A cloth machine and platform integrated equipment safety state judgment method

Abstract

This invention provides a method for determining the safety status of integrated equipment combining a concrete placing boom and a platform. The method includes: collecting multiple safety status indicators, performing synchronized processing and preprocessing using a unified timescale, and grouping them according to operating conditions; calculating the window mean and standard deviation of each safety status indicator based on a sliding window partition; calculating the sample mean and standard deviation of the window mean and standard deviation using data from the normal operating period of the equipment as a benchmark; calculating the mean deviation and standard deviation deviation based on the window mean and standard deviation, combined with the normal state benchmark, and linearly combining them with preset weights to obtain the risk value of each individual indicator; and weighted summing of the risk values ​​of each individual indicator to obtain the overall risk score of the integrated equipment. This method can accurately determine the overall safety status of the equipment, effectively improving the real-time performance, stability, and interpretability of the determination.

Description

Technical Field

[0001] This invention belongs to the field of construction safety monitoring and intelligent judgment technology, and specifically relates to a method for judging the safety status of integrated equipment of concrete placing machine and platform. Background Technology

[0002] In the construction of high-rise, super high-rise, and complex structures, concrete placing booms are often integrated with attached, supported, or climbing steel platforms to meet the needs of high-altitude concrete transport and collaborative operations. This type of equipment experiences significant coupling, dynamism, and uncertainty in stress. Current mainstream safety monitoring uses single-index limit alarm methods (such as fixed thresholds for tilt angle, wind speed, strain, etc.), which have the following drawbacks:

[0003] 1. Under different operating conditions, the normal fluctuation range of the same indicator varies significantly. For example, when the boom is fully extended, in strong winds, or under high pump pressure, the values ​​of tilt angle and strain will naturally be higher. Fixed thresholds are prone to false alarms under normal operating conditions, while during the hazard accumulation stage, they are missed because the threshold has not been reached.

[0004] 2. The actual risks of equipment often stem from the simultaneous anomalies of multiple indicators, such as increased torque, increased strain, enhanced vibration, and attitude deviation. Individual indicators may not exceed limits independently, but the overall risk has increased significantly, which cannot be identified by traditional methods.

[0005] 3. Short-term disturbances exist at the construction site, such as pumping pulsations, boom reversal impacts, and gusts of wind. Judgments based on instantaneous sampled values ​​are prone to unstable alarms, while simply using long-period average values ​​can mask early signs of short-term anomalies escalating.

[0006] 4. The connection point between the concrete placing boom and the platform is a critical weak point, and its stress and strain changes best reflect abnormal states during load transfer. Existing methods do not pay enough attention to this and lack targeted monitoring.

[0007] Therefore, existing monitoring and assessment methods still have room for improvement in terms of the real-time nature, stability, and interpretability of the overall safety status of equipment. Summary of the Invention

[0008] This invention provides a method for determining the safety status of an integrated equipment combining a fabric placing machine and a platform, achieving real-time performance, stability, and interpretability in safety status determination.

[0009] The technical solution of the present invention is as follows:

[0010] A method for determining the safety status of an integrated equipment combining a concrete placing boom and a platform includes the following steps:

[0011] S1, Monitoring data acquisition: Real-time acquisition of multiple safety status indicators of the integrated equipment. The multiple safety status indicators include at least the parameters reflecting the tilt angle of the base or column of the placing boom, the ambient wind speed, the equivalent working torque of the placing boom, the stress at the joint between the placing boom and the platform, the strain at the joint between the placing boom and the platform, and the structural vibration acceleration.

[0012] S2, Data Preprocessing: The safety status indicators are synchronized with a unified time scale, and missing values ​​are handled, outliers are removed, and filtering and noise reduction are performed to obtain effective time series data. Then, the data is grouped according to the operating conditions based on the equipment operating status, environmental conditions, and operating parameters.

[0013] S3, Sliding window construction: Divide the effective time series data into sliding windows according to the set window length and window step size to obtain continuous window data of each security status index up to time t;

[0014] S4, Window statistical feature extraction: For the window data, calculate the window mean and window standard deviation for each safety status index within the sliding window at time t.

[0015] S5, Establish a statistical benchmark for normal state: Based on the data of the equipment's historical normal operation period, group according to the operating conditions, and calculate the sample mean and sample standard deviation of the window mean and window standard deviation of each safety state indicator, respectively, as the normal state benchmark of the corresponding indicator under the operating conditions.

[0016] S6, Constructing the single-indicator risk deviation: For the i-th safety status indicator in the sliding window at time t, based on the window mean and window standard deviation obtained in step S4, and combined with the normal status benchmark obtained in step S5, calculate the mean deviation and standard deviation deviation respectively, and linearly combine the mean deviation and standard deviation deviation according to a preset weight to obtain the single-indicator risk value of the indicator.

