improves the real-time detection, but also reduces the waste of resources and system burden caused by the mismatch of the detection frequency, thereby optimizing the overall performance of the system. By calculating the warning factor through the real-time collected tension value and the dynamic tension threshold, the crane status can be graded. This graded warning mechanism can respond to different tension abnormalities more accurately, thereby providing effective safety measures and reducing the occurrence of equipment failures or accidents. By comprehensively collecting data such as wind speed, boom inclination, load gravity, and load acceleration, the equipment status can be fully understood. This comprehensive data collection and processing method enables the system to scientifically evaluate the actual operating status of the equipment, reduce the risk of human misjudgment, and thus improve the reliability and safety of the system. This method can promptly identify potential tension anomalies and take corresponding early warning measures, thereby effectively preventing equipment failures and safety accidents caused by tension anomalies. Through a comprehensive early warning mechanism, the safe operation of the crane is guaranteed and the safety of the work site is improved.

[0065] In some embodiments of the present application, when determining whether to adjust the maximum safety tension according to the load gravity, it includes:

[0066] When N is satisfied MAX When <a×G, it is judged that the maximum safe pulling force should be adjusted;

[0067] When N is satisfied MAX When ≥a×G, it is judged that the maximum safety tension is not adjusted;

[0068] Among them, N MAX It represents the maximum safe pulling force, a is the safety factor, and G represents the load gravity.

[0069] It should be noted that by introducing the calculation and judgment of the safety factor a, the system can dynamically adjust the maximum safe tension according to the real-time working conditions, thereby ensuring that the crane can maintain safe operation under various working environments. This effectively avoids potential safety risks caused by changes in the operating environment (such as wind force, load, etc.) and reduces the probability of accidents. Traditional tension monitoring methods usually use a fixed tension threshold, which is difficult to cope with complex and changeable working environments. By using the adjustment mechanism of the safety factor a, the system can flexibly adapt to different working conditions and realize dynamic adjustment of the maximum safe tension. This flexibility enables the crane to operate safely under a wider range of working conditions and improves the adaptability of the system. In actual operation, a fixed tension threshold is prone to false alarms or missed alarms. The present invention uses the safety factor a to determine whether to adjust the maximum safe tension, effectively reducing unnecessary alarms caused by changes in working conditions and improving the accuracy of the alarm. This not only improves the reliability of the system, but also reduces the burden on operators.

[0070] By dynamically adjusting the maximum safe tension, the key components of the crane (such as wire ropes) can be effectively protected under different working conditions. This protection mechanism helps to reduce excessive wear and fatigue damage of the equipment, thereby extending the service life of the equipment and reducing maintenance costs. While adjusting the maximum safe tension, the working status of the crane can be monitored in real time to detect potential problems in a timely manner. This preventive maintenance capability enables operators to take measures before problems occur, avoid sudden failures, and ensure the continued efficient operation of the crane.

[0071] In some embodiments of the present application, the safety factor is determined by the following method:

[0072] The historical maximum wind force level, real-time wind force level and accumulated working time of the crane in the working area are collected, and the safety factor is:

[0073]

[0074] Wherein, a0 is a constant, and its value is 3; Wr is the real-time wind force level; Wh is the historical maximum wind force level, and the values ​​of Wr and Wh are any one of 1, 2, ..., 13; Tu is the accumulated working time of the crane; Th is the maximum service time of the crane wire rope;

[0075] When the safety factor a obtained by calculation is greater than 3, the value of a is 3; when the safety factor a obtained by calculation is less than 2.5, the value of a is 2.5.

