Safety auxiliary system of overhead working truck and working method of safety auxiliary system

Abstract

The invention belongs to the field of overhead working trucks, and discloses an overhead working truck safety auxiliary system and a working method thereof.The overhead working truck safety auxiliary system comprises an upper platform detection unit, a lower platform detection unit, a shear fork support detection unit, a central processing unit, a voice broadcast unit, a warning lamp unit and a vehicle control unit; the central processing unit is in communication connection with the upper platform detection unit, the lower platform detection unit, the scissor support detection unit, the voice broadcast unit, the warning lamp unit and the vehicle control unit. The working safety of the overhead working truck in a complex environment is ensured, collision between the truck and obstacles is avoided through the safety auxiliary system, accidents and economic losses are reduced, an operator is assisted to operate the truck under the condition that the operator operates improperly or a view blind area exists, and the operation safety of the worker is enhanced.

Description

Technical Field

[0001] The invention relates to the field of aerial work vehicles, and in particular to a safety auxiliary system for an aerial work vehicle and a working method thereof. Background Art

[0002] Aerial work vehicles are special vehicles used in industries that require operations at high altitudes. This type of vehicle is designed to safely and effectively lift workers and equipment to the working height, providing a stable platform for various aerial operations, so safety is a very important indicator for aerial work vehicles. The structure of an aerial work vehicle generally includes a vehicle body and a scissor lift, and the scissor lift includes a lower platform, a scissor bracket, and an upper platform.

[0003] Aerial work vehicles are usually used in construction, highway construction, power maintenance and other engineering project scenarios. In these complex work scenarios, the vehicle often works or moves in a lifted state. When the vehicle is lifted, the vehicle area is large and many obstacles will be encountered in all directions. If the operator encounters improper operation or blind spots in the field of vision during the operation, the vehicle will collide with obstacles, causing casualties and economic losses. Summary of the invention

[0004] The purpose of the present invention is to provide a safety auxiliary system for an aerial work vehicle and a working method thereof, so as to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A safety auxiliary system for aerial work vehicles, comprising an upper platform detection unit, a lower platform detection unit, a scissor bracket detection unit, a central processing unit, a voice broadcast unit, a warning light unit, and a vehicle control unit, wherein the central processing unit is respectively connected to the upper platform detection unit, the lower platform detection unit, the scissor bracket detection unit, the voice broadcast unit, the warning light unit, and the vehicle control unit for communication;

[0007] The upper platform detection unit is arranged on the upper platform, and comprises a first ultrasonic detection module and a first microprocessor, wherein the first ultrasonic detection module detects the distance between the obstacle and the upper platform;

[0008] The scissor support detection unit is arranged on the scissor support, and comprises a second ultrasonic detection module and a second microprocessor, and the second ultrasonic detection module detects whether there are obstacles around the middle platform;

[0009] The lower platform detection unit is arranged on the lower platform, and includes a laser radar, a third ultrasonic detection module and a third microprocessor. The laser radar detects the distance and moving speed information of the obstacle in front, and the third ultrasonic detection module detects the obstacles that appear in the blind spot of the operator's field of vision when the aerial work vehicle turns or reverses.

[0010] Furthermore, the upper platform detection unit includes four groups of first ultrasonic detection modules distributed around the upper platform; the upper platform detection unit also includes a first wireless communication unit, and the first microprocessor is electrically connected to the first ultrasonic detection module and the first wireless communication unit respectively.

[0011] Furthermore, the number of the scissors support detection units is the same as the number of nodes of the scissors support of the aerial work vehicle, and the scissors support detection units are arranged on the nodes in a one-to-one correspondence; the scissors support detection unit also includes a second wireless communication unit, and the second microprocessor is electrically connected to the second ultrasonic detection module and the second wireless communication unit, respectively.

[0012] Furthermore, the lower platform detection unit includes four groups of third ultrasonic detection modules distributed around the lower platform; the lower platform detection unit also includes a third wireless communication unit, and the third microprocessor is electrically connected to the third ultrasonic detection module, laser radar, and third wireless communication unit respectively.