[0017] S7, Construct a multi-indicator weighted risk score: The risk values ​​of each single indicator are weighted and summed according to preset weights to obtain the overall risk score of the integrated equipment at time t;

[0018] S8, Safety Status Classification Determination: The overall risk score is compared with a preset classification threshold, and the safety status level of the equipment is output.

[0019] Furthermore, in step S6, the mean deviation of the i-th safety status indicator... Deviation from standard deviation They are obtained respectively through the following formulas:

[0020] ,

[0021] ,

[0022] in, Let be the window mean of the i-th safety status index at time t. Let be the standard deviation of the i-th safety status index at time t. This is the sample mean of the window mean under normal conditions. This represents the sample standard deviation of the window mean under normal conditions. This represents the sample mean of the standard deviation of the window under normal conditions. This is the sample standard deviation of the window standard deviation under normal conditions. It is a preset, extremely small positive number used to prevent the denominator from being zero;

[0023] Single-index risk value of the i-th safety status indicator Obtained through the following formula:

[0024]

[0025] in, and Let be the internal weights of the i-th safety status index in terms of mean deviation and standard deviation, respectively, and satisfy . ;

[0026] The values ​​of the internal weights are configured differently based on the risk type of the safety status indicator:

[0027] For the equivalent working torque of the fabric placing machine, the inclination angle of the base or column, the stress at the joint, and the strain at the joint, set... > ;

[0028] For the aforementioned environmental wind speed and structural vibration acceleration, set > .

[0029] Furthermore, in step S7, the overall risk score... Obtained through the following formula:

[0030]

[0031] Where n is the number of safety status indicators included in the assessment. For single-indicator risk values, Let be the external comprehensive weight corresponding to the i-th safety status indicator, and satisfy . ;

[0032] The external comprehensive weights are determined based on the sensitivity of each safety status index to structural safety. The weights of the equivalent working torque of the concrete placing machine, the stress at the joint, the strain at the joint, and the tilt angle of the base or column are greater than the weights of the ambient wind speed and the structural vibration acceleration.

[0033] Furthermore, in step S8, the security status is divided into four levels:

[0034] when When the time comes, it is determined to be a safe state;

[0035] when When this time, it is determined to be in a state of attention;

[0036] when When this occurs, it is determined to be a warning state;

[0037] when When this occurs, it is determined to be a dangerous situation;

[0038] in, , , For a preset scoring threshold; and / or,

[0039] The determination result of the safety status level is also logically combined with the determination rule based on physical thresholds to jointly determine whether to trigger the disposal measures: when the real-time value of the stress at any joint exceeds the preset absolute safety limit, it is forcibly determined to be a dangerous state regardless of the overall risk score.

[0040] Furthermore, when outputting the security status level of the equipment, a continuous window triggering mechanism is executed: the level determination result is officially output only when a certain security status level appears consecutively for a preset window number K, where K is a preset positive integer.

[0041] Furthermore, in step S5, the sample mean of the window mean Obtained through the following formula:

[0042] ;

[0043] Sample standard deviation of window mean Obtained through the following formula:

[0044] ;

[0045] Sample mean of window standard deviation Obtained through the following formula:

[0046] ;

[0047] Sample standard deviation of window standard deviation Obtained through the following formula:

[0048] ;

[0049] Where N is the number of normal sample windows. Let be the window mean of the ith safety status index within the j-th sliding window. The window standard deviation of the i-th safety status index in the j-th sliding window; and / or,

[0050] The normal state statistical benchmark established in step S5 is adaptively updated during equipment operation: during the time period when the equipment is determined to be in a safe state, the normal state statistical benchmark is iteratively updated using an exponentially weighted moving average method with a preset smoothing factor to adapt to the normal performance drift during long-term equipment operation.

[0051] Furthermore, in step S1, the multiple safety status indicators are collected by the sensor acquisition unit; and / or,

[0052] The safety status indicators also include at least one of the following: boom deployment angle, slewing angular velocity, pitch angular velocity, hydraulic cylinder pressure, delivery pipe pressure, concrete pump flow rate, end hose swing amplitude, platform plate opening / closing status, or climbing mechanism status; and / or,

[0053] The equivalent working torque is calculated from one or more of the following: boom attitude parameters, concrete placement radius, equivalent weight of concrete in the pipe, pumping pressure, end reaction force, structural geometric parameters, and equivalent load parameters.

[0054] Furthermore, in step S2, the missing value processing employs adjacent interpolation, linear interpolation, mean interpolation, or compensation between preceding and following time points; and / or,

[0055] The outlier removal method employs the three-standard-deviation criterion, box plot method, or median absolute deviation method; and / or,

[0056] The filtering and noise reduction employs moving average filtering, median filtering, or low-pass filtering; and / or,

[0057] The working condition grouping criteria include at least one of the following:

[0058] The equipment operating status includes at least one of the following: boom deployment operation, boom retraction or internal installation, pumping operation, non-pumping standby, or climbing conversion.