[0076] It should be noted that the real-time working conditions are accurately reflected: this method integrates historical and real-time wind force levels, accumulated working time and wire rope service time, so that the safety factor a can accurately reflect the current working environment and equipment status. This accuracy helps to perform safer operations under complex and changing working conditions. Through the calculation and adjustment of the safety factor, the system can dynamically adjust the maximum safe tension in real time to ensure that the crane can operate at the appropriate tension threshold in different environments, thereby improving the safety of operation. By introducing factors such as wind force level and working time, the system can better predict and prevent safety hazards caused by changes in the external environment or equipment status, thereby reducing the risk of accidents. Set the upper and lower limits of the safety factor to avoid excessive or insufficient adjustment due to abnormal parameters, thereby improving the reliability and stability of the system. The flexibility of this method enables the system to adapt to different working environments and task requirements, improving the working efficiency and safety of the crane.

[0077] In some embodiments of the present application, when it is determined that the maximum safe pulling force is not to be adjusted, the real-time pulling force value of the crane is collected, and it is determined whether to issue an alarm according to the relationship between the real-time pulling force value and the maximum safe pulling force, including:

[0078] The real-time tension value is compared with the maximum safe tension value. When the real-time tension value is less than or equal to the maximum safe tension value, no alarm is issued;

[0079] When the real-time tension value is greater than the maximum safe tension, an alarm is issued.

[0080] In some embodiments of the present application, when the detection period of the operating data is adjusted according to the change rate of the operating data, it includes:

[0081] Preset an initial detection cycle, collect five sets of data of the load gravity and load acceleration, and calculate the load gravity change rate and the load acceleration change rate;

[0082] The adjusted detection cycle satisfies the following relationship:

[0083]

[0084] Wherein, Tnew is the adjusted detection period; T0 is the initial detection period; N is the number of data points, which is 5; Gi is the data of the i-th load gravity; is the average value of the five groups of load gravity; Ai is the acceleration data of the i-th load; is the average value of the acceleration of five groups of loads; R G is the rate of change of load gravity; R Ais the rate of change of the acceleration of the load; ∈ is a positive number, which is used to prevent the denominator from being zero; max(X,Y) means selecting the larger value of X and Y; it should be emphasized that ∈ is used when max(R G ,R a ) is zero, the denominator in the above formula is guaranteed to be non-zero. In this embodiment, preferably, ∈ is 10 -5 .

[0085] when The value is zero or max(R G ,R A )+∈ is zero, the detection period is not adjusted, that is, T new =T0.

[0086] It should be noted that during the operation of the crane, the load and environmental conditions may change rapidly or slowly. For example, the gravity of the load hoisted by the crane or the acceleration of the load may fluctuate due to different operations or external interference. Through this detection cycle adjustment method, the system can dynamically adjust its own monitoring frequency according to these changes. It can automatically adapt to different working conditions during operation without human intervention. This adaptive capability can ensure that the crane is always in the best monitoring state in various environments, improving the safety and stability of operation. The beneficial effect of adaptive adjustment is to reduce the need for human intervention and be able to respond to different working environments and load changes in a timely manner, making crane operation more flexible and efficient, and reducing the risk of accidents.

[0087] In traditional crane monitoring systems, fixed detection cycles can lead to misjudgment problems. For example, if the detection cycle is too short, the system may trigger alarms frequently, even if the load changes slightly and there is no actual danger; conversely, if the detection cycle is too long, the system may not detect real dangerous situations in time. By adjusting the detection cycle mechanism, the system can avoid unnecessary frequent detection, thereby reducing misjudgments. In particular, when the load gravity and acceleration change slightly, the system will extend the detection cycle to avoid unnecessary alarms; in the case of large changes, the system will shorten the detection cycle to ensure timely response. Reducing misjudgments means that the system's alarms are more credible, and operators will respond to alarms more quickly and accurately, avoiding operational delays or unnecessary downtime caused by false alarms. At the same time, this can also reduce the system's maintenance costs and extend the service life of the equipment. During crane operation, different work tasks and environmental conditions require different monitoring frequencies for the system. Fixed high-frequency detection may occupy a lot of system resources, while fixed low-frequency detection may not be able to detect problems in time. By dynamically adjusting the detection cycle, the system can increase the detection frequency when needed and reduce the detection frequency when the load changes slightly. Doing so not only ensures high-frequency detection at critical moments, but also saves system resources in a stable state and improves the overall efficiency of the system. By optimizing resource allocation, the system can reduce unnecessary calculations and data processing and reduce energy consumption without affecting safety. This optimization not only improves the system's response speed, but also reduces operating costs, making the operation of the crane more economical and sustainable.