[0013] The present invention also provides a working method of the above-mentioned aerial work vehicle safety auxiliary system, comprising:

[0014] Step 1, build an aerial work vehicle safety assistance system on the aerial work vehicle;

[0015] Step 2: Process the ultrasonic data in the aerial work vehicle safety assistance system, detect obstacles in close range in all directions, and use CDMA to solve the co-frequency interference of the ultrasonic module in the aerial work vehicle safety assistance system;

[0016] Step 3: Process the laser radar data in the aerial work vehicle safety assistance system to obtain the distance and speed of the obstacle in front of the vehicle, and use the DBSCAN algorithm to cluster the obtained two-dimensional data of the distance and speed of the obstacle to divide different obstacles into different clusters;

[0017] Step 4, calculate all the cluster centers in each cluster of the cluster, calculate the distance between them and the aerial work vehicle, select the obstacle with the smallest distance, when the distance is less than the warning distance, the warning light unit lights up, and the voice broadcast unit starts to alarm, and the vehicle control unit uses the sliding membrane controller to control the vehicle speed.

[0018] Furthermore, the step 2 comprises:

[0019] The ultrasonic detection module is used to transmit ultrasonic waves in one direction, and the timing starts at the same time of transmission. The ultrasonic wave propagates in the air and reflects back after encountering an obstacle. The ultrasonic detection module stops timing after receiving the reflected wave, and CDMA is used to solve the problem of co-frequency interference in the ultrasonic ranging process. The distance measurement formula is: Where R is the measured distance, T is the time from the ultrasonic wave to the receiving wave, V is the propagation speed of the ultrasonic wave in the air, and the first ultrasonic detection module, the second ultrasonic detection module, and the third ultrasonic detection module process information through the first microprocessor, the second microprocessor, and the third microprocessor respectively, and each microprocessor can obtain a one-dimensional array {R 1 ,R 2 …R i}, where R 1 , R 2 …R i Represents the distance measured by each ultrasonic detection module. When the distance R measured by the aerial work vehicle during operation is less than the preset warning distance R x When the voice broadcast unit starts to alarm.

[0020] Furthermore, the method of solving the same-frequency interference problem in the ultrasonic ranging process by using CDMA includes:

[0021] A specific spread spectrum code C(t) is assigned to each ultrasonic detection module. The wave signal sent by the ultrasonic detection module is A(t), and the spread spectrum signal S(t) is:

[0022] S(t)=A(t)*C(t)

[0023] Where * represents a multiplication operation;

[0024] The mixed signal R(t) received by the receiver is the superposition of the transmitted signal after propagation and interference:

[0025]

[0026] Among them, n i (t) represents the interference signal from other ultrasonic detection modules, n represents the total number of ultrasonic detection modules, and i represents the number of ultrasonic detection modules;

[0027] At the receiving end, in order to avoid the influence of echo signals or interference signals from other ultrasonic detection modules, a correlation operation is performed with a specific spread spectrum code C(t) to determine whether the received signal is a signal sent by a specific detection module. The relevant calculation formula is:

[0028]

[0029] Among them, y s(t) is the ultrasonic signal received after despreading, y ni (t) is the despread output of the interference signal, which approaches 0.

[0030] Furthermore, in step 3, the laser radar detects the distance and speed of the obstacle through the echo signal, and the method includes:

[0031] S101: LiDAR transmits linear frequency modulated continuous wave, echo signal s r (t) is the received target transmission signal. The signal received at the transmission time t can be expressed as:

[0032] s r (t) = Acos(2πf 0 (t-τ)+πβ(t-τ) 2 )

[0033] Where A is the signal amplitude, f 0 is the carrier frequency, β is the modulation frequency, signal is the round trip time, R is the target distance, and c is the speed of light;

[0034] S102: The received echo signal s r (t) is mixed with the transmitted signal to obtain the intermediate frequency signal s i (t) is expressed as follows:

[0035]

[0036] in, is the Doppler shift, λ is the wavelength, and v is the target velocity;

[0037] S103: Perform one-dimensional fast Fourier transform on each pulse of the processed intermediate frequency signal, convert the time domain signal into the frequency domain, perform sampling within a pulse period T, the sampled data is x[n], and perform fast Fourier transform on x[n]:

[0038]

[0039] Where N is the number of sampling points, m is the number of data, and j is the imaginary unit. 2 = -1, k is the frequency index, and the spectrum peak k obtained by fast Fourier transform * The corresponding frequency is T s is the sampling period, and the distance information is obtained through the following relationship:

[0040]

[0041] S104: The distance fast Fourier transform result of multiple pulse cycles is x[R,mt ], where R is the distance, n t Represents different pulse periods, for each column x[R,n t ] is subjected to fast Fourier transform to obtain the Doppler frequency domain signal s[R,q]:

[0042]

[0043] Among them, e is a natural constant, M is the number of pulse cycles, and q is represented by the velocity index. The spectrum peak q is obtained by two fast Fourier transforms. * The corresponding frequency The speed information can be obtained through the following relationship get;

[0044] In step 3, the identified two-dimensional data is clustered using the DBSCAN algorithm to identify different obstacles, and the obstacle targets closest to the aerial work vehicle are selected, including:

[0045] After two fast Fourier transforms of the original signal, a two-dimensional data set {(R i ,V i )},R i ,V i Represents distance and speed respectively. After standardization, these data are X={(x i ,y i )},The different target point cloud data are classified into different clusters through the DBSCAN algorithm, and the cluster center is obtained based on the average value of all points in the cluster. For each cluster center, the position of the aerial work vehicle is calculated. The process is as follows:

[0046] S200: For each unvisited data point p:

[0047] Calculate the ε domain of p: N ∈ (p)={b∈X|||pb||≤∈}

[0048] Among them, p is the data point currently being processed, b is a point in the ε domain of p, ε is the domain radius of the DBSCAN algorithm, X is a two-dimensional data set, N ∈ (p) is the domain of P calculated;

[0049] S201: If | N ∈ (p)|≥minpts, minpts is the minimum number of samples required to form a core point, then p is a core point, create a new cluster C and add p and the points in its area to C: C = {p}∪N ∈ (p), for each point b∈N ∈(p): If b has not been visited, mark it as unvisited. If b is a core point, add the points in its ε domain to cluster C.

[0050] S202: Continue to process other points in the data set X until all points are visited, and mark the points that are not assigned to any cluster as noise points;

[0051] Calculate the cluster center C based on the mean of all points in each cluster center for Where N is the number of data points in the cluster, x i is the normalized information of the intra-cluster distance, y i To normalize the speed information within the cluster, for each cluster center, calculate its distance S to the aerial work vehicle and select the obstacle target with the smallest distance.

[0052] Furthermore, the method for controlling the speed of the sliding film controller in step 4 includes:

[0053] The expected speed of the aerial work vehicle is v d , the actual speed is v s , which is obtained by integrating the vehicle running acceleration data a detected by the acceleration sensor installed on the lower platform of the aerial work vehicle, and the control input is u;

[0054] The synovial surface s is defined as:

[0055] s=v s -v d ;

[0056] The control rate u of the sliding mode controller is designed as:

[0057] u = -k·sign(s);

[0058] Where k is a positive control gain, sign(*) is the sign function, when s>0, sign(s)=1; when s<0, sign(s)=-1;

[0059] The control input u is used to control the vehicle to obtain the desired speed.

[0060] Compared with the prior art, the beneficial effects of the present invention are: the present invention ensures the safety of aerial work vehicles working in complex environments, avoids collisions between vehicles and obstacles through the safety assistance system, reduces the occurrence of accidents and economic losses, assists operators in operating the vehicle in the event of improper operation or blind spots, and enhances the safety of workers' operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 It is a module diagram of a safety auxiliary system for an aerial work vehicle of the present invention.

[0062] Figure 2 This is a schematic diagram of the installation of the upper platform detection unit, the scissor bracket detection unit, and the lower platform detection unit on the aerial vehicle.

[0063] Figure 3 It is a module diagram of the upper platform detection unit.

[0064] Figure 4 It is a module diagram of the lower platform detection unit.

[0065] Figure 5 It is the module diagram of the scissor stand detection unit.

[0066] Figure 6 The present invention is a flow chart of the working method of a high-altitude vehicle safety auxiliary system.

[0067] Figure 7 It is the flow chart of DBSCAN algorithm of the present invention.