[0059] Environmental conditions range, including different wind speed ranges;

[0060] The range of operating parameters includes different fabric radii.

[0061] Furthermore, the window data in step S3 Obtained through the following formula:

[0062]

[0063] in, Let L be the sampled value of the i-th security status index at time t, and L be the window length; and / or,

[0064] Window mean in step S4 Obtained through the following formula:

[0065] ;

[0066] Window standard deviation in step S4 Obtained through the following formula:

[0067] ;

[0068] in, Let be the window mean of the i-th safety status index at time t. Let L be the standard deviation of the window for the i-th safety status index at time t, and L be the window length.

[0069] Furthermore, the method for determining the safety status of the integrated equipment of the placing boom and platform also includes:

[0070] S9, Result Output and Early Warning Handling: Output the overall risk score, risk values ​​of each individual indicator, major deviations in safety status indicators and safety status levels in real time, and trigger at least one of the following handling measures when the safety status level reaches the early warning or danger level: audible and visual alarm, remote information push, work prompt, load reduction control, restricted operation, or shutdown interlock.

[0071] The beneficial effects of this invention are as follows:

[0072] This invention discloses a method for determining the safety status of an integrated equipment combining a concrete placing boom and a platform. This method involves monitoring data acquisition, data preprocessing, sliding window construction, window statistical feature extraction, establishing a normal state statistical benchmark, constructing a single-indicator risk deviation, constructing a multi-indicator weighted risk score, and determining the safety status in a graded manner. This enables the graded determination and early warning output of the overall safety status of the equipment. This safety status determination method improves the real-time performance, stability, and interpretability of equipment safety status assessment. Attached Figure Description

[0073] Figure 1 This is a flowchart of a method for determining the safety status of an integrated equipment combining a fabric placing machine and a platform, according to an embodiment of the present invention.

[0074] Figure 2 This is a schematic diagram of the structure of the placing machine, platform, and sensor acquisition unit in a method for determining the safety status of an integrated equipment combining a placing machine and a platform, according to an embodiment of the present invention.

[0075] Figure 3 This is an application flowchart of a safety status determination method for an integrated equipment combining a fabric placing machine and a platform, according to an embodiment of the present invention.

[0076] In the diagram: 1. Platform; 2. Vibration acceleration sensor; 3. Wind speed sensor; 4. Stress sensor; 5. Strain sensor; 6. Tilt sensor; 7. Fabric placing machine. Detailed Implementation

[0077] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. The advantages and features of the present invention will become clearer from the following description and claims. It should be noted that the drawings are all in a very simplified form and use non-precise proportions, and are only used to facilitate and clarify the illustration of the embodiments of the present invention.

[0078] refer to Figures 1 to 3 This embodiment provides a method for determining the safety status of an integrated equipment combining a fabric placing machine and a platform, including the following steps: S1-S8.

[0079] S1, Monitoring Data Acquisition: Multiple safety status indicators of the integrated equipment are acquired in real time through a sensor acquisition unit. These indicators include at least parameters reflecting the tilt angle of the base or column of the placing boom 7, ambient wind speed, equivalent working torque of the placing boom, stress at the junction of the placing boom 7 and platform 1, strain at the junction of the placing boom 7 and platform 1, and structural vibration acceleration. The sensor acquisition unit may include a tilt sensor 6, a wind speed sensor 3, a stress sensor 4, a strain sensor 5, and a vibration acceleration sensor 2.

[0080] For details, please refer to Figure 2Tilt sensors 6 are installed at key locations on the base or column of the placing boom 7 to reflect the overall attitude deviation and stability of the equipment. Wind speed sensors 3 are installed at a high point on the outer edge of platform 1 to measure the overall attitude deviation and stability of the equipment in real time. The equivalent working torque of the placing boom can be calculated from one or more of the following: boom attitude parameters, placing radius, equivalent weight of concrete in the pipe, pumping pressure, end reaction force, and structural geometric parameters. It can also be obtained by conversion from the equivalent load parameters directly output by the control system, used to characterize the comprehensive operating load level under boom deployment, material conveying, and pumping. Stress sensors 4 and strain sensors 5 are installed at the connection node between the placing boom 7 base and platform 1 and at adjacent main load-bearing components to reflect the stress level during the transfer of working load to the platform system and the deformation response of key connection areas, respectively. Vibration acceleration sensors 2 are installed near the base of the placing boom 7, the main beam of platform 1, or connection nodes to reflect the dynamic response and abnormal vibration level of the equipment and platform system, forming six core safety status indicators. The sampling frequency of each sensor in the sensor acquisition unit can be set from 1Hz to 20Hz as needed.