[0088] In some embodiments of the present application, when the maximum safe pulling force is adjusted in real time according to the boom inclination angle, load gravity and load acceleration to obtain a dynamic pulling force threshold, it includes:

[0089] The dynamic tension threshold satisfies the following relationship:

[0090] F t =F max ×(1-f(θ))(1-f(G))(1-f(A));

[0091] Among them, Ft is the dynamic tension threshold, Fmax is the maximum safe tension, f(θ) is the influence coefficient of the boom inclination angle, f(G) is the influence coefficient of the load gravity, and f(A) is the influence coefficient of the load acceleration.

[0092] In some embodiments of the present application, the inclination angle of the boom of the crane when it is not working is obtained, and the boom inclination angle influence coefficient satisfies the following relationship:

[0093]

[0094] Where, θ is the boom inclination angle, θm It is the inclination angle of the crane boom when it is not working.

[0095] In some embodiments of the present application, the load gravity influence coefficient is determined by the following method:

[0096]

[0097] The load acceleration influence coefficient is determined by the following method:

[0098]

[0099] Among them, G is the load gravity collected in real time; Gmin is the minimum load gravity data in historical data; Gmax is the maximum load gravity data in historical data; A is the load acceleration collected in real time; Amin is the minimum load acceleration data in historical data; Amax is the maximum load acceleration data in historical data.

[0100] It should be noted that the calculation method of the dynamic tension threshold enables the crane to accurately adjust the tension demand according to the real-time working condition changes, rather than relying on a static maximum safe tension value. This real-time adjustment enables the crane to respond to different working conditions more accurately, improving the safety and stability of operation.

[0101] By introducing the three key factors of boom inclination, load gravity and load acceleration into the calculation of dynamic tension threshold, the system can more comprehensively evaluate the current working status. Any change in any factor will lead to the adjustment of the tension threshold, thus preventing safety accidents caused by neglect of a single factor.

[0102] Since this method can be adjusted according to actual working conditions, the crane can operate safely in various complex environments. Whether it is load changes, tilt angle adjustments, or acceleration fluctuations, the system can respond flexibly to ensure the safety and efficiency of the operation.

[0103] Through accurate calculation and real-time adjustment of various influencing factors, the system can effectively reduce the risk of accidents caused by operation or environmental changes. Operators can perform complex lifting tasks with greater confidence, while reducing dependence on human intervention.

[0104] In some embodiments of the present application, a warning factor is calculated according to the real-time tension value and the dynamic tension threshold, and a graded warning is performed according to the warning factor, including:

[0105] The real-time tension value is collected and recorded as F, the dynamic tension threshold is recorded as Fx, and the warning factor P satisfies the following relationship:

[0106] P = F / Fx;

[0107] When P≤85%, no warning is given; when 85%<P≤100%, a warning is given for the current state of the crane; when P>100%, an alarm is given for the current state of the crane.

[0108] It should be noted that by introducing the early warning factor P, the system can quantify the relationship between the real-time pulling force value and the dynamic pulling force threshold of the crane. It can reflect the relative relationship between the real-time pulling force and the safety threshold, thereby improving the accuracy of the early warning. Especially when approaching the safety threshold, the system can issue an early warning, so that the operator has enough time to take necessary measures.