[0068] In the figure: 1 represents the upper platform, 2 represents the lower platform, 3 represents the scissors bracket, 4 represents the upper platform detection unit, 400 represents the first ultrasonic detection module, 401 represents the first microprocessor, 402 represents the first wireless communication unit, 403 represents the first power module, 5 represents the lower platform detection unit, 500 represents the third ultrasonic detection module, 501 represents the third microprocessor, 502 represents the third wireless communication unit, 503 represents the third power module, 504 represents the laser radar, 6 represents the scissors bracket detection unit, 600 represents the second ultrasonic detection module, 601 represents the second microprocessor, 602 represents the second wireless communication unit, 603 represents the second power module, 7 represents the central processing unit, 8 represents the voice broadcast unit, 9 represents the warning light unit, and 10 represents the vehicle control unit. DETAILED DESCRIPTION

[0069] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0070] See also Figure 1-Figure 5 A safety auxiliary system for aerial work vehicles includes an upper platform detection unit 4, a lower platform detection unit 5, a scissor bracket detection unit 6, a central processing unit 7, a voice broadcast unit 8, a warning light unit 9, and a vehicle control unit 10. The central processing unit 7 is respectively communicated with the upper platform detection unit 4, the lower platform detection unit 5, the scissor bracket detection unit 6, the voice broadcast unit 8, the warning light unit 9, and the vehicle control unit 10.

[0071] Continue reading Figure 2 and Figure 3 The upper platform detection unit 4 is arranged on the upper platform 1, and includes a first ultrasonic detection module 400, a first microprocessor 401, a first wireless communication unit 402, and a first power module 403. The first ultrasonic detection module 400 detects the distance between the obstacle and the upper platform 1. There are four groups of the first ultrasonic detection modules 400, which are respectively located at the front, back, left, and right of the upper platform 1. The first ultrasonic detection module 400 uses the principle of ultrasonic ranging to identify the distance between the obstacle and the platform. The first microprocessor 401 is electrically connected to the first ultrasonic detection module 400, the first wireless communication unit 402, and the first power module 403. When working, the first power module 403 supplies power to the first ultrasonic detection module 400, the first microprocessor 401, and the first wireless communication unit 402. The first ultrasonic detection module 400 collects and transmits detection data to the first microprocessor 401 for processing. The first microprocessor 401 transmits the data to the first wireless communication unit 402. The first wireless communication unit 402 transmits the data to the central processor 7. The central processor 7 is equipped with a corresponding wireless communication unit.

[0072] Continue reading Figure 2 and Figure 5 The scissor support detection unit 6 is arranged on the scissor support 3, wherein the number of the scissor support detection units 6 is the same as the number of nodes of the scissor support 3 of the aerial work vehicle, and the node refers to the inflection point of the V shape, excluding the intersection of the X shape, and the scissor support detection unit 6 is arranged on the node one by one. The scissor support detection unit 6 includes a second ultrasonic detection module 600, a second microprocessor 601, a second wireless communication unit 602 and a second power supply module 603, and the second microprocessor 601 is electrically connected to the second ultrasonic detection module 600, the second wireless communication unit 602 and the second power supply module 603 respectively. The second ultrasonic detection module 600 detects whether there are obstacles around the intermediate platform through the ultrasonic module ranging principle, and the second wireless communication unit 602 is used to realize wireless communication and control. When working, the second power supply module 603 supplies power to the second ultrasonic detection module 600, the second microprocessor 601, and the second wireless communication unit 602. The second ultrasonic detection module 600 collects detection data and transmits it to the second microprocessor 601 for processing. The second microprocessor 601 transmits the data to the second wireless communication unit 602, and the second wireless communication unit 602 transmits the data to the central processor 7.

[0073] Continue reading Figure 2 and Figure 4The lower platform detection unit 5 is arranged on the lower platform 2, and includes a third ultrasonic detection module 500, a third microprocessor 501, a third wireless communication unit 502, a third power module 503, and a laser radar 504. The laser radar 504 is preferably a millimeter wave radar, which is installed in front of the lower platform 2. The laser radar 504 detects the speed of the obstacle in front of the lower platform 2 and the distance between the obstacle and the lower platform 2. The third ultrasonic detection module 500 detects the distance between the obstacle and the lower platform 2. There are four groups of the third ultrasonic detection module 500, which are respectively located in the front, back, left and right of the lower platform 2. The third microprocessor 501 is electrically connected to the third ultrasonic detection module 500, the third wireless communication unit 502 and the third power module 503, respectively. The third wireless communication unit 502 is used to realize wireless communication and control. When working, the third power supply module 503 supplies power to the second ultrasonic detection module 600, the second microprocessor 601, and the second wireless communication unit 602. The second ultrasonic detection module 600 collects detection data and transmits it to the second microprocessor 601 for processing. The second microprocessor 601 transmits the data to the second wireless communication unit 602, and the second wireless communication unit 602 transmits the data to the central processor 7.