[0081] Step S1 uses a sensor acquisition unit to collect six core safety status indicators in real time. This allows for the simultaneous coverage of overall equipment attitude deviation, external environmental disturbances, operating load levels, stress and deformation response of key connection areas, and structural dynamic vibration characteristics with fewer monitoring parameters. This makes the safety status indicator system both concise and targeted, and is particularly suitable for determining the safety status of integrated equipment such as concrete placing booms and platforms under complex working conditions.

[0082] S2, Data Preprocessing: All safety status indicators are synchronized with a unified time scale, and missing values ​​are handled, outliers are removed, and noise is reduced by filtering to obtain effective time series data. Then, the data is grouped according to the operating conditions based on the equipment operating status, environmental conditions, and operating parameters.

[0083] Specifically, missing values ​​are handled using adjacent interpolation, linear interpolation, mean interpolation, or compensation at different time points. Outlier removal employs the three-standard-deviation criterion, box plot method, or median absolute deviation method. Filtering and noise reduction utilizes moving average filtering, median filtering, or low-pass filtering to reduce noise in highly fluctuating data such as wind speed, transport pressure, and vibration acceleration, ensuring the accuracy and stability of subsequent sliding window statistical features.

[0084] The grouping of operating conditions should be based on at least one of the following: equipment operating status, environmental condition range, or operational parameter range. Equipment operating status should include at least one of the following: boom deployed operation, boom retracted or internal, pumping operation, non-pumping standby, or climbing transition. Environmental condition ranges should include different wind speed ranges. Operational parameter ranges should include different deployment radius ranges. Grouping operating conditions improves the adaptability and interpretability of judgment results under different operational stages, deployment states, and environmental conditions.

[0085] Step S2 achieves data preprocessing of various safety status indicators through unified time-stamp synchronization, missing value handling, outlier removal, filtering and noise reduction, and grouping by operating condition, thereby obtaining continuous, reliable, and effective time series data and avoiding interference from overlapping operating conditions to subsequent judgments.

[0086] S3, according to the set window length and window step size, divide the effective time series data into sliding windows to obtain continuous window data of each security status indicator up to time t.

[0087] Specifically, window data Obtained through the following formula:

[0088]

[0089] in, Let L be the sampled value of the i-th security status index at time t, and L be the window length.

[0090] Preferably, the window step size can be set to one or more sampling intervals, and the window length can be determined according to the on-site sampling frequency and actual needs. The number of data points corresponding to 30 seconds, 60 seconds or 120 seconds can be selected.

[0091] S4, Window statistical feature extraction: For the window data, calculate the window mean and window standard deviation for each safety status indicator within the sliding window corresponding to time t.

[0092] Specifically, window mean Obtained through the following formula:

[0093] ;

[0094] Window standard deviation Obtained through the following formula:

[0095] ;

[0096] in, Let be the window mean of the i-th safety status index at time t. Let L be the standard deviation of the window for the i-th safety status index at time t, and L be the window length.

[0097] Steps S3 and S4, through the construction of a sliding window and sliding window statistical analysis, transform the original instantaneous monitoring values ​​into window mean and window standard deviation, thereby simultaneously characterizing two types of abnormal features: continuous offset and enhanced fluctuation, and improving the ability to identify abnormal states in complex dynamic processes.

[0098] S5. Establish a statistical benchmark for normal operation: Based on the data of the equipment's historical normal operation period, group the equipment according to the operating conditions, and calculate the sample mean and sample standard deviation of the window mean and window standard deviation of each safety status indicator, respectively, as the normal status benchmark of the corresponding indicator under the operating conditions.

[0099] Specifically, the sample mean of the window mean. Obtained through the following formula:

[0100] ;

[0101] Sample standard deviation of window mean It can be obtained through the following formula:

[0102] ;

[0103] Sample mean of window standard deviation It can be obtained through the following formula:

[0104] ;

[0105] Sample standard deviation of window standard deviation It can be obtained through the following formula:

[0106] ;

[0107] Where N is the number of normal sample windows. Let be the window mean of the ith safety status index within the j-th sliding window. Let be the window standard deviation of the i-th safety status index in the j-th sliding window.

[0108] Furthermore, the normal state statistical benchmark established in step S5 is adaptively updated during equipment operation: during the time period when the equipment is determined to be in a safe state, the normal state statistical benchmark is iteratively updated using an exponentially weighted moving average method with a preset smoothing factor to adapt to the normal performance drift during long-term equipment operation, thereby avoiding misjudgment or omission caused by a fixed benchmark and improving the applicability and robustness of the safety determination method throughout its entire life cycle.

[0109] In step S5, based on the data from the equipment's historical normal operating period, the sample mean and sample standard deviation of each safety status indicator are calculated according to the window mean and window standard deviation for each group of operating conditions. This establishes the statistical benchmark for normal status under each operating condition, thereby providing a comparable reference for the subsequent calculation of deviation of real-time monitoring data. This allows for reasonable differentiation of the differences of the same indicator under different operating conditions, effectively avoiding the problem of misjudgment of fixed thresholds caused by changes in operating conditions.