[0109] Effectiveness of the graded warning mechanism: The graded warning mechanism of the warning factor P can respond accordingly according to different risk levels. When P is less than or equal to 85%, the system considers that the crane is within the safe range and will not issue a warning. This avoids unnecessary interference and ensures that the system is not overly sensitive in safe situations. When P is between 85% and 100%, the system will issue a warning on the current state of the crane and will not alarm. This warning level reminds the operator that the pulling force of the crane is close to the safety limit and needs to be operated with caution. When P exceeds 100%, the system will immediately alarm. This alarm mechanism can send a clear signal when danger is about to occur, prompting the operator to take immediate measures to prevent accidents.

[0110] The hierarchical warning mechanism can provide appropriate response measures at different stages, thus effectively avoiding premature or late reactions. When approaching the safety threshold, the system will issue a warning to give the operator enough time to make adjustments; when exceeding the safety threshold, the system will immediately issue an alarm to prevent any potential danger. This hierarchical warning method greatly improves the operational safety of the crane.

[0111] By properly setting the threshold of the warning factor P, the system can effectively reduce the false alarm rate. When the tension value is within the safe range, the system will not issue unnecessary alarms, avoiding operator tension and misoperation. When the system does issue a warning or alarm, these alarms are more targeted, and operators can have more confidence in the accuracy of the alarm system.

[0112] The graded warning not only improves safety, but also reduces downtime and inspection time caused by false alarms. Operators can work more efficiently within the safety range without worrying about unnecessary interruptions, thereby improving overall work efficiency.

[0113] See also Figure 2 As shown, an embodiment of the present invention further provides a tension detection and early warning system for a crane, comprising:

[0114] A data acquisition unit, comprising: a wind speed sensor, an inclination sensor and a load sensor for acquiring monitoring data, wherein the load sensor is used to acquire the load gravity of the crane;

[0115] The data acquisition unit is further configured to acquire instructions for crane acceleration;

[0116] The data processing module is configured to calculate the boom inclination influence coefficient, the load gravity influence coefficient, the load acceleration influence coefficient, adjust the detection cycle, calculate the dynamic tension threshold, and generate an early warning factor;

[0117] The alarm module is configured for early warning or alarm.

[0118] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A tension detection and early warning method for a crane, characterized in that: include: Obtaining the maximum safe pulling force of the crane in a static state, collecting the load gravity of the crane load, and determining whether to adjust the maximum safe pulling force according to the load gravity; When it is determined that the maximum safe pulling force is not to be adjusted, the real-time pulling force value of the crane is collected, and whether to issue an alarm is determined according to the relationship between the real-time pulling force value and the maximum safe pulling force; When it is determined that the maximum safe pulling force is to be adjusted, the operation data of the crane is collected over time, and the change rate of the operation data is calculated; The operation data include: boom inclination angle, load gravity and load acceleration; adjusting a detection period of the operating data according to a rate of change of the operating data; The maximum safe pulling force is adjusted in real time according to the boom inclination angle, load gravity and load acceleration to obtain a dynamic pulling force threshold; The real-time pulling force value of the crane is collected, an early warning factor is calculated according to the real-time pulling force value and a dynamic pulling force threshold, and a graded early warning is performed according to the early warning factor.

2. The tension detection and early warning method for a crane according to claim 1, characterized in that: When judging whether to adjust the maximum safety tension according to the load gravity, it includes: When N is satisfied MAX When <a×G, it is judged that the maximum safe pulling force should be adjusted; When N is satisfied MAX When ≥a×G, it is judged that the maximum safety tension is not adjusted; Among them, N MAX It represents the maximum safe pulling force, a is the safety factor, and G represents the load gravity.

3. The tension detection and early warning method for a crane according to claim 2, characterized in that: The safety factor is determined by the following method: The historical maximum wind force level, real-time wind force level and accumulated working time of the crane in the working area are collected, and the safety factor is: Wherein, a0 is a constant, and its value is 3; Wr is the real-time wind force level; Wh is the historical maximum wind force level, and the values ​​of Wr and Wh are any one of 1, 2, ..., 13; Tu is the accumulated working time of the crane; Th is the maximum service time of the crane wire rope; When the safety factor a obtained by calculation is greater than 3, the value of a is 3; when the safety factor a obtained by calculation is less than 2.5, the value of a is 2.