[0074] The central processing unit 7 processes the received data. When the identified obstacle distance is the warning distance, the central processing unit 7 controls the voice broadcast unit 8 and the warning light unit 9. The voice broadcast unit 8 outputs an alarm audio, and the warning light unit 9 lights up to warn the operating staff to pay attention to the obstacle.

[0075] See also Figure 6 and Figure 7 , a working method of the aerial work vehicle safety assistance system as described above, comprising the following steps:

[0076] Step 1: build an aerial work vehicle safety assistance system on the aerial work vehicle, collect ultrasonic data through the first ultrasonic detection module 400, the second ultrasonic detection module 600 and the third ultrasonic detection module 500, and collect laser data through the laser radar 504.

[0077] Step 2: Process the ultrasonic data in the aerial work vehicle safety assistance system, detect obstacles in all directions, and use CDMA (Code Division Multiple Access) to solve the co-frequency interference of the ultrasonic module in the aerial work vehicle safety assistance system. Specifically include:

[0078] The ultrasonic detection module is used to transmit ultrasonic waves in one direction, and the timing starts at the same time of transmission. The ultrasonic wave propagates in the air and reflects back after encountering an obstacle. The ultrasonic detection module stops timing after receiving the reflected wave, and CDMA is used to solve the problem of co-frequency interference in the ultrasonic ranging process. The distance measurement formula is: Where R is the measured distance, T is the time from the emission to the reception of the ultrasonic wave, V is the propagation speed of the ultrasonic wave in the air, the first ultrasonic detection module 400, the second ultrasonic detection module 600, and the third ultrasonic detection module 500 process information through the first microprocessor 401, the second microprocessor 601, and the third microprocessor 501 respectively, and each microprocessor can obtain a one-dimensional array {R 1 ,R 2 …R i}, where R 1 , R 2 …R i Represents the distance measured by each ultrasonic detection module. When the distance R measured by the aerial work vehicle during operation is less than the preset warning distance R x When the voice broadcast unit 8 starts to alarm, the warning light unit 9 lights up.

[0079] Among them, the use of CDMA to solve the problem of co-frequency interference in the ultrasonic ranging process includes:

[0080] A specific spread spectrum code C(t) is assigned to each ultrasonic detection module. The wave signal sent by the ultrasonic detection module is A(t), and the spread spectrum signal S(t) is:

[0081] S(t)=A(t)*C(t)

[0082] Where * represents a multiplication operation.

[0083] The mixed signal R(t) received by the receiver is the superposition of the transmitted signal after propagation and interference:

[0084]

[0085] Among them, n i (t) represents the interference signal from other ultrasonic detection modules, n represents the total number of ultrasonic detection modules, and i represents the number of ultrasonic detection modules.

[0086] At the receiving end, in order to avoid the influence of echo signals or interference signals from other ultrasonic detection modules, a correlation operation is performed with a specific spread spectrum code C(t) to determine whether the received signal is a signal sent by a specific detection module. The relevant calculation formula is:

[0087]

[0088]

[0089] Among them, y s (t) is the ultrasonic signal received after despreading, y ni (t) is the despread output of the interference signal, which approaches 0.

[0090] Step 3, processing the data of the laser radar 504 in the aerial work vehicle safety assistance system to obtain the distance and speed of the obstacle in front of the vehicle, and clustering the obtained two-dimensional data of the distance and speed of the obstacle using the DBSCAN algorithm to divide different obstacles into different clusters.

[0091] The laser radar 504 detects the distance and speed of the obstacle through the echo signal, and the method includes:

[0092] S101: The laser radar 504 transmits a linear frequency modulated continuous wave (FMCW), and the echo signal s r (t) is the received target transmission signal. The signal received at the transmission time t can be expressed as:

[0093] s r (t) = Acos(2πf 0 (t-τ)+πβ(t-τ) 2 )

[0094] Where A is the signal amplitude, f 0 is the carrier frequency, β is the modulation frequency, signal is the round trip time, R is the target distance, and c is the speed of light.

[0095] S102: The received echo signal s r (t) is mixed with the transmitted signal to obtain the intermediate frequency signal s i (t) is expressed as follows:

[0096]

[0097] in, is the Doppler shift, λ is the wavelength, and v is the target velocity.