[0110] S6, Constructing the single-indicator risk deviation: For the i-th safety status indicator in the sliding window at time t, based on the window mean and window standard deviation obtained in step S4, and combined with the normal status benchmark obtained in step S5, calculate the mean deviation and standard deviation deviation respectively, and linearly combine the mean deviation and standard deviation deviation according to a preset weight to obtain the single-indicator risk value of the indicator.

[0111] Specifically, the deviation of the mean of the i-th safety status indicator Deviation from standard deviation They are obtained respectively through the following formulas:

[0112] ,

[0113] ,

[0114] in, Let be the window mean of the i-th safety status index at time t. Let be the standard deviation of the i-th safety status index at time t. This is the sample mean of the window mean under normal conditions. This represents the sample standard deviation of the window mean under normal conditions. This represents the sample mean of the standard deviation of the window under normal conditions. This is the sample standard deviation of the window standard deviation under normal conditions. It is a preset, extremely small positive number used to prevent the denominator from being zero.

[0115] Single-index risk value of the i-th safety status indicator Obtained through the following formula:

[0116]

[0117] in, and Let be the internal weights of the i-th safety status index in terms of mean deviation and standard deviation, respectively, and satisfy . .

[0118] Furthermore, the values ​​of the internal weights are configured differently based on the risk type of the safety status indicator:

[0119] For the equivalent working torque of the fabric placing machine, the inclination angle of the base or column, the stress at the joint, and the strain at the joint, set... > For the aforementioned environmental wind speed and structural vibration acceleration, set... > This is to more accurately reflect the abnormal behavior of different safety status indicators.

[0120] Step S6 calculates the mean deviation and standard deviation deviation by combining the window mean and standard deviation with the normal state benchmark, and then linearly combines them with preset weights to form a single indicator risk value. This enables a comprehensive assessment of the risk level of each safety state indicator from two dimensions: "horizontal deviation" and "fluctuation amplification". This not only determines whether the monitoring indicator continues to deviate from the normal level, but also captures whether its fluctuation has significantly increased, effectively improving the ability to identify early risk signs.

[0121] S7, Construct a multi-indicator weighted risk score: The risk values ​​of each single indicator are weighted and summed according to preset weights to obtain the overall risk score of the integrated equipment at time t.

[0122] Specifically, overall risk score Obtained through the following formula:

[0123]

[0124] Where n is the number of indicators included in the judgment. Let be the external comprehensive weight corresponding to the i-th security status indicator, and satisfy . .

[0125] Furthermore, the external comprehensive weights are determined based on the sensitivity of each safety status indicator to structural safety. The weights of the equivalent working torque of the concrete placing boom, the stress at the joint, the strain at the joint, and the tilt angle of the base or column are greater than the weights of the ambient wind speed and the structural vibration acceleration, so as to reflect the more direct impact of the working load level, the stress on key connections, and the overall stable posture on the safety status.

[0126] Optionally, the external comprehensive weights can also be determined based on historical accident experience, finite element analysis results, expert scores, analytic hierarchy process (AHP), or entropy weight method. Step S7 achieves a leap from single-indicator assessment to multi-indicator comprehensive assessment by weighting and summing the risk values ​​of each individual indicator according to preset weights. This yields a comprehensive score that reflects the overall safety status of the integrated equipment of the concrete placing boom and platform under multi-source coupling effects, effectively reducing the risk of missed and false alarms compared to the traditional single-indicator threshold method.

[0127] S8, Safety Status Classification Determination: The overall risk score is compared with a preset classification threshold, and the safety status level of the equipment is output.

[0128] Specifically, the security status is divided into four levels:

[0129] when When the time comes, it is determined to be a safe state;

[0130] when When this time, it is determined to be in a state of attention;

[0131] when When this occurs, it is determined to be a warning state;

[0132] when When this occurs, it is determined to be a dangerous situation;

[0133] in, , , This is a preset scoring threshold.

[0134] Furthermore, the safety status level determination result is logically combined with the determination rule based on physical thresholds to jointly determine whether to trigger response measures: when the real-time value of the stress at any joint exceeds the preset absolute safety limit, regardless of the overall risk score, it is forcibly determined to be a dangerous state. This combined determination rule avoids the smoothing or masking of local extreme outliers that may occur due to the weighted fusion of multiple indicators, ensuring that safety protection measures can be triggered immediately under the most unfavorable operating conditions, significantly improving the system's safety redundancy and fault tolerance.

