Multi-wavelet　has　many　excellent　properties　that　single　wavelet　cannot　satisfy　simultaneously,　such　as　symmetry,　orthogonality,　compact　support　and　high　vanishing　moments　etc.　It　contains　several　scaling　functions　and　wavelet　functions,　which　can　make　it　match　different　characteristics　of　analyzed　signal.　Therefore,　it　is　always　used　in　bearing　fault　diagnosis.　However,　multi-wavelet　is　multi-dimensional　and　vibration　signal　is　one-dimensional,　so　the　1-D　vibration　signal　should　be　preprocessed　before　being　decomposed　with　multi-wavelet.　It　means　that　the　initial　data　need　to　be　converted　to　r-dimensional　data,　and　then　is　input　to　a　tower　algorithm.　If　preprocessing　is　done,　multi-wavelet　properties　will　be　destroyed.　Due　to　balanced　multi-wavelet　has　unique　properties,　the　preprocessing　can　be　omitted.　In　this　paper,　a　balanced　multi-wavelet　called　CL4BAL　is　designed　through　balancing　original　CIA　multi-wavelet　and　is　applied　in　the　vibration　signal　processing.　Comparing　the　frequency　band　index　after　decomposition　and　reconstruction　of　CL4BAL　and　CIA　multi-wavelet,　it　can　be　proved　that　CL4BAL　is　much　better　than　that　of　CIA　multi-wavelet　in　bearing　fault　diagnosis.