[0098] S103: Perform one-dimensional fast Fourier transform (one-dimensional FFT) on each pulse of the processed intermediate frequency signal, convert the time domain signal to the frequency domain, perform sampling within a pulse period T, the sampled data is x[n], and perform fast Fourier transform (FFT) on x[n]:

[0099]

[0100] Where N is the number of sampling points, m is the number of data, and j is the imaginary unit. 2 = -1, k is the frequency index, and the spectrum peak k obtained by fast Fourier transform (FFT) * The corresponding frequency is T s is the sampling period, and the distance information is obtained through the following relationship:

[0101]

[0102] S104: The distance fast Fourier transform result of multiple pulse cycles is x[R,m t ], where R is the distance, n t Represents different pulse periods, for each column x[R,n t ] is subjected to fast Fourier transform to obtain the Doppler frequency domain signal s[R,q]:

[0103]

[0104] Among them, e is a natural constant, M is the number of pulse cycles, and q is represented by the velocity index. The spectrum peak q is obtained by two fast Fourier transforms. * The corresponding frequency The speed information can be obtained through the following relationship get.

[0105] Among them, the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm is used to cluster the identified two-dimensional data, identify different obstacles, and select the obstacle targets closest to the aerial work vehicle, including:

[0106] After two fast Fourier transforms of the original signal, a two-dimensional data set {(R i ,V i )},R i ,V i Represents distance and speed respectively. After standardization, these data are X={(x i ,y i )}, the different target point cloud data are classified into different clusters through the DBSCAN algorithm, and the cluster center is obtained based on the average value of all points in the cluster. For each cluster center, the position of the aerial work vehicle is calculated, such as Figure 7 As shown, the process is as follows:

[0107] S200: For each unvisited data point p:

[0108] Compute the epsilon domain of p:

[0109] N ∈ (p)={b∈X|||pb||≤∈}

[0110] Among them, p is the data point currently being processed, b is a point in the ε domain of p, ε is the domain radius of the DBSCAN algorithm, X is a two-dimensional data set, N ∈(p) is the domain of P calculated.

[0111] S201: If | N ∈ (p)|≥minpts, minpts is the minimum number of samples required to form a core point, then p is a core point, create a new cluster C and add p and the points in its area to C: C = {p}∪N ∈ (p), for each point b∈N ∈ (p): If b has not been visited, mark it as unvisited. If b is a core point, add the points within its ε domain to cluster C.

[0112] S202: Continue to process other points in the data set X until all points are visited, and mark the points that are not assigned to any cluster as noise points.

[0113] Calculate the cluster center C based on the mean of all points in each cluster center for Where N is the number of data points in the cluster, x i is the normalized information of the intra-cluster distance, y i To normalize the speed information within the cluster, for each cluster center, calculate its distance S to the aerial work vehicle and select the obstacle target with the smallest distance.

[0114] Step 4, calculate all the cluster centers in each cluster of the cluster, calculate the distance between them and the aerial work vehicle, select the obstacle with the smallest distance, when the distance is less than the warning distance, the warning light unit 9 lights up, and the voice broadcast unit 8 starts to alarm, and the vehicle control unit 10 uses the sliding membrane controller to control the vehicle speed.

[0115] The method of controlling the speed of the sliding film controller includes:

[0116] The expected speed of the aerial work vehicle is v d , the actual speed is v s , which is obtained by integrating the vehicle running acceleration data a detected by the acceleration sensor installed on the lower platform of the aerial work vehicle, and the control input is u;

[0117] The synovial surface s is defined as:

[0118] s=v s -v d ;

[0119] The control rate u of the sliding mode controller is designed as:

[0120] u = -k·sign(s);

[0121] Where k is a positive control gain, sign(*) is the sign function, when s>0, sign(s)=1; when s<0, sign(s)=-1;

[0122] The control input u is used to control the vehicle to obtain the desired speed.

[0123] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A safety assistance system for an aerial work vehicle, characterized in that: It includes an upper platform detection unit, a lower platform detection unit, a scissor bracket detection unit, a central processing unit, a voice broadcast unit, a warning light unit, and a vehicle control unit. The central processing unit is respectively connected to the upper platform detection unit, the lower platform detection unit, the scissor bracket detection unit, the voice broadcast unit, the warning light unit, and the vehicle control unit for communication; The upper platform detection unit is arranged on the upper platform, and comprises a first ultrasonic detection module and a first microprocessor, wherein the first ultrasonic detection module detects the distance between the obstacle and the upper platform; The scissor support detection unit is arranged on the scissor support, and comprises a second ultrasonic detection module and a second microprocessor, and the second ultrasonic detection module detects whether there are obstacles around the middle platform; The lower platform detection unit is arranged on the lower platform, and includes a laser radar, a third ultrasonic detection module and a third microprocessor. The laser radar detects the distance and moving speed information of the obstacle in front, and the third ultrasonic detection module detects the obstacles that appear in the blind spot of the operator's field of vision when the aerial work vehicle turns or reverses.