[0135] Furthermore, when outputting the safety status level of the equipment, a continuous window triggering mechanism is implemented: the determination result of that level is only officially output when a certain safety status level occurs consecutively for a preset window number K, where K is a preset positive integer. By introducing the continuous window triggering mechanism, false alarms caused by single abnormal sampling due to instantaneous disturbances, sensor noise, or occasional impacts are avoided, thus improving the stability and reliability of safety status determination, while not affecting timely response to continuously deteriorating trends.

[0136] The above method achieves graded judgment and early warning output of the overall safety status of equipment by monitoring data collection, data preprocessing, sliding window construction, window statistical feature extraction, establishment of normal state statistical benchmark, construction of single indicator risk deviation, construction of multi-indicator weighted risk score and safety status classification judgment, thereby improving the real-time performance, stability and interpretability of equipment safety status judgment.

[0137] As a preferred implementation method, in order to achieve differentiated response and automated early warning handling for different risk levels, the integrated equipment safety status determination method further includes: S9, result output and early warning handling: output the overall risk score, the risk values ​​of each single indicator, the main deviation safety status indicators and safety status level in real time, and automatically trigger handling measures such as audible and visual alarms, remote information push, operation prompts, load reduction control, limited operation or shutdown interlock when the safety status level reaches the early warning or danger level.

[0138] As a preferred implementation, in order to enhance the adaptability of the safety assessment method to complex working conditions, the safety status indicators may also include monitoring data of auxiliary detection indicators such as boom extension angle, slewing angular velocity, pitch angular velocity, hydraulic cylinder pressure, delivery pipe pressure, concrete pump flow rate, end hose swing amplitude, platform plate opening and closing status, and climbing mechanism status.

[0139] Example 1:

[0140] refer to Figures 2 to 3 Taking an integrated equipment combining a concrete placing boom and platform used at a construction site of a super high-rise building as an example, the number of safety status indicators, n, is preferably six, corresponding to the tilt angle of the placing boom 7 base or column, ambient wind speed, equivalent working torque of the placing boom, stress at the joint, strain at the joint, and structural vibration acceleration. Tilt angle sensors 6 are arranged at key locations on the placing boom 7 base or column; wind speed sensors 3 are arranged at a high point on the outer edge of the platform 1; stress sensors 4 and strain sensors 5 are arranged at the connection node between the placing boom 7 base and platform 1 and at adjacent main load-bearing components; and vibration acceleration sensors 2 are arranged near the placing boom 7 base, the main beam of platform 1, or the connection node. Simultaneously, boom posture parameters, pumping pressure parameters, and equipment operating status parameters are read from the placing boom control system, and the equivalent working torque of the placing boom is calculated or converted to form six types of safety status indicators. The sampling frequency of each sensor can be set from 1Hz to 20Hz as needed.

[0141] The sensor acquisition unit continuously collects the above safety status indicators and synchronizes them using a unified clock. Linear interpolation is used to compensate for individual missing data points; significant abrupt changes are eliminated using a three-standard-deviation method; and short-window moving average or median filtering is used to reduce noise in the wind speed and vibration acceleration data, resulting in a pre-processed effective data sequence.

[0142] Based on the equipment's operating status, the data is divided into working status and built-in status. In the working status, the data is further grouped according to the fabric radius range, pumping pressure range, and wind speed range to establish a corresponding normal benchmark sample library.

[0143] The sliding window length is set to 60 sampling points, and the window step size is 1 sampling point. For each indicator, the window mean and standard deviation are calculated within each window. For example, the mean of the placement machine base tilt angle in the current window reflects whether there has been a continuous shift in the equipment over a recent period; the standard deviation of the vibration acceleration in the current window reflects whether there is a significant amplification of structural vibration; and the combined mean and standard deviation of stress and strain in the current window reflect whether there is increased stress and enhanced local response fluctuations in key connection areas.

[0144] During the normal operation of the equipment, normal monitoring data is continuously collected for several days. A normal sample window set is formed using the same sliding window parameters. The mean and standard deviation of the mean sequence and standard deviation sequence of each indicator window are statistically analyzed under each working condition group to obtain the benchmark indicators under different working conditions.

[0145] During the real-time judgment phase, the real-time mean deviation and standard deviation deviation of the i-th indicator are calculated. Specifically, the tilt angle of the fabric placing machine's base 7 can be set to α. i =0.7、β i =0.3 indicates a greater focus on the overall attitude deviation; α can be set for wind speed. i =0.3、β i =0.7 indicates a greater focus on increased volatility; α can be set for the equivalent working torque of the fabric placing machine. i =0.7、β i =0.3, indicating a greater focus on sustained high load levels; α can be set for stress and strain at joints. i =0.6、β i =0.4 indicates a greater focus on the state of sustained stress enhancement; for vibration acceleration, α can be set. i =0.3、β i =0.7 indicates a greater focus on dynamic shock and vibration response fluctuations.

