hydraulic, adjusting mobile embedded nodes of the per- ceived distance and signal transmit power, at the edge of the state, achieves lightweight data-driven service  push。

Moving track of mobile embedded node  is  shown in Fig。 1。 Among them, there are three kinds of  critical points in mobile embedded node。 The dotted  circle  in the graph is the effective sensing radius of the embedded node。 When the residual energy of mobile embedded nodes is decreased and the crowd data is larger, the node can move from A to B in order to meet the requirement of the mechanical hydraulic characteristic detection。 In order to achieve lightweight data-driven, the data size is reduced from the B position to the C position。 Among them, A, B, C three positions can be driven by the crowd data to achieve adaptive switching。

Crowd data scale could be obtained by formula (1)。 Here, SMC is the crowd data scale。 Di is the mobile em- bedded device crowd forwarding data。 DMN is  the aver- age value of the  hydraulic characteristics  of the data  in A, B, C three different locations。 DMC is the total data of crowd sensing。 IMN is the  set  of  mobile  crowd  nodes。 IME  is the set of mechanical  equipment。

power of the mobile embedded node can be adjusted adaptively according to the size of the crowd data。 The

effective sensing radius of the mobile embedded node is related to the residual energy of the node。 Mobile em-

bedded node adjusts its position and signal transmission power according to the residual energy。 When the em- bedded node forwarding of swarm intelligence  data meets  the  demand  characteristic  analysis  of mechanical

i∈IMN ∩IMEThe transfer process of the three locations is  as follows:

Here, TER denotes the residual energy threshold。 TPT denotes the signal transmit power threshold。  These values could be obtained by formula 

Here, Ei is the energy consumption of mobile embed- ded node。 Si is the crowd data。 MN is the number of mo- bile crowd nodes。 Ti is the signal sending  power  of mobile crowd node。 Di is the sending data of mobile em- bedded node。 DME is the hydraulic characteristic data of mechanical equipment。

For a number of mechanical equipment at  the  same time to detect and analyze the hydraulic characteristics, there is a need to set up a  mobile  mechanical  equip- ment characteristic analysis network。 The network is composed of multiple mobile embedded nodes。 Each node has the crowd function。 Topology  is  shown  in Fig。 2。

When the node 3 is unable to detect and analyze the hy- draulic characteristics of the mechanical equipment due to energy failure, the nodes are 1, 2, and 4 after moving to up- date the analysis network topology, as shown in Fig。 3。 The solid circle for 1 node represents the analysis of network characteristics of hydraulic machinery and equipment  2 and 4。

3 Mobile embedded machine hydraulic characteristic  analysis mechanism

The data output and input of the hydraulic control mod- ule in the mechanical equipment must have a linear pro- portional relationship。 The linear relation can be realized by the adaptive controller of embedded node。 When a mechanical hydraulic control signal is  sent  to  be  sent, the mobile embedded node moves to the mechanical equipment end of the hydraulic valve radio frequency working area on the circumference。 Hydraulic pump pis- ton B chamber suctions air, and at the same time, C cav- ity starts frequency pision antenna to  transmit hydraulic signal。 When the piston of the hydraulic  pump is discharged from the D cavity, the feedback signal of the mobile embedded node is received, and the balance ratio of the elastic and electromagnetic coupling is con- trolled。 Based on the force of the piston B cavity and  the C cavity, combined with the pressure of the D chamber, the  hydraulic  characteristic  analyses  of  the  mechanical