2. A safety assistance system for aerial work vehicles according to claim 1, characterized in that: The upper platform detection unit includes four groups of first ultrasonic detection modules distributed around the upper platform; the upper platform detection unit also includes a first wireless communication unit, and the first microprocessor is electrically connected to the first ultrasonic detection module and the first wireless communication unit respectively.

3. A safety assistance system for aerial work vehicles according to claim 1, characterized in that: The number of the scissors support detection units is the same as the number of nodes of the scissors support of the aerial work vehicle, and the scissors support detection units are arranged on the nodes in a one-to-one correspondence; the scissors support detection unit also includes a second wireless communication unit, and the second microprocessor is electrically connected to the second ultrasonic detection module and the second wireless communication unit respectively.

4. The aerial work vehicle safety assistance system according to claim 1, characterized in that: The lower platform detection unit includes four sets of third ultrasonic detection modules distributed around the lower platform; the lower platform detection unit also includes a third wireless communication unit, and the third microprocessor is electrically connected to the third ultrasonic detection module, the laser radar, and the third wireless communication unit respectively.

5. A working method of the aerial work vehicle safety assistance system as claimed in any one of claims 1 to 4, characterized in that: include: Step 1, build an aerial work vehicle safety assistance system on the aerial work vehicle; Step 2: Process the ultrasonic data in the aerial work vehicle safety assistance system, detect obstacles in close range in all directions, and use CDMA to solve the co-frequency interference of the ultrasonic module in the aerial work vehicle safety assistance system; Step 3: Process the laser radar data in the aerial work vehicle safety assistance system to obtain the distance and speed of the obstacle in front of the vehicle, and use the DBSCAN algorithm to cluster the obtained two-dimensional data of the distance and speed of the obstacle to divide different obstacles into different clusters; Step 4, calculate all the cluster centers in each cluster of the cluster, calculate the distance between them and the aerial work vehicle, select the obstacle with the smallest distance, when the distance is less than the warning distance, the warning light unit lights up, and the voice broadcast unit starts to alarm, and the vehicle control unit uses the sliding membrane controller to control the vehicle speed.

6. The working method of the aerial work vehicle safety assistance system according to claim 5, characterized in that: The step 2 comprises: The ultrasonic detection module is used to transmit ultrasonic waves in one direction, and the timing starts at the same time of transmission. The ultrasonic wave propagates in the air and reflects back after encountering an obstacle. The ultrasonic detection module stops timing after receiving the reflected wave, and CDMA is used to solve the problem of co-frequency interference in the ultrasonic ranging process. The distance measurement formula is: Where R is the measured distance, T is the time from ultrasonic emission to reception, V is the propagation speed of ultrasonic wave in the air, the first ultrasonic detection module, the second ultrasonic detection module, and the third ultrasonic detection module process information through the first microprocessor, the second microprocessor, and the third microprocessor respectively, and each microprocessor can obtain a one-dimensional array {R1, R2…R i }, where R1, R2…R i Represents the distance measured by each ultrasonic detection module. When the distance R measured by the aerial work vehicle during operation is less than the preset warning distance R x When the voice broadcast unit starts to alarm.

7. The working method of the aerial work vehicle safety assistance system according to claim 6, characterized in that: The method of solving the same-frequency interference problem in the ultrasonic ranging process by using CDMA includes: A specific spread spectrum code C(t) is assigned to each ultrasonic detection module. The wave signal sent by the ultrasonic detection module is A(t), and the spread spectrum signal S(t) is: S(t)=A(t)*C(t) Where * represents a multiplication operation; The mixed signal R(t) received by the receiver is the superposition of the transmitted signal after propagation and interference: Among them, n i (t) represents the interference signal from other ultrasonic detection modules, n represents the total number of ultrasonic detection modules, and i represents the number of ultrasonic detection modules; At the receiving end, in order to avoid the influence of echo signals or interference signals from other ultrasonic detection modules, a correlation operation is performed with a specific spread spectrum code C(t) to determine whether the received signal is a signal sent by a specific detection module. The relevant calculation formula is: Among them, y s (t) is the ultrasonic signal received after despreading, y ni (t) is the despread output of the interference signal, which approaches 0.