[0146] In this embodiment, the comprehensive weights of the six core indicators can be set as follows: 0.18 for the inclination angle of the base or column of the concrete placing boom, 0.12 for the ambient wind speed, 0.22 for the equivalent working torque of the concrete placing boom, 0.20 for the stress at the joint, 0.18 for the strain at the joint, and 0.10 for the structural vibration acceleration. The above weights are merely examples and can be adjusted in actual applications based on the equipment structure, platform stress system, and monitoring focus.

[0147] Using the risk values ​​of the individual indicators and their combined weights, the overall risk score is calculated. Assume the preset thresholds are respectively =1.0、 =2.0、 =3.0. Therefore, if the overall risk score is less than 1.0, it is considered safe; between 1.0 and 2.0, it is considered a concern; between 2.0 and 3.0, it is considered a warning; and a score not less than 3.0 is considered dangerous. Furthermore, if three consecutive warning windows appear, a formal warning is output; if two consecutive dangerous windows appear, a danger alarm is output, and signals for restricted operation, limiting the material placement radius, pausing pumping, or stopping the machine are sent to the control system.

[0148] In practical applications, when the equipment is operating under conditions of large-radius material placement and high pumping pressure, even if a single instantaneous data point has not yet reached the absolute alarm threshold, if the average tilt angle of the base or column of the placing boom continues to rise, the average stress and strain at the joints are higher than the normal benchmark, and the standard deviation of vibration acceleration increases significantly, the overall risk score will continue to rise, thus prompting a timely warning. This judgment method can identify risk accumulation trends earlier than traditional single-threshold alarms and is more suitable for continuous safety monitoring of integrated equipment combining placing booms and platforms.

[0149] The above description is merely a description of preferred embodiments of the present invention and is not intended to limit the scope of the present invention in any way. Any changes or modifications made by those skilled in the art based on the above disclosure shall fall within the protection scope of the claims.

Claims

1. A method for determining the safety status of an integrated equipment combining a fabric placing machine and a platform, characterized in that, Includes the following steps: S1, Monitoring data acquisition: Real-time acquisition of multiple safety status indicators of the integrated equipment. The multiple safety status indicators include at least the parameters reflecting the tilt angle of the base or column of the placing boom, the ambient wind speed, the equivalent working torque of the placing boom, the stress at the joint between the placing boom and the platform, the strain at the joint between the placing boom and the platform, and the structural vibration acceleration. S2, Data Preprocessing: The safety status indicators are synchronized with a unified time scale, and missing values ​​are handled, outliers are removed, and filtering and noise reduction are performed to obtain effective time series data. Then, the data is grouped according to the operating conditions based on the equipment operating status, environmental conditions, and operating parameters. S3, Sliding window construction: Divide the effective time series data into sliding windows according to the set window length and window step size to obtain continuous window data of each security status index up to time t; S4, Window statistical feature extraction: For the window data, calculate the window mean and window standard deviation for each safety status index within the sliding window at time t. S5, Establish a statistical benchmark for normal state: Based on the data of the equipment's historical normal operation period, group according to the operating conditions, and calculate the sample mean and sample standard deviation of the window mean and window standard deviation of each safety state indicator, respectively, as the normal state benchmark of the corresponding indicator under the operating conditions. S6, Constructing the single-indicator risk deviation: For the i-th safety status indicator in the sliding window at time t, based on the window mean and window standard deviation obtained in step S4, and combined with the normal status benchmark obtained in step S5, calculate the mean deviation and standard deviation deviation respectively, and linearly combine the mean deviation and standard deviation deviation according to a preset weight to obtain the single-indicator risk value of the indicator. S7, Construct a multi-indicator weighted risk score: The risk values ​​of each single indicator are weighted and summed according to preset weights to obtain the overall risk score of the integrated equipment at time t; S8, Safety Status Classification Determination: The overall risk score is compared with a preset classification threshold, and the safety status level of the equipment is output.

2. The method for determining the safety status of the integrated equipment combining a placing boom and a platform as described in claim 1, characterized in that, In step S6, the mean deviation of the i-th safety status index Deviation from standard deviation They are obtained respectively through the following formulas: ， ， in, Let be the window mean of the i-th safety status index at time t. Let be the standard deviation of the i-th safety status index at time t. This is the sample mean of the window mean under normal conditions. This represents the sample standard deviation of the window mean under normal conditions. This represents the sample mean of the standard deviation of the window under normal conditions. This is the sample standard deviation of the window standard deviation under normal conditions. It is a preset, extremely small positive number used to prevent the denominator from being zero; Single-index risk value of the i-th safety status indicator Obtained through the following formula: in, and Let be the internal weights of the i-th safety status index in terms of mean deviation and standard deviation, respectively, and satisfy . ; The values ​​of the internal weights are configured differently based on the risk type of the safety status indicator: For the equivalent working torque of the fabric placing machine, the inclination angle of the base or column, the stress at the joint, and the strain at the joint, set... > ; For the aforementioned environmental wind speed and structural vibration acceleration, set > .