5.

4. The tension detection and early warning method for a crane according to claim 3, characterized in that: When it is determined that the maximum safe pulling force is not to be adjusted, the real-time pulling force value of the crane is collected, and it is determined whether to issue an alarm according to the relationship between the real-time pulling force value and the maximum safe pulling force, including: The real-time tension value is compared with the maximum safe tension value. When the real-time tension value is less than or equal to the maximum safe tension value, no alarm is issued; When the real-time tension value is greater than the maximum safe tension, an alarm is issued.

5. The tension detection and early warning method for a crane according to claim 4, characterized in that: When the detection period of the operating data is adjusted according to the change rate of the operating data, it includes: Preset an initial detection cycle, collect five sets of data of the load gravity and load acceleration, and calculate the load gravity change rate and the load acceleration change rate; The adjusted detection cycle satisfies the following relationship: Wherein, Tnew is the adjusted detection period; T0 is the initial detection period; N is the number of data points, which is 5; Gi is the data of the i-th load gravity; is the average value of the five groups of load gravity; Ai is the acceleration data of the i-th load; is the average value of the acceleration of five groups of loads; R G is the rate of change of load gravity; R A is the rate of change of the acceleration of the load; ∈ is a positive number, used to prevent the denominator from being zero; max(X,Y) means selecting the larger value between X and Y.

6. The tension detection and early warning method for a crane according to claim 5, characterized in that: When the maximum safe pulling force is adjusted in real time according to the boom inclination angle, load gravity and load acceleration to obtain a dynamic pulling force threshold, it includes: The dynamic tension threshold satisfies the following relationship: F t =F max ×(1-f(θ))(1-f(G))(1-f(a)); Among them, Ft is the dynamic tension threshold, Fmax is the maximum safe tension, f(θ) is the influence coefficient of the boom inclination angle, f(G) is the influence coefficient of the load gravity, and f(A) is the influence coefficient of the load acceleration.

7. The tension detection and early warning method for a crane according to claim 6, characterized in that: The inclination angle of the boom of the crane when it is not working is obtained, and the inclination angle influence coefficient of the boom satisfies the following relationship: Where, θ is the boom inclination angle, θ m It is the inclination angle of the crane boom when it is not working.

8. The tension detection and early warning method for a crane according to claim 7, characterized in that: The load gravity influence coefficient is determined by the following method: The load acceleration influence coefficient is determined by the following method: Among them, G is the load gravity collected in real time; Gmin is the minimum load gravity data in historical data; Gmax is the maximum load gravity data in historical data; A is the load acceleration collected in real time; Amin is the minimum load acceleration data in historical data; Amax is the maximum load acceleration data in historical data.

9. The tension detection and early warning method for a crane according to claim 8, characterized in that: Calculating a warning factor according to the real-time tension value and the dynamic tension threshold, and performing graded warning according to the warning factor, including: The real-time tension value is collected and recorded as F, the dynamic tension threshold is recorded as Fx, and the warning factor P satisfies the following relationship: P = F / Fx; When P≤85%, no warning is given; when 85%<P≤100%, a warning is given for the current state of the crane; when P>100%, an alarm is given for the current state of the crane.

10. A tension detection and early warning system for a crane, used to apply the tension detection and early warning method for a crane according to any one of claims 1 to 9, characterized in that: The system comprises: A data acquisition unit, comprising: a wind speed sensor, an inclination sensor and a load sensor for acquiring monitoring data, wherein the load sensor is used to acquire the load gravity of the crane; The data acquisition unit is further configured to acquire instructions for crane acceleration; The data processing module is configured to calculate the boom inclination influence coefficient, the load gravity influence coefficient, the load acceleration influence coefficient, adjust the detection cycle, calculate the dynamic tension threshold, and generate an early warning factor; The alarm module is configured for early warning or alarm.

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