8. The working method of the aerial work vehicle safety assistance system according to claim 5, characterized in that: In step 3, the laser radar detects the distance and speed of the obstacle through the echo signal, and the method includes: S101: LiDAR transmits linear frequency modulated continuous wave, echo signal s r (t) is the received target transmission signal. The signal received at the transmission time t can be expressed as: s r (t)=Acos(2πf0(t-τ)+πβ(t-τ) 2 ) Where A is the signal amplitude, f0 is the carrier frequency, β is the modulation frequency, signal is the round trip time, R is the target distance, and c is the speed of light; S102: The received echo signal s r (t) is mixed with the transmitted signal to obtain the intermediate frequency signal s i (t) is expressed as follows: in, is the Doppler shift, λ is the wavelength, and v is the target velocity; S103: Perform one-dimensional fast Fourier transform on each pulse of the processed intermediate frequency signal, convert the time domain signal into the frequency domain, perform sampling within a pulse period T, the sampled data is x[n], and perform fast Fourier transform on x[n]: Where N is the number of sampling points, m is the number of data, and j is the imaginary unit. 2 = -1, k is the frequency index, and the spectrum peak k obtained by fast Fourier transform * The corresponding frequency is T s is the sampling period, and the distance information is obtained through the following relationship: S104: The distance fast Fourier transform result of multiple pulse cycles is x[R,m t ], where R is the distance, n t Represents different pulse periods, for each column x[R,n t ] is subjected to fast Fourier transform to obtain the Doppler frequency domain signal s[R,q]: Among them, e is a natural constant, M is the number of pulse cycles, and q is represented by the velocity index. The spectrum peak q is obtained by two fast Fourier transforms. * The corresponding frequency The speed information can be obtained through the following relationship get; In step 3, the identified two-dimensional data is clustered using the DBSCAN algorithm to identify different obstacles, and the obstacle targets closest to the aerial work vehicle are selected, including: After two fast Fourier transforms of the original signal, a two-dimensional data set {(R i ,V i )},R i ,V i Represent the distance and speed respectively. After standardization, these data are X={(x i ,y i )},The different target point cloud data are classified into different clusters through the DBSCAN algorithm, and the cluster center is obtained based on the average value of all points in the cluster. For each cluster center, the position of the aerial work vehicle is calculated. The process is as follows: S200: For each unvisited data point p: Compute the epsilon domain of p: N ∈ (p)={b∈X|||p-b||≤ε} Among them, p is the data point currently being processed, b is a point in the ε domain of p, ε is the domain radius of the DBSCAN algorithm, X is a two-dimensional data set, N ∈ (p) is the domain of P calculated; S201: If | N ∈ (p)|≥minpts, minpts is the minimum number of samples required to form a core point, then p is a core point, create a new cluster C and add p and the points in its area to C: C = {p}∪N ∈ (p), for each point b∈N ∈ (p): If b has not been visited, mark it as unvisited. If b is a core point, add the points in its ε domain to cluster C. S202: Continue to process other points in the data set X until all points are visited, and mark the points that are not assigned to any cluster as noise points; Calculate the cluster center C based on the mean of all points in each cluster center for Where N is the number of data points in the cluster, x i is the normalized information of the intra-cluster distance, y i To normalize the speed information within the cluster, for each cluster center, calculate its distance S to the aerial work vehicle and select the obstacle target with the smallest distance.

9. The working method of the aerial work vehicle safety assistance system according to claim 5, characterized in that: The method for controlling the speed of the sliding film controller in step 4 includes: The expected speed of the aerial work vehicle is v d , the actual speed is v s , which is obtained by integrating the vehicle running acceleration data a detected by the acceleration sensor installed on the lower platform of the aerial work vehicle, and the control input is u; The synovial surface s is defined as: s=v s -v d ; The control rate u of the sliding mode controller is designed as: u = -k·sign(s); Where k is a positive control gain, sign(*) is the sign function, when s>0, sign(s)=1; when s<0, sign(s)=-1; The control input u is used to control the vehicle to obtain the desired speed.

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