3. The method for determining the safety status of the integrated equipment combining a placing boom and a platform as described in claim 1, characterized in that, In step S7, the overall risk score Obtained through the following formula: Where n is the number of safety status indicators included in the assessment. For single-indicator risk values, Let be the external comprehensive weight corresponding to the i-th safety status indicator, and satisfy . ; The external comprehensive weights are determined based on the sensitivity of each safety status indicator to structural safety. The weights of the equivalent working torque of the concrete placing machine, the stress at the joint, the strain at the joint, and the tilt angle of the base or column are greater than the weights of the ambient wind speed and the structural vibration acceleration.

4. The method for determining the safety status of the integrated equipment combining a placing boom and a platform as described in claim 1, characterized in that, In step S8, the security status is divided into four levels: when When the time comes, it is determined to be a safe state; when When this time, it is determined to be in a state of attention; when When this occurs, it is determined to be a warning state; when When this occurs, it is determined to be a dangerous situation; in, , , For a preset scoring threshold; and / or, The determination result of the safety status level is also logically combined with the determination rule based on physical thresholds to jointly determine whether to trigger the disposal measures: when the real-time value of the stress at any joint exceeds the preset absolute safety limit, it is forcibly determined to be a dangerous state regardless of the overall risk score.

5. The method for determining the safety status of the integrated equipment combining a placing boom and a platform as described in claim 4, characterized in that, When outputting the security status level of the equipment, a continuous window triggering mechanism is executed: the level determination result is officially output only when a certain security status level appears consecutively for a preset window number K, where K is a preset positive integer.

6. The method for determining the safety status of the integrated equipment of the placing boom and platform as described in claim 1, characterized in that, In step S5 Sample mean of window mean Obtained through the following formula: ； Sample standard deviation of window mean Obtained through the following formula: ； Sample mean of window standard deviation Obtained through the following formula: ； Sample standard deviation of window standard deviation Obtained through the following formula: ； Where N is the number of normal sample windows. Let be the window mean of the ith safety status index within the j-th sliding window. The window standard deviation of the i-th safety status index in the j-th sliding window; and / or, The normal state statistical benchmark established in step S5 is adaptively updated during equipment operation: during the time period when the equipment is determined to be in a safe state, the normal state statistical benchmark is iteratively updated using an exponentially weighted moving average method with a preset smoothing factor to adapt to the normal performance drift during long-term equipment operation.

7. The method for determining the safety status of the integrated equipment of the placing boom and platform as described in claim 1, characterized in that, In step S1 The multiple safety status indicators are collected through a sensor acquisition unit; and / or, The safety status indicators also include at least one of the following: boom deployment angle, slewing angular velocity, pitch angular velocity, hydraulic cylinder pressure, delivery pipe pressure, concrete pump flow rate, end hose swing amplitude, platform plate opening / closing status, or climbing mechanism status; and / or, The equivalent working torque is calculated from one or more of the following: boom attitude parameters, concrete placement radius, equivalent weight of concrete in the pipe, pumping pressure, end reaction force, structural geometric parameters, and equivalent load parameters.

8. The method for determining the safety status of the integrated equipment of the placing boom and platform as described in claim 1, characterized in that, In step S2 The missing value processing employs adjacent interpolation, linear interpolation, mean interpolation, or compensation between consecutive time points; and / or, The outlier removal method employs the three-standard-deviation criterion, box plot method, or median absolute deviation method; and / or, The filtering and noise reduction employs moving average filtering, median filtering, or low-pass filtering; and / or, The working condition grouping criteria include at least one of the following: The equipment operating status includes at least one of the following: boom deployment operation, boom retraction or internal installation, pumping operation, non-pumping standby, or climbing conversion. Environmental conditions range, including different wind speed ranges; The range of operating parameters includes different fabric radii.

9. The method for determining the safety status of the integrated equipment of the placing boom and platform as described in claim 1, characterized in that, Window data in step S3 Obtained through the following formula: in, Let L be the sampled value of the i-th security status index at time t, and L be the window length; and / or, Window mean in step S4 Obtained through the following formula: ； Window standard deviation in step S4 Obtained through the following formula: ； in, Let be the window mean of the i-th safety status index at time t. Let L be the standard deviation of the window for the i-th safety status index at time t, and L be the window length.

10. The method for determining the safety status of the integrated equipment of the placing boom and platform as described in claim 1, characterized in that, Also includes: S9, Result Output and Early Warning Handling: Output the overall risk score, risk values ​​of each individual indicator, major deviations in safety status indicators and safety status levels in real time, and trigger at least one of the following handling measures when the safety status level reaches the early warning or danger level: audible and visual alarm, remote information push, work prompt, load reduction control, restricted operation, or shutdown interlock.

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